Autism Spectrum Disorders

Number: 0648

Policy
Applicable CPT / HCPCS / ICD-10 Codes
Background
References

Policy

Scope of Policy

This Clinical Policy Bulletin addresses autism spectrum disorders.

Medical Necessity

Aetna considers autism spectrum disorder (ASD) evaluation and diagnosis medically necessary when developmental delays or persistent deficits in social communication and social interaction across multiple contexts have been identified and when the evaluation is performed by the appropriate certified/licensed health care professional.

The following services may be included in the assessment and treatment of the member's condition:
1. ASD specific developmental evaluation;
2. Cognitive and adaptive behaviors evaluations;
3. Speech, language and comprehensive communication evaluation by speech-language pathologist;
4. Formal audiological hearing evaluation including frequency-specific brainstem auditory evoked response (see CPB 0181 - Evoked Potential Studies) or otoacoustic emissions;
5. Measurement of blood lead level if the child exhibits developmental delay and pica, or lives in a high-risk environment (see CPB 0553 - Lead Testing); additional periodic lead screening can be considered if the pica persists;
6. Genetic testing specifically high resolution chromosome analysis (karyotype) and DNA analysis for fragile X syndrome in the presence of mental retardation (or if mental retardation can not be excluded) if there is a family history of fragile X or mental retardation of undetermined etiology, or if dysmorphic features are present (see CPB 0140 - Genetic Testing);
7. Comparative genomic hybridization (CGH), when medical necessity criteria are met in CPB 0787 - Comparative Genomic Hybridization (CGH);
8. Medical evaluation (complete medical history and physical examination, including neurologic evaluation);
9. Parent and/or child interview (including siblings of children with autism);
10. Quantitative plasma amino acid assays to detect phenylketonuria;
11. Selective metabolic testing if the child exhibits any of the following:
  1. Clinical and physical findings suggestive of a metabolic disorder:
    1. Cyclic vomiting, recurrent vomiting and dehydration
    2. Early seizure
    3. Lethargy
    4. Hearing impairment
    5. Hypotonia
    6. Visual impairment
    7. Unusual odor; or
  2. Dysmorphic or coarse features; or
  3. Evidence of mental retardation or mental retardation can not be ruled out; or
  4. Occurrence or adequacy of newborn screening for a birth defect is questionable;
12. Genetic counseling for parents of a child with autism (see CPB 0189 - Genetic Counseling);
13. Electroencephalogram (EEG) for clinical spells that might represent seizures;
14. Physical therapy (PT) and/or occupational therapy (OT) evaluations for sensorimotor deficits;
15. Sleep-deprived EEG study only if the child exhibits any of the following conditions:
  1. Clinical seizures; or
  2. High suspicion of subclinical seizures; or
  3. Symptoms of developmental regression (clinically significant loss of social and communicative function) at any age, but especially in toddlers and preschoolers;
16. Video-EEG when criteria are met in CPB 0322 - Electroencephalographic (EEG) Video Monitoring;
17. Pharmacotherapy for management of co-morbidities;
  
  Note: Coverage of pharmacotherapy is subject to the member's specific benefits for drug coverage. Please check benefit plan descriptions for details. Information on pharmacotherapy options for autism can be found in the Background section below.
18. Behavior modification, for management of behavioral co-morbidities;
  
  Note: Interventions for behavioral co-morbidities are covered under the member's behavioral health benefits. Please check benefit plan descriptions for details.
19. Intensive educational interventionsFootnote1* in which the child is engaged in systematically planned and developmentally appropriate educational activity toward identified objectives, including services rendered by a speech-language pathologist to improve communication skills;
  Footnote1* Notes:
  1. Many Aetna plans exclude coverage of educational services. For example, speech therapy or ABA services during class would be excluded under these plans. Please check benefit plan exclusions;
  2. There is insufficient evidence for the superiority of any particular intensive educational intervention strategy (such as applied behavior analysis or other behavioral approaches, educational approaches such as structured teaching (e.g., Treatment and Education of Autistic and Related Communication-Handicapped Children (TEACCH)), social-relational approaches (e.g., Developmental, Individual-differences, Relationship-based (DIR) therapy (DIR floortime therapy), Relationship Development Intervention (RDI) model) or developmental models (e.g., Early Start Denver Model (ESDM)) over other intensive educational intervention strategies. (see CPB 0554 - Applied Behavior Analysis);
20. Alternative and augmentative communication aids (e.g., sign language, flashcards, communication boards, etc.) if demonstrated as effective for the individual with PDD;
  
  Note: Some plans exclude coverage of “communication aids”. Please check benefit plan exclusions.
21. Physical and occupational therapy for co-morbid physical impairments;
22. Medical therapy or psychotherapy, as indicated for co-morbid medical or psychological conditions
  
  Note: Psychotherapy is covered under the member's behavioral health benefits. Please check benefit plan descriptions.
Experimental, Investigational, or Unproven

Aetna considers the following procedures and services experimental, investigational, or unproven because the peer-reviewed medical literature does not support the use of these procedures and services in the assessment and treatment of autism and other pervasive developmental disorders:
1. Assessment
  1. Allergy testing (including food allergy for gluten, casein, candida, and other molds; allergen specific IgG and IgE)
  2. Artificial intelligence-based devices (e.g., Canvas Dx) for diagnosis of ASD
  3. Blood levels of methylation capacity (e.g., methionine , S-adenosylmethionine (SAM), S-adenosylhomocysteine (SAH), and the SAM/SAH ratio) as biomarkers for diagnosis and therapeutic targets of ASD
  4. Blood tests for metabolomic analyses (e.g., NPDX ASD ADM Panel I by NeuroPointDX)
  5. Celiac antibody testing
  6. Ciliary neurotrophic factor (as a biomarker for ASD)
  7. EarliPoint test (an eye-tracking test) for the diagnosis of autism spectrum disorder
  8. Electronystagmography (in the absence of dizziness, vertigo, or balance disorder)
  9. Erythrocyte glutathione peroxidase studies
  10. Event-related brain potentials
  11. GABA receptor polymorphisms testing
  12. Genetic panels other than CGH (e.g., the Fulgent ASD panel, the Greenwood Genetic Center's Syndromic Autism Panel, and the MitoMed-Autism Assay)
  13. Genetic testing for COX10, DRD2, HTR2C, MTHFR, RELN, SLC25A12 and UGT2B15 for diagnosis of autism and other pervasive developmental disorders and their drug treatment
  14. Gut microbiota profiles and nuclear factor kappa B as diagnostic biomarkers of ASD
  15. Hair analysis for trace elements (see CPB 0300 - Hair Analysis)
  16. Homocysteine testing (see CPB 0763 - Homocysteine Testing)
  17. Intestinal permeability studies
  18. Latent class analysis (for determination of psychosis-related clinical profiles in children with autism spectrum disorders)
  19. Magnetoencephalography/magnetic source imaging (see CPB 0279 - Magnetic Source Imaging/Magnetoencephalography)
  20. Measurement of androgen levels (blood, saliva, or urine) for the diagnosis of ASD
  21. Measurement of citrate synthase enzyme activity
  22. Measurements of plasma oxytocin (OXT) and vasopressin (VP) levels
  23. Measurements of plasma central carbon metabolites (e.g., alpha-ketoglutarate, alanine, lactate, phenylalanine, pyruvate, and succinate) (including the NPDX ASD Test (NeuroPointDX))
  24. Measurement of urine oligosaccharides for screening/diagnosis of ASD
  25. Micronutrients (i.e., trace elements, trace minerals or vitamin) level testing
  26. Neuroimaging studies such as CT, functional MRI (fMRI), MRI, MRS (see CPB 0202 - Magnetic Resonance Spectroscopy (MRS)), PET (see CPB 0071 - Positron Emission Tomography (PET)), and SPECT (see CPB 0376 - Single Photon Emission Computed Tomography (SPECT))
  27. Nutritional testing (e.g., testing for arabinose and tartaric acid)
  28. Olfactory function testing
  29. Provocative chelation tests for mercury
  30. Saliva analysis (e.g., Clarifi ASD, Quadrant Biosciences, Inc.)
  31. Serum cytokine and growth factor levels
  32. Stool analysis
  33. Tests for amino acids (except quantitative plasma amino acid assays to detect phenylketonuria), fatty acids (non-esterified), organic acids, citrate, silica, urine vanillylmandelic acid
  34. Tests for glutamatergic candidate genes
  35. Tests for heavy metals (e.g., antimony, arsenic, barium, beryllium, bismuth, mercury)
  36. Tests for immunologic or neurochemical abnormalities
  37. Tests for micronutrients such as vitamin levels
  38. Tests for mitochondrial disorders including lactate and pyruvate
  39. Tests for single-nucleotide polymorphisms within the OXT and VP receptor genes
  40. Tests for trace metals (e.g., aluminum, cadmium, chromium, copper, iron, lead, lithium, magnesium, manganese, nickel, selenium, zinc)
  41. Thyroid function testing
  42. Tympanometry (in the absence of hearing loss)
  43. Urinary peptide testing
  44. Use of biomarkers of mitochondrial dysfunction for the management of ASD
  45. Whole-exome sequencing;
2. Treatments
  1. Acupuncture
  2. Anti-fungal medications (e.g., fluconazole, ketoconizole, metronidazole, nystatin)
  3. Anti-viral medications (e.g., acyclovir, amantadine, famciclovir, isoprinosine, oseltamivir, valacyclovir)
  4. Auditory integration training (auditory integration therapy) (see CPB 0256 - Sensory and Auditory Integration Therapy)
  5. BioMat
  6. Chelation Therapy (see CPB 0234 - Chelation Therapy)
  7. Cognitive rehabilitation (see CPB 0214 - Cognitive Rehabilitation)
  8. Electro-convulsive therapy (for the treatment of autistic catatonia)
  9. Elimination diets (e.g., gluten and milk elimination)
  10. Emotion recognition training
  11. Facilitated communication
  12. GABAergic agents (e.g., acamprosate, arbaclofen, and valproic acid)
  13. Herbal remedies (e.g., astragalus, berberis, echinacea, garlic, plant tannins, uva ursi)
  14. Hippotherapy (See CPB 0151 - Hippotherapy)
  15. Holding therapy
  16. Immune globulin infusion
  17. Manipulative therapies
  18. Massage therapy
  19. Methyl B12
  20. Music therapy and rhythmic entrainment interventions
  21. Memantine
  22. Neurofeedback/EEG biofeedback (see CPB 0132 - Biofeedback)
  23. Nutritional supplements (e.g., dimethylglycine, glutathione, magnesium, megavitamins, omega-3 fatty acids, and high-dose pyridoxine)
  24. Nutritional therapy (e.g., casein-free and gluten-free diets, ketogenic and modified Atkins diets)
  25. Oxytocin
  26. Prebiotic / probiotic therapy
  27. Quantum Reflex Integration
  28. Secretin infusion
  29. Sensory integration therapy (see CPB 0256 - Sensory and Auditory Integration Therapy)
  30. Stem cell transplantation
  31. Systemic hyperbaric oxygen therapy (see CPB 0172 - Hyperbaric Oxygen Therapy (HBOT))
  32. Tomatis sound therapy
  33. Transcranial direct current stimulation
  34. Vestibular stimulation
  35. Vision therapy (see CPB 0489 - Vision Therapy)
  36. Vitamins and minerals (calcium, germanium, magnesium, manganese, selenium, tin, tungsten, vanadium, zinc, etc.)
  37. Weighted blankets or vests.
Policy Limitations and Exclusions

Note: Neuropsychological or psychological testing (see CPB 0158 - Neuropsychological and Psychological Testing) involving standardized parent interviews and direct, structured behavioral observation is considered medically necessary for the diagnosis of pervasive developmental disorders. Diagnostic tools used in conjunction with clinical assessment to establish the diagnosis of autism include Autism Diagnostic Interview-Revised (ADI-R), Autism Diagnostic Observation Schedule-2nd edition (ADOS-2), Childhood Autism Rating Scale 2nd edition (CARS-2) and Asperger Syndrome Diagnostic Scale. Developmental/intelligence testing with separate estimates for verbal and nonverbal skills is considered medically necessary.

Note: Many Aetna plans exclude coverage of educational services. Developmental/intelligence testing in educational settings would be excluded from coverage under these plans. Please check benefit plan exclusions.
Related Policies

Table:
CPT Codes / HCPCS Codes / ICD-10 Codes
Code	Code Description
CPT codes covered if selection criteria are met:
80047	Basic metabolic panel (Calcium, ionized)
80048	Basic metabolic panel (Calcium, total)
80053	Comprehensive metabolic panel
81228	Cytogenomic constitutional (genome-wide) microarray analysis; interrogation of genomic regions for copy number variants (eg, bacterial artificial chromosome [BAC] or oligo-based comparative genomic hybridization [CGH] microarray analysis)
81229	interrogation of genomic regions for copy number and single nucleotide polymorphism (SNP) variants for chromosomal abnormalities
81277	Cytogenomic neoplasia (genome-wide) microarray analysis, interrogation of genomic regions for copy number and loss-of-heterozygosity variants for chromosomal abnormalities
81349	Cytogenomic (genome-wide) analysis for constitutional chromosomal abnormalities; interrogation of genomic regions for copy number and loss-of-heterozygosity variants, low-pass sequencing analysis
83655	Chemistry examination; lead
88245	Chromosome analysis for breakage syndromes; baseline Sister Chromatid Exchange (SCE), 20 - 25 cells
88248	baseline breakage, score 50 - 100 cells, count 20 cells, 2 karyotypes (e.g., for ataxia telangiectasia, Fanconi anemia, fragile X)
88249	score 100 cells, clastogen stress (e.g., diepoxybutane, mitomycin C, ionizing radiation, UV radiation)
88261	Chromosome analysis; count 5 cells, 1 karyotype, with banding
88262	count 15 - 20 cells, 2 karyotypes, with banding
88263	count 45 cells for mosaicism, 2 karyotypes, with banding
88264	analyze 20 - 25 cells
+90785	Interactive complexity (List separately in addition to the code for primary procedure)
90832 - 90840	Psychotherapy
90845 - 90853	Other psychotherapy [covered for co-morbid medical or psychological conditions - not covered for neurofeedback]
92521	Evaluation of speech fluency (eg, stuttering, cluttering)
92522	Evaluation of speech sound production (eg, articulation, phonological process, apraxia, dysarthria)
92523	Evaluation of speech sound production (eg, articulation, phonological process, apraxia, dysarthria); with evaluation of language comprehension and expression (eg, receptive and expressive language)
92524	Behavioral and qualitative analysis of voice and resonance
92605	Evaluation for prescription of non-speech-generating augmentative and alternative communication device
92606	Therapeutic service(s) for the use of non-speech-generating device, including programming and modification
92607	Evaluation for prescription for speech-generating augmentative and alternative communication device, face-to-face with the patient; first hour
+ 92608	each additional 30 minutes (List separately in addition to code for primary procedure)
92609	Therapeutic services for the use of speech-generating device, including programming and modification
92650	Auditory evoked potentials; screening of auditory potential with broadband stimuli, automated analysis
92651	Auditory evoked potentials; for hearing status determination, broadband stimuli, with interpretation and report
92652	Auditory evoked potentials; for threshold estimation at multiple frequencies, with interpretation and report
92653	Auditory evoked potentials; neurodiagnostic, with interpretation and report
95812	Electroencephalogram (EEG) extended monitoring; 41 - 60 minutes [covered for symptoms that may indicate seizures - not EEG biofeedback]
95813	greater than one hour [covered for symptoms that may indicate seizures - not EEG biofeedback]
95816	Electroencephalogram (EEG); including recording awake and drowsy [covered for symptoms that may indicate seizures - not EEG biofeedback]
95819	including recording awake and asleep [covered for symptoms that may indicate seizures - not EEG biofeedback]
95822	recording in coma or sleep only [covered for symptoms that may indicate seizures - not EEG biofeedback]
96110	Developmental screening (eg, developmental milestone survey, speech and language delay screen), with scoring and documentation, per standardized instrument
96112 - 96113	Developmental test administration (including assessment of fine and/or gross motor, language, cognitive level, social, memory and/or executive functions by standardized developmental instruments when performed), by physician or other qualified health care professional, with interpretation and report
96116	Neurobehavioral status exam (clinical assessment of thinking, reasoning and judgment, [eg, acquired knowledge, attention, language, memory, planning and problem solving, and visual spatial abilities]), by physician or other qualified health care professional, both face-to-face time with the patient and time interpreting test results and preparing the report
+96121	each additional hour (List separately in addition to code for primary procedure)
96127	Brief emotional/behavioral assessment (eg, depression inventory, attention-deficit/hyperactivity disorder [ADHD] scale), with scoring and documentation, per standardized instrument
96130 – 96131	Psychological testing evaluation services by physician or other qualified health care professional, including integration of patient data, interpretation of standardized test results and clinical data, clinical decision making, treatment planning and report, and interactive feedback to the patient, family member(s) or caregiver(s), when performed
96132 – 96133	Neuropsychological testing evaluation services by physician or other qualified health care professional, including integration of patient data, interpretation of standardized test results and clinical data, clinical decision making, treatment planning and report, and interactive feedback to the patient, family member(s) or caregiver(s), when performed
96136 – 96137	Psychological or neuropsychological test administration and scoring by physician or other qualified health care professional, two or more tests, any method
96138 – 96139	Psychological or neuropsychological test administration and scoring by technician, two or more tests, any method
96146	Psychological or neuropsychological test administration, with single automated, standardized instrument via electronic platform, with automated result only
96156	Health behavior assessment, or re-assessment (ie, health-focused clinical interview, behavioral observations, clinical decision making)
96158 - 96171	Health behavior intervention
97151 - 97158	Adaptive Behavior Assessments and treatment
97161 - 97168	Physical and occupational therapy evaluation and re-evaluation
CPT codes not covered for indications listed in the CPB:
SLC25A12, Biomat, Growth factor levels, genetic testing for COX10, Plasma oxytocin (OXT), testing of single-nucleotide polymorphisms within the OXT and VP receptor genes, blood levels of methylation capacity (e.g., Met, SAM, SAH and the SAM/SAH ratio as biomarkers for ASD, gut microbiota profiles, nuclear factor kappa B (NF-κB), measurement of citrate synthase enzyme activity, Artificial Intelligence-based devices (e.g., Canvas Dx), Eye tracking studies, EarliPoint test (an eye-tracking test) - no specific code
0063U	Neurology (autism), 32 amines by LC-MS/MS, using plasma, algorithm reported as metabolic signature associated with autism spectrum disorder [metabolomic analysis of blood samples]
0170U	Neurology (autism spectrum disorder [ASD]), RNA, next-generation sequencing, saliva, algorithmic analysis, and results reported as predictive probability of ASD diagnosis
0263U	Neurology (autism spectrum disorder [ASD]), quantitative measurements of 16 central carbon metabolites (ie, α- ketoglutarate, alanine, lactate, phenylalanine, pyruvate, succinate, carnitine, citrate, fumarate, hypoxanthine, inosine, malate, S-sulfocysteine, taurine, urate, and xanthine), liquid chromatography tandem mass spectrometry (LC-MS/MS), plasma, algorithmic analysis with result reported as negative or positive (with metabolic subtypes of ASD)
0322U	Neurology (autism spectrum disorder [ASD]), quantitative measurements of 14 acyl carnitines and microbiome-derived metabolites, liquid chromatography with tandem mass spectrometry (LC-MS/MS), plasma, results reported as negative or positive for risk of metabolic subtypes associated with ASD
38205	Blood-derived hematopoietic cell harvesting for transplantation. per collection; allogeneic
38206 - 38215	Transplant preparation procedures
38230	Bone marrow harvesting for transplantation; allogeneic
38232	autologous
38240	Hematopoietic progenitor cell (HPC); allogeneic transplantation per donor
38241	autologous transplantation
70450	Computed tomography, head or brain; without contrast material
70460	with contrast material(s)
70470	without contrast material, followed by contrast material(s) and further sections
70496	Computed tomographic angiography, head, with contrast material(s), including noncontrast images, if performed, and image postprocessing
70544	Magnetic resonance angiography, head; without contrast material(s)
70545	with contrast material(s)
70546	without contrast material(s), followed by contrast material(s) and further sequences
70551	Magnetic resonance (e.g., proton) imaging, brain (including brain stem); without contrast material
70552	with contrast material(s)
70553	without contrast material, followed by contrast material(s) and further sequences
76390	Magnetic resonance spectroscopy
78600	Brain imaging, less than 4 static views
78601	with vascular flow
78605	Brain imaging, minimum 4 static views
78606	with vascular flow
78608	Brain imaging, positron emission tomography (PET); metabolic evaluation
78609	perfusion evaluation
80178	Lithium
81291	Methylenetetrahydrofolate Reductase (MTHFR), DNA Mutation
81415	Exome (eg, unexplained constitutional or heritable disorder or syndrome); sequence analysis
81416	sequence analysis, each comparator exome (eg, parents, siblings) (List separately in addition to code for primary procedure)
81417	re-evaluation of previously obtained exome sequence (eg, updated knowledge or unrelated condition/syndrome)
82108	Aluminum
82136	Amino acids, 2 to 5 amino acids, quantitative, each specimen
82139	Amino acids, 6 or more amino acids, quantitative, each specimen
82180	Ascorbic acid (Vitamin C), blood
82300	Cadmium
82306	Calcifediol (25-OH Vitamin D-3)
82310	Calcium; total
82495	Chromium
82507	Citrate
82525	Copper
82607	Cyancobalamin (Vitamin B-12)
82608	unsaturated binding capacity
82652	Vitamin D; 1, 25 dihydroxy, includes fraction(s), if performed
82725	Fatty acids, nonesterified
82726	Very long chain fatty acids
82746	Folic acid; serum
82747	RBC
82784	Gammaglobulin; IgA, IgD, IgG, IgM, each [for celiac antibodies]
82785	Gammaglobulin; IgE
83015	Heavy metal (e.g., arsenic, barium, beryllium, bismuth, antimony, mercury); screen
83018	quantitative, each
83090	Homocysteine
83516	Immunoassay for analyte other than infectious agent antibody or infectious agent antigen; qualitative or semiquantitative, multiple step method
83518	qualitative or semiquantitative, single step method (eg, reagent strip)
83519	quantitative, by radioimmunoassay (eg, RIA)
83520	not otherwise specified [for celiac antibodies]
83540	Iron
83550	Iron binding capacity
83605	Lactate (lactic acid)
83655	Lead
83735	Magnesium
83785	Manganese
83885	Nickel
83918	Organic acids; total, quantitative, each specimen
83919	qualitative, each specimen
83921	Organic acid, single, quantitative [not covered for tartaric acid nutritional testing]
84030	Phenylalanine (PKU), blood
84100	Phosphorus inorganic (phosphate)
84105	urine
84207	Pyridoxal phosphate (Vitamin B-6)
84210	Pyruvate
84252	Riboflavin (Vitamin B-2)
84255	Selenium
84285	Silica
84375 - 84379	Sugars [not covered for nutritional or arabinose testing]
84425	Thiamine (Vitamin B-1)
84443	Thyroid stimulating hormone (TSH)
84446	Tocopherol alpha (Vitamin E)
84479	Thyroid hormone (T3 or T4) uptake or thyroid hormone binding ratio (THBR)
84585	Vanillylmandelic acid (vma), urine
84588	Vasopressin (antidiuretic hormone, ADH)
84590	Vitamin A
84591	Vitamin, not otherwise specified
84597	Vitamin K
84600	Volatiles (eg, acetic anhydride, diethylether)
84630	Zinc
86001	Allergen specific IgG quantitative or semi-quantitative, each allergen
86003	Allergen specific IgE; quantitative or semi-quantitative, each allergen
86005	qualitative, multi-allergen screen (dipstick, paddle or disk)
86051	Aquaporin-4 (neuromyelitis optica [NMO]) antibody; enzyme-linked immunosorbent immunoassay (ELISA)
86052	cell-based immunofluorescence assay (CBA), each
86053	flow cytometry (ie, fluorescence-activated cell sorting [FACS]), each
86140	C-reactive protein
86160	Complement; antigen, each component
86161	functional activity, each component
86162	total hemolytic (CH50)
86231	Endomysial antibody (EMA), each immunoglobulin (Ig) class
86255	Fluorescent noninfectious agent antibody; screen, each antibody
86256	titer, each antibody
86332	Immune complex assay
86343	Leukocyte histamine release test (LHR)
86485	Skin test; candida
86628	Antibody; candida
88341 - 88344	Immunohistochemistry or immunocytochemistry, per specimen
88346	Immunofluorescence, per specimen; initial single antibody stain procedure
88350	Immunofluorescence, per specimen; each additional single antibody stain procedure (List separately in addition to code for primary procedure
90281	Immune globulin (Ig), human, for intramuscular use
90283	Immune globulin (IgIV), human, for intravenous use
90870	Electroconvulsive therapy (includes necessary monitoring) [for the treatment of autistic catatonia]
90901	Biofeedback training by any modality [neurofeedback/EEG biofeedback]
92065	Orthopic and/or pleoptic training, with continuing medical direction and evaluation
92507	Treatment of speech, language, voice, communication, and/or auditory processing disorder; individual
92508	group, 2 or more individuals
92540	Basic vestibular evaluation, includes spontaneous nystagmus test with eccentric gaze fixation nystagmus, with recording, positional nystagmus test, minimum of 4 positions, with recording, optokinetic nystagmust test, bidirectional foveal and peripheral stimulation, with recording, and oscillating tracking test, with recording
92541 - 92548	Vestibular function tests, with recording (e.g., ENG, PENG), and medical diagnostic evaluation
92550	Tympanometry and reflex threshhold measurements
92567	Tympanometry (impedance testing)
92568 - 92569	Acoustic reflex testing
92570	Acoustic immittance testing, includes typanometry (impedance testing), acoustic reflex threshold testing, and acoustic reflex decay testing
95004	Percutaneous tests (scratch, puncture, prick) with allergenic extracts, immediate type reaction, including test interpretation and report by a physician, specify number of tests
95017	Allergy testing, any combination of percutaneous (scratch, puncture, prick) and intracutaneous (intradermal), sequential and incremental, with venoms, immediate type reaction, including test interpretation and report, specify number of tests
95018	Allergy testing, any combination of percutaneous (scratch, puncture, prick) and intracutaneous (intradermal), sequential and incremental, with drugs or biologicals, immediate type reaction, including test interpretation and report, specify number of tests
95024	Intracutaneous (intradermal) tests with allergenic extracts, immediate type reaction, including test interpretation and report by a physician, specify number of tests
95027	Intracutaneous (intradermal) tests, sequential and incremental, with allergenic extracts for airborne allergens, immediate type reaction, including test interpretation and report by a physician, specify number of tests
95028	Intracutaneous (intradermal) tests with allergenic extracts, delayed type reaction, including reading, specify number of tests
95044	Patch or application test(s) (specify number of tests)
95052	Photo patch test(s) (specify number of tests)
95056	Photo tests
95060	Ophthalmic mucous membrane tests
95065	Direct nasal mucous membrane tests
95070	Inhalation bronchial challenge testing (not including necessary pulmonary function tests); with histamine, methacholine, or similar compounds
95071	with antigens or gases, specify
95076	Ingestion challenge test (sequential and incremental ingestion of test items, eg, food, drug or other substance); initial 120 minutes of testing
+95079	Ingestion challenge test (sequential and incremental ingestion of test items, eg, food, drug or other substance); each additional 60 minutes of testing (List separately in addition to code for primary procedure)
95961	Functional cortical and subcortical mapping by stimulation and/or recording of electrodes on brain surface, or of depth electrodes, to provoke seizures or identify vital brain structures; initial hour of physician attendance
+ 95962	each additional hour of physician attendance (List separately in addition to code for primary procedure)
95965	Magnetoencephalography (MEG), recording and analysis; for spontaneous brain magnetic activity (e.g., epileptic cerebral cortex localization)
95966	for evoked magnetic fields, single modality (e.g., sensory, motor, language, or visual cortex localization)
+ 95967	for evoked magnetic fields, each additional modality (e.g., sensory, motor, language, or visual cortex localization) (List separately in addition to code for primary procedure)
96020	Neurofunctional testing selection and administration during noninvasive imaging functional brain mapping, with test administered entirely by a physician or other qualified health care professional (ie, psychologist), with review of test results and report
96125	Standardized cognitive performance testing (eg, Ross Information Processing Assessment) per hour of a qualified health care professional's time, both face-to-face time administering tests to the patient and time interpreting these test results and preparing the report
96902	Microscopic examination of hairs plucked or clipped by the examiner (excluding hair collected by the patient) to determine telogen and anagen counts, or structural hair shaft abnormality
97124	Therapeutic procedure, one or more areas, each 15 minutes; massage, including effleurage, petrissage and/or tapotement (stroking, compression, percussion)
97129	Therapeutic interventions that focus on cognitive function (eg, attention, memory, reasoning, executive function, problem solving, and/or pragmatic functioning) and compensatory strategies to manage the performance of an activity (eg, managing time or schedules, initiating, organizing, and sequencing tasks), direct (one-on-one) patient contact; initial 15 minutes
+97130	each additional 15 minutes (List separately in addition to code for primary procedure)
97140	Manual therapy techniques (e.g., mobilization/manipulation, manual lymphatic drainage, manual traction), one or more regions, each 15 minutes
97530	Therapeutic activities, direct (one-on-one) patient contact (use of dynamic activities to improve functional performance), each 15 minutes
97533	Sensory integrative techniques to enhance sensory processing and promote adaptive responses to environmental demands, direct (one-on-one) patient contact, each 15 minutes
97802 - 97804	Medical nutrition therapy
97810 - 97814	Acupuncture
98925 - 98929	Osteopathic manipulative treatment (OMT)
98940 - 98943	Chiropractic manipulative treatment (CMT)
99183	Physician or other qualified health care professional attendance and supervision of hyperbaric oxygen therapy, per session
Other CPT codes related to the CPB:
0362T	Behavior identification supporting assessment, each 15 minutes of technicians' time face-to-face with a patient, requiring the following components: administration by the physician or other qualified health care professional who is on site; with the assistance of two or more technicians; for a patient who exhibits destructive behavior; completion in an environment that is customized to the patient's behavior
0373T	Adaptive behavior treatment with protocol modification, each 15 minutes of technicians' time face-to-face with a patient, requiring the following components: administration by the physician or other qualified health care professional who is on site; with the assistance of two or more technicians; for a patient who exhibits destructive behavior; completion in an environment that is customized to the patient's behavior
97010 - 97546	Modalities and therapeutic procedures
98960	Education and training for patient self-management by a qualified, nonphysician health care professional using a standardized curriculum, face-to-face with the patient (could include caregiver/family) each 30 minutes; individual patient
98961	2-4 patients
98962	5-8 patients
99201 - 99215	Office or other outpatient visit
HCPCS codes covered if selection criteria are met:
E1902	Communication board, non-electronic augmentative or alternative communication device
E2500 - E2599	Speech generating devices
V5008	Hearing screening
V5362	Speech screening
V5363	Language screening
HCPCS codes not covered for indications listed in the CPB:
A4575	Topical hyperbaric oxygen chamber, disposable
A9152	Single vitamin/mineral/trace element, oral, per dose, not otherwise specified [omega-3 fatty acid supplements]
E0446	Topical oxygen delivery system, not otherwise specified, includes all supplies and accessories
G0068	Professional services for the administration of anti-infective, pain management, chelation, pulmonary hypertension, and/or inotropic infusion drug(s) for each infusion drug administration calendar day in the individual's home, each 15 minutes
G0176	Activity therapy, such as music, dance, art or play therapies not for recreation, related to the care and treatment of patient's disabling mental health problems, per session (45 minutes or more)
G0277	Hyperbaric oxygen under pressure, full body chamber, per 30 minute interval
G0515	Development of cognitive skills to improve attention, memory, problem solving (includes compensatory training), direct (one-on-one) patient contact, each 15 minutes
J0600	Injection, edetate calcium disodium, up to 1000 mg
J0610	Injection, calcium gluconate, per 10 ml
J0612	Injection, calcium gluconate (fresenius kabi), per 10 mg
J0613	Injection, calcium gluconate (wg critical care), per 10 mg
J0620	Injection, calcium glycerophosphate and calcium lactate, per 10 ml
J0133	Injection, acyclovir, 5 mg
J1450	Injection, fluconazole, 200 mg
J1561	Injection, immune globulin, (Gamunex/Gamunex-C/Gammaked), nonlyophilized (e.g., liquid), 500 mg
J1566	Injection, immune globulin, intravenous, lyophilized (e.g., powder), not otherwise specified, 500 mg
J1568	Injection, immune globulin, (Octagam), intravenous, nonlyophilized (e.g., liquid), 500 mg
J1569	Injection, immune globulin, (Gammagard liquid), nonlyophilized, (e.g., liquid), 500 mg
J1572	Injection, immune globulin, (Flebogamma), intravenous, nonlyophilized (e.g., liquid), 500 mg
J1836	Injection, metronidazole, 10 mg
J2590	Injection, oxytocin, up to 10 units
J2850	Injection, secretin, synthetic, human, 1mcg
J3415	Injection, pyridoxine HCl, 100 mg
J3420	Injection, vitamin B-12 cyanocobalamin, up to 1,000 mcg [methyl B12]
J3475	Injection, magnesium sulphate, per 500 mg
P2031	Hair analysis (excluding arsenic)
S0030	Injection, metronidazole, 500 mg
S8035	Magnetic source imaging
S8040	Topographic brain mapping
S8940	Equestrian/Hippotherapy, per session
S9355	Home infusion therapy, chelation therapy; administrative services, professional pharmacy services, care coordination, and all necessary supplies and equipment (drugs and nursing visits coded separately), per diem
S9470	Nutritional counseling, dietitian visit
Other HCPCS codes related to the CPB:
G0151	Services performed by a qualified physical therapist in the home health or hospice setting, each 15 minutes
G0153	Services performed by a qualified speech-language pathologist in the home health or hospice setting, each 15 minutes
G0161	Services performed by a qualified speech-language pathologist, in the home health setting, in the establishment or delivery of a safe and effective speech-language pathology maintenance program, each 15 minutes
S9128	Speech therapy, in the home, per diem
S9129	Occupational therapy, in the home, per diem
S9131	Physical therapy, in the home, per diem
T1029	Comprehensive environmental lead investigation, not including laboratory analysis, per dwelling
ICD-10 codes covered if selection criteria are met:
F84.0 - F84.9	Pervasive developmental disorders
Z13.41	Encounter for autism screening
ICD-10 codes not covered for indications listed in the CPB (not all-inclusive):
E88.40 – E88.49	Mitochondrial metabolism disorders [Mitochondrial dysfunction]

Background

Autism spectrum disorders (ASD) are a group of biologically based chronic neurodevelopmental disorders characterized by impairments in two major domains:

deficits in social communication and social interaction and
restricted repetitive patterns of behavior, interests and activities.

The exact cause is unknown, but is believed to have many factors, including a strong genetic component.

Signs and symptoms of ASD generally appear prior to three years of age and include difficulties with language, deficient social skills and restricted or repetitive body movements and behaviors. Autism and other autism spectrum disorders (ASD) may be suspected by the following symptoms: any loss of any language or social skills at any age; no 2-word spontaneous (not just echolalic) phrases by 24 months; no babbling by 12 months; no gesturing (e.g., pointing, waving bye-bye) by 12 months; or no single words by 16 months.

Autism spectrum disorders (ASD) include autism, childhood disintegrative disorder and Asperger’s syndrome, and are chronic life-long conditions. Autism has been estimated to affect approximately 1 in 1,000 children in the United States, and other pervasive developmental disorders have been estimated to affect approximately 2 in 1,000 children in the United States. Based on recent prevalence estimates of 10 to 20 cases per 10,000 individuals, between 60,000 and 115,000 children under the age of 15 years meet diagnostic criteria for autism.

There is no cure for ASD. However, there is a consensus that treatment must be individualized depending upon the specific strengths, weaknesses and needs of the child and family. Early diagnosis and early intensive treatment have the potential to affect outcome, particularly with respect to behavior, functional skills and communication. There is increasing evidence that intervention is more effective when initiated as early as possible.

Diagnosis and treatment of ASD may involve a variety of tools. Developmental screening, usually performed during a routine well child exam, identifies atypical (unusual) behaviors such as social, interactive and communicative behaviors that are delayed, abnormal or absent. Once identified, a comprehensive multidisciplinary assessment is recommended in order to make an accurate and appropriate diagnosis.

Appropriate certified/licensed healthcare professionals for evaluation and management of autism include the following: board certified behavioral analyst; developmental pediatrician; neurologist; occupational therapist; physical therapist; primary care provider; psychiatrist; psychologist; or speech-language pathologist and audiologist.

According to the American Academy of Neurology (AAN)'s practice parameter, Screening and Diagnosis of Autism (Filipek et al, 2000), autism is characterized by severe deficiencies in reciprocal social interaction, verbal and non-verbal communication, and restricted interests. It usually commences before the age of 3 years and lasts over the whole lifetime. Early signs that distinguish autism from other atypical patterns of development include poor use of eye gaze, lack of gestures to direct other people's attention (especially to show things of interest), decreased social responsiveness, and lack of age-appropriate play with toys (especially imaginative use of toys). A typical symptom of autism is absence of speech development, observed from infancy, taking the form of complete mutism at later stages. It has been emphasized that most pathological symptoms of autism result from altered perception of external stimuli, which arouse fear and anxiety. Currently, there are no biological markers for autism and there is no proven cure for this disorder.

Because there are no biological markers for autism, screening must focus on behavior. Studies comparing autistic and typically developing children demonstrated that problems with eye contact, orienting to one’s name, joint attention, pretend play, imitation, non-verbal communication, and language development are measurable by 18 months of age. These symptoms are stable in children from toddler age through preschool age. Retrospective analysis of home videotapes also has identified behaviors that distinguish infants with autism from other developmental disabilities as early as 8 months of age.

Current screening methods may not identify children with milder variants of autism, those without mental retardation or language delay, such as verbal individuals with high-functioning autism and Asperger’s disorder, or older children, adolescents, and young adults.

There are relatively few appropriately sensitive and specific autism screening tools for infants and toddlers, and this continues to be the current focus of many research centers. The Checklist for Autism in Toddlers (CHAT) for 18-month-old infants, and the Autism Screening Questionnaire for children 4 years of age and older, have been validated on large populations of children. However, it should be noted that the CHAT is less sensitive to milder symptoms of autism, as children later diagnosed with PDD-NOS, Asperger’s, or atypical autism did not yield positive results on the CHAT at 18 months.

The AAN’s practice parameter noted that specific neuropsychological impairments can be identified, even in young children with autism, that correlate with the severity of autistic symptoms. Performance on tasks that rely on rote, mechanical, or perceptual processes are typically spared; deficient performance exists on tasks requiring higher-order conceptual processes, reasoning, interpretation, integration, or abstraction. Dissociations between simple and complex processing are reported in the areas of language, memory, executive function, motor function, reading, mathematics, and perspective-taking. However, there is no reported evidence that confirms or excludes a diagnosis of autism based on these cognitive patterns alone.

The AAN’s practice parameter recommended that diagnosis of autism should include the use of standardized parent interviews regarding current concerns and behavioral history related to autism, and direct, structured observation of social and communicative behavior and play. Recommended instruments for parental interviews include the Gilliam Autism Rating Scale, Parent Interview for Autism, Pervasive Developmental Disorders Screening Test–Stage 3, and Autism Diagnostic Interview–Revised. Recommended instruments for observation include the Childhood Autism Rating Scale, Screening Tool for Autism in Two-Year-Old, and Autism Diagnostic Observation Schedule-Generic. The AAN practice parameter did not recommend that neuropsychological testing be used for the diagnosis of autism, but instead should be performed as needed, in addition to a cognitive assessment, to assess social skills and relationships, educational functioning, problematic behaviors, learning style, motivation and reinforcement, sensory functioning, and self-regulation.

Similarly, the American Academy of Child And Adolescent Psychiatry (AACAP)’s practice parameter for the assessment and treatment of autism recommended neuropsychological testing only when the clinical context indicates that it may be helpful. Psychological testing is recommended in the AACAP practice parameter to assess for cognitive and intellectual functioning, in order to determine eligibility and plan for educational and other services.

Mental retardation (IQ less than 70) is associated with 70 % of cases of autism and seizures with 33 % of cases. Furthermore, the recurrence risk for siblings is about 3 to 5 %, corresponding to an incidence 75 times greater than that in the general population. These features, in conjunction with the increased number of male patients (3:1 male:female ratio), suggest a genetic predisposition. On the other hand, parallel evidence of immune abnormalities in autistic patients argues for an implication of the immune system in pathogenesis. Additionally, some neurological disorders such as tuberous sclerosis, neurofibromatosis, fragile X syndrome, and phenylketonuria may also be associated with autistic features. In these cases, autism is defined as "secondary".

The AAN's practice parameter Screening and Diagnosis of Autism (Filipek et al, 2000) recommended genetic testing in children with autism, specifically high resolution chromosome analysis (karyotype) and DNA analysis for fragile X syndrome in the presence of mental retardation (or if mental retardation can not be excluded), if there is a family history of fragile X or undiagnosed mental retardation, or if dysmorphic features are present. However, there is little likelihood of positive karyotype or fragile X testing in high-functioning autism.

An assessment prepared for the Agency for Healthcare Research and Quality (Sun et al, 2015) on genetic testing for developmental disability, intellectual disability and autism spectrum disorders concluded that "little evidence from controlled studies exists to directly link genetic testing to health outcomes. Published studies have reported superior diagnostic yields of newer genetic tests (e.g., aCGH) in identifying DD-related genetic abnormalities, and some have identified the impact of the tests on medical management (e.g., medical referrals, diagnostic imaging, further laboratory testing). However, these findings are not sufficient for drawing a conclusion that use of the tests will lead to improved health outcomes ...."

The AAN (Filipek et al, 2000) recommended selective metabolic testing if the child exhibits clinical and physical findings suggestive of a metabolic disorder such as

lethargy, cyclic vomiting, or early seizure, or
dysmorphic or coarse features, or
evidence of mental retardation, or
mental retardation can not be ruled out, or
occurrence or adequacy of newborn screening for a birth defect is questionable.

The AAN also recommended lead screening if the child exhibits developmental delay and pica.

Epileptiform abnormalities on electroencephalography (EEG) are common in children with autism spectrum disorders (ASDs), with reported frequencies ranging from 10 % to 72 % (AAP, 2007). Some studies have suggested that epileptiform abnormalities on EEG and/or epilepsy are more common in the subgroup of children with ASDs who have a history of regression, whereas other studies have not demonstrated this association. Autistic regression with epileptiform abnormalities on EEG has been compared by analogy with Landau-Kleffner syndrome and electrical status epilepticus in sleep, but there are important differences between these conditions, and the treatment implications are unclear (AAP, 2007). Whether subclinical seizures have adverse effects on language, cognition, and behavior is debated, and there is no evidence-based recommendation for the treatment of children with ASDs and epileptiform abnormalities on EEG, with or without regression. A report from the American Academy of Pediatrics (AAP, 2007) states that universal screening of patients with ASDs by EEG in the absence of a clinical indication is not currently supported. The report states, however, that because of the increased prevalence of seizures in this population, a high index of clinical suspicion should be maintained, and EEG should be considered when there are clinical spells that might represent seizures.

Localized structural and functional brain correlates of PDD have yet to be established. Structural neuroimaging studies performed in autistic patients have reported abnormalities such as increased total brain volume and cerebellar abnormalities. However, none of these abnormalities fully account for the full range of autistic symptoms. Functional neuroimaging has demonstrated temporal lobe abnormalities and abnormal interaction between frontal and parietal brain areas. However, the value of functional neuroimaging such as positron emission tomography (PET), single photon emission computed tomography (SPECT) and functional magnetic resonance imaging (fMRI) in diagnosing autism has not been established. Functional neuroimaging techniques are at the early stage of identifying abnormalities at the neurotransmitter and systems levels. Further studies with well-defined patient populations and appropriate activation paradigms will better elucidate the pathophysiology of this disorder.

The AAN (Filipek et al, 2000) stated that there is no clinical evidence to support the role of routine clinical neuroimaging (CT, MRI, PET SPECT, and fMRI) in the diagnostic evaluation of autism, even in the presence of megalocephaly. Additionally, the AAN stated that there is insufficient evidence to recommend EEG studies in all individuals with autism. Sleep-deprived EEG study may be performed if

the patient has clinical seizures or suspicion of subclinical seizures; or
a history of regression (clinically significant loss of social and communicative function) at any age, but especially in toddlers and preschoolers.

Moreover, the AAN considered event-related potentials and magnetoencephalography to be research tools, which have no evidence of routine clinical utility (Filipek et al, 2000).

Philip and colleagues (2012) stated that recent years have seen a rapid increase in the investigation of ASD through the use of fMRI. These investigators performed a systematic review and ALE meta-analysis of fMRI studies of ASD. A disturbance to the function of social brain regions is among the most well replicated finding. Differences in social brain activation may relate to a lack of preference for social stimuli as opposed to a primary dysfunction of these regions. Increasing evidence points towards a lack of effective integration of distributed functional brain regions and disruptions in the subtle modulation of brain function in relation to changing task demands in ASD. The authors stated that limitations of the literature to date include the use of small sample sizes and the restriction of investigation to primarily high-functioning males with autism.

The AAN (Filipek et al, 2000) also found inadequate supporting evidence of the following procedures in the management of autism:

allergy testing (especially food allergy for gluten, casein, candida, and other molds),
erythrocyte glutathione peroxidase studies,
hair analysis,
intestinal permeability studies,
stool analysis, and
tests for celiac antibodies, immunologic or neurochemical abnormalities, micronutrients such as vitamin levels, mitochondrial disorders including lactate and pyruvate, thyroid function, and urinary peptides.

Hair Analysis is a test in which a sample of an individual's hair, typically from the back of the neck, is sent to a laboratory for measurement of its mineral content. The AAN (Filipek et al, 2000) found inadequate supporting evidence for hair analysis for treatment of autism.

Autistic patients may suffer from gastrointestinal disturbances such as abdominal pains, diarrhea, and the so-called leaky-gut syndrome. Secretin, a hormone produced by the pancreas to stimulate the production of gastric juices, has been used to aid digestion before intestinal biopsy or endoscopy. Secretin is a hormone made in the duodenum which causes the stomach to make pepsin, the liver to make bile and the pancreas to make a digestive juice. Early case studies suggested that secretin improved gastrointestinal symptoms as well as behavior, eye contact, alertness, and expressive language in autistic children. However, such claims are not borne out by recent well-designed studies.

A randomized, double blind, placebo-controlled, cross-over study (Corbett et al, 2001) investigated the effect of a single intravenous dose of porcine secretin on autistic children. The authors found that significant differences were not observed on the majority of the dependent variables. Statistically significant differences were observed on measures of positive affect and activity level following secretin infusion. In general, autistic children did not demonstrate the improvements described in the initial retrospective report. This is in agreement with the findings of Owley and colleagues (2001) who reported that there was no evidence for efficacy of secretin in a multi-center, randomized, placebo-controlled, double-blind trial. In a single-blinded, prospective, open-label study, Lightdale and associates (2001) reported that intravenous secretin had no effects in a 5-week period on the language and behavior of 20 children with autism and gastrointestinal symptoms.

The National Academy of Sciences (NAS) (2001) has stated that there is no known cure for autism, and that "[e]ducation, both directly of children, and of parents and teachers, is currently the primary form of treatment for autistic spectrum disorders." The National Academy of Sciences recommends that educational services begin as soon as a child is suspected of having autistic spectrum disorder, and that those services should include a minimum of 25 hours a week, 12 months a year, in which the child is engaged in systematically planned and developmentally appropriate educational activity toward identified objectives. Brasic (2003) has stated that, while parents may choose to utilize a variety of experimental treatments including medication, they should concurrently utilize intensive individual special education by an educator familiar with instructing children with autistic disorder and related conditions.

The NAS report concluded that "there is little evidence concerning the effectiveness of discipline-specific therapies, and there are no adequate comparisons of different comprehensive treatments. However, there is substantial research supporting the effectiveness of many specific therapeutic techniques and of comprehensive programs in contrast to less intense, nonspecific interventions." "The consensus across programs is generally strong concerning the need for: early entry into an intervention program; active engagement in intensive instructional programming for the equivalent of a full school day, including services that may be offered in different sites, for a minimum of 5 days a week with full-year programming; use of planned teaching opportunities, organized around relatively brief periods of time for the youngest children (e.g., 15- to 20-minute intervals); and sufficient amounts of adult attention in one-to-one or very small group instruction to meet individualized goals."

The NAS report concluded that functional communication training has been shown to be effective in treatment of autism: "There is strong empirical support for the efficacy of functional communication training to replace challenging behaviors. This approach includes a functional assessment of the particular behavior to determine its function for a child (e.g., desire for tangible or sensory item, attention, or to escape a situation or demand) and teaching communication skills that serve efficiently and effectively as functional equivalents to challenging behaviors, a method that has been documented to be the most effective for reductions in challenging behavior (Horner et al, 1990; see Horner et al, 2000)."

The NAS report also concluded that there is evidence to support the use of augmentative and alternative communication strategies (AAC) in children with autism. "For children with autism who do not acquire functional speech or have difficulty processing and comprehending spoken language, augmentative and alternative communication (AAC) and assistive technology (AT) can be useful components of an educational program." "AAC is defined as ’an area of clinical practice that attempts to compensate (either temporarily or permanently) for the impairment and disability patterns of individuals with severe expressive communication disorders’ (American Speech-Language-Hearing Association, 1989). AAC may involve supporting existing speech or developing independent use of a non-speech symbol system, such as sign language, visual symbols (pictures and words) displayed on communication boards, and voice output devices with synthesized and digitized speech. AT is any commercial, hand-made, or customized device or service used to support or enhance the functional capabilities of individuals with disabilities. AT includes computer-assisted instruction, mobility devices, high and low technology adaptations and AAC."

A structured evidence assessment of interventions in alternative and augmentative communication (ACC) (training to compensate for the impairment and disability patterns) in persons with severe expressive communication disorders (including autism, mental retardation, and other disabilities) concluded that ACC interventions are effective in terms of behavior change, generalization, and, to a lesser degree, maintenance (Schlosser and Lee, 2000).

A number of discipline-specific intensive intervention programs have been advocated for the treatment of autism, including Lovaas therapy, the Rutgers Program, the LEAP Program, the Denver Program, the Autism Pre-school Program, and TEACCH Program. The objectives of treatment are to improve the child's early social communication and social interaction skills, leading to the potential development of play and flexibility of behavior. The NAS (2001) concluded that, although there is substantial research supporting the effectiveness of comprehensive programs in contrast to less intense, non-specific interventions, "there is little evidence concerning the effectiveness of discipline-specific therapies, and there are no adequate comparisons of different comprehensive treatments."

Lovaas therapy is a method of early behavioral intervention for the treatment of PDD. It entails the employment of intensive teaching techniques designed to reinforce appropriate social behaviors in children with autism and related disorders. Every task (trial) consists of a directive to the patient, a response from the patient, and a reaction from the therapist. The patient learns to respond in a manner that generates reinforcement reaction from the therapist. Lovaas therapy is usually practiced 30 to 40 hours a week.

Lovaas therapy was based on a study by Lovaas published in 1987; however, the study had several problems which include

choice of outcome measure,
criteria for subject selection and the intellectual level of the subjects, and
method for assigning subjects to control groups.

These methodological problems made it difficult to ascertain the effects of early behavioral intervention on autistic children. Recent reviews suggested that there is no available treatment that meets criteria for well-established or probably efficacious treatment; and that more research is needed to refine current behavioral treatment approaches.

Delprato (2001) compared discrete trial training (Lovaas Therapy) and normalized behavioral language intervention for young children with autism. The author reported that in studies with language criterion responses, normalized language training was more effective than discrete trial training. Furthermore, in studies that assessed parental affect, normalized treatment yielded more positive affect than discrete trial training.

Boyd and Corley (2001) reported the outcome survey of early intensive behavioral intervention (EIBI) programs for young children with autism in a community setting. Based on both individual case reviews and parent questionnaires, they found that these programs failed to support any instances of "recovery", but yielded a high degree of parental satisfaction. Moreover, a follow-up inquiry into the type of services each child was receiving in his or her post-EIBI setting documented continued dependence on extensive educational and related developmental services, suggesting that the promise of future treatment sparing did not materialize. The authors concluded that there is a need for further research designed to document the effectiveness of services provided to young children with autism.

The Alberta Heritage Foundation for Medical Research (AHFMR) evaluated the effectiveness of intensive intervention programs for children with autism (Ludwig and Harstall, 2001). These programs range from strict operant discrimination learning such as Lovaas therapy to broader applied behavior analysis such as the Rutgers Program to more developmentally oriented programs such as the Denver Program and the Treatment and Education of Autistic and Communication Handicapped Children (TEACCH) Program. Furthermore, these treatment programs vary in their intensity from 40 hours per week for Lovaas Therapy and the Rutgers Program to a range of 15 hours per week for the LEAP Program.

The evaluation by AHFMR was primarily based on the results of 3 systematic evidence reviews, including those by ECRI (2000) and the British Columbia Office of Health Technology Assessment (BCOHTA) (Bassett, 2000). Two of the critical findings of this assessment are as follows:

studies on Lovaas therapy were methodologically flawed. ECRI concluded that Lovaas Therapy appears to increase scores on IQ tests and behavioral adaptation, at least in some children with autism. However, given the designs and methodological flaws of the studies, it could not be determined if the changes in IQ and functional parameters could be attributed to the Lovaas therapy. BCOHTA concluded that the original Lovaas study as well as other follow-up studies were still inadequate to establish the degree to which this form of therapy resulted in "normal" children, and
there is insufficient evidence to establish a relationship between amount (intensity and duration) of any intensive intervention treatment program and outcomes measures (intelligence tests, language development, adaptive behavior tests).

Smith (1999) evaluated the evidence supporting intensive intervention programs for autism. Smith noted that most reports of major gains made by children with autism have "withered under scrutiny". Smith emphasized the need to validate the long-term benefits of these intervention programs. Smith noted that most studies of specific intensive intervention programs do not provide data on the children’s progress following termination of treatment. Smith noted that this is a critical omission because even if treatment is successful while ongoing, the benefits may not be durable. Smith concluded that methodological weaknesses in the research hinder us from drawing conclusions from existing early intervention studies.

An assessment of intensive intervention programs for autism by the Canadian Coordinating Office for Health Technology Assessment (CCOHTA) (McGahan, 2001) concluded that "there are few published controlled primary studies regarding the efficacy of behavioral interventions; most have methodological flaws that make interpretation of results difficult. Study design in this area could benefit from the inclusion of an adequate control group and the application of consistent outcome measures used for all children enrolled in a study, administered by the same, blinded assessor at the beginning and end of the study."

In assessing the evidence supporting specific intensive intervention programs for children with autism, the NAS (2001) concluded that "[a]s a group, these studies show that intensive early interventions with children with autistic spectrum disorders makes a clinically significant difference for many children …. However, each of the studies has methodological weaknesses, and most of the reports were descriptive rather than evaluations with controlled experimental research designs. There are virtually no data on the relative merit of one model over another, either overall or as related to individual differences in children …. In sum, it appears that a majority of children participating in comprehensive behavioral interventions made significant progress in at least some developmental domains, although methodological limitations preclude definitive attributions of that progress to specific intervention procedures".

A New Zealand Health Technology Assessment (Doughty, 2004) reviewed the conclusions of 5 recently published systematic evidence reviews of intensive behavioral interventions for autism-spectrum disorders. The assessment found that all of these systematic evidence reviews draw attention to the lack of well-conducted research on early intervention for autism in young children. The assessment found that all of the systematic evidence reviews reached the same conclusion, that "to date there is insufficient evidence to allow conclusions to be drawn about best practice. Furthermore, researchers have yet to establish a relationship between the amount (per day and total duration) of any form of early comprehensive treatment program and overall outcome." The New Zealand Health Technology Assessment also reviewed recently published primary research on intensive behavioral interventions for autism. The assessment found that, despite the relatively large volume of studies published and extent of interest of a variety of stakeholders in the effectiveness of interventions for young children with autism, only 5 primary studies published since 2000 met selection criteria for relevance and methodological quality. The assessment concluded that these studies provide preliminary evidence suggesting that early intervention (note this includes different types of behavioral intervention, across different settings) may lead to selected gains in a number of specific domains. The report concluded, however, that "further research is required to address the methodological limitations of existing studies and replicate their findings. In particular studies with larger sample sizes (from multisite collaborations using identical methods and outcome measures) are required to provide greater statistical power and more precise estimates of effectiveness."

A position statement on early intervention for autism from the Canadian Paediatric Society (2004) reviewed the published literature on intervention programs, and concluded that the evidence for these programs is "weak" and "suboptimal".

More recently, an assessment by the Scottish Intercollegiate Guidelines Network (SIGN, 2007) stated that "[a]ll studies included in this review [of applied behavior analysis] were marked by considerable methodological flaws and there was also a concern that many had enrolled high functioning children with autism, making it difficult to generalize from the conclusions". The review concluded that a causal relationship can not be established between a particular program of intensive behavioral intervention and the achievement of "normal functioning". SIGN concluded that "[t]he Lovaas program should not be presented as an intervention that will lead to normal functioning". SIGN also noted that a comprehensive literature search did not find any good quality evidence for other intensive behavioral interventions.

A systematic evidence review and metanalysis found inadequate evidence that applied behavior intervention programs have better outcomes than standard care for children with autism (Spreckley and Boyd, 2009). The authors reviewed systematic reviews and randomized or quasi-randomized controlled trials of applied behavioral interventions delivered to preschool children with autism spectrum disorder. Quantitative data on cognitive, language, and behavior outcomes were extracted and pooled for meta-analysis. The authors reported that thirteen studies met the inclusion criteria. Six of these were randomized comparison trials with adequate methodologic quality. Meta-analysis of 4 studies concluded that, compared with standard care, applied behavioral intervention programs did not significantly improve the cognitive outcomes of children in the experimental group. There was no additional benefit over standard care for expressive language, for receptive language, or adaptive behavior. The authors concluded that there is inadequate evidence that applied behavioral interventions have better outcomes than standard care for children with autism. The authors stated that appropriately powered clinical trials with broader outcomes are required.

An special report on applied behavior analysis for autism spectrum disorders by the BlueCross BlueShield Association Technology Evaluation Center (BCBSA, 2009) found that the strongest evidence of effectiveness came from 2 randomized controlled clinical trials (Smith et al, 2000; Sallows and Graupner, 2005); however, weaknesses in research design, differences in the treatments and outcomes compared, and inconsistent results mean that the impact of applied behavior analysis versus other treatments on outcomes for children with autism can not be determined. The report stated that, given the lack of a definitive evidence on the relative effectiveness of applied behavior analysis, one can not answer the question of whether there are characteristics of children that predict a greater likelihood of success. The assessment also stated that the findings on whether more intense treatment leads to better outcomes were inconsistent, and no conclusions can be drawn.

The BlueCross BlueShield Association's special report on "Early Intensive Behavioral Intervention Based on Applied Behavior Analysis among Children with Autism Spectrum Disorders" (2010) stated that overall, the quality and consistency of results of this body of evidence are weak. Consequently, no conclusions can be drawn from this literature on how well early intensive behavioral intervention (based on applied behavior analysis or ABA; hereafter referred to as "EIBI") works. Weaknesses in research design and analysis, as well as inconsistent results across studies, undermine confidence in the reported results. It is important to distinguish between certainty about ineffectiveness and uncertainty about effectiveness. Based on the weakness of the available evidence, we are uncertain about the effectiveness of EIBI for autism spectrum disorders (ASDs). Furthermore, the authors stated that the variability of presentation and progression among children with ASDs, as well as potential differences in delivery of behavioral interventions, make this topic challenging to study. Nevertheless, given the importance of caring for children with ASDs, additional research is needed to identify those characteristics of treatment – content, technique, intensity, starting and ending age, etc. – that maximize its effectiveness. Because of the challenges in launching a very large randomized controlled trial (RCT) and the ethical necessity to provide some treatment to the control group, this body of research needs to be built piece by piece, with a series of studies that investigate different components of the larger research question. For this to be effective, however, the overall quality of studies needs to be improved, including a greater emphasis on RCTs, where at all possible; substantially larger sample sizes; uniformity of outcomes evaluated and instruments used to measure them; and consistent treatments that do not vary widely within treatment groups (i.e., experimental or control group).

The cost of continuing the current course of assuming that EIBI works may not be obvious. EIBI is costly financially for society and requires a large time commitment from children, their families, and their teachers or therapists. However, these programs may not appear to pose any harm for the children themselves. Nevertheless, the opportunity costs could be high, indeed, of providing sub-optimal care to these children, simply because we as a society do not know what works best. The children may be treated with an intervention that is not as effective as the alternatives. And if we accept an intervention because it seems to work, without solid evidence, research on the alternatives or on how it can be improved is likely to be stifled.

Other interventions that have little or insufficient evidence of effectiveness in the treatment of children with autism are auditory integration training (also referred to auditory integration therapy, [AIT]), cognitive rehabilitation, facilitated communication, gluten and milk elimination diets, holding therapy, immune globulin therapy, music therapy, nutritional supplements (e.g., megavitamins, high-dose pyridoxine and magnesium, dimethylglycine), sensory integration therapy, and vision therapy.

Facilitated Communication is a method of providing assistance to a nonverbal individual by typing words using a typewriter, computer keyboard or other communication device. An assessment of interventions for autism conducted by the NAS (2001) concluded that there is insufficient evidence of the effectiveness of facilitated communication (FC) for autism. The NAS report stated: "There are over 50 research studies of FC with 143 communicators. Based on these research studies, the American Speech-Language-Hearing Association (1994) has stated that there is a lack of scientific evidence validating FC skills and a preponderance of evidence of facilitator influence on messages attributed to communicators (ASHA Technical Report, 1994). Thus, there is now a large body of research indicating that FC does not have scientific validity."

The AAP (2001) stated that available information does not support the claims of proponents that FC is effective in the treatment of autism, and considered it experimental. In a review on autism, Levy and colleagues (2009) stated that popular biologically based treatments include anti-infectives, chelation medications, gastrointestinal medications, hyperbaric oxygen therapy, off-label drugs (e.g., secretin), and intravenous immunoglobulins. Non-biologically based treatments include AIT, chiropractic therapy, cranio-sacral manipulation, FC, interactive metronome, and transcranial stimulation. However, few studies have addressed the safety and effectiveness of most of these treatments.

Chelation Therapy is treatment that aims at lowering levels of mercury, lead or other heavy metals in the body. Medication is taken on a regular schedule that chelates (binds with) the metal to lessen its toxic effect on the body. In a review on autism, Levy and colleagues (2009) found that few studies have addressed the safety and effectiveness of chelation therapy for autism

Sensory Integration Therapy is a method to improve the way the brain processes and organizes external stimuli, such as touch, movement, body awareness, sight and sound. The NAS report (2001) concluded that there is insufficient evidence of the effectiveness of sensory integration therapy for autism. By focusing a child on play, sensory integration therapy emphasizes the neurological processing of sensory information as a foundation for learning of higher-level skills. The goal is to improve subcortical (sensory integrative) somatosensory and vestibular functions by providing controlled sensory experiences to produce adaptive motor responses. The hypothesis is that, with these experiences, the nervous system better modulates, organizes, and integrates information from the environment, which in turn provides a foundation for further adaptive responses and higher-order learning. The NAS report states, however, that "[t]here is a paucity of research concerning sensory integration treatments in autism …. These interventions have also not yet been supported by empirical studies." In addition, the AAP (2001) stated that research data supporting the effectiveness of sensory integration therapy in managing autistic children is scant.

Vision therapy is a primarily optometric treatment method that focuses on neurological and muscular function and the brain-eye connection for developing efficient visual skills and processing. Orthoptics is a component of vision therapy. Orthoptics is therapy limited in scope to eye muscle training, typically for straightening eye gaze so that both eyes appear to be looking toward the same direction. After initial training, the individual performs the eye exercises at home. The NAS concluded that there is insufficient evidence of the effectiveness of vision therapy for autism. "A variety of visual therapies (including oculomotor exercises, colored filters, i.e., Irlen lenses, and ambient prism lenses) have been used with children with autism in attempts to improve visual processing or visual spatial perception. There are no empirical studies regarding the efficacy of the use of Irlen lenses or oculomotor therapies specifically in children with autism …. As with auditory integration therapy, studies have not provided clear support for either its theoretical or its empirical basis."

Other therapies involving sensory stimulation have insufficient evidence of effectiveness for treatment of autism, including holding therapy and vestibular stimulation. Holding Therapy is a practice that consists of forced holding by a therapist or parent until the child stops resisting, eye contact is made or a fixed time period has elapsed. Vestibular Stimulation is the input the body receives when experiencing movement or gravity.

Bell (2004) assessed the evidence for the effectiveness of music therapy for autism for the Wessex Institute for Health Research and Development, and concluded that there is insufficient evidence to support its use. The assessment concluded that children with autism may demonstrate slight improvements in speech and imitation during music therapy sessions, but the clinical importance of these changes may be negligible. The assessment found that the impact of music therapy on behavior and social functioning is unclear, and the long-term effects are uncertain. The assessment also stated that it is unclear whether music therapy is better than other forms of behavioral therapy for children with autism. The assessment stated that these conclusions are limited by the poor quality of the evidence, in particular the biased selection of the children, the small numbers involved, the contamination effect of the crossover design of many of the studies, the uncertain relevance of many of the outcome measures and the short follow-up. The assessment concluded "[w]ithout further research, no recommendation about the clinical effectiveness of music therapy for autism can be made."

The AAP stated that speech therapy and physical therapy play important roles in the comprehensive, interdisciplinary management of children with autistic spectrum disorder (2001). An assessment by the National Initiative for Autism: Screening and Assessment (NIASA) (National Autistic Society, 2003) stated that children with co-morbid specific developmental disorders will require additional therapeutic services. "These services include speech and language therapy for augmented communication programs, physiotherapy and occupational therapy for visual perceptual problems, fine and gross motor co-ordination difficulties including with writing, unusual sensory responses, self-care skills and provision of equipment and environmental adaptations." However, there is a lack of high-quality evidence for speech/language therapy for autism. The evidence for the effectiveness of speech/language therapy for autism is derived from case reports, single-case research designs, small-scale studies, and anecdotal reports.

Physical therapy for children with autistic spectrum disorders focuses on developing strength, coordination and movement (CARD, 2001). Therapists work on improving gross motor skills, such as running, reaching, and lifting. This therapy is concerned with improving function of the body's larger muscles through physical activities including exercise and massage. Occupational therapists commonly focus on improving fine motor skills, such as brushing teeth, feeding, and writing, or sensory motor skills that include balance (vestibular system), awareness of body position (proprioceptive system), and touch (tactile system).

Immune globulin infusions are concentrated antibodies administered intravenously to treat certain infectious diseases or boost the immune system response. The AAP (2001) has concluded that there is no scientific evidence to justify the use of infusions of immune globulin in treating autism.

Cognitive Rehabilitation is a systematic, goal oriented treatment program to improve cognitive (mental/intellectual) function and functional abilities (memory, judgment, perception and reasoning). The bulk of the evidence supporting cognitive rehabilitation for autism comes from case studies, anecdotal evidence and expert opinion. The effectiveness of cognitive rehabilitation in treating autism has not been critically evaluated in well-designed studies.

In a Cochrane review on the use of music therapy for the treatment of autistic spectrum disorders, Gold et al (2006) stated that published studies were of limited applicability to clinical practice. However, the findings indicate that music therapy may help children with autistic spectrum disorder to improve their communicative skills. The authors noted that more research is needed to examine whether the effects of music therapy are enduring, and to investigate the effects of music therapy in typical clinical practice.

In a Cochrane review, Millward et al (2008) noted that it has been suggested that peptides from gluten and casein may have a role in the origins of autism and that the physiology and psychology of autism might be explained by excessive opioid activity linked to these peptides. Research has reported abnormal levels of peptides in the urine and cerebrospinal fluid of people with autism. These investigators examined the effectiveness of gluten and/or casein free diets as an intervention to improve behavior, cognitive and social functioning in individuals with autism. The authors concluded that research has shown of high rates of use of complementary and alternative therapies for children with autism including gluten and/or casein exclusion diets. However, current evidence for the effectiveness of these diets is poor. They stated that large scale, good quality randomized controlled trials are needed. This is in agreement with the observations of Curtis and Patel (2008) who stated that larger studies are needed to determine optimum multi-factorial treatment plans for autism and attention deficit hyperactivity disorder involving nutrition, environmental control, medication, as well as behavioral/education/speech/physical therapies.

The Tomatis sound therapy has been used to improve language skills in children with autism. It entails the use classical music that includes complex rhythms, melodies and harmonic relationships known to create improved brain function. The music is filtered with a device that Dr. Alfred Tomatis invented and called the Electronic Ear. The filtering or "gating", which the Electronic Ear provides, creates a gymnastic program that activates and rehabilitates the middle ear muscles and the whole auditory system. Programs are progressively filtered to gradually awaken the ear and auditory system to the full range of high frequencies.

Corbett et al (2008) examined the effects of the Tomatis sound therapy on language skills in children with autism utilizing a randomized, double-blind, placebo-controlled, cross-over design. The results indicated that although the majority of the children demonstrated general improvement in language over the course of the study, it did not appear to be related to the treatment condition. The percent change for Group 1 (placebo/treatment) for treatment was 17.41 %, and placebo was 24.84 %. Group 2 (treatment/placebo) showed -3.98 % change for treatment and 14.15 % change for placebo. The results reflect a lack of improvement in language using the Tomatis sound therapy for children with autism.

Hyperbaric oxygen therapy is a mode of treatment in which an individual breathes 100% oxygen at greater than normal atmospheric pressure. Rossignol and associates (2009) performed a multi-center, randomized, double-blind, controlled trial to evaluate the effectiveness of hyperbaric treatment in children with autism. A total of 62 children with autism were recruited from 6 centers, aged 2 to 7 years (mean of 4.92 +/- 1.21 years). Subjects were randomly assigned to 40 hourly treatments of either hyperbaric treatment at 1.3 atmosphere (atm) and 24 % oxygen (treatment group, n = 33) or slightly pressurized room air at 1.03 atm and 21 % oxygen (control group, n = 29). Outcome measures included Clinical Global Impression (CGI) scale, Aberrant Behavior Checklist (ABC), and Autism Treatment Evaluation Checklist (ATEC). After 40 sessions, mean physician CGI scores significantly improved in the treatment group compared to controls in overall functioning (p = 0.0008), receptive language (p < 0.0001), social interaction (p = 0.0473), and eye contact (p = 0.0102); 9/30 children (30 %) in the treatment group were rated as "very much improved" or "much improved" compared to 2/26 (8 %) of controls (p = 0.0471); 24/30 (80 %) in the treatment group improved compared to 10/26 (38 %) of controls (p = 0.0024). Mean parental CGI scores significantly improved in the treatment group compared to controls in overall functioning (p = 0.0336), receptive language (p = 0.0168), and eye contact (p = 0.0322). On the ABC, significant improvements were observed in the treatment group in total score, irritability, stereotypy, hyperactivity, and speech (p < 0.03 for each), but not in the control group. In the treatment group compared to the control group, mean changes on the ABC total score and sub-scales were similar except a greater number of children improved in irritability (p = 0.0311). On the ATEC, sensory/cognitive awareness significantly improved (p = 0.0367) in the treatment group compared to the control group. Post-hoc analysis indicated that children over the age of 5 years and children with lower initial autism severity had the most robust improvements. Hyperbaric treatment was safe and well-tolerated. The authors concluded that children with autism who received hyperbaric treatment at 1.3 atm and 24 % oxygen for 40 hourly sessions had significant improvements in overall functioning, receptive language, social interaction, eye contact, and sensory/cognitive awareness compared to children who received slightly pressurized room air.

Moreover, the authors stated that because this study was not designed to measure the long-term outcomes of hyperbaric treatment in children with autism, additional studies are needed to determine if the significant improvements observed in this study last beyond the study period. It is possible that ongoing treatments would be necessary to maintain the improvements observed, but this study was not designed to examine that possibility. These findings suggest that additional hyperbaric treatments beyond 40 total sessions may lead to additional improvements; however, further studies are needed to formally validate these observations. Finally, this study was not designed to determine if higher hyperbaric treatment parameters (higher atmospheric pressure and oxygen levels, which can only be provided in a clinic setting) would lead to better or more long-lasting results. Additional studies are needed to investigate that possibility.

It is interesting to note that Yildiz and colleagues (2008) stated that neither the Undersea Hyperbaric Medical Society nor the European Committee for Hyperbaric Medicine "approves" autism as an indication for hyperbaric oxygen therapy. The authors concluded that there is insufficient evidence to support the use of hyperbaric oxygen therapy in the treatment of children with autism.

It has been claimed that weighted blankets are beneficial for patients with autism since they "calm" the nervous system so afflicted individuals can relax and sleep. It is believed that weighted blanket leads to releases of melatonin, which plays a role in the body and brain’s sensory processing. Melantonin has been used for autistic children with sleep disorders despite insufficient evidence of its effectiveness in this population. Moreover, there is a lack of evidence regarding the clinical benefits of weighted blankets for individuals with autism or other pervasive developmental disorders.

Stephenson and Carter (2009) noted that therapists who use sensory integration therapy may recommend that children wear weighted vests as an intervention strategy that they claim may assist in remediating problems such as inattentiveness, hyperactivity, stereotypic behaviors and clumsiness. These investigators reviewed 7 studies on weighted vests. The authors concluded that while there is only a limited body of research and a number of methodological weaknesses, on balance, indications are that weighted vests are ineffective. There may be an arguable case for continued research on this intervention but weighted vests can not be recommended for clinical application at this point.

Ichim and colleagues (2007) stated that ASDs are a group of neurodevelopmental conditions whose incidence is reaching epidemic proportions, afflicting approximately 1 in 166 children. Autistic disorder, or autism is the most common form of ASD. Although several neurophysiological alterations have been associated with autism, immune abnormalities and neural hypo-perfusion appear to be broadly consistent. These appear to be causative since correlation of altered inflammatory responses, and hypo-perfusion with symptomatology was reported. Mesenchymal stem cells (MSC) are in late phases of clinical development for treatment of graft versus host disease and Crohn's Disease, 2 conditions of immune dysregulation. Cord blood CD34+ cells are known to be potent angiogenic stimulators, having demonstrated positive effects in not only peripheral ischemia, but also in models of cerebral ischemia. Additionally, anecdotal clinical cases have reported responses in autistic children receiving cord blood CD34+ cells. These researchers proposed the combined use of MSC and cord blood CD34+cells may be useful in the treatment of autism.

Thompson and colleagues (2010) summarized data from a review of neurofeedback (NFB) training with 150 patients with Asperger's syndrome (AS) and 9 patients with ASD seen over a 15-year period in a clinical setting. The main objective was to examine if NFB (also known as EEG biofeedback) made a significant difference in patients diagnosed with AS. A further aim of the current report was to provide practitioners with a detailed description of the method used to address some of the key symptoms of AS in order to encourage further research and clinical work to refine the use of NFB plus biofeedback in the treatment of AS. All charts were included for review where there was a diagnosis of AS or ASD and pre- and post-training testing results were available for one or more of the standardized tests used. Patients received 40 to 60 sessions of NFB, which was combined with training in meta-cognitive strategies and, for most older adolescent and adult patients, with biofeedback of respiration, electrodermal response, and, more recently, heart rate variability. For the majority of patients, feedback was contingent on decreasing slow wave activity (usually 3 to 7 Hz), decreasing beta spindling if it was present (usually between 23 and 35 Hz), and increasing fast wave activity termed sensorimotor rhythm (SMR) (12 to 15 or 13 to 15 Hz depending on assessment findings). The most common initial montage was referential placement at the vertex (CZ) for children and at FCz (midway between FZ and CZ) for adults, referenced to the right ear. Meta-cognitive strategies relevant to social understanding, spatial reasoning, reading comprehension, and math were taught when the feedback indicated that the patient was relaxed, calm, and focused. Significant improvements were found on measures of attention (T.O.V.A. and IVA), core symptoms (Australian Scale for Asperger's Syndrome, Conners' Global Index, SNAP version of the DSM-IV criteria for attention-deficit hyperactivity disorder (ADHD), and the ADD-Q), achievement (Wide Range Achievement Test), and intelligence (Wechsler Intelligence Scales). The average gain for the Full Scale IQ score was 9 points. A decrease in relevant EEG ratios was also observed. The ratios measured were (4 to 8 Hz)(2)/(13 to 21 Hz)(2), (4 to 8 Hz)/(16 to 20 Hz), and (3 to 7 Hz)/(12 to 15 Hz). The positive outcomes of decreased symptoms of Asperger's and attention deficit hyperactivity disorder (including a decrease in difficulties with attention, anxiety, aprosodias, and social functioning) plus improved academic and intellectual functioning, provided preliminary support for the use of NFB as a helpful component of effective intervention in people with AS.

Massage involves manipulation of tissues (as by rubbing or kneading) with the hand or an instrument for therapeutic purposes. Lee et al (2011) examined the effectiveness of massage as a treatment option for autism. These investigators searched the following electronic databases using the time of their inception through March 2010: MEDLINE, AMED, CINAHL, EMBASE, PsycINFO, Health Technology Assessment, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, Psychology and Behavioral Sciences Collection, 6 Korean medical databases (KSI, DBpia, KISTEP, RISS, KoreaMed, and National Digital Library), China Academic Journal (through China National Knowledge Infrastructure), and 3 Japanese medical databases (Journal@rchive, Science Links Japan, and Japan Science & Technology link). The search phrase used was "(massage or touch or acupressure) and (autistic or autism or Asperger's syndrome or pervasive developmental disorder)". The references in all located articles were also searched. No language restrictions were imposed. Prospective controlled clinical studies of any type of massage therapy for autistic patients were included. Trials in which massage was part of a complex intervention were also included. Case studies, case series, qualitative studies, uncontrolled trials, studies that failed to provide detailed results, and trials that compared one type of massage with another were excluded. All articles were read by 2 independent reviewers, who extracted data from the articles according to predefined criteria. Risk of bias was assessed using the Cochrane classification. Of 132 articles, only 6 studies met inclusion criteria. One RCT found that massage plus conventional language therapy was superior to conventional language therapy alone for symptom severity (p < 0.05) and communication attitude (p < 0.01). Two RCTs reported a significant benefit of massage for sensory profile (p < 0.01), adaptive behavior (p < 0.05), and language and social abilities (p < 0.01) as compared with a special education program. The fourth RCT showed beneficial effects of massage for social communication (p < 0.05). Two non-RCTs suggested that massage therapy is effective. However, all of the included trials have high risk of bias. The main limitations of the included studies were small sample sizes, predefined primary outcome measures, inadequate control for non-specific effects, and a lack of power calculations or adequate follow-up. The authors concluded that limited evidence exists for the effectiveness of massage therapy as a symptomatic treatment of autism. Because the risk of bias was high, firm conclusions can not be drawn. They stated that future, more rigorous RCTs are warranted.

The Agency for Healthcare Research and Quality's report on comparative effectiveness of therapies for children with ASDs (AHRQ, 2011) has the following conclusions:

Early intensive behavioral and developmental interventions such as the UCLA/Lovaas Model improve cognitive, language, and adaptive outcomes in certain subgroups of children (Low confidence scale).
The evidence is insufficient to understand the effectiveness, benefits, or adverse events from any other behavioral interventions.
Secretin does not improve language, cognition, behavior, communication, autism symptom severity, or socialization (High confidence scale).
The evidence is insufficient to understand the effectiveness, benefits, or adverse events from any educational intervention.
The evidence is insufficient to understand the effectiveness, benefits, or adverse events from any allied health or complementary and alternative medicine intervention.

In a Cochrane review, Sinha et al (2011) examined the effectiveness of AIT or other methods of sound therapy in individuals with ASDs. For this update, these investigators searched the following databases in September 2010: CENTRAL (2010, Issue 2), MEDLINE (1950 to September week 2, 2010), EMBASE (1980 to Week 38, 2010), CINAHL (1937 to current), PsycINFO (1887 to current), ERIC (1966 to current), LILACS (September 2010) and the reference lists of published papers. One new study was found for inclusion. Randomized controlled trials involving adults or children with ASDs were reviewed. Treatment was AIT or other sound therapies involving listening to music modified by filtering and modulation. Control groups could involve no treatment, a waiting list, usual therapy or a placebo equivalent. The outcomes were changes in core and associated features of ASDs, auditory processing, quality of life and adverse events. Two independent review authors performed data extraction. All outcome data in the included papers were continuous. They calculated point estimates and standard errors from t-test scores and post-intervention means. Meta-analysis was inappropriate for the available data. These researchers identified 6 RCTs of AIT and 1 of Tomatis therapy, involving a total of 182 individuals aged 3 to 39 years. Two were cross-over trials; 5 trials had fewer than 20 participants. Allocation concealment was inadequate for all studies. Twenty different outcome measures were used and only 2 outcomes were used by 3 or more studies. Meta-analysis was not possible due to very high heterogeneity or the presentation of data in unusable forms. Three studies (Bettison 1996; Zollweg 1997; Mudford 2000) did not demonstrate any benefit of AIT over control conditions. Three studies (Veale 1993; Rimland 1995; Edelson 1999) reported improvements at 3 months for the AIT group based on the Aberrant Behavior Checklist, but they used a total score rather than subgroup scores, which is of questionable validity, and Veale's results did not reach statistical significance. Rimland (1995) also reported improvements at 3 months in the AIT group for the Aberrant Behaviour Checklist subgroup scores. The study addressing Tomatis therapy (Corbett 2008) described an improvement in language with no difference between treatment and control conditions and did not report on the behavioral outcomes that were used in the AIT trials. The authors concluded that there is no evidence that AIT or other sound therapies are effective as treatments for ASDs. As synthesis of existing data has been limited by the disparate outcome measures used between studies, there is insufficient evidence to prove that this treatment is ineffective. However, of the 7 studies including 182 participants that have been reported to date, only 2 (with an author in common), involving a total of 35 participants, reported statistically significant improvements in the AIT group and for only 2 outcome measures (Aberrant Behaviour Checklist and Fisher's Auditory Problems Checklist). As such, there is no evidence to support the use of AIT at this time.

Alcantara and associates (2011), using 8 databases, performed a systematic review of the literature on the effectiveness of chiropractic care in patients with ASD. Eligibility criteria for inclusion included:

the study was a primary investigation/report published in an English peer-reviewed journal;
the study involved patients less than or equal to 18 years; and
patients are diagnosed with autism, Asperger's Syndrome, Pervasive Developmental Disorder-Not Otherwise Specified (PDD-NOS), or ASD.

Review of the literature revealed a total of 5 articles consisting of 3 case reports, 1 cohort study and 1 randomized comparison trial. The literature is lacking on documenting chiropractic care of children with ASD. These researchers stated that at the heart of the core symptoms of ASD (i.e., impaired social interactions, deficits in communication and repetitive or restricted behavioral patterns) is abnormal sensory processing. Preliminary studies indicated that chiropractic adjustment may attenuate sensorimotor integration based on somatosensory evoked potentials studies. The authors concluded that they encourage further research for definitive studies on chiropractic's effectiveness for ASD.

In a Cochrane review, James et al (2011) examined the efficacy of omega-3 fatty acids for improving core features of ASD (e.g., social interaction, communication, and stereotypies) and associated symptoms. These investigators searched the following databases on June 2, 2010: CENTRAL (2010, Issue 2), MEDLINE (1950 to May Week 3 2010), EMBASE (1980 to 2010 Week 21), PsycINFO (1806 to current), BIOSIS (1985 to current), CINAHL (1982 to current), Science Citation Index (1970 to current), Social Science Citation Index (1970 to current), metaRegister of Controlled Trials (November 20, 2008) and ClinicalTrials.gov (December 10, 2010). Dissertation Abstracts International was searched on December 10, 2008, but was no longer available to the authors or editorial base in 2010. All RCTs of omega-3 fatty acids supplementation compared to placebo in individuals with ASD were reviewed. Three authors independently selected studies, assessed them for risk of bias and extracted relevant data. They conducted meta-analysis of the included studies for 3 primary outcomes (social interaction, communication, and stereotypy) and 1 secondary outcome (hyper-activity). These researchers included 2 trials with a total of 37 children diagnosed with ASD who were randomized into groups that received either omega-3 fatty acids supplementation or a placebo. They excluded 6 trials because they were either non-RCTs, did not contain a control group, or the control group did not receive a placebo. Overall, there was no evidence that omega-3 supplements had an effect on social interaction (mean difference (MD) 0.82, 95 % confidence interval [CI]: -2.84 to 4.48, I(2) = 0 %), communication (MD 0.62, 95 % CI: -0.89 to 2.14, I(2) = 0 %), stereotypy (MD 0.77, 95 % CI: -0.69 to 2.22, I(2) = 8 %), or hyper-activity (MD 3.46, 95 % CI: -0.79 to 7.70, I(2) = 0 %). The authors concluded that to date there is no high quality evidence that omega-3 fatty acids supplementation is effective for improving core and associated symptoms of ASD. Given the paucity of rigorous studies in this area, there is a need for large well-conducted RCTs that examine both high- and low-functioning individuals with ASD, and that have longer follow-up periods.

Wuang et al (2010) examined the effectiveness of a 20-week Simulated Developmental Horse-Riding Program (SDHRP) by using an innovative exercise equipment (Joba) on the motor proficiency and sensory integrative functions in 60 children with autism (age of 6 years, 5 months to 8 years, 9 months). In the 1st phase of 20 weeks, 30 children received the SDHRP in addition to their regular occupational therapy while another 30 children received regular occupational therapy only. The arrangement was reversed in the 2nd phase of another 20 weeks. Children with autism in this study showed improved motor proficiency and sensory integrative functions after 20-week SDHRP (p < 0.01). In addition, the therapeutic effect appeared to be sustained for at least 24 weeks (6 months). This study utilized Joba, an exercise equipment that served as simulated horseback riding; not conventional horseback riding.

Kern et al (2011) noted that anecdotal reports and some studies suggested that equine-assisted activities may be beneficial in ASD. These investigators examined the effects of equine-assisted activities on overall severity of autism symptoms using the Childhood Autism Rating Scale (CARS) and the quality of parent-child interactions using the Timberlawn Parent-Child Interaction Scale. In addition, this study examined changes in sensory processing, quality of life, and parental treatment satisfaction. Children with ASD were evaluated at 4 time-points:

before beginning a 3-to-6 month waiting period,
before starting the riding treatment,
after 3 months, and
6 months of riding.

A total of 24 participants completed the waiting list period and began the riding program, and 20 participants completed the entire 6 months of riding. Pre-treatment was compared to post-treatment with each child acting as his or her own control. A reduction in the severity of autism symptoms occurred with the therapeutic riding treatment. There was no change in CARS scores during the pre-treatment baseline period; however, there was a significant decrease after treatment at 3 months and 6 months of riding. The Timberlawn Parent-Child Interaction Scale showed a significant improvement in Mood and Tone at 3 months and 6 months of riding and a marginal improvement in the reduction of Negative Regard at 6 months of riding. The parent-rated quality of life measure showed improvement, including the pre-treatment waiting period. All of the ratings in the Treatment Satisfaction Survey were between good and very good. The authors concluded that these results suggested that children with ASD benefit from equine-assisted activities. The findings of this small study need to be validated by well-designed studies.

An UpToDate review on "Autism spectrum disorder in children and adolescents: Overview of management" (Weissman and Bridgemohan, 2013a) does not mention the use of hippotherapy as a management tool. Furthermore, an UpToDate review on "Autism spectrum disorders in children and adolescents: Complementary and alternative therapies" (Weissman and Bridgemohan, 2013b) states that "The use of therapeutic horseback riding (hippotherapy) for children with ASD is based upon the hypothesis that therapeutic horseback riding stimulates multiple domains of functioning (e.g., cognitive, social, gross motor). In a nonrandomized study, 19 children with autism who participated in 12 weeks of therapeutic horseback riding (hippotherapy) demonstrated improvements in attention, distractibility, and social motivation compared with 15 wait-list controls. Additional studies are necessary before this therapy can be recommended".

In a Cochrane review, Williams et al (2013) determined if treatment with a selective serotonin reuptake inhibitor (SSRI):

improves the core features of autism (social interaction, communication and behavioral problems);
improves other non-core aspects of behavior or function such as self-injurious behavior;
improves the quality of life of adults or children and their care-givers;
has short- and long-term effects on outcome; and
causes harm.

These investigators searched the following databases up until March 2013: CENTRAL, Ovid MEDLINE, Embase, CINAHL, PsycINFO, ERIC and Sociological Abstracts. They also searched ClinicalTrials.gov and the International Clinical Trials Registry Platform (ICTRP). This was supplemented by searching reference lists and contacting known experts in the field. Randomized controlled trials of any dose of oral SSRI compared with placebo, in people with ASD were selected for analysis. Two authors independently selected studies for inclusion, extracted data and appraised each study's risk of bias. A total of 9 RCTs with 320 participants were included. Four SSRIs were evaluated: fluoxetine (3 studies), fluvoxamine (2 studies), fenfluramine (2 studies) and citalopram (2 studies). Five studies included only children and 4 studies included only adults. Varying inclusion criteria were used with regard to diagnostic criteria and intelligence quotient of participants; 18 different outcome measures were reported. Although more than 1 study reported data for Clinical Global Impression (CGI) and obsessive-compulsive behavior (OCB), different tool types or components of these outcomes were used in each study. As such, data were unsuitable for meta-analysis, except for 1 outcome (proportion improvement). One large, high-quality study in children showed no evidence of positive effect of citalopram; 3 small studies in adults showed positive outcomes for CGI and OCB; 1 study showed improvements in aggression, and another in anxiety. The authors concluded that there is no evidence of effect of SSRIs in children and emerging evidence of harm. There is limited evidence of the effectiveness of SSRIs in adults from small studies in which risk of bias is unclear.

Furthermore, an UpToDate review on "Autism spectrum disorder in children and adolescents: Pharmacologic interventions" (Weissman and Bridgemohan, 2014) lists SSRI as one of the potential treatments for repetitive behaviors, stereotypies, and rigidity in children with ASD. The review also notes that "When used in children and adolescents with depression, SSRI have been associated with increased suicidal ideation. Increased suicidal ideation has not been demonstrated in studies of SSRI in individuals with ASD. However, most studies did not assess suicidal ideation and included too few subjects to detect rare adverse effects, such as suicidal ideation".

In an open-label study, Erickson et al (2014) evaluated the safety, tolerability, and effectiveness of arbaclofen, a selective GABA-B agonist, in non-syndromic ASD. This study enrolled 32 children and adolescents with either autistic disorder or PDD-not otherwise specified, and a score greater than or equal to 17 on the ABC-Irritability subscale. Arbaclofen was generally well-tolerated. The most common adverse events were agitation and irritability, which typically resolved without dose changes, and were often felt to represent spontaneous variation in underlying symptoms. Improvements were observed on several outcome measures in this exploratory trial, including the ABC-Irritability (the primary end-point) and the Lethargy/Social Withdrawal subscales, the Social Responsiveness Scale, the CY-BOCS-PDD, and CGI scales. The authors concluded that placebo-controlled study of arbaclofen is needed.

Acupuncture

In a systematic review and meta-analysis, Lee and associates (2018) evaluated the available evidence regarding the safety and efficacy acupuncture for children with ASD. These investigators searched 13 databases for studies published up to December 2016; RCTs evaluating the efficacy of acupuncture for children with ASD were included. Outcome measures were the overall scores on scales evaluating the core symptoms of ASD and the scores for each symptom, such as social communication ability and skills, stereotypies, language ability, and cognitive function; effect sizes were presented as MD. A total of 27 RCTs with 1,736 subjects were included. Acupuncture complementary to behavioral and educational intervention significantly decreased the overall scores on the CARS (MD -8.10, 95 % CI: -12.80 to -3.40) and ABC (MD -8.92, 95 % CI -11.29 to -6.54); however, it was unclear which of the ASD symptoms improved. Acupuncture as a monotherapy also reduced the overall CARS score. The reported adverse events (AEs) were acceptable. The authors concluded that the findings of this review suggested that acupuncture may be safe and effective for pediatric ASD. However, these researchers stated that it is not conclusive due to the heterogeneity of the acupuncture treatment methods used in the studies.

Liu and colleagues (2019a) stated that ASD is a neurodevelopment disorder without definitive cure. Previous studies have provided evidence for the safety and efficacy of scalp acupuncture in children with ASD. However, the efficacy of scalp acupuncture treatment (SAT) in children with ASD has not been evaluated systematically. In a systematic review and meta-analysis, these researchers examined the efficacy of SAT in children with ASD. Information from 6 databases, including Medline, Embase, Cochrane database, AMED, China National Knowledge Infrastructure, and Wanfang Data, were retrieved from the inception of each database from 1980 through September 2018; RCTs evaluating the efficacy of SAT for patients with ASD were included. The primary outcome measures were the CARS and ABC; secondary outcome measures were Psychoeducational Profile (3rd Edition) (PEP-3) scores. Risk of bias assessment and data synthesis were conducted with Review Manager 5.3 software. Methodological quality was assessed with the Cochrane risk of bias tool. A total of 14 trials with 968 subject were conducted and 11 of the trials were suitable for meta-analysis. Compared with behavioral and educational interventions, SAT significantly decreased the overall CARS scores for children under 3 years of age (MD = 3.08, 95 % CI: -3.96 to -2.19, p < 0.001) and above 3 years old (MD = 5.29, 95 % CI: -8.53 to -2.06, p < 0.001), ABC scores (MD = 4.70, 95 % CI: -6.94 to -2.79, p < 0.001). Furthermore, SAT significantly improved PEP-3 scores in communication (MD = 3.61, 95 % CI: 2.85 to 4.37, p < 0.001), physical ability (MD = 2.00, 95 % CI: 1.16 to 2.84, p < 0.001), and behavior (MD = 2.76, 95 % CI: 1.80 to 2.71, p < 0.001). The authors concluded that SAT may be an effective treatment for children with ASD. Moreover, these researchers stated that given the heterogeneity and number of subjects, RCTs of high quality and design are needed before widespread application of this therapy.

Auditory Integration Therapy

Auditory Integration Training (AIT) is a procedure for reducing painful hypersensitivity to sound. The NAS report (2001) concluded that there is insufficient evidence of the effectiveness of AIT in autism. Proponents of auditory integration therapy suggest that music can "massage" the middle ear (hair cells in the cochlea), reduce hyper-sensitivities and improve overall auditory processing ability. The NAS concluded that "auditory integration therapy has received more balanced investigation than has any other sensory approach to intervention, but in general studies have not supported either its theoretical basis or the specificity of its effectiveness." Based on a lack of clearly demonstrated effectiveness, the AAP (2001) also recommended against the use of AIT for autism.

A Cochrane review (Sinha et al, 2011) reviewed the evidence for AIT and other sound therapies for autism, and concluded that there is "no evidence that auditory integration therapy or other sound therapies are effective as treatments for autism spectrum disorders." The evidence review identified 6 relatively small studies of AIT and one of Tomatis therapy met the inclusion criteria for AIT. These largely measured different outcomes and reported mixed results. The report found that, of the seven studies including 182 participants that have been reported to date, only two (with an author in common), involving a total of 35 participants, report statistically significant improvements in the auditory integration therapy group and for only two outcome measures.

Al-Ayadhi and colleagues (2019) stated that neurotrophic factors, including the glial cell line-derived neurotrophic factor (GDNF), are of importance for synaptic plasticity regulation, intended as the synapses' ability to strengthen or weaken their responses to differences in neuronal activity. Such plasticity is essential for sensory processing, which has been shown to be impaired in ASD. This study was the first to examine the impact of AIT of sensory processing abnormalities in autism on plasma GDNF levels. A toal of 15 ASD children, aged between 5 and 12 years, were enrolled and underwent the present research study; AIT was carried out throughout 10 days with a 30-min session twice-daily. Before and after AIT, CARS, SRS, and Short Sensory Profile (SSP) scores were calculated, and plasma GDNF levels were assayed by an EIA test. A substantial decline in autistic behavior was observed after AIT in the scaling parameters used. Median plasma GDNF level was 52.142 pg/ml before AIT. This level greatly increased immediately after AIT to 242.05 pg/ml (p < 0.001). The levels were depressed to 154.00 pg/ml and 125.594 pg/ml 1 month and 3 months later, respectively, but they were still significantly higher compared with the levels before the treatment (p = 0.001, p = 0.01, respectively). There was an improvement in the measures of autism severity as an effect of AIT that induced the up-regulation of GDNF in plasma. The authors concluded that further research, on a large scale, is needed to evaluate if the cognitive improvement of ASD children following AIT is related or not connected to the up-regulation of GDNF.

Ciliary Neurotrophic Factor (CNTF) as a Biomarker for ASD

Brondino and colleagues (2019) stated that ciliary neurotrophic factor (CNTF) is a neurotrophin that could signal neuronal suffering and at the same time acts as a neuroprotective agent. These researchers evaluated CNTF serum levels in ASD. They noted that considering the role of CNTF as a neuronal damage signal and the role of neuro-inflammation, excito-inhibitory imbalance and excito-toxicity in the pathogenesis of ASD, a possible alteration of CNTF in ASD could be hypothesized. These investigators recruited 23 individuals with ASD and intellectual disability (ID), 20 ID subjects and 26 typical adults. A complete medical and psychopathological characterization of the participants was performed; CNTF serum levels were measured with ELISA. Serum levels of CNTF were significantly higher in the ASD+ID group compared to ID (p < 0.001) or typically developed subjects (p < 0.001). The authors concluded that CNTF may be considered as a potential biomarker candidate for ASD in the context of severe ID. They stated these findings support the hypothesis of neurotrophic imbalance in ASD.

Developmental, Individual-differences, Relationship-based (DIR) FloorTime Therapy

Floor time therapy is a series of 20- to 30-min periods during which parents interact and play with their autistic child on the floor. The aim of the interaction is to promote social and communicative abilities. A British Medical Journal Clinical Evidence systematic assessment on autism (Parr, 2006) concluded that the effectiveness of floor time therapy for autism is unknown.

Praphatthanakunwong et al (2018) state that the Developmental, Individual-differences, Relationship-based model (DIR/Floortime) is one of the well-known therapies for autism spectrum disorder (ASD), in which its main principle is to promote holistic development of an individual and relationships between the caregivers and children. Parental engagement is an essential element to DIR/Floortime treatment and involved with various factors. Finding those supporting factors and eliminating factors that might be an obstacle for parental engagement are essential for children with ASD to receive the full benefits of treatment. Thus, the authors conducted a cross-sectional study of parents with children aged 2–12 years who were diagnosed with ASD to examine the association between parents, children and provider and service factors with parental engagement in DIR/Floortime treatment. Data were collected using a parent, child, provider and service factors questionnaire. Patient Health Questionaire-9, Clinical Global Impressions-Severity and Childhood Autism Rating Scale were also used to collect data. For parent engagement in DIR/Floortime, the authors evaluated quality of parental engagement in DIR/Floortime and parent application of DIR/Floortime techniques at home. Finally, Clinical Global Impressions-Improvement and Functional Emotional Developmental Level were used to assess child development. The authors found that parents who were married, had lower income and higher knowledge of DIR/Floortime theory were more likely to have higher parent engagement (p=0.044 respectively). Furthermore, severity of the diagnosis and the continuation of the treatment significantly correlated with parent engagement (p=0.030 respectively). It was found that parents who applied the techniques for more than 1 hour/day, or had a high-quality parent engagement, significantly correlated with better improvement in child development (p=0.053, respectively). The authors concluded that factors associated with parents, children, and provider and service factors had a significant correlation with parent engagement in DIR/Floortime in which children whose parents had more engagement in DIR/Floortime techniques had better improvement in child development. The authors acknowledged limitations to their study. First, even though their number of participants in this study exceed the calculated sample size, further studies should include a larger number of participants. Moreover, they did not include the samples who irregularly received or stopped the treatment. Therefore, there might be a selection bias in their participants. Second, despite their participants being diagnosed by pediatricians and child and adolescence psychiatrists according to DSM-IV-TR ASD diagnostic criteria, they did not use a gold standard instrument to diagnose, for example, the Autism Diagnostic Observation Schedule. Third, they did not use Fisher’s exact test, which was usually used in other studies for analysis of small sizes. More recent studies found comparable statistical results between using likelihood ration and Fisher’s exact test. However, after using Fisher’s exact test, they still found significant association between severity and time spent practicing daily life skills (p=0.031). Fourth, even though this research examined various factors associated with parents, children and therapists, there may be some important factors that are not included in this study such as the expectations towards treatment and the motivation in receiving the treatment. Finally, although their study showed a correlation between parent engagement and child development, they did not include some specific skills related to ASD (e.g., communication skills, social skills, behavior problems and emotional problems) in their assessment. Therefore, these factors should be included in future studies.

Boshoff et al (2020) state that occupational therapy is often part of the multi-disciplinary approach within the Developmental, Individual-differences, Relationship-based (DIR) Floortime™ Model. The model addresses the emotional development of children, which is considered to be critical for the other child developmental areas. The authors conducted a systematic review to inform practitioner decision-making about the use of this model, as no systematic reviews exist on child development outcomes. The authors identified 9 studies with varying quality levels. Outcomes were mostly reported for increased socio-emotional development. The authors state that the evidence base for this model is emerging from a published research perspective. It is recommended that the use of this model be supported by sound clinical reasoning processes, intervention fidelity, use of valid outcome measures, and regular monitoring. Higher quality research is urgently needed to progress the research base for this intervention.

Electro-Convulsive Therapy

DeJong et al (2014) performed a systematic review to examine the effectiveness of a range of treatments for autistic catatonia. The review identified 22 relevant papers, reporting a total of 28 cases including both adult and pediatric patients. Treatments included electro-convulsive therapy (ECT), medication, behavioral and sensory interventions. Quality assessment found the standard of the existing literature to be generally poor, with particular limitations in treatment description and outcome measurement. The authors concluded that there was some limited evidence to support the use of ECT, high dose lorazepam and behavioral interventions for people with autistic catatonia; however, there is a need for controlled, high-quality trials. They also noted that reporting of side effects and adverse events should also be improved, in order to better evaluate the safety of these treatments.

Emotion Recognition Training for the Treatment of Autism Spectrum Disorder

Berggren and colleagues (2018) evaluated the generalizability of findings from RCTs evaluating emotion recognition training (ERT) for children and adolescents with ASD. These investigators presented a systematic review and narrative synthesis of the determinants of external validity in RCTs on ERT. Generalizability of the findings across situations, populations, settings, treatment delivery, and intervention formats was considered. These researchers identified 13 eligible studies. Participants were predominantly boys with ASD in the normative IQ range (IQ over 70), with an age span from 4 to 18 years across studies. Interventions and outcome measures were highly variable. Several studies indicated that training may improve ER, but it is still largely unknown to what extent training effects are translated to daily social life. The authors concluded that the generalizability of findings from currently available RCTs remains unclear.

FDA-Approved Pharmacotherapy for Autism

As of 2017, there were two FDA-approved medications on the market for the treatment of irritability associated with autistic disorder, risperidone and aripiprazole.

In 2006, the U.S. Food and Drug Administration (FDA) approved Risperdal (risperidone) for the treatment of irritability associated with autistic disorder, including symptoms of aggression, deliberate self-injury, temper tantrums, and quickly changing moods, in children and adolescents aged 5 to 16 years. This was noted to be the first FDA-approved medication for use in children and adolescents with autism (BioSpace, 2006). The drug is marketed by Janssen, L.P, a subsidiary of Johnson & Johnson.

In a systematic review on novel and emerging treatments for ASD, Rossignol (2009) stated that risperidone was FDA-approved for the treatment of ASD. The use of novel, unconventional, and off-label treatments for ASD is common, with up to 74 % of children with ASD using these treatments; however, treating physicians are often unaware of this usage. The author performed a systematic review of electronic scientific databases to identify studies of novel and emerging treatments for ASD, including nutritional supplements, diets, medications, and non-biological treatments. A grade of recommendation ("Grade") was then assigned to each treatment using a validated evidence-based guideline as outlined in this review: Grade A: Supported by at least 2 prospective randomized controlled trials (RCTs) or 1 systematic review; Grade B: Supported by at least 1 prospective RCT or 2 non-RCTs; Grade C: Supported by at least 1 non-RCT or 2 case series; and Grade D: Troublingly inconsistent or inconclusive studies or studies reporting no improvements. Potential adverse effects for each treatment were also reviewed. Grade A treatments for ASD include melatonin, acetylcholinesterase inhibitors, naltrexone, and music therapy. Grade B treatments include carnitine, tetrahydrobiopterin, vitamin C, alpha-2 adrenergic agonists, hyperbaric oxygen treatment, immunomodulation and anti-inflammatory treatments, oxytocin, and vision therapy. Grade C treatments for ASD include carnosine, multi-vitamin/mineral complex, piracetam, polyunsaturated fatty acids, vitamin B6/magnesium, elimination diets, chelation, cyproheptadine, famotidine, glutamate antagonists, acupuncture, AIT, massage, and neurofeedback. The author concluded that the reviewed treatments for ASD are commonly used, and some are supported by prospective RCTs. Promising treatments include melatonin, antioxidants, acetylcholinesterase inhibitors, naltrexone, and music therapy. All of the reviewed treatments are currently considered off-label for ASD and some have adverse effects. The author stated that further studies exploring these treatments are needed.

In 2009, Bristol-Myers Squibb Company announced the FDA approval of Abilify (aripiprazole) for the treatment of irritability associated with autistic disorder in pediatric patients ages 6 to 17 years, including symptoms of aggression towards others, deliberate self-injuriousness, temper tantrums, and quickly changing moods (BMS, 2009).

Approval was based on two 8-week, randomized, double-blind, placebo-controlled ,Phase III trials in pediatric patients (6 to 17 years of age) who met the DSM-IV criteria for autistic disorder and demonstrated behaviors such as tantrums, aggression, self-injurious behavior, or a combination of these problems. Efficacy was evaluated using two assessment scales: the Aberrant Behavior Checklist (ABC) and the Clinical Global Impression-Improvement (CGI-I) scale. The primary outcome measure in both trials was the change from baseline to endpoint in the Irritability subscale of the ABC (ABC-I). The ABC-I subscale measured symptoms of irritability in autistic disorder. Results of the first 8-week trial, contained 98 children and adolescents with autistic disorder. The participants received daily doses of placebo or Abilify 2 to 15 mg/day. Abilify, starting at 2 mg/day with increases allowed up to 15 mg/day based on clinical response, significantly improved scores on the ABC-I subscale and on the CGI-I scale compared with placebo. The mean daily dose of Abilify at the end of 8week treatment was 8.6 mg/day (Otsuka, 2016).

The second 8-week trial contained 218 children and adolescents with autistic disorder. Three fixed doses of Abilify (5 mg/day, 10 mg/day, or 15 mg/day) were compared to placebo. Abilify dosing started at 2 mg/day and was increased to 5 mg/day after one week. After a second week, it was increased to 10 mg/day for patients in the 10 and 15 mg dose arms, and after a third week, it was increased to 15 mg/day in the 15 mg/day treatment arm (Study 2 in Table 29). All three doses of Abilify significantly improved scores on the ABC-I subscale compared with placebo (Otsuka, 2016).

Abilify is available as oral tablets, orally-disintegrating tablets, and oral solution for treatment of irritability associated with autistic disorder. According to prescribing information (Otsuka, 2016), it is not known if Abilify is safe or effective in children under 6 years of age with irritability associated with autistic disorder.

GABAergic Agents

Brondino et al (2016) stated that it has been hypothesized that autism may result from an imbalance between excitatory glutamatergic and inhibitory GABAergic pathways. Commonly used medications such as valproate, acamprosate, and arbaclofen may act on the GABAergic system and be a potential treatment for people with ASD. These investigators evaluated the state-of-the-art of clinical trials of GABA modulators in autism. The authors concluded that there is insufficient evidence to suggest the use of these drugs in autistic subjects, even if data are promising. They stated that short-term use of all the reviewed medications appeared to be safe; however, future well-designed trials are needed to elucidate these preliminary findings.

GABA Receptor Polymorphisms Testing

Mahdavi and colleagues (2018) noted that previous studies have reported the association of GABA receptor subunits B3, A5, and G3 single-nucleotide polymorphisms (SNPs) in chromosome 15q11-q13 with ASDs. However, the currently available results are inconsistent. These investigators examined the association between ASD and the GABA receptor SNPs in chromosomal region 15q11-q13. The association was calculated by the overall OR with a 95 % CI. These researchers used sensitivity analyses and the assessment of publication bias in their meta-analysis. A total of 8 independent case-control studies involving 1,408 cases and 2,846 healthy controls were analyzed, namely, 8 studies for GABRB3 SNPs as well as 4 studies for GABRA5 and GABRG3 polymorphisms. The meta-analysis showed that GABRB3 polymorphisms in general were not significantly associated with autism (OR = 0.846; 95 % CI: 0.595 to 1.201, I2 = 79.1 %). Further analysis indicated that no associations were found between GABRB3 SNPs and autism on rs2081648 (OR = 0.84; 95 % CI: 0.41 to 1.72, I2 = 89.2 %) and rs1426217 (OR = 1.13; 95 % CI: 0.64 to 2.0, I2 = 83 %). An OR of 0.95; 95 % CI: 0.77 to 1.17 was reported; I2 = 0.0 %) for GABRA5 SNPs and an OR of 0.96; 95 % CI: 0.24 to 3.81 was obtained from GABRG3 SNPs; I2 = 97.8 %). The authors concluded that the findings of this meta-analysis provided strong evidence that different SNPs of GABA receptor B3, A5, and G3 subunit genes located on chromosome 15q11-q13 are not associated with the development of autism spectrum diseases in different ethnic populations.

Genetic Testing for DRD2, HTR2C, MTHFR, RELN, SLC25A12 and UGT2B15

Wang and associates (2014) noted that the reelin gene (RELN), which plays a crucial role in the migration and positioning of neurons during brain development, has been strongly posed as a candidate gene for ASD. Genetic variants in RELN have been investigated as risk factors of ASD in numerous epidemiologic studies but with inconclusive results. To clearly discern the effects of RELN variants on ASD, these researchers conducted a meta-analysis integrating case-control and transmission disequilibrium test (TDT) studies published through 2001 to 2013. Odds ratios (ORs) with 95 % CIs were used to estimate the associations between 3 RELN variants (rs736707, rs362691, and GGC repeat variant) and ASD. Overall, the summary ORs for rs736707, rs362691, and GGC repeat variant were 1.11 [95 % CI: 0.80 to 1.54], 0.69 (95 % CI: 0.56 to 0.86), and 1.09 (95 % CI: 0.97 to 1.23), respectively. Besides, positive result was also obtained in subgroup of broadly-defined ASD for rs362691 (OR = 0.67, 95 % CI: 0.52 to 0.86). The authors concluded that the findings of this meta-analysis revealed that the RELN rs362691, rather than rs736707 or GGC repeat variant, might contribute to ASD risk.

Liu and colleagues (2015) noted that the solute carrier family 25 (aspartate/glutamate carrier), member 12 gene (SLC25A12) has been suggested as a candidate gene for ASD given its role in mitochondrial function and adenosine triphosphate (ATP) synthesis. Evidence is growing for the association between SLC25A12 variants (rs2056202 and rs2292813) and ASD risk, but the results are inconsistent. To clarify the effect of these 2 variants on ASD, these researchers performed a meta-analysis integrating case-control and TDT studies. The PubMed, Embase, Cochrane Library, Web of Science, Chinese BioMedical Literature, Wanfang, and Chinese National Knowledge Infrastructure databases were systematically searched to identify relevant studies published up to May 2014; ORs and 95 % CIs were calculated to assess the strength of association. A total of 775 cases, 922 controls, and 1,289 families available from 8 studies concerning rs2056202, and 465 cases, 450 controls, and 1,516 families available from 7 studies concerning rs2292813 were finally included. In the overall meta-analysis, the rs2056202 T allele and rs2292813 T allele were both significantly associated with a decreased risk of ASD (rs2056202: OR = 0.809, p = 0.001, 95 % CI: 0.713 to 0.917, I(2) = 0.0 %, and p (heterogeneity) = 0.526; rs2292813: OR = 0.752, p < 0.001, 95 % CI: 0.649 to 0.871, I(2) = 0.0 %, p (heterogeneity) = 0.486). Besides, subjects with T-T haplotype of rs2056202-rs2292813 had a significantly reduced risk of ASD (OR = 0.672, p < 0.001, 95 % CI: 0.564 to 0.801, I(2) = 0.0 %, p (heterogeneity) = 0.631). Sensitivity analysis, cumulative meta-analysis, and publication bias diagnostics confirmed the reliability and stability of these results. The authors concluded that the findings of this meta-analysis suggested that rs2056202 and rs2292813 in SLC25A12 may contribute to ASD risk.

Aoki and Cortese (2016) stated that mitochondrial dysfunction has been reported to be involved in the pathophysiology of ASD. Studies investigating the possible association between ASD and polymorphism in SLC25A12, which encodes the mitochondrial aspartate/glutamate carrier, have yielded inconsistent results. These researchers conducted a systematic review and meta-analysis of such studies to elucidate if and which SLC25A12 single nucleotide polymorphisms (SNPs) are associated with ASD. They searched PubMed, Ovid, Web of Science, and ERIC databases through September 20, 2014; ORs were aggregated using random effect models. Sensitivity analyses were conducted based on study design (family-based or case-control); 15 out of 79 non-duplicate records were retained for qualitative synthesis. These investigators pooled 10 datasets from 9 studies with 2,001 families, 735 individuals with ASD and 632 typically developing (TD) individuals for the meta-analysis of rs2292813, as well as 11 datasets from 10 studies with 2,016 families, 852 individuals with ASD and 1,058 TD individuals for the meta-analysis of rs2056202. They found a statistically significant association between ASD and variant in rs2292813 (OR = 1.190, 95 % CI: 1.052 to 1.346, p = 0.006) as well as in rs2056202 (OR = 1.206, 95 % CI: 1.035 to 1.405, p = 0.016). Sensitivity analyses including only studies with family-based design demonstrated significant association between ASD and polymorphism in rs2292813 (OR = 1.216, 95 % CI: 1.075 to 1.376, p = 0.002) and rs2056202 (OR = 1.267, 95 % CI: 1.041 to 1.542, p = 0.018). In contrast, sensitivity analyses including case-control design studies only failed to find a significant association. The authors concluded that further research on the role of SLC25A12 and ASD may pave the way for potential innovative therapeutic interventions.

Long and Goldblatt (2016) noted that a polymorphism is a variant within a gene that does not necessarily affect its function, unlike a pathogenic mutation. Genetic testing for 2 common polymorphisms in the methylenetetrahydrofolate reductase gene (MTHFR), 677C>T and 1298A>C, is being accessed by general practitioners (GPs) and alternative medicine practitioners (based on in-house records from referrals), and promoted through some pharmacies in Western Australia (based on the authors' personal communication). Due to the large, varied and often conflicting data reported on MTHFR, these polymorphisms have been weakly associated with multiple conditions, including autism, schizophrenia, cardiac disease, fetal neural tube defects, poor pregnancy outcomes and colorectal cancer. These investigators explained the difficulty in translating inconclusive results – and results of uncertain clinical relevance – of genetic-association studies on common polymorphisms into clinical practice. They explored why testing for polymorphisms needs to be re-considered in a diagnostic clinical setting. The authors concluded that on the basis of the available scientific evidence, they proposed that there are very limited clinical indications for testing for the 677C>T and the 1298A>C polymorphisms in the MTHFR gene, and that testing is not indicated as a non-specific screening test in the asymptomatic general population.

Ziegler and colleagues (2017) noted that ASD is a highly heritable neural development disorder characterized by social impairment. The earlier the diagnosis is made, the higher are the chances of obtaining relief of symptoms. A very early diagnosis uses molecular genetic tests, which are also offered commercially. These investigators performed a systematic search of databases PubMed, Medline, Cochrane, Econlit and the NHS Center for Reviews and Dissemination for articles in English and German from January 1, 2000 to December 31, 2015. Original articles published in peer-reviewed journals were screened in a 2-step process:

they focused their search on economic evaluations of genetic tests for ASD, and
they searched for any economic evaluation (EE) of genetic tests.

These researchers identified 185 EE of genetic tests for various diseases. However, not a single EE of genetic tests has been found for ASD. The outcomes used in the EE of the genetic tests were heterogeneous, and results were generally not comparable. The authors concluded that there is no evidence for cost-effectiveness of any genetic diagnostic test for ASD, although such genetic tests are available commercially. They stated that cost-effectiveness analyses for genetic diagnostic tests for ASD are needed; there is a clear lack in research for EE of genetic tests.

Furthermore, an UpToDate review on "Autism spectrum disorder: Diagnosis" (Augustyn, 2017) does not mention testing for the DRD2, HTR2C, MTHFR, RELN, SLC25A12 and UGT2B15 genes.

Latent Class Analysis

Kyriakopoulos et al (2015) stated that in children with ASD, high rates of idiosyncratic fears and anxiety reactions and thought disorder are thought to increase the risk of psychosis. The critical next step is to identify whether combinations of these symptoms can be used to categorize individual patients into ASD subclasses, and to test their relevance to psychosis. In this study, all patients with ASD (n = 84) admitted to a specialist national inpatient unit from 2003 to 2012 were rated for the presence or absence of impairment in affective regulation and anxiety (peculiar phobias, panic episodes, explosive reactions to anxiety), social deficits (social disinterest, avoidance or withdrawal and abnormal attachment) and thought disorder (disorganized or illogical thinking, bizarre fantasies, over-valued or delusional ideas). Latent class analysis of individual symptoms was conducted to identify ASD classes. External validation of these classes was performed using as a criterion the presence of hallucinations. Latent class analysis identified 2 distinct classes. Bizarre fears and anxiety reactions and thought disorder symptoms differentiated ASD patients into those with psychotic features (ASD-P: 51 %) and those without (ASD-NonP: 49 %). Hallucinations were present in 26 % of the ASD-P class but only 2.4 % of the ASD-NonP. Both the ASD-P and the ASD-NonP class benefited from inpatient treatment although inpatient stay was prolonged in the ASD-P class. The authors concluded that the findings of this study provided the first empirically derived classification of ASD in relation to psychosis based on 3 underlying symptom dimensions, anxiety, social deficits and thought disorder. They stated that these results can be further developed by testing the reproducibility and prognostic value of the identified classes.

Measurements of Plasma Central Carbon Metabolites for Evaluation of Autism Spectrum Disorder

UpToDate reviews on "Autism spectrum disorder in children and adolescents: Overview of management" (Weissman, 2019), "Autism spectrum disorder: Screening tools" (Augustyn, 2019), "Autism spectrum disorder: Clinical features" (Augustyn and von Hahn, 2019a), and "Autism spectrum disorder: Evaluation and diagnosis" (Augustyn and von Hahn, 2019b) do not mention measurements of plasma central carbon metabolites as a management option.

Measurements of Plasma Oxytocin and Vasopressin for Evaluation of Autism Spectrum Disorder

Zhang and associates (2016) stated that ASD is defined by impairments of social interaction and the presence of obsessive behaviors. The "twin" nonapeptides oxytocin (OXT) and arginine-vasopressin (AVP) are known to play regulatory roles in social behaviors. However, the plasma levels and behavioral relevance of OXT and AVP in children with ASD have seldom been examined. It is also unclear if mothers of children with ASD have abnormal plasma peptide levels. By means of well-established methods of neuropeptide measurement and a relatively large sample size, these researchers determined the plasma levels of these 2 neuropeptides in 85 normal children, 84 children with ASD, and 31 mothers from each group of children. As expected, children with ASD had lower plasma OXT levels than gender-matched controls (p = 0.028). No such difference was found for plasma AVP concentrations. Correlation analysis showed that ASD children with higher plasma OXT concentrations tended to have less impairment of verbal communication (Rho = -0.22, p = 0.076), while those with higher plasma AVP levels tended to have lower levels of repetitive use of objects (Rho = -0.231, p = 0.079). Unlike the findings in children, maternal plasma OXT levels showed no group difference. However, plasma AVP levels in the mothers of ASD children tended to be lower than in the mothers of normal children (p = 0.072). The authors concluded that these findings suggested that the OXT system was dysregulated in children with ASD, and that OXT and AVP levels in plasma appeared to be associated with specific autistic symptoms. The plasma levels of OXT or AVP in mothers and their ASD children did not appear to change in the same direction.

The authors stated that this study had several drawbacks. It remained unclear whether peripheral OXT or AVP levels represent the central neuropeptide levels and activities. Some studies in pregnant women, adult suicide attempters, and adult patients undergoing surgical procedures have indicated a lack of correlation between OXT concentrations in plasma and cerebrospinal fluid (CSF). However, a recent study on children and adult patients have reported a positive correlation of OXT levels between the 2 compartments and this relationship was stronger when only children were included in the analysis. Also in studies with children, higher peripheral OXT levels had been shown to correspond with greater interaction skills in normal individuals. Recently-published studies on human neonates and children had also suggested that plasma AVP was a surrogate for brain AVP activity and a biomarker of social functioning in children with ASD. All these findings indicated that a correlation between OXT/AVP levels in plasma and CSF was more likely to occur in pediatric populations. The subjects in this study were all children, thus, these researchers speculated that plasma OXT or AVP concentrations, to some extent, represented brain neuropeptide levels. Subsequent work, if possible, should focus on OXT and AVP levels in CSF, which were more directly relevant to behavioral effects or psychopathology.

Wilczyński and colleagues (2019b) noted that ASD is a neurodevelopmental disorder characterized by deficits in social interactions, communication, and the presence of stereotyped, repetitive behaviors; OXT and AVP are neuropeptides produced in hypothalamus and they are related to processing emotions and social behavior. In the light of a growing number of scientific reports related to this issue, these 2 neurohormones started to be linked with the basis of neurodevelopmental disorders, including the ASD. In a systematic review, these investigators examined studies regarding the differences in OXT and AVP levels in ASD and neurotypical persons. Literature review focused on publications in the last 10 years located via the Medline/PubMed database as well as the Google Scholar browser. Selection was made by assumptive criteria of inclusion and exclusion. From the 487 studies qualified to the initial abstract analysis, 12 met the 6 inclusion criteria and were included in the full-text review. The authors concluded that currently, available studies still do not provide unequivocal answers as to the differences in concentrations of those neuropeptides between children with ASD and neurotypical control. Thus, it is necessary to continue the research taking into account necessity of proper homogenization of study groups, utilization of objective and quantifiable tools for ASD diagnosis and broadening the range of biochemical and molecular factors analyzed.

Memantine for the Treatment of Autism Spectrum Disorder

In a prospective, 12-week, open-label, clinical trial, Joshi and colleagues (2016) evaluated the tolerability and effectiveness of memantine for the treatment of core social and cognitive deficits in adults with high-functioning ASD. Measures for assessment of therapeutic response included the Social Responsiveness Scale-Adult Research Version (SRS-A), disorder-specific Clinical Global Impression scales, Behavior Rating Inventory of Executive Functioning-Adult Self-Report, Diagnostic Analysis of Nonverbal Accuracy Scale, and Cambridge Neuropsychological Test Automated Battery. A total of 18 adults (mean age of 28 ± 9.5 years) with high-functioning ASD (SRS-A raw score, 99 ± 17) were treated with memantine (mean dose of 19.7 ± 1.2 mg/day; range of 15 to 20 mg), and 17 (94 %) completed the trial. Treatment with memantine was associated with significant reduction on informant-rated (SRS-A, -28 ± 25; p < 0.001) and clinician-rated (Clinical Global Impression-Improvement subscale ≤ 2, 83 %) measures of autism severity. In addition, memantine treatment was associated with significant improvement in ADHD and anxiety symptom severity. Significant improvement was noted in nonverbal communication on the Diagnostic Analysis of Nonverbal Accuracy Scale test and in executive function per self-report (Behavior Rating Inventory of Executive Functioning-Adult Self-Report Global Executive Composite, -6 ± 8.8; p < 0.015) and neuropsychological assessments (Cambridge Neuropsychological Test Automated Battery). Memantine treatment was generally well-tolerated and was not associated with any serious adverse events (AEs). The authors concluded that treatment with memantine appeared to be beneficial for the treatment of ASD and associated psychopathology and cognitive dysfunction in intellectually capable adults. Moreover, they stated that future placebo-controlled trials are needed.

In a 12-week, randomized, placebo-controlled, study with a 48-week open-label extension, Aman and associates (2017) examined the safety, tolerability, and effectiveness of memantine (once-daily extended-release [ER]) in children with autism. A total of 121 children aged 6 to 12 years with Diagnostic and Statistical Manual of Mental Disorders, 4th ed., Text Revision (DSM-IV-TR)-defined autistic disorder were randomized (1:1) to placebo or memantine ER for 12 weeks; 104 children entered the subsequent extension trial. Maximum memantine doses were determined by body weight and ranged from 3 to 15 mg/day. There was 1 serious adverse event (SAE) (affective disorder, with memantine) in the 12-week study and 1 SAE (lobar pneumonia) in the 48-week extension; both were deemed unrelated to treatment. Other AEs were considered mild or moderate and most were deemed not related to treatment. No clinically significant changes occurred in clinical laboratory values, vital signs, or electrocardiogram (ECG). There was no significant between-group difference on the primary effectiveness outcome of caregiver/parent ratings on the SRS, although an improvement over baseline at week 12 was observed in both groups. A trend for improvement at the end of the 48-week extension was observed. No improvements in the active group were observed on any of the secondary end-points, with 1 communication measure showing significant worsening with memantine compared with placebo (p = 0.02) after 12 weeks. The authors concluded that this trial did not demonstrate clinical effectiveness of memantine ER in autism; however, the tolerability and safety data were reassuring. They noted that these findings could inform future trial design in this population and may facilitate the investigation of memantine ER for other clinical applications.

Furthermore, the largest RCT study of memantine for ASD, conducted by Forrest Pharmaceuticals, had negative results. Since this was a negative trial, the results have not been published but are posted on ClinicalTrials.gov.

Elnaiem et al (2022) noted that the FDA has approved drugs that address only autism-related symptoms rather than the underlying impairments. N-Methyl-D-Aspartate receptor antagonists have recently emerged as a promising therapeutic option for a variety of neurologic and developmental problems, including autism. In a systematic review and meta-analysis, these investigators examined the safety and effectiveness of memantine in autism. They carried out a comprehensive electronic search for relevant RCTs in 4 databases. Using RevMan software, these investigators extracted and pooled data as a risk ratio (RR) or normalized MDs in an inverse variance strategy. This systematic review and meta-analysis included 5 trials. There was no difference in enhancing social responsiveness when compared to placebo, though memantine lowered the likelihood of anxiety (RR = 0.25; 95 % CI: 0.07 to 0.87, p = 0.03). However, memantine aggravated impulsive behaviors. Furthermore, in another trial that compared memantine added to risperidone versus risperidone added to placebo, memantine was found to be safe and effective. The authors concluded that memantine showed safety in reducing acute symptoms of anxiety and other symptoms encountered in pediatric patients with ASDs; however, memantine did not improve the core symptoms of autism. These researchers stated that further long-term trials are needed to examine its potential effectiveness.

Metabolomic Analyses of Blood Samples (as a Biomarker for ASD)

Metabolomics is the large-scale study of small molecules, commonly known as metabolites, within cells, biofluids, tissues or organisms. Collectively, these small molecules and their interactions within a biological system are known as the metabolome.

NeuroPointDX, the neurological disorders division of Stemina Biomarker Discovery, announced that it has validated a first-generation autism diagnostic blood test panel in the Children’s Autism Metabolome Project (CAMP), its clinical study (Smith et al., 2019; Smith, et al., 2020). The NPDX ASD Test NeuroPointDX is intended to identify metabolic subtypes associated with autism spectrum disorder (ASD). According to the manufacturer, this plasma-based test, provided through NeuroPointDX’s CLIA-certified laboratory, may be used to screen children as young as 18 months. The manufacturer states that children who receive a positive result on the test should be prioritized for further clinical evaluation by a neurodevelopmental specialist. The test provides quantitative assessment of 16 central carbon metabolites that were found to be abnormal in some of the autistic children included in the Children’s Autism Metabolome Project (Smith, et al., 2020). However, the clinical utility of this testing for diagnosing and managing persons with autism spectrum disorder has not been established (Sainani & Goodman, 2019).

Smith et al (2019) stated Autism Spectrum Disorder (ASD) is behaviorally and biologically heterogeneous and likely represents a series of conditions arising from different underlying genetic, metabolic, and environmental factors. There are currently no reliable diagnostic biomarkers for ASD. Based on evidence that dysregulation of branch chain amino acids (BCAA) may contribute to the behavioral characteristics of ASD, the authors tested whether dysregulation of amino acids (AA) was a pervasive phenomenon in individuals with ASD. This is the first paper to report results from the Children’s Autism Metabolome Project (CAMP, ClinicalTrials.gov Identifier: NCT02548442), a large-scale effort to define autism biomarkers based on metabolomic analyses of blood samples from young children. Dysregulation of AA metabolism was identified by comparing plasma metabolites from 516 children with ASD with those from 164 age-matched typically-developing (TYP) children recruited into CAMP. ASD subjects were stratified into subpopulations based on shared metabolic phenotypes associated with BCAA dysregulation. The authors identified groups of AAs with positive correlations that were, as a group, negatively correlated with BCAA levels in ASD. Imbalances between these two groups of AAs identified three ASD associated Amino Acid Dysregulation Metabotypes (AADM). The combination of glutamine, glycine, and ornithine AADMs identified a dysregulation in AA/BCAA metabolism that is present in 16.7% of the CAMP ASD subjects and is detectable with a specificity of 96.3% and a PPV of 93.5%. The authors concluded that identification and utilization of metabotypes of ASD can lead to actionable metabolic tests that support early diagnosis and stratification for targeted therapeutic interventions.

West et al (2014) stated the diagnosis of autism spectrum disorder (ASD) at the earliest age possible is important for initiating optimally effective intervention. In the United States the average age of diagnosis is 4 years. Identifying metabolic biomarker signatures of ASD from blood samples offers an opportunity for development of diagnostic tests for detection of ASD at an early age. The objective of this study was to discover metabolic features present in plasma samples that can discriminate children with ASD from typically developing (TD) children. The ultimate goal is to identify and develop blood-based ASD biomarkers that can be validated in larger clinical trials and deployed to guide individualized therapy and treatment. Blood plasma was obtained from children aged 4 to 6, 52 with ASD and 30 age-matched TD children. Samples were analyzed using 5 mass spectrometry-based methods designed to orthogonally measure a broad range of metabolites. Univariate, multivariate and machine learning methods were used to develop models to rank the importance of features that could distinguish ASD from TD. A set of 179 statistically significant features resulting from univariate analysis were used for multivariate modeling. Subsets of these features properly classified the ASD and TD samples in the 61-sample training set with average accuracies of 84% and 86%, and with a maximum accuracy of 81% in an independent 21-sample validation set. The authors concluded that this analysis of blood plasma metabolites resulted in the discovery of biomarkers that may be valuable in the diagnosis of young children with ASD. The results will form the basis for additional discovery and validation research for:

determining biomarkers to develop diagnostic tests to detect ASD earlier and improve patient outcomes,
gaining new insight into the biochemical mechanisms of various subtypes of ASD,
identifying biomolecular targets for new modes of therapy, and
providing the basis for individualized treatment recommendations.

Music Therapy

Crawford and colleagues (2017) stated that preliminary studies have indicated that music therapy may benefit children with ASD. In an international, multi-center, 3-arm, single-masked RCT, including a National Institute for Health Research (NIHR)-funded center, these researchers examined the effects of improvisational music therapy (IMT) on social affect and responsiveness of children with ASD. Randomization was via a remote service using permuted blocks, stratified by study site. Subjects were children aged between 4 and 7 years with a confirmed diagnosis of ASD and a parent or guardian who provided written informed consent. These investigators excluded children with serious sensory disorder and those who had received music therapy within the past 12 months. All parents and children received enhanced standard care (ESC), which involved three 60-min sessions of advice and support in addition to treatment as usual. In addition, they were randomized to either 1 (low-frequency) or 3 (high-frequency) sessions of IMT per week, or to ESC alone, over 5 months in a ratio of 1 : 1 : 2. The primary outcome was measured using the social affect score derived from the ADOS at 5 months: higher scores indicated greater impairment; secondary outcomes included social affect at 12 months and parent-rated social responsiveness at 5 and 12 months (higher scores indicated greater impairment). A total of 364 participants were randomized between 2011 and 2015. A total of 182 children were allocated to IMT (90 to high-frequency sessions and 92 to low-frequency sessions), and 182 were allocated to ESC alone. A total of 314 (86.3 %) of the total sample were followed-up at 5 months [165 (90.7 %) in the intervention group and 149 (81.9 %) in the control group]. Among those randomized to IMT, 171 (94.0 %) received it. From baseline to 5 months, mean scores of ADOS social affect decreased from 14.1 to 13.3 in music therapy and from 13.5 to 12.4 in standard care [MD: music therapy versus standard care = 0.06, 95 % CI: -0.70 to 0.81], with no significant difference in improvement. There were also no differences in the parent-rated social responsiveness score, which decreased from 96.0 to 89.2 in the music therapy group and from 96.1 to 93.3 in the standard care group over this period (MD: music therapy versus standard care = -3.32, 95 % CI: -7.56 to 0.91). There were 7 admissions to hospital that were unrelated to the study interventions in the 2 IMT arms compared with 10 unrelated admissions in the ESC group. The authors concluded that adding IMT to the treatment received by children with ASD did not improve social affect or parent-assessed social responsiveness.

In an assessor-blinded, randomized clinical trial, conducted in 9 countries, Bieleninik and associates (2017) examined the effects of IMT on generalized social communication skills of children with ASD. Children aged 4 to 7 years with ASD were enrolled in this study; they were recruited from November 2011 to November 2015, with follow-up between January 2012 and November 2016. These researchers compared ESC (n = 182) versus ESC plus IMT (n = 182), allocated in a 1:1 ratio; ESC consisted of usual care as locally available plus parent counseling to discuss parents' concerns and provide information about ASD. In IMT, trained music therapists sang or played music with each child, attuned and adapted to the child's focus of attention, to help children develop affect sharing and joint attention. The primary outcome was symptom severity over 5 months, based on the ADOS, social affect domain (range of 0 to 27; higher scores indicate greater severity; minimal clinically important difference, 1). Pre-specified secondary outcomes included parent-rated social responsiveness. All outcomes were also assessed at 2 and 12 months. Among 364 participants randomized (mean age of 5.4 years; 83 % boys), 314 (86 %) completed the primary end-point and 290 (80 %) completed the last end-point. Over 5 months, participants assigned to IMT received a median of 19 music therapy, 3 parent counseling, and 36 other therapy sessions, compared with 3 parent counseling and 45 other therapy sessions for those assigned to ESC. From baseline to 5 months, mean ADOS social affect scores estimated by linear mixed-effects models decreased from 14.08 to 13.23 in the IMT group and from 13.49 to 12.58 in the ESC group (MD, 0.06; 95 % CI: -0.70 to 0.81; p = 0.88), with no significant difference in improvement. Of 20 exploratory secondary outcomes, 17 showed no significant difference. The authors concluded that among children with ASD, IMT, compared with ESC, resulted in no significant difference in symptom severity based on the ADOS social affect domain over 5 months. They stated that these findings did not support the use of IMT for symptom reduction in children with ASD.

Geretsegger et al (2022) stated that music therapy has been used in autism since the early 1950s; however, its availability to autistic individuals varies across countries and settings. The use of music therapy requires specialized academic and clinical training that enables therapists to tailor the intervention to the specific needs of the individual. This current review on music therapy for autistic individuals is an update of the previous Cochrane review update published in 2014 (following the original Cochrane review published in 2006). The authors concluded that compared with earlier versions of this review, the new studies included in this update helped to increase the certainty and applicability of this review's findings through larger sample sizes, extended age groups, longer periods of intervention and inclusion of follow-up assessments, and by predominantly using validated scales measuring generalized behavior (i.e., behavior outside of the therapy context). This new evidence is important for autistic individuals and their families as well as for policymakers, service providers and clinicians, to aid in decisions around the types and amount of intervention that should be provided and in the planning of resources. The applicability of the findings is still limited to the age groups included in the studies, and no direct conclusions can be drawn regarding music therapy in autistic individuals above the young adult age. These researchers stated that more research using rigorous designs, relevant outcome measures, and longer-term follow-up periods is needed to corroborate these findings and to examine if the effects of music therapy are enduring.

Nutritional Therapy

Sausmikat and Smollich (2016) provided evidence-based data on nutritional interventions for children and adolescents with ASD, thus enabling practitioners to competently assess these diets. Applying defined inclusion and exclusion criteria, a systematic literature research in PubMed, Cinahl and the Cochrane Library was conducted. Studies published earlier than 1999 were excluded. Study quality was assessed by using the CONSORT, STROBE or Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist, respectively. A total of 12 RCTs and 2 non-controlled studies were included in the evaluation (n = 971). There is no proven efficacy of the widely used gluten-free and casein-free diets (GFCF), and no respective predictive marker has been proven significant. The authors concluded that based on available data, no evidence-based recommendations regarding nutritional interventions for children and adolescents with ASD can be made. They stated that future studies need to clarify whether particular patients may yet benefit from certain diets.

Oxytocin Therapy

Tachibana et al (2013) stated that oxytocin (OT) has been a candidate for the treatment of ASD, and the impact of intra-nasally delivered OT on ASD has been investigated. However, most previous studies were conducted by single-dose administration to adults; and, therefore, the long-term effect of nasal OT on ASD patients and its effect on children remain to be clarified. These researchers conducted a singled-armed, open-label study in which OT was administered intra-nasally over the long term to 8 male youth with ASD (10 to 14 years of age; intelligence quotient [IQ] 20 to 101). The OT administration was performed in a step-wise increased dosage manner every 2 months (8, 16, 24 IU/dose). A placebo period (1 to 2 weeks) was inserted before each step. The outcome measures were autism diagnostic observation schedule – generic (ADOS-G), child behavior checklist (CBCL), and the aberrant behavior checklist (ABC). In addition, side effects were monitored by measuring blood pressure and examining urine and blood samples. Six of the 8 participants showed improved scores on the communication and social interaction domains of the ADOS-G. However, regarding the T-scores of the CBCL and the scores of the ABC, these investigators could not find any statistically significant improvement, although several subcategories showed a mild tendency for improvement. Care-givers of 5 of the 8 participants reported certain positive effects of the OT therapy, especially on the quality of reciprocal communication. All participants showed excellent compliance and no side effects. The authors concluded that although these findings on the effectiveness of long-term nasal OT therapy still remain controversial, to the best of these researchers’ knowledge, this was the first report documenting the safety of long-term nasal OT therapy for children with ASD. They stated that even though these data were too preliminary to draw any definite conclusions about effectiveness, they do suggest this therapy to be safe, promising, and worthy of a large-scale, double-blind placebo-controlled study.

Anagnostou et al (2014) reviewed the literature for OT and ASD and reported on early dosing, safety and efficacy data of multi-dose OT on aspects of social cognition/function, as well as repetitive behaviors and co-occurring anxiety within ASD. A total of 15 children and adolescents with verbal IQs greater than or equal to 70 were diagnosed with ASD using the ADOS and the ADI-R. They participated in a modified maximum tolerated dose study of intra-nasal OT (Syntocinon). Data were modeled using repeated measures regression analysis controlling for week, dose, age, and sex. Among 4 doses tested, the highest dose evaluated, 0.4 IU/kg/dose, was found to be well-tolerated. No serious or severe adverse events were reported and adverse events reported/observed were mild-to-moderate. Over 12 weeks of treatment, several measures of social cognition/function, repetitive behaviors and anxiety showed sensitivity to change with some measures suggesting maintenance of effect 3 months past discontinuation of intra-nasal OT. The authors concluded that the findings of this pilot study suggested that daily administration of intra-nasal OT at 0.4 IU/kg/dose in children and adolescents with ASD is safe and has therapeutic potential. Moreover, they stated that larger studies are needed.

Preti et al (2014) noted that little is known about the effectiveness of pharmacological interventions on ASD. These investigators performed a systematic review of RCTs of OT interventions in autism (from January 1990 to September 2013). A search of computerized databases was supplemented by manual search in the bibliographies of key publications. The methodological quality of the studies included in the review was evaluated independently by 2 researchers, according to a set of formal criteria. Discrepancies in scoring were resolved through discussion. The review yielded 7 RCTs, including 101 subjects with ASD (males = 95) and 8 males with Fragile X syndrome. The main categories of target symptoms tested in the studies were repetitive behaviors, eye gaze, and emotion recognition. The studies had a medium to high risk of bias. Most studies had small samples (median = 15). All the studies but 1 reported statistically significant between-group differences on at least 1 outcome variable. Most findings were characterized by medium effect size. Only 1 study had evidence that the improvement in emotion recognition was maintained after 6 weeks of treatment with intra-nasal OT. Overall, OT was well-tolerated and side effects, when present, were generally rated as mild; however, restlessness, increased irritability, and increased energy occurred more often under OT. The authors concluded that RCTs of OT interventions in autism yielded potentially promising findings in measures of emotion recognition and eye gaze, which were impaired early in the course of the ASD condition and might disrupt social skills learning in developing children. They stated that there is a need for larger, more methodologically rigorous RCTs in this area. They noted that future studies should be better powered to estimate outcomes with medium to low effect size, and should try to enroll female participants, who were rarely considered in previous studies; risk of bias should be minimized. These researchers stated that human long-term administration studies are needed before clinical recommendations can be made.

Evans et al (2014) noted that the last decade has seen a large number of published findings supporting the hypothesis that intra-nasally delivered OT can enhance the processing of social stimuli and regulate social emotion-related behaviors such as trust, memory, fidelity, and anxiety. The use of nasal spray for administering OT in behavioral research has become a standard method, but many questions still exist regarding its action. Oxytocin is a peptide that cannot cross the blood-brain barrier, and it has yet to be shown that it does indeed reach the brain when delivered intra-nasally. Given the evidence, it seems highly likely that OT does affect behavior when delivered as a nasal spray. These effects may be driven by at least 3possible mechanisms:

the intra-nasally delivered OT may diffuse directly into the central nervous system (CNS) where it directly engages OT receptors;
the intra-nasally delivered OT may trigger increased central release via an indirect peripheral mechanism; and
the indirect peripheral effects may directly lead to behavioral effects via some mechanism other than increased central release.

Although intra-nasally delivered OT likely affects behavior, there are conflicting reports as to the exact nature of those behavioral changes: some studies suggested that OT effects are not always "pro-social" and others suggested effects on social behaviors are due to a more general anxiolytic effect. In this critique, the authors drew from work in healthy human populations and the animal literature to review the mechanistic aspects of intra-nasal OT delivery, and discussed intra-nasal OT effects on social cognition and behavior. They concluded that future work should control carefully for anxiolytic and gender effects, which could underlie inconsistencies in the existing literature.

Quintana et al (2015) stated that accumulating evidence demonstrated the important role of OT in the modulation of social cognition and behavior. This has led many to suggest that the intra-nasal administration of OT may benefit psychiatric disorders characterized by social dysfunction, such as ASD and schizophrenia. These investigators reviewed nasal anatomy and OT pathways to central and peripheral destinations, along with the impact of OT delivery to these destinations on social behavior and cognition. The primary goal of this review is to describe how these identified pathways may contribute to mechanisms of OT action on social cognition and behavior (i.e., modulation of social information processing, anxiolytic effects, increases in approach-behaviors). The authors proposed a 2-level model involving 3 pathways to account for responses observed in both social cognition and behavior after intra-nasal OT administration and suggested avenues for future research to advance this research field.

Furthermore, an UpToDate review on "Autism spectrum disorder in children and adolescents: Pharmacologic interventions" (Weissman and Bridgemohan, 2015) states that "Pharmacologic agents that demonstrated potential benefit for social deficits in individuals with autism spectrum disorder in small open-label studies include oxytocin, D-cycloserine, tetrahydrobiopterin, and cognition enhancers used in the treatment of Alzheimer disease (e.g., galantamine, memantine, and rivastigmine). Additional controlled studies are necessary to confirm efficacy and safety before these therapies can be recommended".

Owada and colleagues (2019) stated that discrepancies in efficacy between single-dose and repeated administration of oxytocin for ASD have led researchers to hypothesize that time-course changes in efficacy are induced by repeated administrations of the peptide hormone. However, repeatable, objective, and quantitative measurement of ASD's core symptoms are lacking, making it difficult to examine potential time-course changes in efficacy. These researchers tested this hypothesis using repeatable, objective, and quantitative measurement of the core symptoms of ASD. They examined videos recorded during semi-structured social interaction administered as the primary outcome in single-site exploratory (n = 18, cross-over within-subjects design) and multi-site confirmatory (n = 106, parallel-group design), double-blind, placebo-controlled 6-week trials of repeated intra-nasal administrations of oxytocin (48 IU/day) in men with ASD. The main outcomes were statistical representative values of objectively quantified facial expression intensity in a repeatable part of the Autism Diagnostic Observation Schedule: the maximum probability (i.e., mode) and the natural logarithm of mode on the probability density function of neutral facial expression and the natural logarithm of mode on the probability density function of happy expression. A recent study by these researchers revealed that increases in these indices characterized autistic facial expression, compared with neurotypical individuals. The current results revealed that oxytocin consistently and significantly decreased the increased natural logarithm of mode on the probability density function of neutral facial expression compared with placebo in exploratory (effect-size, -0.57; 95 % CI: -1.27 to 0.13; p = 0.023) and confirmatory trials (-0.41; -0.62 to -0.20; p < 0.001). A significant interaction between time-course (at baseline, 2, 4, 6, and 8 weeks) and the efficacy of oxytocin on the natural logarithm of mode on the probability density function of neutral facial expression was found in confirmatory trial (p < 0.001). Post-hoc analyses revealed maximum efficacy at 2 weeks (p < 0.001, Cohen's d = -0.78; 95 % CI: -1.21 to -0.35) and deterioration of efficacy at 4 weeks (p = 0.042, Cohen's d = -0.46; 95 % CI: -0.90 to -0.01) and 6 weeks (p = 0.10, Cohen's d = -0.35; 95 % CI: -0.77 to 0.08), while efficacy was preserved at 2 weeks post-treatment (i.e., 8 weeks) (p < 0.001, Cohen's d = -1.24; 95 % CI: -1.71 to -0.78). Quantitative facial expression analyses successfully verified the positive effects of repeated oxytocin on autistic individuals' facial expressions and demonstrated a time-course change in efficacy. The authors concluded that these findings support further development of optimization of objective, quantitative, and repeatable outcome measures for autistic social deficits and to establish optimized regimen of oxytocin treatment for ASD.

The authors stated that this study had several potential limitations and methodological considerations that should be considered. First, subjects in this trials were all adult, male, Japanese individuals with ASD. Thus, while the uniformity in subjects’ demographic characteristics enhanced the ability to detect scientifically sound evidence, it should be noted that the current findings may not be generalizable to other clinical or non-clinical populations. Second, since the outcome measure of current study was developed in the authors’ research team, the findings should be replicated by other research groups. The majority of the quantification methods were automatically conducted and independent of human labor, facilitating the replication of the current findings. Third, as some autistic characteristics in facial expression at baseline, such as a high mode of neutral facial expression and log-PDF mode of happy facial expression were not significantly improved by oxytocin treatment, these investigators were unable to conclude that oxytocin could treat or recover all characteristics of facial expression in individuals with ASD. Furthermore, these researchers did not show an association between the effects of oxytocin on the quantified facial expression and those on beneficial therapeutic outcomes, such as Clinical Global Impressions (CGI) or Global Assessment of Functioning (GAF). Although the effects of oxytocin on the variability of neutral facial expression exhibited weak correlations with the neural effect of oxytocin on anterior cingulate activity during a social judgment task (ρ = −0.56, p = 0.028) and on resting state functional connectivity between anterior cingulate and dorsomedial prefrontal cortices (ρ = −0.60, p = 0.019) assessed with functional MRI in the exploratory trial, the current results did not necessarily support the clinically beneficial effects of oxytocin. Fourth, the possibility of further improving the method of quantifying facial expressions, the task used to induce facial expressions in individuals with autism, and the outcome variables, should be considered. FaceReader and ADOS are not optimized for longitudinal facial expression analyses in individuals with ASD. It could be useful to validate these tools (and other available software) in this methodological context using electromyography (EMG), and/or action unit processing. The outcome variables used were determined based on the results of the authors’ previous case-control comparison in a limited sample size.

Sikich et al (2021) stated that experimental studies and small clinical trials have suggested that treatment with intra-nasal OT may reduce social impairment in individuals with ASD. These researchers carried out a 24-week, placebo-controlled, phase-II clinical trial of intra-nasal OT therapy in children and adolescents 3 to 17 years of age with ASD. Subjects were randomly assigned in a 1:1 ratio, with stratification according to age and verbal fluency, to receive OT or placebo, administered intra-nasally, with a total target dose of 48 international units daily. The primary outcome was the least-squares mean change from baseline on the ABC modified Social Withdrawal subscale (ABC-mSW), which includes 13 items (scores range from 0 to 39, with higher scores indicating less social interaction). Secondary outcomes included 2 additional measures of social function and an abbreviated measure of IQ. Of the 355 children and adolescents who underwent screening, 290 were enrolled. A total of 146 subjects were assigned to the OT group and 144 to the placebo group; 139 and 138 subjects, respectively, completed both the baseline and at least 1 post-baseline ABC-mSW assessments and were included in the modified intention-to-treat (ITT) analyses. The least-squares mean change from baseline in the ABC-mSW score (primary outcome) was -3.7 in the OT group and -3.5 in the placebo group (least-squares mean difference, -0.2; 95 % CI: -1.5 to 1.0; p = 0.61). Secondary outcomes generally did not differ between the trial groups. The incidence and severity of AEs were similar in the 2 groups. The authors concluded that this phase-II clinical trial of 24 weeks of daily intra-nasal OT treatment, as compared with placebo, did not improve social interaction or other measures of social function related to ASD.

Prebiotic / Probiotic Therapy

Shaaban and co-workers (2018) noted that there are limited data on the efficacy of probiotics in children with ASD. In a prospective, open-label study, these investigators examined the efficacy and tolerability of probiotics in a cohort of children with ASD. Gastro-intestinal (GI) flora were assessed by quantitative real-time PCR of stool samples of 30 autistic children aged 5 to 9 years; GI symptoms of autistic children were assessed with a modified 6-item Gastrointestinal Severity Index (6-GSI) questionnaire, and autistic symptoms were assessed with Autism Treatment Evaluation Checklist (ATEC) before and after 3 months of supplementation of probiotics nutritional supplement formula (each gram contains 100 × 106 colony forming units of 3 probiotic strains; Lactobacillus acidophilus, Lactobacillus rhamnosus and Bifidobacteria longum). After probiotic supplementation, the stool PCR of autistic children showed increases in the colony counts of Bifidobacteria and Lactobacilli levels, with a significant reduction in their body weight as well as significant improvements in the severity of autism (assessed by the ATEC), and GI symptoms (assessed by the 6-GSI) compared to the baseline evaluated at the start of the study. The authors concluded that probiotics have beneficial effects on both behavioral and GI manifestations of ASD. Probiotics (a non-pharmacological and relatively risk-free option) could be recommended for children with ASD as an adjuvant therapy. Moreover, these researchers noted that at this study was a single-center trial with a small number of patients (n = 30); they stated that additional large-scale RCTs are needed to confirm the efficacy of probiotics in ASD.

Liu and colleagues (2019b) noted that the therapeutic potentials of probiotics in ASD remains controversial, with the only existing systematic review on this topic published in 2015. Results from new trials have become available in recent years. These researchers conducted an updated systematic review, to evaluate the efficacy of probiotics in relieving behavioral symptoms of ASD and GI co-morbidities. This review included 2 RCTs, which showed improvement of ASD behaviors, and 3 open-label trials, which exhibited a trend of improvement; 4 of these trials concluded from subjective measures that GI function indices showed a trend of improvement with probiotic therapy. The authors concluded that additional rigorous trials are needed to evaluate the effects of probiotic supplements in ASD.

Ng and associates (2019) stated that ASD is a complex developmental condition typically characterized by deficits in social and communicative behaviors as well as repetitive patterns of behaviors. Despite its prevalence (affecting 0.1 % to 1.8% of the global population), the pathogenesis of ASD remains incompletely understood. Patients with ASD are reported to have more frequent GI complaints. There is some anecdotal evidence that probiotics are able to alleviate GI symptoms as well as improve behavioral issues in children with ASD. However, systematic reviews of the effect of prebiotics/probiotics on ASD and its associated symptoms are lacking. Using the keywords (prebiotics OR probiotics or microbiota or gut) and (autism or social or ASD), a systematic literature search was conducted on PubMed, Embase, Medline, Clinicaltrials.gov and Google Scholar databases. The inclusion criteria were original clinical trials, published in English between the period January 1, 1988 and February 1, 2019. A total of 8 clinical trials were systematically reviewed; 2 clinical trials examined the use of prebiotic and/or diet exclusion while 6 involved the use of probiotic supplementation in children with ASD. Most of these were prospective, open-label studies. Prebiotics only improved certain GI symptoms; however, when combined with an exclusion diet (gluten and casein free) showed a significant reduction in anti-sociability scores. As for probiotics, there is limited evidence to support the role of probiotics in alleviating the GI or behavioral symptoms in children with ASD. The 2 available double-blind, randomized, placebo-controlled trials found no significant difference in GI symptoms and behavior. The authors concluded that despite promising pre-clinical findings, prebiotics and probiotics have demonstrated an overall limited efficacy in the management of GI or behavioral symptoms in children with ASD. In addition, there was no standardized probiotics regimen, with multiple different strains and concentrations of probiotics, and variable duration of treatments.

Saliva Analysis Testing

Quadrant Biosciences, Inc. offers Clarifi autism spectrum disorder (ASD) saliva test for children with a clinical suspicion of ASD, such as a positive screen on the modified checklist for autism in toddlers – revised (MCHAT-R), who are 18 months through 6 years of age. The Clarifi test is a healthcare provider administered saliva swab test designed to provide a probability of an autism diagnosis based on regulatory RNAs and microbes found in the saliva. There are conditions that have not been clinically validated and may affect the validity of the test including, but not limited to, dental caries, fever, cold/flu/sinus conditions, feeding tubes, known chromosomal deletions or duplications, epilepsy, and head trauma (Quadrant Biosciences, 2020).

Hicks et al. (2018) state that ASD relies on behavioral assessment and that efforts to define biomarkers of ASD have not resulted in an objective, reliable test. The authors report that studies have demonstrated that RNA levels in ASD have potential utility, but have been limited by a focus on single RNA types, small sample sizes, and lack of developmental delay controls. Thus, the authors conducted a multi-center cross-sectional study which included 456 children, ages 19-83 months. Children were either neurotypical (n = 134) or had a diagnosis of ASD (n = 238), or non-ASD developmental delay (n = 84). Comprehensive human and microbial RNA abundance was measured in the saliva of all participants using unbiased next generation sequencing. Prior to analysis, the sample was randomly divided into a training set (82% of subjects) and an independent validation test set (18% of subjects). The training set was used to develop an RNA-based algorithm that distinguished ASD and non-ASD children. The validation set was not used in model development (feature selection or training) but served only to validate empirical accuracy. The authors found that in the training set (n = 372; mean age 51 months; 51% ASD), a set of 32 RNA features, identified ASD status with a cross-validated area under the curve (AUC) of 0.87 (95% CI: 0.86-0.88). In the completely separate validation test set (n = 84; mean age 50 months; 60% ASD), the algorithm maintained an AUC of 0.88 (82% sensitivity and 88% specificity). Notably, the RNA features were implicated in physiologic processes related to ASD (axon guidance, neurotrophic signaling). The authors concluded that salivary poly-omic RNA measurement represents a novel, non-invasive approach that can accurately identify children with ASD. This technology could improve the specificity of referrals for ASD evaluation or provide objective support for ASD diagnoses. The authors note the study limitations include reliance on microbial measures for ASD identification which will require accounting for features influenced by diet and geography. The current study enrolled children from multiple sites and relied on several microbes found in humans throughout the world (e.g., Lactobacillus). However, validation of RNA from less common bacteria (e.g., Oenococcus oeni) will require sample collection from diverse sites. In addition, numerous medical and demographic factors may influence RNA expression in the oropharynx. The authors state that because medical and demographic features of their cohort generally represent childhood ASD populations, they expect these differences will not impact external validity. Indeed, in the test set (which was matched on ASD:TD:DD ratios, but not medical and demographic factors) the RNA panel maintained predictive accuracy. The authors report that they have developed an objective, quantitative algorithm based on salivary RNA abundance that accurately discriminates children with ASD from peers with DD or TD. This non-invasive test could augment the accuracy of current ASD assessment, as an adjunctive tool for children with positive MCHAT screening, or an objective aid in ASD diagnosis.

Kong et al. (2019) state that while most studies agree that the microbiome composition is different between autistic and neurotypical populations, these studies have yielded inconsistent results as to the nature or extent of these GI bacterial community differences. Compared to the gut, the oral microbiome is understudied, despite dental plaque and saliva samples being easier to obtain than stool samples. The authors designed a pilot study to investigate the oral and gut microbiome simultaneously in patients with ASD and their first-degree family members. The first degree-relative matched design combined with high fidelity 16S rRNA (ribosomal RNA) gene amplicon sequencing was used in order to characterize the oral and gut microbiotas of patients with ASD compared to neurotypical individuals, and explored the utility of microbiome markers for ASD diagnosis and subtyping of clinical comorbid conditions. 20 patients diagnosed with ASD were recruited and compared with 19 family members (parent or sibling) as neurotypical controls. Exclusion criteria for all subjects included known genetic conditions, clinically evident serious infections or inflammatory conditions, history of cancer, severe dental/periodontal diseases or possession of dental braces. Subjects who had received probiotic treatment were asked to stop treatment at least one week prior to sample collection and subjects were excluded if they had taken antibiotics in the preceding month. The authors report that their study identified distinct features of gut and salivary microbiota that differ between individuals with and without an ASD diagnosis. Given the emerging role that the human microbiome plays in systemic diseases, they hope that their analyses will provide clues for developing microbial markers for diagnosing ASD and comorbid conditions, and to guide treatment. The authors pointed out the limitations of their study which include: (1) The use of both sibling and parental controls, where age could contribute to the large inter-individual variability. Future studies should focus on only age-matched sibling controls, if possible. (2) The small sample size, which likely contributed to high FDR in the majority of their analyses and the difficulty in distinguishing true differences from noise. Verification of their findings with a larger cohort is required. Furthermore, the current study was not sufficiently powered for detecting clinically relevant biomarkers.

Hicks et al. (2020) conducted a multicenter, prospective, case-control study to investigate the utility of salivary microRNAs for differentiating children with ASD from peers with typical development (TD) and non-autism developmental delay (DD). The secondary purpose was to explore microRNA patterns among ASD phenotypes. The study included 443 children (2-6 yrs old) diagnosed with ASD per DSM-5 criteria. Children with ASD or DD were assessed with the Autism Diagnostic Observation Schedule II and Vineland Adaptive Behavior Scales II. MicroRNAs were measured with high-throughput sequencing. Differential expression of microRNAs was compared among the ASD (n = 187), TD (n = 125), and DD (n = 69) groups in the training set (n = 381). Multivariate logistic regression defined a panel of microRNAs that differentiated children with ASD and those without ASD. The algorithm was tested in a prospectively collected naïve set of 62 samples (ASD, n = 37; TD, n = 8; DD, n = 17). Relations between microRNA levels and ASD phenotypes were explored. The authors found 14 microRNAs displayed differential expression (false discovery rate < 0.05) among ASD, TD, and DD groups. A panel of 4 microRNAs (controlling for medical/demographic covariates) best differentiated children with ASD from children without ASD in training (area under the curve = 0.725) and validation (area under the curve = 0.694) sets. Eight microRNAs were associated (R > 0.25, false discovery rate < 0.05) with social affect, and 10 microRNAs were associated with restricted/repetitive behavior. The authors concluded that salivary microRNAs are "altered" in children with ASD and associated with levels of ASD behaviors. Salivary microRNA collection is noninvasive, identifying ASD-status with moderate accuracy. A multi-"omic" approach using additional RNA families could improve accuracy, leading to clinical application.

An UpToDate review on "Autism spectrum disorder: Screening tools" (Weissman, 2020) does not mention the utility of saliva analysis testing as a screening or assessment tool for diagnosing autism spectrum disorder. An UpToDate review on "Autism spectrum disorder: Evaluation and diagnosis" (Augustyn and von Hahn, 2019) state that tests for yeast metabolites, gut permeability and micronutrients are not indicated since there are no empiric data to support such analyses. There is no mention of the utility of saliva analysis testing for evaluating and diagnosing children with ASD.

Screening in Young Children

Siu and colleagues (2016) reported on the new US Preventive Services Task Force (USPSTF) recommendation on screening for ASD in young children. The USPSTF reviewed the evidence on the accuracy, benefits, and potential harms of brief, formal screening instruments for ASD administered during routine primary care visits and the benefits and potential harms of early behavioral treatment for young children identified with ASD through screening. This recommendation applies to children aged 18 to 30 months who have not been diagnosed with ASD or developmental delay and for whom no concerns of ASD have been raised by parents, other caregivers, or health care professionals. The USPSTF concluded that the current evidence is insufficient to assess the balance of benefits and harms of screening for ASD in young children for whom no concerns of ASD have been raised by their parents or a clinician. This recommendation is in agreement with:

American Academy of Family Physicians (2015) which states that the current evidence is insufficient to assess the balance of benefits and harms of screening for ASD in children for whom no concerns of ASD have been raised by their parents or clinical provider, and
the UK national Screening Committee (2015), which does not recommend systematic population screening, citing concerns about the stability of ASD diagnosis at a young age, lack of data on positive predictive value, and weakness of the evidence for the efficacy of treatment.

Serum Cytokine and Growth Factor Levels

Lochman and colleagues (2018) noted that the immune system may have a role in the pathogenesis of ASD, including typical and atypical autism. These researchers examined if a cytokine and growth factor panel could be identified for the diagnosis and prognosis in children with ASD, including typical and atypical autism. This trial enrolled 26 children with ASD (typical or atypical) and 11 of their siblings who did not have ASD. A panel of 10 serum cytokines and growth factors were investigated using addressable laser bead assay (ALBIA) and enzyme-linked immunosorbent assay (ELISA) kits. Results were correlated with scores using the CARS and ADOS for the children with ASD and compared with the findings from their siblings without ASD. There were no statistically significant differences in serum cytokine and growth factor levels between children with ASD and their siblings. The scores using CARS and ADOS were significantly greater in children with typical autism compared with children with atypical autism as part of the ASD spectrum. Serum levels of cytokines and growth factors showed a positive correlation with CARS and ADOS scores but differed between children with typical and atypical autism and their siblings. The authors concluded that the findings of this study showed that serum measurement of appropriately selected panels of cytokines and growth factors might have a role in the diagnosis of ASD.

Testing of Single-Nucleotide Polymorphisms Within the Oxytocin and Vasopressin Receptor Genes

Wilczyński and colleagues (2019a) stated that ASD is found in virtually all population groups regardless of ethnic or socio-economic backgrounds. Among others, dominant symptoms of autism persistent throughout its course of development include, inter alia, qualitative disorders of social communication and social interactions. Numerous studies have been performed on animal models as well as groups of healthy individuals to examine the potential role of oxytocinergic and vasopressinergic systems in normal social functioning. In a systematic review, these investigators discussed their potential participation in the development of social cognition dysfunctions in the course of ASD. This literature review identified studies examining single-nucleotide polymorphisms (SNPs) of the OXT and AVP receptor genes and their differential effects on social cognitive dysfunction in the development of ASD. These researchers carried out a systematic review of literature published within the last 10 years and accessible in PubMed, Google Scholar, Cochrane Library, and APA PsycNET databases by each author separately. Inclusion criteria required that articles should be published between January 2008 and August 2018; be published in English or Polish; be located in periodical publications; focus on the role of polymorphisms within OXT and VP receptor genes in autistic population; provide a clear presentation of the applied methodology; and apply proper methodology. From the 491 studies qualified to the initial abstract analysis, 15 met the 6 inclusion criteria and were included in the full-text review. The authors concluded that the analysis of available literature appeared to indicate that there is an association between social cognition dysfunctions in the course of autism and selected alleles of polymorphisms within the OXT receptor AVP 1A receptor genes. However, these researchers stated that previous studies neither specified the nature of this association in an unequivocal way nor select genotypes that were the basis for this association. They stated that further research into this field, which will maintain a more uniform structure of studied groups, is definitely needed, and in the future, it may help bring a better understanding of the pathogenesis of social cognition dysfunctions and their relation to ASD.

Tests for Glutamatergic Candidate Genes

Chiocchetti and associates (2014) noted that ASD are neurodevelopmental disorders with early onset in childhood. Most of the risk for ASD can be explained by genetic variants that act in interaction with biological environmental risk factors. However, the architecture of the genetic components is still unclear. Genetic studies and subsequent systems biological approaches described converging functional effects of identified genes towards pathways relevant for neuronal signaling. Mouse models suggested an aberrant synaptic plasticity at the neuropathological level, which is believed to be conferred by dysregulation of long-term potentiation or depression of neuronal connections. A central pathway regulating these mechanisms is glutamatergic signaling. These researchers hypothesized that susceptibility genes for ASD are enriched for components of this pathway. To further understand the impact of ASD risk genes on the glutamatergic pathway, these investigators performed a systematic review using the literature database "PubMed" and the "AutismKB" knowledgebase. They provided an overview of the glutamatergic system in typical brain function and development, and summarized findings from linkage, association, copy number variants, and sequencing studies in ASD to provide a comprehensive picture of the glutamatergic landscape of ASD genetics. Genetic variants associated with ASD were enriched in glutamatergic pathways, affecting receptor signaling, metabolism and transport. Furthermore, in genetically modified mouse models for ASD, pharmacological compounds acting on ionotropic or metabotropic receptor activity were able to rescue ASD reminiscent phenotypes. The authors concluded that glutamatergic genetic risk factors for ASD showed a complex pattern and further studies are needed to fully understand its mechanisms, before translation of findings into clinical applications and individualized treatment approaches will be possible.

Tests for Olfactory Function

Tonacci and colleagues (2017) stated that olfactory function is a well-known early biomarker for neurodegeneration and neural functioning in the adult population, being supported by a number of brain structures that could be dysfunctioning in neurodegenerative processes. Evidence has suggested that atypical sensory and, particularly, olfactory processing is present in several neurodevelopmental conditions, including ASDs. These investigators presented data obtained by a systematic literature review, conducted according to PRISMA guidelines, regarding the possible association between olfaction and ASDs, and analyzed them critically in order to evaluate the occurrence of olfactory impairment in ASDs, as well as the possible usefulness of olfactory evaluation in such conditions. The results obtained in this analysis suggested a possible involvement of olfactory impairment in ASDs, underlining the importance of olfactory evaluation in the clinical assessment of ASDs. The authors concluded that this assessment could be potentially included as a complementary evaluation in the diagnostic protocol of the condition.

Therapeutic Diets (e.g., Ketogenic Diet and Modified Atkins Diet)

El-Rashidy and colleagues (2017) stated that many diet regimens were studied for patients with ASD over the past several years. Ketogenic diet is gaining attention due to its proven effect on neurological conditions like epilepsy in children. In a case-control study, a total of 45 children aged 3 to 8 years diagnosed with ASD based on DSM-5 criteria were enrolled to compare ketogenic diet versus gluten free casein free diet for the treatment of ASD. Patients were equally divided into 3 groups, first group received ketogenic diet as modified Atkins diet (MAD), second group received gluten free casein free (GFCF) diet, and the third group received balanced nutrition and served as a control group. All patients were assessed in terms of neurological examination, anthropometric measures, as well as Childhood Autism Rating Scale (CARS), Autism Treatment Evaluation Test (ATEC) scales before and 6 months after starting diet. Both diet groups showed significant improvement in ATEC and CARS scores in comparison to control group, yet ketogenic scored better results in cognition and sociability compared to GFCF diet group. The authors concluded that depending on the parameters measured in this study, modified Atkins diet and gluten free casein free diet regimens may safely improve autistic manifestations and could be recommended for children with ASD. Moreover, they noted that this study was a single-center trial with a small number of subjects (n = 45); more large-scale prospective studies are needed to confirm these findings.

Gogou and Kolios (2018) stated that a nutritional background has been recognized in the pathophysiology of autism and a series of nutritional interventions have been considered as complementary therapeutic options. As available treatments and interventions are not effective in all individuals, new therapies could broaden management options for these patients. These investigators provided current literature data regarding the effect of therapeutic diets on ASD. A systematic review was conducted by 2 reviewers independently; prospective clinical and pre-clinical studies were considered. Therapeutic diets that have been used in children with autism include ketogenic and gluten/casein-free diet. These researchers were able to identify 8 studies conducted in animal models of autism demonstrating a beneficial effect on neurophysiological and clinical parameters. Only 1 clinical study was found showing improvement in childhood autism rating scale after implementation of ketogenic diet. With regard to gluten/casein-free diet, 4 clinical studies were totally found with 2 of them showing a favorable outcome in children with autism. Furthermore, a combination of gluten-free and modified ketogenic diet in a study had a positive effect on social affect scores. No serious adverse events (AEs) have been reported. The authors concluded that despite encouraging laboratory data, there is controversy regarding the real clinical effect of therapeutic diets in patients with ASD. They stated that more research is needed to provide sounder scientific evidence.

Transcranial Direct Current Stimulation

Kang and colleagues (2018) noted that ASD is a heterogeneous neurodevelopmental disorder that affects the developmental trajectory in several behavioral domains, including impairments of social communication, cognitive and language abilities. Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique, and it was used for modulating the brain disorders. In this study, these researchers enrolled 13 ASD children (11 males and 2 females; mean ± SD age of 6.5 ± 1.7 years) to examine the effects of tDCS on ASD. Each patient received 10 treatments over the dorsolateral prefrontal cortex (DLPFC) once every 2 days. Also, these investigators enrolled 13 ASD children (11 males and 2 females; mean ± SD age of 6.3 ± 1.7 years) waiting to receive therapy as controls. A maximum entropy ratio (MER) method was adapted to measure the change of complexity of EEG series. It was found that the MER value significantly increased after tDCS. The authors concluded that the findings of this study suggested that tDCS may be helpful in the rehabilitation of children with ASD. Moreover, they stated that further research is needed to examine the potential of brain stimulation treatments for ASD and to interpret the mechanisms of these treatments using neuroimaging techniques.

The authors stated that this study had several drawbacks. First, resting-state EEG of ASD children can be influenced by many factors, including EOG and other movements. Second, the stimulation region of DLPFC was not confirmed by neuroimaging but rather by using a slightly less accurate F3 placement of the standard international system. furthermore, sham stimulation was not obtained in the experiment.

Whole-Exome Sequencing

Tammimies and associates (2015) stated that the use genome-wide tests to provide molecular diagnosis for individuals with ASD requires more study. These researchers performed chromosomal microarray analysis (CMA) and whole-exome sequencing (WES) in a heterogeneous group of children with ASD to determine the molecular diagnostic yield of these tests in a sample typical of a developmental pediatric clinic. Subjects consisted of 258 consecutively ascertained unrelated children with ASD who underwent evaluations to define morphology scores based on the presence of major congenital abnormalities and minor physical anomalies. The probands were stratified into 3 groups of increasing morphological severity:

essential,
equivocal, and
complex (scores of 0 to 3, 4 to 5, and greater than or equal to 6).

All probands underwent CMA, with WES performed for 95 proband-parent trios. Main outcome measure was the overall molecular diagnostic yield for CMA and WES in a population-based ASD sample stratified in 3 phenotypic groups. Of 258 probands, 24 (9.3 %, 95 % CI: 6.1 % to 13.5 %) received a molecular diagnosis from CMA and 8/95 (8.4 %, 95 % CI: 3.7 % to 15.9 %) from WES. The yields were statistically different between the morphological groups. Among the children who underwent both CMA and WES testing, the estimated proportion with an identifiable genetic etiology was 15.8 % (95 % CI: 9.1 % to 24.7 %; 15/95 children). This included 2 children who received molecular diagnoses from both tests. The combined yield was significantly higher in the complex group when compared with the essential group (pair-wise comparison, p = 0.002). The authors concluded that among a heterogeneous sample of children with ASD, the molecular diagnostic yields of CMA and WES were comparable, and the combined molecular diagnostic yield was higher in children with more complex morphological phenotypes in comparison with the children in the essential category. They stated that if replicated in additional populations, these findings may inform appropriate selection of molecular diagnostic testing for children affected by ASD. The drawbacks of this study were:

a relatively small sample size as well as possible ascertainment bias related to the clinical differences that may have existed between families who consented and declined (less than 10 % declined to participate in the study after diagnosis in the developmental pediatric clinics),
only 63.5 % of the children had brain MRI, which may have skewed the final morphological classification in favor of the essential group, and only 49.2 % (127/258) of the study sample underwent IQ testing,
only 36.8 % (95/258) of the children were included in the WES analysis, which could have led to an unmeasured confounding effect on the results,
WES does not provide equal coverage for all the coding sequence regions, and lacks sensitivity and specificity for the detection of structural variants, and
the resolution limits of CMA, the inability to detect the majority of larger indels (greater than20 base pairs) and smaller CNVs (less than 20 kilobases).

Blood Levels of Methylation Capacity as Biomarkers for Diagnosis and Therapeutic Targets of Autism Spectrum Disorder

Guo and colleagues (2020) compared the peripheral blood levels of methionine (Met), S-adenosylmethionine (SAM), S-adenosylhomocysteine (SAH), and the SAM/SAH ratio (the most core and predictive indices of cellular methylation ability) between patients with ASD and control subjects. PubMed, Embase, PsycINFO, Web of Science, and Cochrane Library were searched from inception to August 2, 2019, without language restriction. The random-effects model was used to summarize effect sizes. These investigators retrieved 1,493 records, of which 22 studies met inclusion criteria. The overall analyses revealed that individuals with ASD had significantly decreased levels of Met (22 studies; Hedges' g = -0.62; 95 % CI: -0.89 to -0.35), SAM (8 studies; Hedges' g = -0.60; 95 % CI: -0.86 to -0.34), and the SAM/SAH ratio (8 studies; Hedges' g = -0.98; 95 % CI: -1.30 to -0.66) and significantly increased levels of SAH (8 studies; Hedges' g = 0.69; 95 % CI: 0.43 to 0.94). The findings of the overall analyses were quite stable after being verified by sensitivity analyses and in agreement with the corresponding outcomes of subgroup analyses. Furthermore, these findings from meta-analytic techniques confirmed that the effect estimates of this meta-analysis did not originate from publication bias. The authors concluded that individuals with ASD had substantially aberrant peripheral blood levels of Met, SAM, SAH, and the SAM/SAH ratio, which supported the association between impaired methylation capacity and ASD. Moreover, these researchers stated that further investigations into these indices as potential biomarkers for diagnosis and therapeutic targets of ASD are needed.

Gut Microbiota Profiles and Nuclear Factor Kappa B as Diagnostic Biomarkers of Autism Spectrum Disorder

Bundgaard-Nielsen and colleagues (2020) stated that accumulating evidence has implicated an involvement of the gut-brain axis in ASD and ADHD, however with highly diverse results. In a systematic review, these researchers evaluated studies investigating the gut microbiota composition in individuals with ASD or ADHD and examined if variations in gut microbiota are associated with these disorders. A total of 24 articles were identified in a systematic literature search of PubMed and Embase up to July 22, 2019. They consisted of 20 studies examining ASD and 4 studies examining ADHD. For ASD, several studies agreed on an overall difference in β-diversity, although no consistent bacterial variation between all studies was reported. For ADHD, the findings were more diverse, with no clear differences observed. Several common characteristics in gut microbiota function were identified for ASD compared to controls. In contrast, highly heterogeneous results were reported for ADHD, and thus the association between gut microbiota composition and ADHD remains unclear. For both disorders, methodological differences hampered the comparison of studies. Moreover, these researchers stated that future studies should consider examining differences in gut microbiota function as well as composition. Furthermore, the differences in methodology and demography could have influenced the gut microbiota of the studies, and thus studies are needed that examine the gut microbiota jointly in these often co-morbid diagnoses.

Bezawada and co-workers (2020) stated that differences in microbiota composition in children with ASD compared to unaffected siblings and healthy controls have been reported in various studies. These researchers systematically reviewed the existing literature concerning the role of the gut microbiota in ASD. They carried out an extensive literature search using Medline and Embase data-bases to identify studies (January 1966 through July 2019). A total of 28 papers were included. The studies ranged from 12 to 104 subjects aged between 2 and 18 years from various geographical areas. Majority of studies included fecal samples; however, 4 studies examined mucosal biopsies from different sites. The heterogeneity in ASD diagnostic methodology, gut site sampled and laboratory methods used made meta-analysis inappropriate. Species reported to be significantly higher in abundance in autistic children included Clostridium, Sutterella, Desulfovibrio and Lactobacillus. The findings were however inconsistent across studies. Furthermore, potential confounding effects of anti-microbial use, GI symptoms and diet on the gut microbiota were unclear due to generally poor assessment of these factors. The authors concluded that it is clear that the gut microbiota is altered in ASD, although further exploration is needed to determine whether this is a cause or an effect of the condition.

Iglesias-Vazquez and associates (2020) noted that ASD is a public health problem and has a prevalence of 0.6 % to 1.7 % in children. In addition to psychiatric symptoms, dysbiosis and GI co-morbidities are also frequently reported. The gut-brain microbiota axis suggests that there is a form of communication between microbiota and the brain underlying some neurological disabilities. These investigators compared the composition of gut microbiota in children with and without ASD. Electronic data-bases were searched as far as February 2020. Meta-analyses were performed using RevMan5.3 to estimate the overall relative abundance of gut bacteria belonging to 8 phyla and 17 genera in children with ASD and controls. These investigators included 18 studies examining a total of 493 ASD children and 404 controls. The microbiota was mainly composed of the phyla Bacteroidetes, Firmicutes, and Actinobacteria, all of which were more abundant in the ASD children than in the controls. Children with ASD showed a significantly higher abundance of the genera Bacteroides, Parabacteroides, Clostridium, Faecalibacterium, and Phascolarctobacterium and a lower percentage of Coprococcus and Bifidobacterium. The authors concluded that this meta-analysis suggested that there is a dysbiosis in ASD children that may influence the development and severity of ASD symptomatology. They stated that there is a growing knowledge of the interplay between gut microbiota, GI problems, and the physiopathology and symptomatology of ASD, but more research is needed before clinicians can fully understand the physiological communication between the gut and brain. These researchers stated that further studies should examine several environmental factors that could affect the gut bacterial composition, including lifestyle, diet, exposure to environmental chemicals, and the use of antibiotics, prebiotics or probiotics.

Ho and colleagues (2020) noted that as more animal studies start to disentangle pathways linking the gut microbial ecosystem and neurobehavioral traits, human studies have grown rapidly. Many have since examined the bi-directional communication between the GI tract and the CNS, specifically on the effects of microbial composition on the brain and development. These investigators reviewed at the initial stage aimed to evaluate literature on gut microbial alterations in pediatric neurobehavioral conditions. They searched 5 literature data-bases (Embase, PubMed, PsychInfo, Scopus, and Medline) and found 4,489 published work. As the mechanisms linking gut microbiota to these conditions are divergent, the scope of this review was narrowed to focus on describing gut dysbiosis in children with ASD. Among the final 26 articles, there was a lack of consistency in the reported gut microbiome changes across ASD studies, except for distinguishable patterns, within limits, for Prevotella, Firmicutes at the phylum level, Clostridiales clusters including Clostridium perfringens, and Bifidobacterium species. The authors concluded that these findings were inadequate to confirm a global microbiome change in children with ASD and causality could not be inferred to explain the etiology of the behaviors associated with ASD. These researchers stated that mechanistic studies are needed to elucidate the specific role of the gut microbiome in the pathogenesis of ASD.

Liao and Li (2020) stated that the nuclear factor kappa B (NF-κB) is composed of a series of transcription factors, which are involved in the expression of a plethora of target genes, many of these genes contributing to the regulation of inflammatory responses. Consistent with its central role in inflammatory responses, existing studies of the neurobiological basis for ASD propose the involvement of NF-κB in the etiology of this disorder. These investigators systematically characterized extant literatures regarding the role of NF-κB in the etiology of ASD through data derived from both human studies and animal models. They carried out a systematic electronic search for records indexed within PubMed, Embase, or Web of Science to identify potentially eligible studies. Study inclusion and data extraction was agreed by 2 independent authors after reviewing the abstract and full text. Among the 371 articles identified in the initial screening, 18 met the eligibility criteria for this review, including 14 human case-control studies compared the expression or activation of NF-κB between ASD cases and controls as well as 4 animal studies used mouse model of ASD to examine the level of NF-κB and further evaluate its changes after different drug treatments. These included 18 studies, although relatively small in quantity, appeared to support the role of NF-κB in the etiology of ASD. The authors concluded that evidence generated from both human studies and animal models supported the involvement of NF-κB in the neurobiological basis of ASD, despite some concern regarding whether it functions as a primary contributor causes ASD onset or rather an ancillary factor regulates ASD pathogenesis. The increased understanding of NF-κB in the neurobiological basis of ASD could aid the emergence of clinically relevant diagnostic biomarkers and novel therapeutic strategies acting on the underlying disease pathogenesis. The authors concluded that these findings suggested that potential methodological differences between studies need to be accounted for and keep open the discussion over the existence of aberrantly NF-κB signaling in ASD subjects.

Korteniemi et al (2024) stated that ASDs are a varying group of disorders characterized by deficiency in social interaction and restrictive patterns of behavior and interests. While there are several studies focusing on the neuro-psychiatric pathogenesis of ASD, its etiology remains unclear. The role of gut-brain-axis in ASD has been studied increasingly and a correlation between symptoms and the composition of gut microbiota has been documented in various works. Despite this, the significance of individual microbes and their function is still unknown. In a systematic review, these investigators examined the available evidence on the interrelations between ASD and the gut microbiota in children. They carried out a literature search focusing on the main findings concerning the gut microbiota composition, interventions targeting the gut microbiota, and possible mechanisms explaining the results in children aged between 2 and 18 years of age. Most studies in this review found significant differences between microbial communities, while there was notable variation in results regarding diversity indices or taxonomic level abundance. The most consistent results regarding taxa differences in ASD children's gut microbiota were higher levels of Proteobacteria, Actinobacteria and Sutterella compared to controls. The authors concluded that these findings demonstrated that the gut microbiota of children with ASD is altered compared to one of neurotypically developed children. Moreover, these researchers stated that further investigations are needed to examine if some of these features could be used as potential biomarkers for ASD and how the gut microbiota could be targeted in therapeutical interventions.

Measurement of Citrate Synthase Enzyme Activity for the Diagnosis/Evaluation of Autism Spectrum Disorder

Giulivi et al (2010) noted that impaired mitochondrial function may influence processes highly dependent on energy, such as neurodevelopment, and contribute to ASD. No studies have examined mitochondrial dysfunction and mitochondrial DNA (mtDNA) abnormalities in a well-defined population of children with autism. In an observational study, these researchers examined mitochondrial defects in children with autism. Data were collected from patients aged 2 to 5 years who were a subset of children participating in the Childhood Autism Risk From Genes and Environment study in California, which was a population-based, case-control investigation with confirmed autism cases and age-matched, genetically unrelated, typically developing controls, that was launched in 2003 and is still ongoing. Mitochondrial dysfunction and mtDNA abnormalities were examined in lymphocytes from 10 children with autism and 10 controls. Oxidative phosphorylation capacity, mtDNA copy number and deletions, mitochondrial rate of hydrogen peroxide production, and plasma lactate and pyruvate were measured. These investigators found that the reduced nicotinamide adenine dinucleotide (NADH) oxidase activity (normalized to citrate synthase activity) in lymphocytic mitochondria from children with autism was significantly lower compared with controls (mean, 4.4 [95 % CI: 2.8 to 6.0] versus 12 [95 % CI: 8 to 16], respectively; p = 0.001). The majority of children with autism (6 of 10) had complex I activity below control range values. Higher plasma pyruvate levels were found in children with autism compared with controls (0.23 mM [95 % CI: 0.15 to 0.31 mM] versus 0.08 mM [95 % CI: 0.04 to 0.12 mM], respectively; p = 0.02); 8 of 10 cases had higher pyruvate levels but only 2 cases had higher lactate levels compared with controls. These results were consistent with the lower pyruvate dehydrogenase activity observed in children with autism compared with controls (1.0 [95 % CI: 0.6 to 1.4] nmol × [min × mg protein](-1) versus 2.3 [95 % CI: 1.7 to 2.9] nmol × [min × mg protein](-1), respectively; p = 0.01). Children with autism had higher mitochondrial rates of hydrogen peroxide production compared with controls (0.34 [95 % CI: 0.26 to 0.42] nmol × [min × mg of protein](-1) versus 0.16 [95 % CI: 0.12 to 0.20] nmol × [min × mg protein](-1) by complex III; p = 0.02). Mitochondrial DNA over-replication was found in 5 cases (mean ratio of mtDNA to nuclear DNA: 239 [95 % CI: 217 to 239] versus 179 [95 % CI: 165 to 193] in controls; p = 10(-4)). Deletions at the segment of cytochrome b were observed in 2 cases (ratio of cytochrome b to ND1: 0.80 [95 % CI: 0.68 to 0.92] versus 0.99 [95 % CI: 0.93 to 1.05] for controls; p = 0.01). The authors concluded that in this exploratory study, children with autism were more likely to have mitochondrial dysfunction, mtDNA over-replication, and mtDNA deletions than typically developing children.

Rose et al (2017) noted that gastro-intestinal (GI) symptoms are prevalent in ASD; however, the pathophysiology is poorly understood. Imbalances in the enteric microbiome have been associated with ASD and could result in GI dysfunction potentially via disruption of mitochondrial function as microbiome metabolites modulate mitochondrial function and mitochondrial dysfunction is highly associated with GI symptoms. In a blinded, case-control study, these researchers compared mitochondrial function in rectal and cecum biopsies under the assumption that certain microbiome metabolites, such as butyrate and propionic acid, are more abundant in the cecum as compared to the rectum. Rectal and cecum mucosal biopsies were collected during elective diagnostic colonoscopy. Using a single-blind, case-control design, complex I and IV and citrate synthase activities and complex I-V protein quantity from 10 children with ASD, 10 children with Crohn's disease (CD) and 10 neurotypical children with non-specific GI complaints were measured. The protein for all complexes, except complex II, in the cecum as compared to the rectum was significantly higher in ASD samples as compared to other groups. For both rectal and cecum biopsies, ASD samples demonstrated higher complex I activity, but not complex IV or citrate synthase activity, compared to other groups. Mitochondrial function in the gut mucosa from children with ASD was found to be significantly different than other groups who manifested similar GI symptomatology suggesting a unique pathophysiology for GI symptoms in children with ASD. Abnormalities localized to the cecum suggested a role for imbalances in the microbiome, potentially in the production of butyrate, in children with ASD.

Delhey et al (2017) stated that ASD has been associated with mitochondrial dysfunction; however, few studies have examined the relationship between mitochondrial function and ASD symptoms. These researchers measured Complex I and IV and citrate synthase activities in 76 children with ASD who were not receiving vitamin supplementation or medication. They also measured language using the Preschool Language Scales or Clinical Evaluation of Language Fundamentals, adaptive behavior using the Vineland Adaptive Behavioral Scale, social function using the Social Responsiveness Scale and behavior using Aberrant Behavior Checklist, Childhood Behavior Checklist and the Ohio Autism Clinical Impression Scale. Children with ASD demonstrated significantly greater variation in mitochondrial activity compared to controls with more than expected ASD children having enzyme activity outside of the normal range for citrate synthase (24 %), complex I (39 %) and complex IV (11 %). Poorer adaptive skills were associated with complex IV activity lower or higher than average and lower complex I activity. Poorer social function and behavior was associated with relatively higher citrate synthase activity. Similar to previous studies, these investigators found both mitochondrial underactivity and overactivity in ASD. The authors concluded that the findings of this study confirmed an expanded variation in mitochondrial activity in ASD and showed, for the 1st time, that such variations are related to ASD symptoms. Moreover, these researchers had only demonstrated an association between behavior and biomarkers of mitochondrial activity; and this association does not imply causation. There may be many other factors that influence both mitochondrial activity and behavior. Furthermore, both behavior and mitochondrial function demonstrated significant variability, suggesting that further investigation is needed to ascertain more details of this relationship.

Furthermore, UpToDate reviews on “Autism spectrum disorder: Evaluation and diagnosis” (Augustyn and von Hahn, 2021) and “Autism spectrum disorder in children and adolescents: Overview of management” (Weissman, 2021a) do not mention citrate synthase enzyme activity.

Measurement of Urine Oligosaccharides for Screening / Diagnosis of Autism Spectrum Disorder

An UpToDate review on “Autism spectrum disorder: Evaluation and diagnosis” (Augustyn and von Hahn, 2021) does not mention measurement of oligosaccharides as a management tool.

Methyl B12 (MB12) for the Treatment of ASD

In a 12-week, double-blind, placebo-controlled, cross-over pilot study, Bertoglio et al (2010) examined if methyl B12 treatment could improve behavioral measures in children with autism spectrum disorder (ASD) and whether improvement is associated with increased plasma concentrations of glutathione (GSH) and an increased redox ratio of reduced glutathione to oxidized glutathione (GSH/GSSG), both of which have been previously identified to be low in children with autism. Following this 12-week study, subjects were given the option of entering a 6-month open-label trial of methyl B12. Subjects were 3 to 8 years old with autism. All subjects received 6 weeks of placebo and 6 weeks of methyl B12 at a dose of 64.5 ug/kg every 3 days administered subcutaneously into the buttocks. Blood for GSH analysis and behavioral assessments were obtained at baseline, week 6, and week 12. A total of 30 subjects completed the 12-week, double-blind study and 22 subjects completed the 6-month extension study. No statistically significant mean differences in behavior tests or in glutathione status were identified between active and placebo groups; 9 subjects (30 %) demonstrated clinically significant improvement on the Clinical Global Impression Scale and at least 2 additional behavioral measures. More notably, these responders exhibited significantly increased plasma concentrations of GSH and GSH/GSSG. The authors concluded that comparison of the overall means between groups suggested that methyl B12 was ineffective in treating behavioral symptoms of autism. However, detailed data analysis suggested that methyl B12 may alleviate symptoms of autism in a subgroup of children, possibly by reducing oxidative stress. An increase in glutathione redox status (GSH/GSSG) may provide a biomarker for treatment response to methyl B12. These investigators stated that additional research is needed to delineate a subgroup of potential responders and ascertain a biomarker for response to methyl B12.

In a randomized, placebo-controlled trial, Hendren et al (2016) examined if methyl B12 could improve symptoms of ASD. A total of 57 children with ASD were randomly assigned to 8 weeks of treatment with methyl B12 (75 μg/kg) or saline placebo every 3 days in a subcutaneous injection. The primary outcome measure was overall improvement in symptoms of ASD as measured by the Clinical Global Impressions-Improvement (CGI-I) score. Secondary outcome measures included changes in the Aberrant Behavior Checklist (ABC) and the Social Responsiveness Scale (SRS). Laboratory measures of methionine methylation and antioxidant glutathione metabolism were assessed at baseline and 8 weeks. A total of 50 children (mean age of 5.3 years, 79 % boys) completed the study. The primary outcome measure – the clinician rated CGI-I score – was statistically significantly better (lower) in the methyl B12 group (2.4) than in the placebo group (3.1) (0.7 greater improvement in the methyl B12 group, 95 % confidence interval [CI]: 1.2 to 0.2, p = 0.005). Clinical improvement among children treated with methyl B12 was positively correlated with increases in plasma methionine (p = 0.05), decreases in S-adenosyl-l-homocysteine (SAH) (p = 0.007) and improvements in the ratio of S-adenosylmethionine (SAM) to SAH (p = 0.007), indicating an improvement in cellular methylation capacity. No improvements were observed in the parent-rated ABC or SRS. The authors concluded that methyl B12 treatment improved clinician-rated symptoms of ASD that were correlated with improvements in measures of methionine metabolism and cellular methylation capacity. Moreover, these researchers stated that although the findings were preliminary, this was an exciting finding which suggested that treating a known metabolic abnormality – impaired methylation capacity – holds the potential to improve symptoms. They stated that a larger randomized controlled trial (RCT) with greater power and greater control over laboratory assessments should be a high priority.

These authors stated that this study had several drawbacks. The most significant were the relatively small sample size (n = 50) and the fact that many children were not able to adequately adhere to the laboratory instructions to fast before laboratory draws; thus, only a subset (17 of 27 or 63 %) had valid laboratory information. The laboratory analyses were also performed at a site remote from the clinical site, and it was possible that over-night shipping of laboratory samples (on dry ice) affected the levels of the reported tests, although samples were shipped in batches from all subjects. This limited laboratory assessment limited the power of the analyses to detect differences in laboratory values between groups. Although it was possible that this could significantly affect the overall laboratory results, these researchers did not think it would produce the statistically significant associations observed in the 3 metabolites. Second, although these researchers observed an improvement in the primary outcome measure – the CGI-I– they did not observe improvements in the secondary outcome measures (ABC and SRS). This may be because of a lack of sensitivity of these outcome measures, improvements in other symptom areas that were not captured by these surveys, or improvements that were noted only by the clinician assessment and not by the parents (who completed the ABC and SRS). Inclusion of other measures, such as the Vineland Adaptive Behavior Scale, would have allowed an assessment of changes in adaptive behavior and may have provided an explanation for the observed improvement in the CGI-I. The authors did find statistically significant improvement in the motivation subscale of the SRS in the placebo group, and given the lack of other improvements, these researchers believed that this was most likely a chance finding that was not clinically significant. Third, these investigators were unable to identify a safe red dye to match the placebo color to the color of injectable methyl B12, and although they masked the syringes with opaque material, it was possible that some families were able to perceive that their injected material was colored (although it was unclear that this would hold any meaning for the families). Also, the clinician assessing the primary outcome (CGI-I) was blinded to group assignment and did not see the injection liquid or the syringes. Finally, although this study was the largest randomized, placebo-controlled trial of methyl B12 in autism, it still involved a relatively small sample size, was of short duration, included only children with an IQ of greater than 50, and did not examine other psychiatric co-morbidities, all of which made the findings provocative but in need of corroboration by future investigations.

Li et al (2018) stated that nutritional supplements have been used for correction of deficiencies that may occur in patient with ASD and to improve core symptoms. These investigators provided current best evidence regarding supplements for nutritional deficiencies and core symptoms in children with ASD and examined the safety and effectiveness. They carried out a systematic literature search of scientific data-bases to retrieve relevant RCTs; risk of bias was evaluated for each study. A total of 18 RCTs of 5 supplements were included – B6/Mg was not helpful for improving ASD symptoms (7 RCTs); 2 RCTs of methyl B12 reported some improvement in ASD severity, however, the effects on the correction of deficiencies were inconclusive; 2 RCTs of vitamin D3 both reported increased levels of mean 25(OH)D in serum but inconsistent results in behavioral outcomes. Omega-3 fatty acid supplementation did not affect ASD behaviors but may correct deficiencies (6 RCTs); 1 RCT of folinic acid reported positive results in improving ASD symptoms measured by various behavioral scales. The authors concluded that current evidence for the use of supplements for correcting nutritional deficiencies in children with ASD and to improve the symptoms was little; more studies are needed.

UpToDate reviews on “Autism spectrum disorder in children and adolescents: Overview of management” (Weissman, 2021a), and “Autism spectrum disorder in children and adolescents: Pharmacologic interventions” (Weissman, 2021b) do not mention methyl B12 as a management / therapeutic option.

Furthermore, an UpToDate review on “Autism spectrum disorder in children and adolescents: Complementary and alternative therapies” (Weissman and Harris, 2021) states that “Other interventions that lack definitive scientific evidence of a benefit but are unlikely to be harmful for children with ASD include vitamin B12”.

Artificial Intelligence-Based Devices for Diagnosis of Autism Spectrum Disorder

Chaddad et al (2021) stated that radiomics with deep learning models have become popular in computer-aided diagnosis and have out-performed human experts on many clinical tasks. Specifically, radiomic models based on artificial intelligence (AI) are using medical data (i.e., images, molecular data, clinical variables, etc.) for predicting clinical tasks such as ASD. These investigators discussed the radiomic techniques used for ASD analysis. Currently, the limited radiomic work of ASD is related to the variation of morphological features of brain thickness that is different from texture analysis. These techniques are based on imaging shape features that can be used with predictive models for predicting ASD. This review examined the progress of ASD-based radiomics with a brief description of ASD and the current non-invasive technique used to classify between ASD and healthy control (HC) subjects. With AI, new radiomic models using the deep learning techniques will also be described. To consider the texture analysis with deep convolutional neural networks (CNNs), more investigations are suggested to be integrated with additional validation steps on various MRI sites. Moreover, these researchers stated that for future work, high-precision and high-transparency models can be established by quantifying the deep texture from CNN models to predict early ASD patients.

Megerian et al (2022) noted that ASD can be reliably diagnosed at 18 months, yet significant diagnostic delays persist in the U.S. In a prospective, double-blinded, active comparator, multi-center study, these researchers examined the accuracy of an AI-based software as a medical device designed to aid primary care healthcare providers (HCPs) in diagnosing ASD. The Device combines behavioral features from 3 distinct inputs (a caregiver questionnaire, analysis of 2 short home videos, and an HCP questionnaire) in a gradient boosted decision-tree machine learning algorithm to produce either an ASD-positive, ASD-negative, or indeterminate output. This study compared Device outputs to diagnostic agreement by 2 or more independent specialists in a cohort of 18- to72-month-old subjects with developmental delay concerns (425 study completers, 36 % female, 29 % ASD prevalence). Device output positive predictive value (PPV) for all study completers was 80.8 % (95 % CI: 70.3 % to 88.8 %) and negative predictive value (NPV) was 98.3 % (90.6 % to 100 %). For the 31.8 % of subjects who received a determinate output (ASD-positive or ASD-negative) Device sensitivity was 98.4 % (91.6 % to 100 %) and specificity was 78.9 % (67.6 % to 87.7 %). The Device’s indeterminate output acted as a risk control measure when inputs were insufficiently granular to make a determinate recommendation with confidence. If this risk control measure were removed, the sensitivity for all study completers would fall to 51.6 % (63/122) (95 % CI: 42.4 % to 60.8 %), and specificity would fall to 18.5 % (56/303) (95 % CI: 14.3 % to 23.3 %). Among subjects for whom the Device abstained from providing a result, specialists identified that 91 % had 1 or more complex neurodevelopmental disorders. No significant differences in Device performance were found across subjects’ sex, race/ethnicity, income, or education level. For nearly 1/3 of this primary care sample, the Device enabled timely diagnostic evaluation with a high degree of accuracy. The authors concluded that while future research (replication and follow-up studies) is needed, the Device showed promise to expand primary care diagnostic capacity; thus, enabling earlier intervention for a subset of children and more efficient use of limited specialist resources. Moreover, these researchers stated that although the sample population was ethnically and racially diverse, the study was not powered for statistical inference on co-variates such as co-morbidities, gender, race/ethnicity, education level, or income level. They stated that future studies that include larger samples of sub-populations are needed to build upon the initial finding of consistent Device performance across these co-variates.

The authors stated that cost and reimbursement data are also needed to clarify the extent to which the Device could be used equitably by primary care HCPs in practice. In light of growing pressures on Medicaid programs to cover the early diagnosis of ASD and concurrent budgetary challenges, better use of existing primary care infrastructure, such as that offered by this Device, may support Medicaid programs to remain financially sustainable while adhering to laws and regulations. However, additional costing data are needed to fully understand the likelihood of the Device being widely adopted in U.S. primary care settings, and the extent to which it would be accessible to low-income families or families without health insurance. Furthermore, use of the Device requires access to a smartphone, which not all low-income American families may have.

Welch et al (2022) stated that mental health disorders are a leading cause of medical disabilities across an individual's lifespan. This burden is particularly substantial in children and adolescents because of challenges in diagnosis and the lack of precision medicine approaches. However, the widespread adoption of wearable devices (e.g., smart watches) that are conducive for AI applications to remotely diagnose and manage psychiatric disorders in children and adolescents is promising. These researchers carried out a scoping review to study, characterize, and identify areas of innovations with wearable devices that can augment current in-person physician assessments to individualize diagnosis and management of psychiatric disorders in child and adolescent psychiatry. This scoping review used information from the PRISMA guidelines. These investigators carried out a comprehensive search of several databases from 2011 to June 25, 2021, limited to the English language and excluded animal studies. The databases included Ovid Medline and Epub ahead of print, in-process and other non-indexed citations, and daily; Ovid Embase; Ovid Cochrane Central Register of Controlled Trials; Ovid Cochrane Database of Systematic Reviews; Web of Science; and Scopus. The initial search yielded 344 articles, from which 19 (5.5 %) articles were left on the final source list for this scoping review. Articles were divided into 3 main groups as follows: studies with the main focus on ASAD, ADHD, and internalizing disorders such as anxiety disorders. Most of the studies used either cardio-fitness chest straps with electrocardiogram sensors or wrist-worn biosensors, such as watches by Fitbit. Both allowed passive data collection of the physiological signals. The authors concluded that this scoping review found a large heterogeneity of methods and findings in AI studies in child psychiatry. Overall, the largest gap identified in this scoping review was the lack of RCTs, as most studies available were pilot studies and feasibility trials. Moreover, these investigators stated that future directions should focus specifically on enrolling larger number of more diverse groups of patients. Future research should also focus on assessing which tools, mobile and wearable, are most efficient in collecting the most reliable data in various patient populations, as the primary outcome of interest.

The authors stated that this study had several drawbacks. First, these researchers did not perform a systematic review or prospectively register a protocol. This was expected to be a nascent area; hence, a scoping review was most appropriate. Second, it was possible that they have missed important original literature on the use of mobile and wearable AI in children psychiatry. This was mitigated by an extensive search of multiple databases, searching references of included articles, and ensuring duplicate review of all the abstracts and full-text articles. Third, these researchers chose not to include non-original or non-peer-reviewed research and non-English articles, which might have resulted in missing key conclusions drawn from this research. Fourth, they also did not examine each of the machine learning technologies in detail but rather resorted to a brief description of the methods used in each of the studies.

Joudar et al (2022) stated that the exact nature, harmful effects and etiology of ASD have caused widespread confusion; AI science helps solve challenging diagnostic problems in the medical field via extensive experiments. Disease severity is closely related to triage decisions and prioritization contexts in medicine because both have been widely used to diagnose various diseases via AI, machine learning and automated decision-making techniques. Recently, taking advantage of high-performance AI algorithms has achieved accessible success in diagnosing and predicting risks from clinical and biological data. In contrast, less progress has been made with ASD because of obscure reasons. According to academic literature, ASD diagnosis works from a specific perspective, and much of the confusion arises from the fact that how AI techniques are currently integrated with the diagnosis of ASD concerning the triage and priority strategies and gene contributions. To this end, these researchers carried out a systematic review of the literature to examine the respective AI methods using the available datasets, highlighted the tools and strategies used for diagnosing ASD and investigate how AI trends contribute to distinguishing triage and priority for ASD and gene contributions. Accordingly, this study checked the Science Direct, IEEE Xplore Digital Library, Web of Science (WoS), PubMed, and Scopus databases. A set of 363 articles from 2017 to 2022 was collected to reveal a clear picture and a better understanding of all the academic literature through a final set of 18 articles. The retrieved articles were filtered according to the defined inclusion and exclusion criteria and classified into 3 categories. The 1st category included “Triage patients based on diagnosis methods” which accounted for 16.66 % (n = 3/18). The 2nd category included “Prioritization for Risky Genes” which accounted for 66.6 % (n = 12/18) and was classified into 2 sub-categories: “Mutations observation based”, “Biomarkers and toxic chemical observations”. The 3rd category included “E-triage using telehealth” which accounted for 16.66 % (n = 3/18). This multi-disciplinary systematic review revealed the taxonomy, motivations, recommendations and challenges of ASD research that need synergistic attention. Therefore, this systematic review performed a comprehensive science mapping analysis and discussed the open issues that help perform and improve the recommended solution of ASD research direction. Furthermore, this study critically reviewed the literature and attempted to address the current research gaps in knowledge and highlighted weaknesses that require further research. Finally, a new developed methodology has been suggested as future work for triaging and prioritizing ASD patients according to their severity levels by using decision-making techniques.

Eye-Tracking Studies (Eye-Tracking Test) for Differential Diagnosis of Autism Spectrum Disorder

Setien-Ramos et al (2023) noted that eye-tracking studies have shown potential in effectively discriminating between ASD and non-ASD groups. In a systematic review and meta-analysis, these researchers evaluated eye-tracking studies in adults with ASD. A total of 22 studies were included for meta-analysis. Eyes and non-social regions proved better for discriminating between ASD and non-ASD adults, while fixation duration appeared to be the outcome to choose. Active engaged tasks appeared to reduce differences between ASD and non-ASD adults, regardless of the emotional content of the stimuli/task. Proportional fixation duration on eyes and non-social areas in non-active tasks (e.g., free viewing) appeared to be the best eye-tracking design for increasing the sensitivity and specificity in ASD adults.

Furthermore, UpToDate reviews on “Autism spectrum disorder: Evaluation and diagnosis” (Augustyn and von Hahn, 2022a), and “Autism spectrum disorder: Clinical features” (Augustyn and von Hahn, 2022b , 2022) do not mention eye-tracking study as a management option.

Jones et al (2023a) noted that autism spectrum disorder (ASD) is a common and early-emerging neurodevelopmental condition. While 80 % of parents report having had concerns for their child's development before age 2 years, many children are not diagnosed until ages 4 to 5 years or later. In 2 prospective, consecutively enrolled, broad-spectrum, double-blind studies, these investigators developed an objective performance-based tool to aid in early diagnosis and assessment of ASD in children younger than 3 years. They developed an objective eye-tracking-based index test for children aged 16 to 30 months, compared its performance with best-practice reference standard diagnosis of autism (discovery study), and then replicated findings in an independent sample (replication study). Discovery and replication studies were carried out in specialty centers for autism diagnosis and treatment. Reference standard diagnoses were made using best-practice standardized protocols by specialists who were blind to eye-tracking results. Eye-tracking tests were administered by staff blind to clinical results. Children were enrolled from April 27, 2013 to September 26, 2017. Data were analyzed from March 28, 2018, to January 3, 2019. Pre-specified primary endpoints were the sensitivity and specificity of the eye-tracking-based index test compared with the reference standard. Pre-specified secondary endpoints measured convergent validity between eye-tracking-based indices and reference standard assessments of social disability, verbal ability, and non-verbal ability. Data were collected from 1,089 children: 719 children (mean [SD] age, 22.4 [3.6] months) in the discovery study, and 370 children (mean [SD] age, 25.4 [6.0] months) in the replication study. In discovery, 224 (31.2 %) were female and 495 (68.8 %) male; in replication, 120 (32.4 %) were female and 250 (67.6 %) male. Based on reference standard expert clinical diagnosis, there were 386 participants (53.7 %) with non-autism diagnoses and 333 (46.3 %) with autism diagnoses in discovery, and 184 participants (49.7 %) with non-autism diagnoses and 186 (50.3 %) with autism diagnoses in replication. In the discovery study, the area under the receiver operating characteristic curve (AUROC) was 0.90 (95 % CI: 0.88 to 0.92), sensitivity was 81.9 % (95 % CI: 77.3 % to 85.7 %), and specificity was 89.9 % (95 % CI: 86.4 % to 92.5 %). In the replication study, the AUROC was 0.89 (95 % CI: 0.86 to 0.93), sensitivity was 80.6 % (95 % CI: 74.1 % to 85.7 %), and specificity was 82.3 % (95 % CI: 76.1 % to 87.2 %). Eye-tracking test results correlated with expert clinical assessments of children's individual levels of ability, explaining 68.6 % (95 % CI: 58.3 % to 78.6 %), 63.4 % (95 % CI: 47.9 % to 79.2 %), and 49.0 % (95 % CI: 33.8 % to 65.4 %) of variance in reference standard assessments of social disability, verbal ability, and non-verbal cognitive ability, respectively. The authors concluded that in 2 diagnostic studies of children younger than 3 years, objective eye-tracking-based measurements of social visual engagement quantified diagnostic status as well as individual levels of social disability, verbal ability, and non-verbal ability in ASD. These researchers stated that these findings suggested that objective measurements of social visual engagement could be used to aid in the diagnosis and assessment of ASD.

The authors stated that this study had several drawbacks. First, clinical procedures were carried out by a relatively small group of expert clinicians, and eye-tracking procedures were implemented under well-controlled laboratory conditions in the discovery study or with a single prototype standalone eye-tracking device in the replication study. The efforts in this study should be complemented by studies collecting reference standard and index test data at multiple different sites with multiple different clinical teams and eye-tracking devices. Second, the results of this study should also be complemented by data quantifying repeatability and reproducibility variance in eye-tracking–based measurements. Previous studies have also noted expert clinical uncertainty in the reference standard diagnosis of autism in some children. Third, uncertainty in the reference standard set an upper limit on the performance measures of any comparison test. In the present trial, these investigators did not prospectively track expert clinician certainty of diagnosis in all children. Consequently, they were unable to examine the effects of clinician certainty in the discovery or replication studies.

Jones et al (2023b) stated that in the U.S., children with signs of autism often experience more than 1 year of delay before diagnosis and often experience longer delays if they are from racially, ethnically, or economically disadvantaged backgrounds. Most diagnoses are also received without the use of standardized diagnostic instruments. To aid in early autism diagnosis, eye-tracking measurement of social visual engagement has shown potential as a performance-based biomarker. These researchers examined the performance of eye-tracking measurement of social visual engagement (index test) relative to expert clinical diagnosis in young children referred to specialty autism clinics. In this study of 16- to 30-month-old children enrolled at 6 U.S. specialty centers from April 2018 through May 2019, staff blind to clinical diagnoses used automated devices to measure eye-tracking-based social visual engagement. Expert clinical diagnoses were made using best practice standardized protocols by specialists who were blind to index test results. This study was completed in a 1-day protocol for each participant. Primary outcome measures were test sensitivity and specificity relative to expert clinical diagnosis. Secondary outcome measures were test correlations with expert clinical assessments of social disability, verbal ability, and non-verbal cognitive ability. Eye-tracking measurement of social visual engagement was successful in 475 (95.2 %) of the 499 enrolled children (mean [SD] age, 24.1 [4.4] months; 38 [8.0 %] were Asian; 37 [7.8 %], Black; 352 [74.1 %], White; 44 [9.3 %], other; and 68 [14.3 %], Hispanic). By expert clinical diagnosis, 221 children (46.5 %) had autism and 254 (53.5 %) did not. In all children, measurement of social visual engagement had sensitivity of 71.0 % (95 % CI: 64.7 % to 76.6 %) and specificity of 80.7 % (95 % CI: 75.4 % to 85.1 %). In the subgroup of 335 children whose autism diagnosis was certain, sensitivity was 78.0 % (95 % CI: 70.7 % to 83.9 %) and specificity was 85.4 % (95 % CI: 79.5 % to 89.8 %). Eye-tracking test results correlated with expert clinical assessments of individual levels of social disability (r = -0.75 [95 % CI: -0.79 to -0.71]), verbal ability (r = 0.65 [95 % CI: 0.59 to 0.70]), and non-verbal cognitive ability (r = 0.65 [95 % CI: 0.59 to 0.70]). The authors concluded that in 16- to 30-month-old children referred to specialty clinics, eye-tracking-based measurement of social visual engagement was predictive of autism diagnoses by clinical experts. Moreover, these researchers stated that further investigation of this test's role in early diagnosis and assessment of autism in routine specialty clinic practice is needed.

In an editorial to the afore-mentioned study by Jones et al (2023b), Dawson (2023) stated that while the study by Jones et al (2023b) represents a milestone in the development of autism diagnostic biomarkers, there remains work to be carried out before an eye-tracking test is used in clinical practice. Demonstrating that an eye-tracking test improves diagnostic certainty would require following children whose diagnosis was uncertain longitudinally to determine whether the test improves prediction of a later definitive autism diagnosis. Future studies will need to examine how feasible, acceptable, reliable, and efficient the eye-tracking test is when used by clinicians as an aid in autism diagnosis in practice. Research will need to evaluate how information from the eye-tracking test should be weighted and integrated with other sources of information, such as parent report and clinical observation, to arrive at a diagnostic decision. For example, could the time spent on clinical observational assessment of the child be reduced in cases where the eye-tracking test indicated a very high likelihood of autism? If so, this could potentially help address the current long wait-lists to see an autism specialist. It will be important to understand the influences of sex, other demographic factors, and co-occurring conditions, such as intellectual disability, on diagnostic accuracy to ensure that potential biases are mitigated. The risks and benefits of incorporating objective biomarkers into standard clinical care should be carefully examined based on input from clinicians, care-givers, autistic individuals, healthcare administrators, as well as other stake-holders to ensure that this new approach to improving autism diagnostic certainty would result in long-term benefit for autistic individuals and their families.

de Belen et al (2023) noted that a number of differences in joint attention behavior between children with SD and typically developing (TD) individuals have previously been documented. In a cross-sectional study, these investigators employed eye-tracking technology to examine response to joint attention (RJA) behaviors in 77 children aged 31 to 73 months. They carried out a repeated-measures analysis of variance to identify differences between groups. Furthermore, they analyzed correlations between eye-tracking and clinical measures using Spearman's correlation. The children diagnosed with ASD were less likely to follow gaze compared to TD children. Children with ASD were less accurate at gaze following when only eye gaze information was available, compared to when eye gaze with head movement was observed. Higher accuracy gaze-following profiles were associated with better early cognition and more adaptive behaviors in children with ASD. Less accurate gaze-following profiles were associated with more severe ASD symptomatology. The authors concluded that there were differences in RJA behaviors between ASD and TD preschool children. Several eye-tracking measures of RJA behaviors in pre-school children were found to be associated with clinical measures for ASD diagnosis. This study also highlighted the construct validity of using eye-tracking measures as potential biomarkers in the evaluation and diagnosis of ASD in pre-school children.

The authors stated that this study had several drawbacks. First, there was a gender skew towards males in the ASD group, as would be clinically expected. Nevertheless, further studies with more female participants are needed to clarify these findings, as differences in autism presentation and diagnosis between males and females have been documented. For example, studies have reported that girls on the spectrum behave similarly to neurotypical boys and girls on certain socially orientated tasks (e.g., girls showed enhanced attention to faces during scenes that did not have social interactions). Furthermore, TD men with high autistic-like traits exhibited worse accuracy of gaze shifts, while TD women exhibited similar eye-gaze following behavior regardless of autistic-like traits. Thus, a follow-up study examining the contribution of biological sex to joint attention behaviors in ASD is needed. Second, the participant groups also differed in sample size, with the ASD group being 3 times as large as the TD group. The ASD participants in this study were recruited from an ASD-specific center, and there was good uptake to the study. Despite significant efforts of the team to recruit control participants, there was less interest from families of neurotypical children at the center to participate in the study, which was probably not surprising given the study was less meaningful for children without a developmental diagnosis. Third, it was also useful to note that the participant groups were matched on chronological age but not on developmental abilities. This may have accentuated the key findings of this trial, especially the observed significant group differences and correlations between different eye-tracking measures and different clinical information in the ASD group. These researchers stated that further studies with larger sample sizes with a developmentally age-matched group are suggested to confirm this finding. Fourth, children with ASD were not excluded from the study if they had a co-morbid diagnosis. Although this has implications for any strict interpretation of the findings reported here, the inclusion of co-morbid conditions in ASD research is ecologically valid. Indeed, it is rare in clinical practice to encounter a young person who has a “pure” autism spectrum diagnosis with no other psychiatric or developmental co-morbidities. Moreover, it was important to consider the drawbacks due to the pre-recorded nature of the stimuli. In this study, these researchers aimed to examine if such stimuli could aid in identifying differences in RJA behaviors in ASD and TD pre-school children and determine possible correlations between the derived eye-tracking measures and clinical information. The results in this study suggested that differences in certain eye-tracking measures exist in the context of the stimuli used in this study. However, these investigators acknowledged that it was not as ecologically valid as a live interaction task where an actor may exaggerate/augment their cues and even have multiple attempts to initiate joint attention. In comparison, the actor made no exaggerated cues in both the Eyes-Only and Head/Eyes conditions. These investigators stated that future research should compare the presence and absence of exaggerated and pre-recorded movements in these 2 conditions for a more ecologically valid scenario.

Finally, given the cross-sectional nature of the study, it was impossible to infer any causative mechanisms. For example, it was unclear if adaptive functioning may result in improved social engagement, as reflected by gaze accuracy, or whether the development of gaze accuracy may aid in improving adaptive behaviors. Furthermore, it was unclear if the observed eye-tracking profile was the result of differences in abilities or due to the lack of interest and motivation in engaging in social interactions and following gaze. However, the association between these measures was clinically important. From a clinical perspective, the finding suggested that eye-tracking technology could be used as a biomarker of adaptive functioning in young children, and could potentially be implemented into a diagnostic test battery, or as a measure of treatment progress. This will have implications for targeting the intervention, in terms of skills building versus increasing interest and engagement in social-communicative tasks. These researchers stated that future studies are needed for further investigation of this issue.

Wei et al (2023) noted that machine learning (ML) has been widely employed to identify ASD based on eye-tracking; however, its accuracy is uncertain. These researchers summarized the available evidence on the performances of ML algorithms in classifying ASD and TD individuals based on eye-tracking data. They searched Medline, Embase, Web of Science, Scopus, Cochrane Library, IEEE Xplore Digital Library, Wan Fang Database, China National Knowledge Infrastructure, Chinese BioMedical Literature Database, VIP Database for Chinese Technical Periodicals, from database inception to December 24, 2021. Studies using ML methods to classify ASD and TD individuals based on eye-tracking technologies were included. These researchers extracted the data on study population, model performances, algorithms of ML, and paradigms of eye-tracking. A total of 261 articles were identified, of which 24 studies with sample sizes ranging from 28 to 141 were included (n = 1,396 individuals). ML based on eye-tracking yielded the pooled classified accuracy of 81 % (I2 = 73 %), specificity of 79 % (I2 = 61 %), and sensitivity of 84 % (I2 = 61 %) in classifying ASD and TD individuals. In subgroup analysis, the accuracy was 88 % (95 % CI: 85 % to 91 %), 79 % (95 % CI: 72 % to 84 %), 71 % (95 % CI: 59 % to 91 %) for preschool-aged, school-aged, and adolescent-adult group. Eye-tracking stimuli and ML algorithms varied widely across studies, with social, static, and active stimuli and Support Vector Machine and Random Forest most commonly reported. Regarding the model performance evaluation, 15 studies reported their final results on validation datasets, 4 based on testing data-sets, and 5 did not report whether they used validation datasets. Most studies failed to report the information on eye-tracking hard-ware and the implementation process. The authors concluded that using eye-tracking data, ML has shown potential in identifying ASD individuals with high accuracy, especially in preschool-aged children. However, the heterogeneity between studies, the absence of test set-based performance evaluations, the small sample size, and the non-standardized implementation of eye-tracking might deteriorate the reliability of results. These researchers stated that further well-designed and well-executed studies with comprehensive and transparent reporting are needed to determine the optimal eye-tracking paradigms and ML algorithms.

Measurement of Androgen Levels (Blood, Saliva, or Urine) for the Diagnosis of ASD

Wang et al (2024) noted that accumulating evidence suggested that the ASD population exhibits altered hormone levels, including androgens. However, studies on the regulation of androgens, such as testosterone and dehydroepiandrosterone (DHEA), in relation to sex differences in individuals with ASD were limited and inconsistent. In a systematic review and meta-analysis, these investigators examined the blood, urine, or saliva androgen data between individuals with ASD and controls. They carried out a systematic search for eligible studies published before January 16, 2023 in 6 international and 2 Chinese databases. These researchers computed summary statistics with a random-effects model. Publication bias was evaluated using funnel plots and heterogeneity using I2 statistics. Subgroup analysis was carried out by age, sex, sample source, and measurement method to explain the heterogeneity. A total of 17 case-control studies (individuals with ASD, 825; controls, 669) were assessed. Androgen levels were significantly higher in individuals with ASD than that in controls (standard mean difference [SMD]: 0.27, 95 % CI: 0.06 to 0.48, p = 0.01). Subgroup analysis showed significantly elevated levels of urinary total testosterone, urinary DHEA, and free testosterone in individuals with ASD. DHEA level was also significantly elevated in males with ASD. The authors concluded that androgen levels, especially free testosterone, may be elevated in individuals with ASD; and DHEA levels may be specifically elevated in males. These researchers stated that changes in the total testosterone and DHEA levels in individuals with ASD remain ambiguous; thus, in future studies on ASD, more attention should be paid to the changes in free testosterone levels, and additional comprehensive studies on total testosterone and DHEA levels in all individuals with ASD, especially, female individuals, should be carried out to confirm the relationship between ASD and androgens.

The authors stated that this systematic review and meta-analysis had several drawbacks. First, they did not analyze some of the clinical confounding factors, such as body mass index (BMI), country, race, intake of relevant drugs, the individuals’ condition at birth, and the mother’s information. Environmental risk factors may not only increase the risk of ASD via several complex underlying mechanisms, such as genetic and epigenetic effects, inflammation and oxidative stress, or hypoxia and ischemic injury, but also affect early development and androgen levels in individuals with ASD. Second, the sample size of female individuals with ASD was insufficient. Most of the included studies had evaluated male individuals with ASD, and there were only few studies on female individuals with ASD. Third, there was a relatively high heterogeneity; however, the source of heterogeneity could not be well explained after subgroup analysis. The random-effects model was used, which may be related to different methods and measurement units in androgen level measurement; therefore, greatly affecting the accuracy of the results.

Use of Biomarkers of Mitochondrial Dysfunction for the Management of ASD

Nickel et al (2023) noted that previous research suggested potential mitochondrial dysfunction and changes in fatty acid metabolism in a subgroup of individuals with ASD, indicated by higher lactate, pyruvate levels, and mitochondrial disorder prevalence. These investigators examined potential mitochondrial dysfunction in ASD by evaluating blood metabolite levels linked to mitochondrial metabolism. Blood levels of creatine kinase (CK), alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate, pyruvate, free and total carnitine, as well as acylcarnitines were obtained in 73 adults with ASD (47 men, 26 women) and compared with those of 71 neurotypical controls (NTC) (44 men, 27 women). Correlations between blood parameters and psychometric ASD symptom scores were also examined. Lower CK (pcorr = 0.045) levels were found exclusively in males with ASD compared to NTC, with no such variation in females. ALT and AST levels did not differ significantly between both groups. After correction for anti-psychotic and anti-depressant medication, CK remained significant. ASD subjects had lower serum lactate levels (pcorr = 0.036) compared to NTC; however, pyruvate and carnitine concentrations showed no significant difference. ASD subjects had significantly increased levels of certain acylcarnitines, with a decrease in tetra-deca-dienoyl-carnitine (C14:2), and certain acylcarnitines correlated significantly with autistic symptom scores. These researchers found reduced serum lactate levels in ASD, in contrast to previous studies suggesting elevated lactate or pyruvate. This difference may reflect the focus of this trial on high-functioning adults with ASD, who were likely to have fewer secondary genetic conditions associated with mitochondrial dysfunction. The authors concluded that the findings of significantly altered acylcarnitine levels in ASD support the hypothesis of altered fatty acid metabolism in a subset of ASD patients. Moreover, these investigators stated that mores studies are needed to validate these findings and examine the integration of these results to personalize treatment.

The authors stated that this study had several drawbacks. First, altered lactate and CK levels may be a result of physical exercise, blood collection (fist clenching and unclenching), and medication. Second, these researchers included secondary analyses that assessed the type of medication (e.g., antidepressant, antipsychotic, oral contraceptives); however, due to the different medications, correction for the respective dosage was not feasible. Third, subjects were not evaluated before breakfast and were only requested to not engage in physical activity the day before measurement; thus, the authors could not exclude a biasing effect due to nutrition or longer lasting effects of sport activities. For example, red meat was reported to be a rich source of L-carnitine in adults and milk in infants and children. Fourth, in the study, IQ was assessed using the MWT-B, which primarily measures crystalline intelligence, potentially leading to a bias of IQ scores in individuals with ASD.

Frye et al (2024) stated that ASD is a neurodevelopmental disorder affecting 1 in 36 children, and is associated with physiological abnormalities, most notably mitochondrial dysfunction, at least in a subset of individuals. In a systematic review and meta-analysis, these investigators identified 204 relevant studies that examined biomarkers of mitochondrial dysfunction in ASD individuals. Significant elevations (all p < 0.01) in the prevalence of lactate (17 %), pyruvate (41 %), alanine (15 %) and creatine kinase (9 %) were found in ASD. Individuals with ASD had significant differences (all p < 0.01) with moderate-to-large effect sizes (Cohen's d' ≥ 0.6) compared to controls in mean pyruvate, lactate-to-pyruvate ratio, ATP, and creatine kinase. Some studies found abnormal tricarboxylic acid (TCA) cycle metabolites associated with ASD. A total of 13 controlled studies reported mitochondrial DNA (mtDNA) deletions or variations in the ASD group in blood, peripheral blood mononuclear cells (PBMCs), lymphocytes, leucocytes, granulocytes, and brain. Meta-analyses discovered significant differences (p < 0.01) in copy number of mtDNA overall and in ND1, ND4 and CytB genes. Four studies linked specific mtDNA haplogroups to ASD. A series of studies found a subgroup of ASD with elevated mitochondrial respiration that was associated with increased sensitivity of the mitochondria to physiological stressors and neurodevelopmental regression. Lactate, pyruvate, lactate-to-pyruvate ratio, carnitine, and acyl-carnitines were associated with clinical features such as delays in language, social interaction, cognition, motor skills, and with repetitive behaviors and GI symptoms, although not all studies found an association. Lactate, carnitine, acyl-carnitines, ATP, CoQ10, as well as mtDNA variants, heteroplasmy, haplogroups and copy number were associated with ASD severity. Variability was found across biomarker studies primarily due to differences in collection and processing techniques as well as the intrinsic heterogeneity of the ASD population. Several studies reported alterations in mitochondrial metabolism in mothers of children with ASD and in neonates who develop ASD. Treatments targeting mitochondria, especially carnitine and ubiquinol, appeared beneficial in ASD. The link between mitochondrial dysfunction in ASD and common physiological abnormalities in individuals with ASD including GI disorders, oxidative stress, and immune dysfunction was outlined. Several subtypes of mitochondrial dysfunction in ASD were discussed, including one related to neurodevelopmental regression, another related to alterations in microbiome metabolites, and another related to elevations in acyl-carnitines. Mechanisms linking abnormal mitochondrial function with alterations in pre-natal brain development and post-natal brain function were outlined. Given the multi-system complexity of some individuals with ASD, this review presented evidence for the mitochondria being central to ASD by contributing to abnormalities in brain development, cognition, and co-morbidities such as immune and GI dysfunction as well as neurodevelopmental regression. A diagnostic approach to identify mitochondrial dysfunction in ASD was outlined. From this evidence, it is clear that many individuals with ASD exhibit alterations in mitochondrial function that may need to be addressed in order to achieve optimal clinical outcomes. The fact that alterations in mitochondrial metabolism may be found during pregnancy and early in the life of individuals who eventually develop ASD provides promise for early life predictive biomarkers of ASD. These researchers stated that further studies may improve the understanding of the role of the mitochondria in ASD by better defining subgroups and understanding the molecular mechanisms driving some of the unique changes found in mitochondrial function in those with ASD.

The authors stated that this systematic review and meta-analysis had several drawbacks, mostly due to the variability in the studies reviewed. This variation can be seen in the asymmetry of study results. Several biomarkers, including lactate, pyruvate, lactate, lactate-to-pyruvate ratio, alanine and CoQ10 showed significantly Luis Furuya-Kanamori (LFK) values suggesting outlier studies might be contributing to the results and suggesting publication bias. However, there were several sources of variation besides publication bias that might account for the variability in the results. First, biomarkers are derived from a wide variation of tissues, ranging from blood to brain tissue to neuroimaging to genetics. Second, even for common biomarkers, the techniques used to measure these biomarkers, including collection and laboratory techniques, are not standardized. For example, some insist on biomarkers measured in the fasting state while others may measure biomarkers after a meal. As food intake changes the metabolic state, these 2 methods of measuring biomarkers might not be completely comparable. Some studies did not provide the results of the biomarkers in tabular form so the values could not be incorporated into the meta-analysis. Although many studies were carried out in the U.S., many studies were conducted in the Middle East and some in the Far East. Differences in the characteristics of children in these different areas may bias individual study samples. Some findings were unexpected. For example, the mean alanine was lower in ASD compared to controls yet 8.2 % of those with ASD showed a consistent elevation in the alanine-to-lysine ratio even when it was repeated. This could be due to the fact that many children with ASD have low amino acid concentrations in general, presumably due to feeding or digestive abnormalities. As such, the relative ratio of alanine-to-lysine may be a superior biomarker than the alanine concentration alone. Lastly, from reviewing the patterns of abnormalities associated with mitochondrial dysfunction related to ASD, it is clear that there are several patterns that emerge. These will need to be better defined in the future so a clearer understanding of the various metabolic abnormalities related to ASD can be developed.

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Last Review 09/20/2024

Effective: 09/17/2002

Next Review: 07/10/2025
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