Autism Spectrum Disorders
Number: 0648
Table Of Contents
PolicyApplicable CPT / HCPCS / ICD-10 Codes
Background
References
Policy
Scope of Policy
This Clinical Policy Bulletin addresses autism spectrum disorders.
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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 (see Appendix for documentation and qualified provider requirements).
The following services may be included in the assessment and treatment of the member's condition:
- ASD specific developmental evaluation;
- Cognitive and adaptive behaviors evaluations;
- Speech, language and comprehensive communication evaluation by speech-language pathologist;
- Formal audiological hearing evaluation including frequency-specific brainstem auditory evoked response (see CPB 0181 - Evoked Potential Studies) or otoacoustic emissions;
- 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;
- Genetic testing specifically high-resolution chromosome analysis (karyotype), and DNA analysis for fragile X syndrome in the presence of intellectual disability (or if intellectual disability cannot be excluded) if there is a family history of fragile X or intellectual disability of undetermined etiology. If dysmorphic features or other clinical findings are present suggesting a genetic syndrome, other testing might be indicated when medical necessity criteria are met in CPB 0140 - Genetic Testing;
- Comparative genomic hybridization (CGH) (also referred to as chromosomal microarray analysis [CMA]), when medical necessity criteria are met in CPB 0787 - Comparative Genomic Hybridization (CGH);
- Medical evaluation (complete medical history and physical examination, including neurologic evaluation);
- Parent and/or child interview (including siblings of children with autism);
- Quantitative plasma amino acid assays to detect phenylketonuria;
- Selective metabolic testing if the child exhibits any of the following:
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Clinical and physical findings suggestive of a metabolic disorder:
- Cyclic vomiting, recurrent vomiting and dehydration
- Early seizure
- Lethargy
- Hearing impairment
- Hypotonia
- Visual impairment
- Unusual odor; or
- Dysmorphic or coarse features; or
- Evidence of intellectual disability or intellectual disability can not be ruled out; or
- Occurrence or adequacy of newborn screening for a birth defect is questionable;
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- Genetic counseling for parents of a child with autism (see CPB 0189 - Genetic Counseling);
- Electroencephalogram (EEG) for clinical spells that might represent seizures;
- Physical therapy (PT) and/or occupational therapy (OT) evaluations for sensorimotor deficits;
- Sleep-deprived EEG study only if the child exhibits any of the following conditions:
- Clinical seizures; or
- High suspicion of subclinical seizures; or
- Symptoms of developmental regression (clinically significant loss of social and communicative function) at any age, but especially in toddlers and preschoolers;
- Video-EEG when criteria are met in CPB 0322 - Attended Electroencephalographic (EEG) Video Monitoring;
- 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.
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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.
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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:
- Many Aetna plans exclude coverage of educational services. For example, speech therapy or applied behavior analysis (ABA) services during class would be excluded under these plans. Please check benefit plan exclusions;
- The current evidence is insufficient to demonstrate the superiority of any specific intensive educational intervention strategy, including behavioral approaches (e.g., ABA), educational approaches (e.g., structured teaching such as Treatment and Education of Autistic and Related Communication-Handicapped Children [TEACCH]), social-relational approaches (e.g., Developmental, Individual-differences, Relationship-based [DIR]/Floortime therapy and Relationship Development Intervention [RDI]), or developmental models (e.g., Early Start Denver Model [ESDM]), compared with other intensive educational intervention strategies for individuals with ASD (see CPB 0554 - Applied Behavior Analysis);
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Alternative and augmentative communication aids (e.g., sign language, flashcards, communication boards, etc.) if demonstrated as effective for the individual with ASD;
Note: Some plans exclude coverage of “communication aids”. Please check benefit plan exclusions.
- Physical and occupational therapy for co-morbid physical impairments;
- 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.
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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 spectrum disorders (ASD):
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Assessment
- Allergy testing (including food allergy for gluten, casein, candida, and other molds; allergen specific IgG and IgE)
- Artificial intelligence-based devices (e.g., Canvas Dx) for diagnosis of ASD
- Auditory brainstem response testing
- 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
- Blood tests for metabolomic analyses (e.g., NPDX ASD ADM Panel I by NeuroPointDX)
- Celiac antibody testing
- Ciliary neurotrophic factor (as a biomarker for ASD)
- EarliPoint test (an eye-tracking test) for the diagnosis of ASD
- Electronystagmography (in the absence of dizziness, vertigo, or balance disorder)
- Erythrocyte glutathione peroxidase studies
- Event-related brain potentials
- Fecal metabolites as diagnostic biomarkers of ASD
- GABA receptor polymorphisms testing
- Genetic panels that are not targeted to specific syndromic indications (e.g., the Fulgent ASD panel, the Greenwood Genetic Center's Syndromic Autism Panel, and the MitoMed-Autism Assay)
- Genetic testing for ABCA12, COX10, DRD2, HTR2C, MTHFR, RELN, SLC25A12 and UGT2B15 for diagnosis of ASD or guiding its drug treatment
- Gut microbiota profiles and nuclear factor kappa B as diagnostic biomarkers of ASD
- Hair analysis for trace elements (see CPB 0300 - Hair Analysis)
- Homocysteine testing (see CPB 0763 - Homocysteine Testing)
- Intestinal permeability studies
- Latent class analysis (for determination of psychosis-related clinical profiles in children with ASD)
- Magnetoencephalography/magnetic source imaging (see CPB 0279 - Magnetic Source Imaging/Magnetoencephalography)
- Measurement of androgen levels (blood, saliva, or urine) for the diagnosis of ASD
- Measurement of blood levels of insulin-like growth factor-1 levels, and thyroid hormone (thyroxine and triiodothyronine)
- Measurements of cerebrospinal fluid (CSF) biomarkers (e.g., chemokines, cytokines, folate, ganglioside GM, growth factors, neopterin, oxytocin, and vasopressin)
- Measurement of citrate synthase enzyme activity
- Measurements of plasma oxytocin (OXT) and vasopressin (VP) levels
- Measurements of plasma central carbon metabolites (e.g., alpha-ketoglutarate, alanine, lactate, phenylalanine, pyruvate, and succinate) (including the NPDX ASD Test (NeuroPointDX))
- Measurement of urine oligosaccharides for screening/diagnosis of ASD
- Micronutrients (i.e., trace elements, trace minerals or vitamin) level testing
- 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))
- Nutritional testing (e.g., testing for arabinose and tartaric acid)
- Olfactory function testing
- Provocative chelation tests for mercury
- Saliva analysis (e.g., Clarifi ASD, Quadrant Biosciences, Inc.)
- Serum cytokine and growth factor levels
- Stool analysis
- Tests for amino acids (except quantitative plasma amino acid assays to detect phenylketonuria), fatty acids (non-esterified), organic acids, citrate, silica, urine vanillylmandelic acid
- Tests for glutamatergic candidate genes
- Tests for heavy metals (e.g., antimony, arsenic, barium, beryllium, bismuth, mercury)
- Tests for immunologic or neurochemical abnormalities
- Tests for micronutrients such as vitamin levels
- Tests for mitochondrial disorders including lactate and pyruvate
- Tests for single-nucleotide polymorphisms within the OXT and VP receptor genes
- Tests for trace metals (e.g., aluminum, cadmium, chromium, copper, iron, lead, lithium, magnesium, manganese, nickel, selenium, zinc)
- Thyroid function testing
- Tympanometry (in the absence of hearing loss)
- Urinary peptide testing
- Use of biomarkers of mitochondrial dysfunction for the management of ASD;
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Treatments
- Acupuncture (see CPB 0135- Acupuncture and Dry Needling)
- Auditory integration training (auditory integration therapy) (see CPB 0256 - Sensory and Auditory Integration Therapy)
- BioMat
- Chelation therapy (see CPB 0234 - Chelation Therapy)
- Cognitive rehabilitation (see CPB 0214 - Cognitive Rehabilitation)
- Electroconvulsive therapy (for the treatment of autistic catatonia) (see CPB 0445 - Electroconvulsive Therapy)
- Elimination diets (e.g., gluten and milk elimination)
- Emotion recognition training
- Facilitated communication
- Hippotherapy, also known as equine therapy (see CPB 0151 - Hippotherapy)
- Holding therapy
- Immunoglobulin infusion (see CPB 0206 - Parenteral Immunoglobulins)
- Injectable anti-fungal medications (e.g., fluconazole, metronidazole)
- Injectable anti-viral medications (e.g., acyclovir)
- Injectable vitamins and minerals (calcium, magnesium, manganese, selenium, zinc)
- Manipulative therapies (see CPB 0107 - Chiropractor Services)
- Massage therapy
- Methyl B12
- Music therapy and rhythmic entrainment interventions
- Neurofeedback/EEG biofeedback (see CPB 0132 - Biofeedback)
- Nutritional supplements (e.g., dimethylglycine, glutathione, magnesium, megavitamins, omega-3 fatty acids, and high-dose pyridoxine)
- Nutritional therapy (e.g., casein-free and gluten-free diets, ketogenic and modified Atkins diets)
- Oxytocin
- Quantum Reflex Integration
- Secretin infusion
- Sensory integration therapy (see CPB 0256 - Sensory and Auditory Integration Therapy)
- Stem cell transplantation
- Systemic hyperbaric oxygen therapy (see CPB 0172 - Hyperbaric Oxygen Therapy (HBOT))
- Tomatis sound therapy
- Transcranial direct current stimulation (see CPB 0469 - Transcranial Magnetic Stimulation and Cranial Electrical Stimulation)
- Vestibular stimulation
- Vision therapy (see CPB 0489 - Orthoptic Vision Therapy)
- Weighted blankets or vests.
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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.
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Related Policies
- CPB 0071 - Positron Emission Tomography (PET)
- CPB 0107 - Chiropractor Services
- CPB 0132 - Biofeedback
- CPB 0135 - Acupuncture and Dry Needling
- CPB 0140 - Genetic Testing
- CPB 0151 - Hippotherapy
- CPB 0158 - Neuropsychological and Psychological Testing
- CPB 0172 - Hyperbaric Oxygen Therapy (HBOT)
- CPB 0181 - Evoked Potential Studies
- CPB 0189 - Genetic Counseling
- CPB 0202 - Magnetic Resonance Spectroscopy (MRS)
- CPB 0206 - Parenteral Immunoglobulins
- CPB 0214 - Cognitive Rehabilitation
- CPB 0234 - Chelation Therapy
- CPB 0256 - Sensory and Auditory Integration Therapy
- CPB 0279 - Magnetic Source Imaging/Magnetoencephalography
- CPB 0300 - Hair Analysis
- CPB 0322 - Attended Electroencephalographic (EEG) Video Monitoring
- CPB 0376 - Single Photon Emission Computed Tomography (SPECT)
- CPB 0445 - Electroconvulsive Therapy
- CPB 0469 - Transcranial Magnetic Stimulation and Cranial Electrical Stimulation
- CPB 0489 - Orthoptic Vision Therapy
- CPB 0553 - Lead Testing
- CPB 0554 - Applied Behavior Analysis
- CPB 0763 - Homocysteine Testing
- CPB 0787 - Comparative Genomic Hybridization (CGH)
Background
Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by persistent impairments in social communication and social interaction, accompanied by restricted, repetitive patterns of behavior, interests, or activities. The condition exists along a spectrum, with substantial variability in clinical presentation, symptom severity, functional impact, and support needs across affected individuals. According to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision (DSM-5-TR, 2022), published by the American Psychiatric Association (APA), the diagnosis of ASD is based on specific diagnostic criteria requiring persistent deficits in social communication and interaction across multiple contexts. These deficits include difficulties with social-emotional reciprocity, nonverbal communication such as eye contact, facial expressions, and gestures, and the development, maintenance, and understanding of relationships. In addition, individuals must exhibit at least two types of restricted and repetitive patterns of behavior, interests, or activities, such as repetitive motor movements or speech, insistence on sameness or adherence to routines, highly restricted or fixated interests, or hyper- or hyporeactivity to sensory stimuli. Symptoms must be present during the early developmental period, cause clinically significant impairment in social, occupational, educational, or other important areas of functioning, and not be better explained by intellectual disability alone, although both conditions may co-occur (APA, 2022; CDC, 2025).
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 12 months of age. Specifically, by 12 months of age, children who later receive an autism diagnosis often exhibit diminished social attention, poor eye contact, reduced reaction to speech, and reduced interest in interaction and play, as well as less smiling, expressiveness, and vocalization and babbling. Characteristically, they also commonly fail to point or respond to being called by their name. Between 12 months and 3 years old, children who are later diagnosed with autism begin to exhibit many of the key characteristics of autism that are found in older children and adults. These include reduced attention to social stimuli (visual and verbal), limited eye contact, reduced social engagement, and increased isolation. Language delays and a paucity of joint attention are also among the most commonly reported parental concerns during this early period of development (National Academies of Sciences, Engineering, and Medicine, 2025). However, there is no reported evidence that confirms or excludes a diagnosis of autism based on these cognitive patterns alone.
Symptoms must be present in the early developmental period, although they may not become fully apparent until later when social demands increase, and they must cause clinically significant impairment in daily functioning. The diagnosis also requires that these difficulties are not better explained by intellectual disability alone, although both conditions may co-occur. The DSM-5-TR further classifies autism by levels of support needs, ranging from Level 1 (requiring support) to Level 3 (requiring very substantial support), and allows clinicians to include additional specifiers, such as the presence of intellectual or language impairment or association with other medical or mental conditions.
In 2013, in the transition to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, the American Psychiatric Association made a major change by consolidating several previously separate diagnoses, such as autistic disorder, Asperger’s disorder, childhood disintegrative disorder, and pervasive developmental disorder not otherwise specified (PDD-NOS), into a single diagnosis of ASD. This shift was based on growing research showing that these conditions were not truly distinct disorders, but rather part of a continuum with varying levels of severity and symptom presentation. The DSM-5 replaced the earlier subcategories with a spectrum model to better reflect differences in support needs and functioning, while also improving diagnostic consistency and reliability among clinicians. Additionally, the criteria were reorganized into two main domains: social communication deficits and restricted, repetitive behaviors, from the previous three-domain structure. This change emphasized that autism presents along a spectrum and allowed for more individualized descriptions through severity levels and specifiers, rather than relying on rigid diagnostic labels.
Pervasive developmental disorder (PDD) was an older medical term for a group of conditions that included classic autism and Asperger's syndrome. However, PDD is no longer used to indicate a separate diagnosis. These conditions are included under autism spectrum disorder (ASD).
ASD is one of the most prevalent neurodevelopmental disorders in childhood and represents a significant public health concern. Based on 2022 data, ASD prevalence is estimated to occur in 1 in 31 children; ASD is also reported to occur in all racial and ethnic groups and is 3.4 times as prevalent among boys as among girls (CDC, 2025). Research indicates a strong genetic component to autism, with studies suggesting that 60–90% of the risk is inherited, demonstrating a high heritability. While not caused by a single gene, autism involves combinations of rare mutations and common genetic variations, often interacting with environmental factors. Recent breakthroughs have identified hundreds of contributing genes, often impacting brain development pathways. While autism is recognized for this high heritability, the absence of one hundred percent concordance in monozygotic twins and the increased concordance rates observed in dizygotic twins relative to full siblings provides substantial evidence for the possibility of environmental susceptibility factors (Hallmayer et al., 2011). Later studies have re-analyzed large datasets and argued for a higher heritability estimate, suggesting that earlier findings may have underestimated genetic influence (Sandin et al., 2017; Rylaarsdam & Guemez-Gamboa, 2019; Bai et al., 2019). Additionally, parallel evidence of immune and electroencephalographic abnormalities in patients with autism argues for a neurobiologic or immunologic implication in pathogenesis. Further, some neurological disorders such as tuberous sclerosis, neurofibromatosis, fragile X syndrome, and phenylketonuria may also be associated with autistic features. In summation, autism is a complex condition with no single, universally identified cause, and current evidence points to a multi-factor interaction rather than one direct genetic or environmental linkage (Jutla & Veenstra-VanderWeele, 2019; Bai et al., 2019). With prevalence and incidence data noting a growing population of those with ASD, early detection is crucial to maximize developmental potential and improve behavioral, social, and communicative outcomes.
There is broad consensus that treatment should be individualized to address each child's unique strengths, challenges, and the needs of the family. Early identification and the prompt initiation of intensive, evidence-based interventions are associated with improved outcomes, particularly in the areas of behavior, communication, and functional skill development, with growing evidence supporting greater effectiveness when treatment begins as early as possible. Comprehensive evaluation and management of ASD may involve a multidisciplinary team of qualified, licensed, or certified healthcare professionals, including board-certified behavior analysts, developmental pediatricians, neurologists, occupational therapists, physical therapists, primary care providers, psychiatrists, psychologists, speech-language pathologists, and audiologists.
Multiple clinical guidelines, such as those promulgated by the American Academy of Pediatrics (AAP), National Institute for Health and Care Excellence (NICE), and American Academy of Child and Adolescent Psychiatry (AACAP), align upon several fundamental principles in the management of ASD. The disorder necessitates early and comprehensive assessment; the utilization of evidence-based behavioral and developmental interventions; the application of pharmacotherapy restricted to specific targeted symptoms; the maintenance of coordinated, multidisciplinary care spanning medical, academic, and familial systems; and the implementation of proactive lifespan planning that adjusts to the individual's evolving needs.
Additionally, the NICE Quality Standard (QS51) (2014) outlines key quality statements in the assessment and diagnosis of ASD in children and young people. It emphasizes the importance of timely recognition and referral, ensuring that children suspected of having autism receive appropriate assessments without unnecessary delays. The quality statements highlight the need for a comprehensive, multidisciplinary approach to diagnosis, involving various trained professionals and incorporating input from families. Additionally, the standard stresses the importance of providing clear information and support to families throughout the assessment process. Overall, QS51 aims to improve the quality of care and support for children and young people with autism, ensuring they receive timely and effective interventions tailored to their needs.
Screening and Diagnosis
The 2020 AAP clinical report on autism spectrum disorder (ASD), reaffirmed in October 2025, emphasizes early identification as a critical determinant of outcomes and recommends ongoing developmental surveillance at every well-child visit, supplemented by standardized screening. General developmental screening is advised at 9, 18, and 30 months, with ASD-specific screening at 18 and 24 months using validated tools such as the Modified Checklist for Autism in Toddlers, Revised, with Follow-Up (M-CHAT-R/F). A central principle is that clinicians should not adopt a "wait and see" approach; any parental concern or abnormal screening result should prompt immediate referral for both diagnostic evaluation and early intervention services. Attention is given to high-risk populations, including siblings of children with ASD and children with existing developmental concerns, as early detection in these groups can significantly improve access to services and long-term developmental trajectories.
The AACAP Practice Parameter (2014) and NICE Autism Guideline (CG128) (2017) align with these recommendations by underscoring the disorder’s developmental onset and the necessity for early assessment when social, communication, or cognitive delays are observed, noting that individuals can present for evaluation at any point in development. Patients may also present with regression after achieving some milestones (Webb & Jones, 2009). Multidisciplinary care and service coordination are key components, given ASD’s heterogeneity and frequent co-occurrence with other developmental or psychiatric conditions. Highlighted by all these guidelines, the NICE Guideline specifically notes individuals such as parents, teachers, and healthcare providers should be trained in recognizing the early signs of autism, typical developmental milestones, and atypical behaviors (2017).
Clinical guidelines emphasize that ASD diagnosis is clinical and rooted in observed behavior and developmental history. Diagnosis centers on DSM-5-TR criteria, with deficits in social communication and interaction alongside restricted, repetitive behaviors, and recommends multidisciplinary evaluation including structured observation and standardized instruments (e.g., ADOS (Autism Diagnostic Observation Schedule) or CARS-2 (Childhood Autism Rating Scale, Second Edition)) combined with formal assessment of cognition, language, and adaptive functioning. This assessment/evaluation should also gather information from multiple sources, including parents, teachers, and other caregivers, to create a holistic view of the person’s behavior and development.
Medical evaluation should include hearing and vision screening and genetic testing such as chromosomal microarray and fragile X testing. Additional investigations, such as metabolic testing, electroencephalogram (EEG), or neuroimaging, are reserved for cases with specific clinical indications and are not used in routine screening or assessment. The AACAP guideline notes that ASD’s wide range of expression necessitates careful differential diagnosis to distinguish ASD from other developmental or psychiatric disorders (e.g., language disorders, social anxiety, stereotypic movement disorder, etc.) and again stresses multidisciplinary assessment and coordination of services by trained clinicians. All three sources note the high prevalence of co-occurring conditions such as intellectual disability, attention-deficit/hyperactivity disorder (ADHD), anxiety, sleep, and gastrointestinal (GI) disorders, thus underscoring the importance of comprehensive evaluation to guide intervention planning.
Validated tools for identifying and diagnosing ASD are typically divided into screening instruments and comprehensive diagnostic measures. While not exhaustive, common screening tools include the Modified Checklist for Autism in Toddlers, Revised with Follow-Up (Questions) (M-CHAT-R/F) for toddlers, a brief parent questionnaire for children aged 16–30 months, used for early detection of risk; the Social Communication Questionnaire (SCQ), used in children at least four years old to screen for social/communication difficulties; the Social Responsiveness Scale (SRS), which measures the severity of autism-related social impairment; and the Screening Tool for Autism in Toddlers and Young Children (STAT). The Ages and Stages Questionnaire (ASQ) is a general developmental screening tool that examines milestones and developmental challenges at specific ages. Self-report measures such as the Autism Spectrum Quotient and Ritvo Autism Asperger Diagnostic Scale-Revised can help with screening in adolescents and adults. As screening tools, these and others are useful for identifying individuals who may require further evaluation but are not sufficient for diagnosis on their own.
The AAP Guideline also notes tools such as the Behavior Assessment System for Children, Diagnostic Interview for Social and Communication Disorders (DISCO), and the Child Behavior Checklist can identify behavioral profiles consistent with ASD while often being used to assess children and youth for other behavioral health conditions (2020). The Wechsler Intelligence Scales and other cognitive tests are often used to evaluate intellectual ability, and the Vineland Adaptive Behavior Scales are used to assess daily living skills and social functioning.
A diagnosis of autism should include the use of standardized caregiver interviews regarding current concerns and behavioral history related to autism, and direct, structured observation of social and communicative behavior and play.
Additionally, diagnostic assessment relies on standardized, clinician-administered instruments such as the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2), Autism Diagnostic Interview-Revised (ADI-R), and Childhood Autism Rating Scale, Second Edition (CARS-2). Importantly, ASD diagnosis is ultimately based on clinical judgment guided by criteria outlined in the DSM-5-TR and involves integrating information from multiple sources, including developmental history, direct observation, and standardized assessment tools (American Psychiatric Association, 2022; Lord et al., 2012; Rutter, Le Couteur, & Lord, 2003; Robins et al., 2014). Of note, the AACAP (2014) and AAP (2020) ASD Guidelines do not recommend 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.
In summary, a comprehensive diagnostic evaluation for ASD is considered medically necessary when there are concerns regarding developmental delay or social-communication differences. This evaluation should be conducted by an appropriately trained and licensed provider and include the following: developmental and medical history; behavioral observation; the use of standardized tools; cognitive/developmental testing; speech-language evaluation; and a hearing evaluation. Conditional components of a diagnostic evaluation would also include genetic testing (when indicated) and an EEG if seizures are suspected, or other neurological testing.
Treatment
For treatment, the AAP places the strongest evidence base behind behavioral and developmental interventions, particularly ABA-based and naturalistic developmental behavioral interventions (NDBIs), which are designed to enhance communication, social skills, adaptive functioning, and behavior regulation. The AAP highlights starting these interventions as early as possible, even before a formal diagnosis, because earlier access to services correlates with improved developmental trajectories. Parent-mediated interventions are also emphasized, as they promote the generalization of skills into everyday contexts. Speech and language therapy, occupational therapy, and physical therapy are important adjuncts tailored to individual needs. Consistent with this, the AACAP parameters call for early, sustained intervention using a variety of treatment modalities and stress that ASD management challenges require coordination across disciplines. While AACAP’s parameter inherently reflects earlier DSM terminology, its core focus remains on individualized programs that incorporate behavioral, educational, and communicative support, with the clinician advocating for appropriate services and family involvement throughout the treatment process.
Both guidelines agree that no medications are indicated for core ASD symptoms such as social deficits or restricted interests. Medications are instead used to target associated or co-occurring symptoms that can impede functioning. The AAP details pharmacologic strategies for irritability, aggression, ADHD symptoms, anxiety, repetitive behaviors, and sleep disturbances, noting that atypical antipsychotics (e.g., risperidone, aripiprazole) may be used for severe irritability or aggression, while stimulants or non-stimulants can address ADHD symptoms, and SSRIs may be considered for anxiety or other target symptoms when behavioral interventions are insufficient. Regular monitoring for efficacy and side effects is emphasized. While the older AACAP practice parameter is broader in age range and includes earlier evidence on various psychotropic agents, its underlying message is consistent: use medication judiciously, focus on targeted symptoms, and integrate medication into a comprehensive treatment plan that includes behavioral and educational strategies.
Evidence supports early identification and intervention in ASD to improve functional outcomes. Behavioral interventions, particularly early intensive behavioral intervention (EIBI), demonstrate the strongest and most consistent evidence for improving communication, adaptive functioning, and social engagement. ASD is heterogeneous, and treatment plans must be individualized based on severity, functional needs, and comorbidities. While numerous alternative therapies have been proposed, most lack sufficient high-quality evidence to support routine use in clinical practice.
The National Academy of Sciences Report (2001) found limited evidence on the effectiveness of discipline-specific therapies for autism, noting that various intensive intervention programs, such as Lovaas therapy and the TEACCH Program, aim to enhance children's social communication and interaction skills. It highlighted the strong empirical support for functional communication training, which effectively replaces challenging behaviors by teaching communication skills that serve as functional equivalents. The report also endorsed augmentative and alternative communication (AAC) strategies for children with autism who struggle with speech, emphasizing their role in educational programs. Additionally, a structured assessment indicated that AAC interventions are effective for behavior change and generalization in individuals with severe expressive communication disorders, while assistive technology (AT) supports the functional capabilities of those with disabilities through various devices and adaptations.
Covered treatment entities for ASD treatment include three domains: core interventions, medication management, and supportive services. These are considered medically necessary when prescribed by a qualified and licensed provider and based on individualized assessment.
Family Support and Educational/Systems-Based Care
Systems-level coordination is a key theme in both guidelines. The AAP advocates for a medical home model where pediatric clinicians coordinate care across healthcare and education systems and facilitate access to early intervention services and school-based services such as IEPs after age three. The aim is individualized, evidence-based, and culturally responsive services that support inclusion and functional development. The AACAP parameter similarly highlights the complexity of ASD management, requiring professionals from diverse disciplines and the advocacy role of clinicians and families to ensure children receive the necessary educational, social, and therapeutic support across settings. Both emphasize reducing fragmentation of services and addressing disparities in access.
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. This report also noted that "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."
Family support and counseling are emphasized as essential components of care, given the significant stress experienced by caregivers. Clinicians are encouraged to provide clear, evidence-based guidance about ASD, including realistic expectations and avoidance of unsupported or potentially harmful treatments. Connecting families to community resources, support groups, and mental health services is critical, as is acknowledging and addressing cultural beliefs and stigma that may influence care engagement. AACAP also highlights the clinician’s role in facilitating family involvement in assessment and treatment planning, advocating for services, and supporting caregivers in their role, particularly as they adjust to the emotional and logistical challenges of ASD management.
Care Across the Lifespan
The AAP, NICE and AACAP underscore the importance of a lifespan approach, including early and proactive planning for adolescence and adulthood. They identify the importance of regular reviews of the individual’s needs and progress to ensure that support remains relevant and effective as the child develops. Transition planning should begin in early adolescence and focus on vocational skills, independent living, and social functioning, as well as the eventual transfer from pediatric to adult healthcare systems. Considerations such as guardianship and decision-making capacity are also addressed during this period. Outcomes in ASD are highly variable and influenced by factors such as early intervention, cognitive and language abilities, and the availability of supports. Overall, the report highlights ASD as a heterogeneous, lifelong condition requiring coordinated, multidisciplinary, and developmentally informed care, with early identification and intervention serving as the foundation for improved long-term functioning.
Acupuncture
Acupuncture is considered experimental, investigational, or unproven for the treatment of ASD.
In a systematic review and meta-analysis, Lee and associates (2018) evaluated the available evidence regarding the safety and efficacy of 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 neurodevelopmental disorder without a 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 subjects 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), as well as 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 the widespread application of this therapy.
Artificial Intelligence-Based Devices for Diagnosis of Autism Spectrum Disorder
Artificial intelligence-based devices (e.g., Canvas Dx) are considered experimental, investigational, or unproven for diagnosis of ASD.
Chaddad et al. (2021) stated that radiomics with deep learning models have become popular in computer-aided diagnosis and have outperformed 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 on 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 techniques used to classify between ASD and healthy control (HC) subjects. With AI, new radiomic models using 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 three distinct inputs (a caregiver questionnaire, analysis of two 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 two or more independent specialists in a cohort of 18- to 72-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 one or more complex neurodevelopmental disorders. No significant differences in device performance were found across subjects’ sex, race/ethnicity, income, or education level. For nearly one-third 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., smartwatches) 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 innovation 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 three main groups as follows: studies with the main focus on ASD, 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 numbers 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 missed important original literature on the use of mobile and wearable AI in child 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 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, highlight 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 three categories. The first category included "Triage patients based on diagnosis methods," which accounted for 16.66% (n = 3/18). The second category included "Prioritization for Risky Genes," which accounted for 66.6% (n = 12/18) and was classified into two sub-categories: "Mutations observation based" and "Biomarkers and toxic chemical observations." The third 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 newly developed methodology has been suggested as future work for triaging and prioritizing ASD patients according to their severity levels by using decision-making techniques.
Auditory Brainstem Response Testing for Evaluation of Autism Spectrum Disorder
Auditory brainstem response testing is considered experimental, investigational, or unproven for evaluation of ASD. See CPB 0256 - Sensory and Auditory Integration Therapy.
Cardoso et al. (2025) stated that ASD is a pervasive developmental disorder characterized by deficits in communication and social interactions, as well as repetitive behavioral patterns. Understanding the relationship between auditory brainstem response (ABR) and hearing is essential, considering the importance of sensory function. ABR testing is a tool that examines the auditory system from the periphery to the brainstem in response to an acoustic stimulus, providing important information regarding the auditory pathways. In a cross-sectional, comparative study, these researchers examined auditory brainstem response findings in children with ASD versus those of a control group. This trial included 23 children (ages 7 to 10 years) diagnosed with ASD and an age- and sex-matched control group of normal-hearing children with typical development. All subjects underwent otoscopy, impedance audiometry, pure-tone audiometry, speech audiometry, as well as brainstem evoked response audiometry. Statistically significant between-group differences were observed in the comparison of the absolute latencies of waves III (p = 0.047) and V (p = 0.034), as well as inter-peak intervals III to V (p = 0.048) and I to V (p = 0.036), with increased values in the study group. The sample was composed of 8.7% females and 91.3% males. The authors concluded that in this sample, children with ASD demonstrated increased ABR latencies compared to the control group, suggesting auditory pathway impairment. These researchers stated that the analysis of ABR in children with ASD can contribute to a better understanding of neuroelectric conduction in the auditory pathway; thus, it can aid in guiding early interventions, as well as future research aiming at a more comprehensive characterization of these electrophysiological phenomena.
The authors stated that this study reported findings that are relevant for clinical practice and should encourage future research, as it revealed that ABR testing can help in the assessment process as well as enable earlier therapeutic intervention. Moreover, these investigators stated that one drawback of this trial was that the cohort was restricted in age range (7 to 10 years) and severity of ASD (all subjects were level 1); thus, these findings could not be generalized. They stated that further investigations are needed to better understand the auditory brainstem responses of children with ASD. Such research should provide essential inputs to inform the evaluation and, consequently, treatment and follow-up of this population.
Auditory Integration Therapy
Auditory integration training (auditory integration therapy) is considered experimental, investigational, or unproven for the treatment of ASD.
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 hypersensitivities, 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 six relatively small studies of AIT and one of Tomatis therapy that 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, reported 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 important 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 on sensory processing abnormalities in autism and on plasma GDNF levels. A total of 15 ASD children, aged between 5 and 12 years, were enrolled and underwent the present research study; AIT was carried out over 10 days with a 30-minute 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. The 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 one month and three 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 to or not connected to the up-regulation of GDNF.
Behavioral Therapies for ASD
The National Academy of Sciences (NAS) Report (2001) indicated that while there is substantial research supporting comprehensive programs for autism, there is limited evidence on the effectiveness of discipline-specific therapies, with no adequate comparisons of different comprehensive treatments. Lovaas therapy, an early behavioral intervention method, employs intensive teaching techniques to reinforce appropriate social behaviors in children with autism. However, the original study by Lovaas in 1987 had methodological flaws, leading to questions about the efficacy of early behavioral interventions. Recent reviews have suggested that no treatment currently meets the criteria for well-established efficacy, highlighting the need for further research to refine these approaches.
Comparative studies, such as those by Delprato (2001) and Boyd and Corley (2001), have shown that normalized language interventions may be more effective than discrete trial training, and while early intensive behavioral intervention (EIBI) programs yield high parental satisfaction, they do not support claims of "recovery" in children. Evaluations by organizations like the Alberta Heritage Foundation for Medical Research and the Canadian Coordinating Office for Health Technology Assessment have pointed out the methodological weaknesses in existing studies, emphasizing the need for better-designed research with adequate control groups and consistent outcome measures. Overall, while some children may show significant progress with intensive interventions, the lack of robust evidence makes it difficult to draw definitive conclusions about the effectiveness of specific programs or the relationship between treatment intensity and outcomes.
Blood Levels of Methylation Capacity as Biomarkers for Diagnosis and Therapeutic Targets of Autism Spectrum Disorder
Blood levels of methylation capacity (e.g., methionine , S-adenosylmethionine (SAM), S-adenosylhomocysteine (SAH), and the SAM/SAH ratio) are considered experimental, investigational, or unproven as biomarkers for diagnosis and therapeutic targets of ASD.
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.
Cerebrospinal Fluid Biomarkers in the Management of Autism Spectrum Disorder
Measurements of cerebrospinal fluid (CSF) biomarkers (e.g., chemokines, cytokines, folate, ganglioside GM, growth factors, neopterin, oxytocin, and vasopressin) are considered experimental, investigational, or unproven for evaluation of ASD.
Srivastava and O'Reilly (2025) stated that ASD is a range of neurodevelopmental conditions characterized by impaired social interaction, learning, as well as restricted or repetitive behaviors. The underlying causes of ASD are still debated; however, researchers have found many physiological traits like gut problems and impaired immune system to aid in understanding the etiology of ASD. CSF plays an important role in maintaining the homeostasis of the neuronal environment and thus, has been analyzed in multiple conditions impacting the CNS. The study of CSF is essential in understanding neurological disorders as its composition changes with the disorders, and these changes may reflect various disorder-related physiological mechanisms. In a systematic review, these investigators searched PubMed, Scopus, and Web of Science for studies published between 1977 and 2025; and selected 49 studies after manual screening. They examined the evidence supporting the hypothesis that ASD changes the properties and composition of CSF. These researchers reported on the different attributes of CSF in the ASD population that could be potential biomarkers and assist in understanding the origins and progression of ASD. They found that in CSF, immune markers, proteins, extra-axial CSF, folate, oxytocin, and vasopressin showed changes in ASD compared to the neurotypicals. These investigators observed gaps in the literature due to variations in age and sample size and noted biases related to sex (i.e., samples were predominantly male subjects) and age (i.e., a handful of studies were conducted on adults). The authors concluded that his systematic review highlighted the need for more research on CSF in ASD to improve the understanding of this disorder and identify CSF biomarkers.
Chelation Therapy
Chelation therapy is considered experimental, investigational, or unproven for treating ASD.
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.
Ciliary Neurotrophic Factor (CNTF) as a Biomarker for ASD
Ciliary neurotrophic factor (as a biomarker for ASD) is considered experimental, investigational, or unproven.
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.
Cognitive Rehabilitation
Cognitive rehabilitation is considered experimental, investigational, or unproven for the treatment of ASD.
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.
See CPB 0214 - Cognitive Rehabilitation.
Developmental, Individual-differences, Relationship-based (DIR) FloorTime Therapy
Floor time therapy, part of the Developmental, Individual-differences, Relationship-based (DIR) model, involves parents engaging with their autistic children through play to enhance social and communicative skills. However, a systematic assessment by Parr (2006) concluded that the effectiveness of floor time therapy for autism remains unknown.
Praphatthanakunwong et al. (2018) emphasized the importance of parental engagement in DIR/Floortime, noting that various factors influence this engagement. Their cross-sectional study of parents with children aged 2–12 diagnosed with autism found that married parents with lower income and greater knowledge of DIR/Floortime were more engaged. Additionally, the severity of the child's diagnosis and ongoing treatment were significantly correlated with parental involvement. The study revealed that parents who practiced DIR/Floortime techniques for over an hour daily or demonstrated high-quality engagement saw better improvements in their children's development. However, the authors acknowledged limitations, including potential selection bias due to participant criteria and the lack of a gold standard diagnostic tool. They also noted the absence of specific assessments related to ASD skills, suggesting that future research should address these gaps.
Boshoff et al. (2020) highlighted that occupational therapy is often integrated into the DIR/Floortime model, which focuses on emotional development as a foundation for other developmental areas. Their systematic review identified nine studies with varying quality, primarily reporting positive outcomes in socio-emotional development. The authors called for higher quality research to strengthen the evidence base for this intervention, recommending that practitioners utilize sound clinical reasoning, intervention fidelity, and valid outcome measures in their practice.
Electro-Convulsive Therapy
Electro-convulsive therapy is considered experimental, investigational, or unproven for the treatment of autistic catatonia.
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
Emotion recognition training is considered experimental, investigational, or unproven for the treatment of ASD.
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.
Equine Therapy / Hippotherapy
Equine therapy, also known as hippotherapy, is considered experimental, investigational, or unproven for the treatment of ASD.
Wuang et al. (2010) evaluated the effectiveness of a 20-week Simulated Developmental Horse-Riding Program (SDHRP) using innovative exercise equipment (Joba) on motor proficiency and sensory integrative functions in 60 children with autism, aged 6 years and 5 months to 8 years and 9 months. In the first phase, 30 children received SDHRP alongside regular occupational therapy, while the other 30 received only occupational therapy. This arrangement was reversed in the second phase. Results indicated significant improvements in motor proficiency and sensory integration after the SDHRP (p < 0.01), with effects sustained for at least 24 weeks.
Kern et al. (2011) explored the impact of equine-assisted activities on autism symptoms, parent-child interactions, sensory processing, quality of life, and parental satisfaction. The study involved 24 participants who completed a waiting list before starting a 3-to-6-month riding program. Results showed a reduction in autism symptom severity, with significant decreases in Childhood Autism Rating Scale (CARS) scores after 3 and 6 months of treatment. Improvements were also noted in parent-child interactions and quality of life, with high satisfaction ratings from parents. The authors concluded that equine-assisted activities may benefit children with ASD, though further validation through well-designed studies is needed.
Eye-Tracking Studies (Eye-Tracking Test) for Differential Diagnosis of Autism Spectrum Disorder
Eye-tracking tests, such as the EarliPoint test) are considered experimental, investigational, or unproven for the diagnosis of ASD.
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.
Jones et al. (2023a) developed an objective eye-tracking-based tool for diagnosing ASD in children aged 16 to 30 months, comparing its performance against standardized clinical diagnoses in two studies. The eye-tracking test demonstrated high sensitivity (81.9%) and specificity (89.9%) in the discovery study, and similar results were replicated in an independent sample. The authors concluded that eye-tracking measurements of social visual engagement could aid in diagnosing and assessing ASD, although they acknowledged limitations such as the small number of expert clinicians involved and the need for further validation across diverse clinical settings.
In a related study, Jones et al. (2023b) highlighted the potential of eye-tracking measurements to identify autism in children referred to specialty clinics, achieving a sensitivity of 71.0% and specificity of 80.7%. The results correlated well with expert assessments of social disability and cognitive abilities. Dawson (2023) emphasized the need for further research to establish the feasibility and reliability of eye-tracking tests in clinical practice, including how these results could be integrated with other diagnostic information to improve the accuracy and efficiency of autism diagnoses.
In a cross-sectional study of 77 preschool-aged children (31-73 months), de Belen et al. (2023) used eye-tracking technology to evaluate response to joint attention (RJA) behaviors in children with autism spectrum disorder (ASD) and typically developing (TD) peers. Children with ASD demonstrated significantly reduced gaze-following abilities compared with TD children and were less accurate when relying solely on eye-gaze cues than when both eye and head movement cues were available. Greater gaze-following accuracy was associated with better cognitive functioning and adaptive behaviors, whereas poorer gaze-following performance correlated with more severe ASD symptoms. The authors concluded that eye-tracking measures of RJA may serve as objective biomarkers for ASD evaluation and diagnosis in preschool children and could potentially be incorporated into diagnostic assessments or measures of treatment response. However, the findings are limited by several factors, including a predominance of male participants in the ASD group, unequal group sizes, lack of developmental matching between groups, inclusion of children with comorbid conditions, use of prerecorded rather than live social stimuli, and the cross-sectional study design, which precludes conclusions regarding causality. Further research with larger, developmentally matched cohorts and more ecologically valid assessment methods is needed to confirm the clinical utility of eye-tracking measures in ASD.
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.
Facilitated Communication
Facilitated communication is considered experimental, investigational, or unproven for the treatment of ASD.
Facilitated Communication (FC) is a method designed to assist nonverbal individuals in expressing themselves through typing on various devices. However, a 2001 assessment by the National Autistic Society (NAS) concluded that there is insufficient evidence supporting the effectiveness of FC for autism. The NAS report highlighted over 50 studies involving 143 communicators, noting that the American Speech-Language-Hearing Association (ASHA) found a lack of scientific validation for FC skills and evidence of facilitator influence on the messages attributed to communicators (ASHA Technical Report, 1994). Consequently, a substantial body of research indicates that FC lacks scientific validity.
The American Academy of Pediatrics (AAP, 2001) also stated that the available information does not support the claims of FC proponents regarding its effectiveness in treating autism, categorizing it as experimental. Levy et al. (2009) reviewed various treatments for autism, noting that popular biologically based interventions include anti-infectives and chelation medications, while non-biologically based treatments encompass FC, among others. However, they pointed out that few studies have adequately addressed the safety and effectiveness of most of these treatments.
GABA Receptor Polymorphisms Testing
GABA receptor polymorphisms testing is considered experimental, investigational, or unproven for the assessment of ASD.
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.
Gastrointestinal, Nutritional, and Dietary Treatments
Autistic patients often experience gastrointestinal disturbances, leading to interest in treatments like secretin. Early case studies suggested that secretin could improve gastrointestinal symptoms and behaviors in autistic children. However, a randomized, double-blind, placebo-controlled study by Corbett et al. (2001) found no significant improvements in most measures, aligning with Owley et al. (2001), who also reported no efficacy for secretin in a multi-center trial. Similarly, Lightdale et al. (2001) found no effects of intravenous secretin on language and behavior over five weeks in children with autism and gastrointestinal symptoms.
Research into dietary interventions, such as gluten and casein-free diets, has also yielded inconclusive results. Millward et al. (2008) noted that while there is a high prevalence of complementary therapies among children with autism, the evidence supporting the effectiveness of these diets is poor, necessitating large-scale, high-quality randomized controlled trials. Curtis and Patel (2008) echoed this need for comprehensive studies to explore multifactorial treatment plans for autism. In a systematic review, Sausmikat and Smollich (2016) concluded that there is no proven efficacy for gluten-free and casein-free diets, highlighting the need for further research to identify which patients might benefit from specific dietary interventions.
Probiotics have been explored as a potential treatment for gastrointestinal and behavioral symptoms in autism. Shaaban et al. (2018) found that probiotics improved both gastrointestinal symptoms and behavioral issues in a small cohort of children. However, Liu et al. (2019b) noted that the therapeutic potential of probiotics remains controversial, with limited evidence supporting their efficacy. Ng et al. (2019) conducted a systematic review and found that while some studies suggested benefits, the overall evidence for probiotics and prebiotics in managing autism symptoms is limited. El-Rashidy et al. (2017) compared ketogenic diets to gluten-free casein-free diets and found that both improved autism symptoms, with the ketogenic diet showing superior results in cognition and sociability. Despite these findings, the authors emphasized the need for larger, more rigorous studies to confirm the effectiveness of dietary interventions in autism.
Genetic Testing
Previous recommendations from the AAN support 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" cannot be excluded), if there is a family history of fragile X or undiagnosed mental retardation, or if dysmorphic features are present (Filipek et al., 2000). An assessment prepared for the Agency for Healthcare Research and Quality (Sun et al, 2015) on genetic testing for developmental disability (DD), intellectual disability and ASD 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., microarray-based comparative genomic hybridization [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, findings were reported as not sufficient for drawing a conclusion that use of these tests would lead to improved health outcomes.
With evolving testing, current AAP, AACAP and NICE Guidelines support genetic evaluation, including chromosomal microarray and fragile X testing, with consideration of other cytogenetic/molecular testing, as indicated. Whole-exome sequencing (WES) may be considered when the history/physical examination, CMA, and fragile X analysis do not identify an etiology (AAP, 2020). The AAP Guideline further notes that genetic tests may explain the etiology or statistical risk for ASD, but they are not diagnostic. As noted, the diagnosis of ASD is made based on clinical symptoms. The AAP Guideline (2020) also notes, "unlike CMA and WES, commercially marketed tests may not have the potential to provide a molecular etiologic diagnosis. Genomic testing technology is evolving rapidly, as is our understanding of the genetic architecture of ASD, and these recommendations for testing will need to be updated as new studies are published".
For whole-exome sequencing, see CPB 0140 - Genetic Testing.
Genetic Testing for ABCA12, DRD2, HTR2C, MTHFR, RELN, SLC25A12 and UGT2B15
Genetic testing for ABCA12, COX10, DRD2, HTR2C, MTHFR, RELN, SLC25A12 and UGT2B15 is considered experimental, investigational, or unproven for diagnosis of ASD or guiding its drug treatment.
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 for 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 from 2001 to 2013. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to estimate the associations between three 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. Additionally, a positive result was obtained in the 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 the 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 two 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 were available from eight studies concerning rs2056202, and 465 cases, 450 controls, and 1,516 families were available from seven studies concerning rs2292813. 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, I² = 0.0%, and p (heterogeneity) = 0.526; rs2292813: OR = 0.752, p < 0.001, 95% CI: 0.649 to 0.871, I² = 0.0%, p (heterogeneity) = 0.486). Additionally, subjects with the 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, I² = 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 nine 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 ten 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 variants 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 a family-based design demonstrated a 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 two 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 reconsidered in a diagnostic clinical setting. The authors concluded that, based on the available scientific evidence, 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.
- 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.
Pal et al. (2025) noted that ASD is a complex neurodevelopmental disorder with genetic, environmental, and molecular roots. Among the thousands of genes that have been associated with ASD, one critical factor has emerged as ABCA12, which plays an important role in lipid transport and metabolism. Traditionally, it has been related to skin disorders; however, it has recently been implicated in broader brain development and function. Some of the implicated effects include dysregulated lipid homeostasis, neuro-inflammation, oxidative stress, as well as abnormalities in synaptic transmission when the ABCA12 system is dysregulated. All the afore-mentioned processes are related to pathology in ASD. These investigators reviewed the emerging function of ABCA12 in autism neurobiology; the core base was derived from in-vivo models and pre-clinical studies. Studies in in-vivo models (e.g., mice and zebrafish) had shown impairments of ABCA12 that led to social deficiency behaviors; but also performed repetitive actions. Based on the effects of the gene on molecular pathways, including neuronal signaling and membrane integrity, and identifying therapeutic approaches targeting ABCA12 or its down-stream effects, pre-clinical studies have contributed to the integration of genetic, functional, and therapeutic perspectives for understanding the contribution of ABCA12 to ASD. The authors concluded that these findings may unlock further investigations geared toward unravelling how lipid metabolism influences neurodevelopment with regards to interventions available for use in ASD.
Global Developmental Screenings for ASD
Siu et al. (2016) reported on the US Preventive Services Task Force (USPSTF) recommendation regarding autism spectrum disorder (ASD) screening in young children. The USPSTF reviewed evidence on the accuracy, benefits, and potential harms of brief screening instruments administered during routine primary care visits, as well as the benefits and harms of early behavioral treatment for children identified with ASD through screening. The recommendation specifically targets children aged 18 to 30 months who have not been diagnosed with ASD or developmental delay and for whom no concerns have been raised by parents or caregivers.
USPSTF concluded that current evidence is insufficient to determine the balance of benefits and harms of screening in these children. This conclusion aligns with the American Academy of Family Physicians (2015), which also states that evidence is insufficient for screening in children without raised concerns, and the UK National Screening Committee (2015), which does not recommend systematic population screening due to concerns about the stability of ASD diagnoses at a young age, lack of data on positive predictive value, and weak evidence for treatment efficacy.
Gut Microbiota Profiles, Fecal Metabolites, and Nuclear Factor Kappa B as Diagnostic Biomarkers of Autism Spectrum Disorder
Gut microbiota profiles and nuclear factor kappa B are considered experimental, investigational, or unproven as diagnostic biomarkers of ASD.
Bundgaard-Nielsen and colleagues (2020) stated that accumulating evidence has implicated the involvement of the gut-brain axis in ASD and ADHD; however, the results are highly diverse. In a systematic review, these researchers evaluated studies investigating the gut microbiota composition in individuals with ASD or ADHD and examined whether 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 databases to identify studies from 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. The majority of studies included fecal samples; however, four 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 antimicrobial use, gastrointestinal (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 databases were searched as far back as February 2020. Meta-analyses were performed using RevMan 5.3 to estimate the overall relative abundance of gut bacteria belonging to eight 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 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 gastrointestinal (GI) tract and the central nervous system (CNS), specifically on the effects of microbial composition on the brain and development. These investigators reviewed literature at the initial stage aimed at evaluating studies on gut microbial alterations in pediatric neurobehavioral conditions. They searched five literature databases (Embase, PubMed, PsychInfo, Scopus, and Medline) and found 4,489 published works. 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 which contribute 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 literature 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 were agreed upon by two 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 that compared the expression or activation of NF-κB between ASD cases and controls, as well as four animal studies that used a mouse model of ASD to examine the level of NF-κB and further evaluate its changes after different drug treatments. These 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 to the onset of ASD or rather as an ancillary factor regulating 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 kept open the discussion over the existence of aberrant NF-κB signaling in ASD subjects.
Korteniemi et al. (2024) stated that ASDs are a varying group of disorders characterized by deficiencies in social interaction and restrictive patterns of behavior and interests. While there are several studies focusing on the neuropsychiatric pathogenesis of ASD, its etiology remains unclear. The role of the 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 gut microbiota composition, interventions targeting the gut microbiota, and possible mechanisms explaining the results in children aged between 2 and 18 years. 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 that 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 therapeutic interventions.
Zheng et al. (2025) noted that ASD is a neurodevelopmental disorder characterized by deficits in social communication and the presence of restricted, repetitive behaviors or interests. Studies have revealed that gut microbiota and their metabolism play important roles in ASD and become the underlying mechanisms of ASD. These investigators carried out long-read 16S rRNA sequencing and untargeted metabolomics to characterize the profiles of gut microbiota and fecal metabolites in 34 ASD patients and 18 healthy control subjects. The associations between gut microbiota, fecal metabolites, and clinical symptoms were analyzed to screen for related biomarkers for ASD. The results revealed the similarity of the overall microbial richness and diversity between ASD patients and controls; however, some specific bacterial taxa showed significant differences, including Klebsiella and Escherichia-Shigella at the genus level, and Clostridium sporogenes, Escherichia coli O157:H7, and Bacteroides ovatus at the species level. The fecal metabolomics validated that many metabolites had significantly differential levels, including a series of organic acids, amino acids, and dopamine. The authors concluded that the associations of gut microbiota and fecal metabolites might shed new light on the pathogenesis of ASD and could aid in understanding the importance of gut microbiota as potential biomarkers and therapeutic targets in the development of ASD.
Hyperbaric Oxygen Therapy
For hyperbaric oxygen therapy, see CPB 0172 - Hyperbaric Oxygen Therapy (HBOT).
Immunoglobulin Infusions
For immunoglobulin infusions, see CPB 0206 - Parenteral Immunoglobulins.
Latent Class Analysis
Latent class analysis is considered experimental, investigational, or unproven for determination of psychosis-related clinical profiles in children with ASD.
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.
Massage and Chiropractic Interventions
Massage therapy involves the manipulation of tissues for therapeutic purposes. Lee et al. (2011) reviewed the effectiveness of massage for autism by searching multiple electronic databases up to March 2010. They included prospective controlled clinical studies and found only six studies that met their criteria. One randomized controlled trial (RCT) indicated that massage combined with conventional language therapy was more effective than language therapy alone for reducing symptom severity (p < 0.05) and improving communication attitude (p < 0.01). Other RCTs reported significant benefits of massage for sensory profiles, adaptive behavior, and social abilities, but all studies had a high risk of bias due to small sample sizes and inadequate controls. The authors concluded that there is limited evidence for the effectiveness of massage therapy in treating autism and called for more rigorous RCTs.
Alcantara et al. (2011) conducted a systematic review of chiropractic care for patients with autism spectrum disorder (ASD) using eight databases. They identified five relevant articles, including three case reports, one cohort study, and one RCT. The review highlighted a lack of substantial literature on chiropractic care for children with ASD. Preliminary studies suggested that chiropractic adjustments might improve sensorimotor integration, but the authors emphasized the need for further research to establish chiropractic's effectiveness for ASD.
Measurement of Androgen Levels (Blood, Saliva, or Urine) for the Diagnosis of ASD
Measurement of androgen levels (blood, saliva, or urine) are considered experimental, investigational, or unproven 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 six international and two Chinese databases. These researchers computed summary statistics with a random-effects model. Publication bias was evaluated using funnel plots, and heterogeneity was assessed 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 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 levels were 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 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 a few studies on female individuals with ASD. Third, there was 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, this greatly affected the accuracy of the results.
Measurement of Blood levels of Thyroid Hormone and Insulin-Like Growth Factor-1 For Diagnosis of Autism Spectrum Disorder
Measurement of blood levels of insulin-like growth factor-1 levels, and thyroid hormone (thyroxine and triiodothyronine) are considered experimental, investigational, or unproven for evaluation of ASD.
Long et al. (2025) stated that the action of the thyroid hormones and insulin-like growth factor 1 (IGF-1) is interdependent. The levels of thyroid hormone and IGF-1 were reported to be altered in individuals with ASD; however, the results were controversial. In a systematic review and meta-analysis, these investigators compared levels of thyroxine (T4), triiodothyronine (T3), thyroid stimulating hormone (TSH), and IGF-1 between the ASD group and neurotypical controls. They searched PubMed, Web of Science, Cochrane, and Embase databases for eligible studies. These researchers calculated pooled SMD with 95% CIs of the data using a random or fixed effect model. The search strategy provided a total of 1710 studies, of which 16 were quantitatively analyzed. The total number of included participants was 2,399 (1,285 cases and 1,114 controls). The meta-analysis showed no significantly changed blood levels of T4, free T3, free T4, and IGF-1 of subjects with ASD compared to non-autistic controls. The blood TSH levels were significantly lower in ASD subjects than in controls (n = 859, Hedges' g = -1.18, 95% CI: -2.17 to -0.20, p = 0.02). Subgroup-analysis results showed that blood free T3 (n = 153, Hedges' g = -0.74, 95% CI: -1.08 to -0.40, p < 0.0001, I2 = 2%), free T4 (n = 153, Hedges' g = -0.72, 95% CI: -1.31 to -0.14, p = 0.02, I2 = 66%), and IGF-1 (n = 397; Hedges' g = -0.92; 95% CI: -1.30 to -0.55, p < 0.00001, I2 = 63%) levels were significantly reduced in subjects with severe ASD symptoms. The authors concluded that individuals with severe ASD may experience a dysfunction of the hypothalamic-pituitary-thyroid axis, and further studies are needed to ascertain the correlation between thyroid hormone and IGF-1 levels and disease severity.
Measurement of Citrate Synthase Enzyme Activity for the Diagnosis/Evaluation of Autism Spectrum Disorder
Measurement of citrate synthase enzyme activity is considered experimental, investigational, or unproven for the diagnosis and evaluation of ASD.
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 gastrointestinal (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 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 compared to the rectum was significantly higher in ASD samples than in 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 from 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 the 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 were 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 first time, that such variations are related to ASD symptoms. Moreover, these researchers demonstrated only an association between behavior and biomarkers of mitochondrial activity; 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.
Measurements of Plasma Oxytocin and Vasopressin for Evaluation of Autism Spectrum Disorder
Measurements of plasma oxytocin (OXT) and vasopressin (VP) levels is considered experimental, investigational, or unproven for evaluation of ASD.
Zhang and associates (2016) stated that ASD is defined by impairments in 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 two 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 in 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 has reported a positive correlation of OXT levels between the two 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 have 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 are more directly relevant to behavioral effects or psychopathology.
Metabolic Testing
Current recommendations support selective metabolic testing if the child exhibits clinical and physical findings suggestive of a metabolic disorder such as lethargy, cyclic vomiting, hypotonia or weakness, visual and hearing impairment, or early seizure; or dysmorphic or coarse features; or evidence of mental retardation; or mental retardation cannot be ruled out; or occurrence or adequacy of newborn screening for a birth defect is questionable. Lead screening is recommended, if the child exhibits developmental delay and pica; however, there is "no evidence at this time for routine testing of hair, blood, or urine for environmental toxins or heavy metals" (AAP, 2020). Ultimately, metabolic testing is based on clinical indication, patient/family history, and physical examination, with overall understanding that "routine metabolic testing for children with ASD is low and not recommended for regular use" (AAP, 2020).
Metabolomic Analyses of Blood Samples (as a Biomarker for ASD)
Blood tests for metabolomic analyses (e.g., NPDX ASD ADM Panel I by NeuroPointDX) are considered experimental, investigational, or unproven for evaluation of 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 by 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 a 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 that 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 branched-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 positive predictive value (PPV) of 93.5%. The authors concluded that the identification and utilization of metabotypes of ASD can lead to actionable metabolic tests that support early diagnosis and stratification for targeted therapeutic interventions.
- 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.
Methyl B12 (MB12) for the Treatment of ASD
Methyl B12 is considered experimental, investigational, or unproven 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 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.
Hendren et al. (2016) performed a randomized, placebo-controlled trial with 57 children to evaluate the impact of methyl B12 (75 µg/kg) on ASD symptoms over eight weeks. The primary outcome, measured by the Clinical Global Impressions-Improvement (CGI-I) score, showed significant improvement in the methyl B12 group compared to placebo. Improvements were also correlated with enhanced plasma methionine levels and better cellular methylation capacity. However, no changes were observed in secondary measures like the Aberrant Behavior Checklist (ABC) or Social Responsiveness Scale (SRS). The authors noted the need for larger trials to confirm these preliminary findings, citing limitations such as a small sample size and adherence issues with laboratory protocols.
Li et al. (2018) reviewed the efficacy of nutritional supplements for addressing deficiencies and improving core symptoms in children with ASD, including 18 randomized controlled trials (RCTs). They found that while methyl B12 showed some promise in improving ASD severity, the evidence was inconclusive regarding deficiency correction. Other supplements, such as B6/Mg and omega-3 fatty acids, did not significantly affect ASD behaviors, and vitamin D3 showed inconsistent behavioral outcomes despite increasing serum levels. The authors concluded that current evidence for nutritional supplements in ASD is limited, emphasizing the need for further research.
Music and Sound Therapy
Music therapy and rhythmic entrainment interventions are considered experimental, investigational, or unproven for managing ASD.
Crawford et al. (2017) conducted a randomized controlled trial on improvisational music therapy (IMT) for children with ASD, finding no significant differences in social affect or responsiveness compared to standard care. Bieleninik et al. (2017) also reported similar results, concluding that IMT did not significantly reduce symptom severity in children with ASD. Bell (2004) and Gold et al. (2006) noted insufficient evidence to support its clinical effectiveness.
The Tomatis sound therapy, which uses filtered classical music to improve language skills, was evaluated by Corbett et al. (2008) in a randomized, double-blind study. The results indicated no significant improvement in language skills related to the treatment conditions. Overall, the evidence for AIT and sound therapies remains inconclusive, with a lack of robust studies demonstrating their effectiveness in treating ASD.
Geretsegger et al. (2022) conducted an updated Cochrane systematic review evaluating music therapy for individuals with autism spectrum disorder (ASD), building on earlier reviews published in 2006 and 2014. The authors reported that music therapy has been used in the treatment of autism since the 1950s; however, access to services varies across countries and clinical settings, and delivery requires specialized academic and clinical training to tailor interventions to individual patient needs. Compared with prior reviews, the updated evidence base included larger sample sizes, broader age ranges, longer intervention durations, follow-up assessments, and greater use of validated measures assessing generalized behaviors outside the therapy setting, thereby increasing confidence in the findings and their clinical applicability. The authors noted that the evidence may inform decision-making by individuals with autism, families, clinicians, service providers, and policymakers regarding the provision and allocation of therapeutic resources. However, the generalizability of the findings remains limited to the age groups studied, and conclusions regarding the effectiveness of music therapy in older adults with autism cannot be established. The authors also emphasized the need for additional high-quality research employing rigorous study designs, clinically relevant outcome measures, and longer-term follow-up to confirm the durability and long-term effects of music therapy interventions.
Neurofeedback / Electroencephalogram Biofeedback
Neurofeedback / electroencephalogram (EEG) biofeedback are considered experimental, investigational, or unproven for treatment of ASD.
Thompson et al. (2010) reviewed neurofeedback (NFB) training data from 150 patients with Asperger's syndrome (AS) and 9 with autism spectrum disorder (ASD) over 15 years. The study aimed to assess the effectiveness of NFB, also known as EEG biofeedback, in addressing key symptoms of AS and to encourage further research. Patients underwent 40 to 60 NFB sessions combined with training in meta-cognitive strategies and biofeedback for respiration, electrodermal response, and heart rate variability.
Feedback during NFB focused on decreasing slow wave activity (3 to 7 Hz), reducing beta spindling (23 to 35 Hz), and increasing sensorimotor rhythm (12 to 15 Hz). Significant improvements were observed in attention (measured by T.O.V.A. and IVA), core symptoms (using the Australian Scale for Asperger's Syndrome and other assessments), academic achievement (Wide Range Achievement Test), and intelligence (Wechsler Intelligence Scales), with an average Full Scale IQ gain of 9 points. The study also noted a decrease in relevant EEG ratios. These positive outcomes suggest that NFB may be a beneficial component in the intervention for individuals with AS.
Neuroimaging
Neurological considerations play a crucial role in the diagnosis and treatment of autism spectrum disorder (ASD). Research indicates that individuals with autism often exhibit differences in brain structure and function, including variations in connectivity and activity in regions associated with social communication, sensory processing, and executive functioning. These neurological factors can influence the presentation of symptoms and the effectiveness of various interventions. Some neurological disorders, such as tuberous sclerosis, neurofibromatosis, fragile X syndrome, and phenylketonuria, may also be associated with autistic features, in which autism is defined as "secondary."
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.
Current recommendations note that there is insufficient evidence to recommend EEG studies in all individuals with autism. A 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, ASD guidelines consider event-related potentials and magnetoencephalography to be research tools, which have no evidence of routine clinical utility.
Related to neuroimaging, localized structural and functional brain correlations of pervasive developmental disorders (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.
Philip and colleagues (2012) stated that recent years have seen a rapid increase in the investigation of ASD using 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 findings. 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.
Current recommendations indicate that distinct neuroimaging results are not found to be more common in ASD than in other neurodevelopmental disorders, and there is no consistent correlation between specific abnormalities and the clinical, etiological, or pathophysiological features of ASD. Incidental findings frequently occur in neuroimaging studies conducted for children diagnosed with ASD, but these findings seldom offer insights into the underlying causes or necessitate any intervention. The decision to perform a clinical MRI should be guided by the patient's medical history and physical examination and could be warranted in cases involving atypical regression, microcephaly, macrocephaly, seizures, intracranial signs of genetic disorders, abnormal neurological assessments, or other relevant clinical concerns (AAP, 2020).
Oxytocin Therapy
Oxytocin therapy is considered experimental, investigational, or unproven for management of ASD.
Oxytocin (OT) has emerged as a potential treatment for ASD, with various studies investigating its effects, particularly through intra-nasal delivery. Tachibana et al. (2013) conducted a long-term, open-label study involving 8 male youth with ASD, administering OT in increasing doses. While six participants showed improved communication and social interaction scores on the Autism Diagnostic Observation Schedule (ADOS-G), no statistically significant improvements were observed in other measures like the Child Behavior Checklist (CBCL) or the Aberrant Behavior Checklist (ABC). The study concluded that long-term nasal OT therapy appears safe, warranting further investigation through larger, controlled trials.
Anagnostou et al. (2014) reviewed the safety and efficacy of multi-dose OT in children and adolescents with ASD, finding that a maximum tolerated dose of 0.4 IU/kg was well-tolerated and led to changes in social cognition, repetitive behaviors, and anxiety. Their findings suggested therapeutic potential, although they emphasized the need for larger studies. Preti et al. (2014) conducted a systematic review of randomized controlled trials (RCTs) on OT interventions, identifying 7 studies with a total of 101 subjects. Most studies reported significant between-group differences, particularly in emotion recognition and eye gaze, but highlighted the need for more rigorous research and larger sample sizes.
Evans et al. (2014) discussed the mechanisms of intra-nasal OT delivery, noting that while it likely affects behavior, the nature of these changes can vary, with some studies indicating non-prosocial effects. Quintana et al. (2015) reviewed the pathways through which OT may influence social cognition and behavior, proposing a model to explain its effects. They called for further research to clarify these mechanisms.
Recent studies, including a phase-II clinical trial by Sikich et al. (2021), found that 24 weeks of daily intra-nasal OT did not significantly improve social interaction or other social function measures in children and adolescents with ASD. Additionally, Prinsen and Alaerts (2025) examined the effects of a single OT dose on interpersonal motor resonance, finding that individual factors influenced outcomes, particularly in those with higher endogenous OT levels. These findings underscore the complexity of OT's effects and the need for personalized approaches in its therapeutic application for social challenges in autism.
Pharmacologic Interventions
As of 2025, two FDA-approved medications for treating irritability associated with autism are risperidone and aripiprazole.
Risperidone (Risperdal) was approved in 2006 for children and adolescents aged 5 to 16, targeting symptoms like aggression and mood swings (BioSpace, 2006). Rossignol (2009) noted its approval and highlighted the prevalence of off-label treatments for autism, with 74% of children using them. Treatments were graded based on evidence, with Grade A treatments including melatonin and naltrexone, and Grade B treatments including oxytocin and vision therapy. The author concluded that while some treatments are supported by research, further studies are needed.
In 2009, aripiprazole (Abilify) was approved for children aged 6 to 17, addressing similar symptoms as risperidone (BMS, 2009). Approval was based on two 8-week trials showing significant improvements in irritability symptoms compared to placebo (Otsuka, 2016).
Brondino et al. (2016) discussed the potential of GABA modulators like valproate and acamprosate for autism but concluded that evidence for their use is insufficient. Williams et al. (2013) conducted a Cochrane review on SSRIs, finding no evidence of effectiveness in children and limited evidence in adults, with some indications of harm. Weissman and Bridgemohan (2014) noted SSRIs as potential treatments for repetitive behaviors but cautioned about increased suicidal ideation in children with depression.
Erickson et al. (2014) evaluated arbaclofen in an open-label study, finding it generally well-tolerated with some improvements in irritability. Joshi et al. (2016) assessed memantine in adults with high-functioning autism, reporting significant reductions in autism severity and associated symptoms. However, Aman et al. (2017) found no significant effectiveness of memantine in children with autism, although safety data were reassuring.
Elnaiem et al. (2022) conducted a systematic review on memantine, finding it did not improve core autism symptoms but showed safety in reducing anxiety. They called for further long-term trials. Additionally, while some research supports folinic acid/Leucovorin for autism, the American Academy of Pediatrics (AAP, 2025) stated that more evidence is needed before broad recommendations can be made.
Physical and Speech Therapy
The American Academy of Pediatrics (AAP) emphasizes the importance of speech and physical therapy in the interdisciplinary management of children with autism spectrum disorder (2001). The National Initiative for Autism: Screening and Assessment (NIASA) (National Autistic Society, 2003) notes that children with co-occurring developmental disorders may require additional therapeutic services, including speech and language therapy for communication, physiotherapy, and occupational therapy for motor coordination and sensory issues. However, there is a lack of high-quality evidence supporting the effectiveness of speech and language therapy for autism, with existing evidence primarily from case reports, small studies, and anecdotal accounts.
Physical therapy for children with ASD 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).
Saliva Analysis Testing
Saliva analysis (e.g., Clarifi ASD, Quadrant Biosciences, Inc.) is considered experimental, investigational, or unproven for evaluating ASD.
Quadrant Biosciences, Inc. offers the 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 a lack of developmental delay controls. Thus, the authors conducted a multi-center cross-sectional study that included 456 children, ages 19-83 months. Children were either neurotypical (n = 134), had a diagnosis of ASD (n = 238), or had 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 from 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 that 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 developmental delay (DD) or typical development (TD). This non-invasive test could augment the accuracy of current ASD assessment, serving as an adjunctive tool for children with positive MCHAT screening or as 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 regarding the nature or extent of these gastrointestinal (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 to characterize the oral and gut microbiotas of patients with ASD compared to neurotypical individuals and to explore the utility of microbiome markers for ASD diagnosis and subtyping of clinical comorbid conditions. Twenty 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 a high false discovery rate (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 years 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 from 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 that 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 non-invasive, identifying ASD status with moderate accuracy. A multi-"omic" approach using additional RNA families could improve accuracy, leading to clinical application.
Sensory Integration Therapy
Sensory Integration Therapy aims to enhance how the brain processes and organizes external stimuli, such as touch and movement. However, the National Autistic Society (NAS) report (2001) concluded that there is insufficient evidence supporting its effectiveness for autism. This therapy focuses on play to improve sensory processing as a foundation for higher-level skills, with the hypothesis that controlled sensory experiences can help the nervous system better integrate environmental information. Despite this, the NAS report noted a lack of empirical research on sensory integration treatments for autism, and the American Academy of Pediatrics (AAP, 2001) echoed that research data supporting its effectiveness is scant.
Sensory integration therapies may also involve the use of weighted blankets, which are claimed to "calm" the nervous system, aiding relaxation and sleep in individuals with autism. It is believed that weighted blankets may promote melatonin release, which is involved in sensory processing. However, evidence for the effectiveness of melatonin in autistic children with sleep disorders is insufficient, and there is a lack of clinical evidence supporting the benefits of weighted blankets for autism or other developmental disorders.
Stephenson and Carter (2009) noted that therapists may recommend weighted vests to address issues like inattentiveness and hyperactivity. Their review of seven studies on weighted vests concluded that, despite methodological weaknesses, the evidence suggests they are ineffective. While further research may be warranted, weighted vests cannot currently be recommended for clinical use.
Serum Cytokine and Growth Factor Levels
Serum cytokine and growth factor levels are considered experimental, investigational, or unproven for evaluating ASD.
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
Tests for single-nucleotide polymorphisms within the oxytocin (OXT) and vasopressin (VP) receptor genes are considered experimental, investigational, or unproven for evaluation of ASD.
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
Tests for glutamatergic candidate genes are considered experimental, investigational, or unproven for evaluating ASD.
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
Olfactory function testing is considered experimental, investigational, or unproven for evaluating ASD.
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.
Transcranial Direct Current Stimulation
Transcranial direct current stimulation is considered experimental, investigational, or unproven for the treatment of ASD.
Kang et al. (2018) investigated the effects of transcranial direct current stimulation (tDCS) on children with autism spectrum disorder (ASD), a heterogeneous neurodevelopmental disorder affecting social communication, cognitive, and language abilities. The study involved 13 ASD children (11 males, 2 females; mean age 6.5 years) who received 10 tDCS treatments over the dorsolateral prefrontal cortex (DLPFC) every two days, compared to a control group of 13 ASD children awaiting therapy. Results showed a significant increase in the maximum entropy ratio (MER) of EEG complexity after tDCS, suggesting its potential benefit in rehabilitating children with ASD. The authors called for further research to explore brain stimulation treatments and their mechanisms using neuroimaging techniques. However, the study had limitations, including the influence of factors like eye movements on resting-state EEG readings, the lack of neuroimaging confirmation for the DLPFC stimulation site, and the absence of sham stimulation in the experiment.
See CPB 0469 - Transcranial Magnetic Stimulation and Cranial Electrical Stimulation.
Use of Biomarkers of Mitochondrial Dysfunction for the Management of ASD
Use of biomarkers of mitochondrial dysfunction are considered experimental, investigational, or unproven 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 and pyruvate levels, as well as 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 antipsychotic and antidepressant 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 more 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 in 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 individuals with ASD. 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 the 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 gastrointestinal (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 prenatal brain development and postnatal 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 comorbidities 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-to-pyruvate ratio, alanine, and CoQ10, showed significantly Luis Furuya-Kanamori (LFK) values, suggesting outlier studies might be contributing to the results and indicating 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 two 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 compared to 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.
Appendix
Documentation and Qualified Providers
For all services, documentation must include a confirmed ASD diagnosis by a qualified and/or licensed provider. Documentation should note an individualized treatment plan with measurable goals, a baseline functional assessment, and ongoing progress notes demonstrating clinical improvement or need for continued care. Additionally, frequency and duration of therapies must be medically necessary and justified by documentation of progress for continued coverage. Of note, services that are primarily educational in nature are not covered under medical benefits, and overall screening, diagnosis, and treatment coverage is subject to the member’s specific benefit plan.
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. In compliance with state and federal laws and regulations, a qualified provider is also clearly defined. A qualified provider is 1) person certified by a national entity (e.g., Behavior Analyst Certification Board) with accredited certification who designs, supervises, or provides treatment for autism within their certified scope and/or 2) a licensed professional such as those listed above that are providing autism services within the scope of their license. Additional training/experience requirements may apply depending on the jurisdiction. A "qualified autism service professional" or other paraprofessional must be supervised by a qualified/licensed provider and have specified educational/training criteria.
National guidelines provide clear examples and expectations of these providers. Primary care physicians (i.e. pediatricians) should screen for ASD using validated tools and refer to clinicians experienced in diagnosis when needed. Qualified clinicians for diagnostic evaluation include those with training and competence in ASD assessment and DSM‑5TR criteria. Professional practice parameters emphasize that diagnostic evaluations should be done by clinicians trained to administer and interpret diagnostic tools and make differential diagnoses (e.g., developmental pediatricians, child psychologists, psychiatrists). Many states require that an ASD diagnosis comes from a licensed physician, licensed clinical psychologist, or other licensed practitioner, and treatment prescribed/ordered by a licensed physician or other licensed professional acting within their scope (e.g., psychologist, SLP, OT). In summary, "Qualified provider" definitions vary by state and by program but commonly require licensure and training within the provider’s scope of practice.
References
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