a research paper about autism

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• Transl Pediatr
• v.9(Suppl 1); 2020 Feb

Autism spectrum disorder: definition, epidemiology, causes, and clinical evaluation

Holly hodges.

1 Department of Pediatrics, Baylor College of Medicine and Meyer Center for Developmental Pediatrics, Texas Children’s Hospital, Houston, TX, USA;

Casey Fealko

2 Western Michigan University Homer Stryker MD School of Medicine, Kalamazoo, MI, USA;

Neelkamal Soares

3 Department of Pediatric and Adolescent Medicine, Western Michigan University Homer Stryker MD School of Medicine, Kalamazoo, MI, USA

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication and the presence of restricted interests and repetitive behaviors. There have been recent concerns about increased prevalence, and this article seeks to elaborate on factors that may influence prevalence rates, including recent changes to the diagnostic criteria. The authors review evidence that ASD is a neurobiological disorder influenced by both genetic and environmental factors affecting the developing brain, and enumerate factors that correlate with ASD risk. Finally, the article describes how clinical evaluation begins with developmental screening, followed by referral for a definitive diagnosis, and provides guidance on screening for comorbid conditions.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication and the presence of restricted interests and repetitive behaviors ( 1 ). In 2013, the Diagnostic and Statistical Manual of Mental Disorders —5 th edition (DSM-5) was published, updating the diagnostic criteria for ASD from the previous 4 th edition (DSM-IV) ( Table 1 ) ( 1 , 2 ).

ASD, autism spectrum disorder; SPCD, social (pragmatic) communication disorder.

In DSM-5, the concept of a “spectrum” ASD diagnosis was created, combining the DSM-IV’s separate pervasive developmental disorder (PDD) diagnoses: autistic disorder, Asperger’s disorder, childhood disintegrative disorder, and pervasive developmental disorder not otherwise specified (PDD-NOS), into one. Rett syndrome is no longer included under ASD in DSM-5 as it is considered a discrete neurological disorder. A separate social (pragmatic) communication disorder (SPCD) was established for those with disabilities in social communication, but lacking repetitive, restricted behaviors. Additionally, severity level descriptors were added to help categorize the level of support needed by an individual with ASD.

This new definition is intended to be more accurate and works toward diagnosing ASD at an earlier age ( 3 ). However, studies estimating the potential impact of moving from the DSM-IV to the DSM-5 have predicted a decrease in ASD prevalence ( 4 , 5 ) and there has been concern that children with a previous PDD-NOS diagnosis would not meet criteria for ASD diagnosis ( 5 - 7 ). There are varying reports estimating the extent of and effects of this change. One study found that with parental report of ASD symptoms alone, the DSM-5 criteria identified 91% of children with clinical DSM-IV PDD diagnoses ( 8 ). However, a systematic review suggests only 50% to 75% of individuals maintain diagnoses ( 9 ) and other studies have also suggested a decreased rate of diagnosis of individuals with ASD under the DSM-5 criteria ( 10 ). Often those who did not meet the requirements were previously classified as high functioning Asperger’s syndrome and PDD-NOS ( 11 , 12 ). Overall, most studies suggest that the DSM-5 provides increased specificity and decreased sensitivity compared to the DSM-IV ( 5 , 13 ); so while those diagnosed with ASD are more likely to have the condition, there is a higher number of children whose ASD diagnosis is missed, particularly older children, adolescents, adults, or those with a former diagnosis of Asperger’s disorder or PDD-NOS ( 14 ). Nevertheless, the number of people who would be diagnosed under the DSM-IV, but not under the new DSM-5 appears to be declining over time, likely due to increased awareness and better documentation of behaviors ( 4 ).

It has yet to be determined how the new diagnosis of SPCD will impact the prevalence of ASD. One study found the new SPCD diagnosis encompasses those individuals who possess subthreshold autistic traits and do not qualify for a diagnosis of ASD, but who still have substantial needs ( 15 ). Furthermore, children who previously met criteria for PDD-NOS under the DSM-IV might now be diagnosed with SPCD.

Epidemiology

The World Health Organization (WHO) estimates the international prevalence of ASD at 0.76%; however, this only accounts for approximately 16% of the global child population ( 16 ). The Centers for Disease Control and Prevention (CDC) estimates about 1.68% of United States (US) children aged 8 years (or 1 in 59 children) are diagnosed with ASD ( 6 , 17 ). In the US, parent-reported ASD diagnoses in 2016 averaged slightly higher at 2.5% ( 18 ). The prevalence of ASD in the US more than doubled between 2000–2002 and 2010–2012 according to Autism and Developmental Disabilities Monitoring Network (ADDM) estimates ( 6 ). Although it may be too early to comment on trends, in the US, the prevalence of ASD has appeared to stabilize with no statistically significant increase from 2014 to 2016 ( 19 ). Changing diagnostic criteria may impact prevalence and the full impact of the DSM-5 diagnostic criteria has yet to be seen ( 17 ).

Insurance mandates requiring commercial plans to cover services for ASD along with improved awareness have likely contributed to the increase in ASD prevalence estimates as well as the increased diagnosis of milder cases of ASD in the US ( 6 , 20 , 21 ). While there was only a modest increase in prevalence immediately after the mandates, there have been additional increases later as health care professionals better understood the regulatory and reimbursement process. The increase in prevalence may also be due to changes in reporting practices. One study in Denmark found the majority of increase in ASD prevalence from 1980–1991 was based on changes of diagnostic criteria and inclusion of outpatient data, rather than a true increase in ASD prevalence ( 21 ).

ASD occurs in all racial, ethnic, and socioeconomic groups, but its diagnosis is far from uniform across these groups. Caucasian children are consistently identified with ASD more often than black or Hispanic children ( 6 ). While the differences appear to be decreasing, the continued discrepancy may be due to stigma, lack of access to healthcare services, and a patient’s primary language being one other than English.

ASD is more common in males ( 22 , 23 ) but in a recent meta-analysis ( 24 ), true male-to-female ratio is closer to 3:1 than the previously reported 4:1, though this study was not done using the DSM-5 criteria. This study also suggested that girls who meet criteria for ASD are at higher risk of not receiving a clinical diagnosis. The female autism phenotype may play a role in girls being misdiagnosed, diagnosed later, or overlooked. Not only are females less likely to present with overt symptoms, they are more likely to mask their social deficits through a process called “camouflaging”, further hindering a timely diagnosis ( 25 ). Likewise, gender biases and stereotypes of ASD as a male disorder could also hamper diagnoses in girls ( 26 ).

Several genetic diagnoses have an increased rate of co-occurring ASD compared to the average population, including fragile X, tuberous sclerosis, Down syndrome, Rett syndrome, among others; however, these known genetic disorders account for a very small amount of overall ASD cases ( 27 - 30 ). Studies of children with sex chromosome aneuploidy describe a specific social functioning profile in males that suggests more vulnerability to autism ( 22 , 23 , 31 , 32 ). With the increased use of chromosomal microarray, several sites (chromosome X, 2, 3, 7, 15, 16, 17, and 22 in particular) have proven to be associated with increased ASD risk ( 28 ).

Other risk factors for ASD include increased parental age and prematurity ( 33 - 35 ). This could be due to the theory that older gametes have a higher probability of carrying mutations which could result in additional obstetrical complications, including prematurity ( 36 ).

ASD is a neurobiological disorder influenced by both genetic and environmental factors affecting the developing brain. Ongoing research continues to deepen our understanding of potential etiologic mechanisms in ASD, but currently no single unifying cause has been elucidated.

Neuropathologic studies are limited, but have revealed differences in cerebellar architecture and connectivity, limbic system abnormalities, and frontal and temporal lobe cortical alterations, along with other subtle malformations ( 28 , 37 , 38 ). A small explorative study of neocortical architecture from young children revealed focal disruption of cortical laminar architecture in the majority of subjects, suggesting problems with cortical layer formation and neuronal differentiation ( 39 ). Brain overgrowth both in terms of cortical size and additionally in terms of increased extra-axial fluid have been described in children with ASD and are areas of ongoing study both in terms of furthering our understanding of its etiology, but also as a potential biomarker ( 40 , 41 ).

Genetic factors play a role in ASD susceptibility, with siblings of patients with ASD carrying an increased risk of diagnosis when compared to population norms, and a much higher, although not absolute, concordance of autism diagnosis in monozygotic twins ( 42 - 44 ).

Genome wide association studies and whole exome sequencing methods have broadened our understanding of ASD susceptibility genes, and learning more regarding the function of these genes can shed light on potential biologic mechanisms ( 45 ). For example candidate genes in ASD include those that play a role in brain development or neurotransmitter function, or genes that affect neuronal excitability ( 46 , 47 ). Many of the genetic defects associated with ASD encode proteins that are relevant at the neuronal synapse or that are involved in activity-dependent changes in neurons, including regulatory proteins such as transcription factors ( 42 , 48 ). Potential “networks” of ASD genetic risk convergence include pathways involved in neurotransmission and neuroinflammation ( 49 ). Transcriptional and splicing dysregulation or alterations in epigenetic mechanisms such as DNA methylation or histone acetylation and modification may play a role ( 42 , 49 - 51 ). A recent study describes 16 newly identified genes associated with ASD that raise new potential mechanisms including cellular cytoskeletal structure and ion transport ( 52 ). Ultimately, ASD remains one of the most genetically heterogeneous neuropsychiatric disorders with rarer de novo and inherited variants in over 700 genes ( 53 ).

While genetics clearly play a role in ASD’s etiology, phenotypic expression of genetic susceptibility remains extremely variable within ASD ( 54 ). Genetic risk may be modulated by prenatal, perinatal, and postnatal environmental factors in some patients ( 35 ). Prenatal exposure to thalidomide and valproic acid have been reported to increase risk, while studies suggest that prenatal supplements of folic acid in patients exposed to antiepileptic drugs may reduce risk ( 55 - 57 ). Research has not confirmed if a small positive trial of folinic acid in autism can be used to recommend supplementation more broadly ( 58 ). Advanced maternal and paternal age have both been shown to have an increased risk of having a child with ASD ( 59 ). Maternal history of autoimmune disease, such as diabetes, thyroid disease, or psoriasis has been postulated, but study results remain mixed ( 60 , 61 ). Maternal infection or immune activation during pregnancy is another area of interest and may be a potential risk factor according to recent investigations ( 62 - 65 ). Both shorter and longer inter-pregnancy intervals have also been reported to increase ASD risk ( 66 ). Infants born prematurely have been demonstrated to carry a higher risk for ASD in addition to other neurodevelopmental disorders ( 34 ). In a prior epidemiologic review, obstetric factors including uterine bleeding, caesarian delivery, low birthweight, preterm delivery, and low Apgar scores were reported to be the few factors more consistently associated with autism ( 67 ). A recent meta-analysis reported several pre, peri and postnatal risk factors that resulted in an elevated relative risk of ASD in offspring ( 35 ), but also revealed significant heterogeneity, resulting in an inability to make true determination regarding the importance of these factors.

Despite the hysteria surrounding the now retracted Lancet article first published in 1998, there is no evidence that vaccines, thimerosal, or mercury is associated with ASD ( 68 - 70 ). In the largest single study to date, there was not an increased risk after measles/mumps/rubella (MMR) vaccination in a nationwide cohort study of Danish children ( 70 ).

Ultimately, research continues to reveal factors that correlate with ASD risk, but no causal determinations have been made. This leaves much room for discovery with investigators continuing to elucidate new variants conveying genetic risk, or new environmental correlates that require further study ( 52 ).

Evaluation in ASD begins with screening of the general pediatric population to identify children at-risk or demonstrating signs suggestive of ASD, following which a diagnostic evaluation is recommended. The American Academy of Pediatrics (AAP) guidelines recommend developmental surveillance at 9, 15 and 30 months well child visits and autism specific screening at 18 months and again at 24 or 30 months ( 28 , 71 ). Early red flags for ASD include poor eye contact, poor response to name, lack of showing and sharing, no gesturing by 12 months, and loss of language or social skills. Screening tools for ASD in this population include the Modified Checklist for Autism in Toddlers, Revised, with Follow-up (M-CHAT-R/F) and Survey of Wellbeing of Young Children (SWYC) ( 72 , 73 ). Red flags in preschoolers may include limited pretend play, odd or intensely focused interests, and rigidity. School age children may demonstrate concrete or literal thinking, have trouble understanding emotions, and may even show an interest in peers but lack conversational skills or appropriate social approach. If there is suspicion of ASD in these groups, screening tools available include the Social Communication Questionnaire (SCQ), Social Responsiveness Scale (SRS), and Autism Spectrum Screening Questionnaire (ASSQ) ( 74 - 76 ).

If concerns are raised at screening, primary care clinicians are recommended to refer the child to early intervention if less than 3 years of age or to the public school system for psychoeducational evaluation in order to establish an individual education program (IEP) if the child is three years of age or older. Clinicians should additionally refer the child to a specialist (pediatric neurologist, developmental-behavioral pediatrician, child psychiatrist, licensed child psychologist) for a definitive diagnosis and comprehensive assessment ( 71 ). A comprehensive assessment should include a complete physical exam, including assessment for dysmorphic features, a full neurologic examination with head circumference, and a Wood’s lamp examination of the skin. A parent interview, collection of any outside informant observations, and a direct clinician observation of the child’s current cognitive, language, and adaptive functioning by a clinician experienced with ASD should be components of this comprehensive assessment. ( 28 , 71 , 77 , 78 ).

Additionally, primary care clinicians need to be aware of (and evaluate for) potential co-occurring conditions in children with ASD. According to a surveillance study of over 2,000 children with ASD, 83% had an additional developmental diagnosis, 10% had at least one psychiatric diagnosis, and 16% at least one neurologic diagnosis ( 79 ). In the past, rates of co-morbid intellectual disability (ID) in patients with ASD were reported from 50% to 70%, with the most recent CDC estimate reported at 31.0% (26.7% to 39.4%) with ID defined as intelligence quotient (IQ) ≤70 ( 6 , 80 ). Other common co-occurring medical conditions include gastrointestinal (GI) disorders, including dietary restrictions and food selectivity, sleep disorders, obesity, and seizures ( 81 - 84 ). Studies using electronic health record (EHR) analysis revealed prevalence of epilepsy ~20% and GI disorders [without inflammatory bowel disease (IBD)] at 10–12% ( 82 ). Epilepsy has been shown to have higher prevalence rates in ASD with comorbid ID and medical disorders of increased risk such as tuberous sclerosis complex (TSC) ( 85 - 87 ). GI disorders or GI symptomatology, including diarrhea, constipation, restrictive eating, or reflux, have been shown to be prominent in ASD across multiple studies ( 81 , 82 , 88 , 89 ). Sleep problems have been reported to occur in anywhere from 50% to 73% of patients with ASD with variation in prevalence dependent on the definition of sleep symptoms or the measurement tool used ( 90 - 92 ). Rates of overweight and obesity in ASD are reported to be roughly 33% and 18% respectively, higher than rates in typically developing children ( 81 - 84 , 93 ).

Other behavioral or psychiatric co-occurring conditions in ASD include anxiety, attention deficit/hyperactivity disorder (ADHD), obsessive compulsive disorder, and mood disorders or other disruptive behavior disorders ( 81 ). Rates of co-occurring ADHD are reported anywhere from 25% to 81% ( 81 , 94 ). A recent meta-analysis of 30 studies measuring rates of anxiety and 29 studies measuring rates of depression reported a high degree of heterogeneity from the current literature, but stated pooled lifetime prevalence for adults with ASD to be 42% for any anxiety disorder and 37% for any depressive disorder, though the use of self-report measures and the presence of ID could influence estimates ( 95 ). In children with ASD seeking treatment, the rate of any anxiety disorder was found to be similar at 42% and in addition this study reported co-morbid oppositional defiant disorder at a rate of 46% and mood disorders at 8%, with 66% of the sample of over 600 patients having more than one co-occurring condition ( 94 ).

Currently no clear ASD biomarkers or diagnostic measures exist, and the diagnosis is made based on fulfillment of descriptive criteria. In light of a relatively high yield in patients with ASD, clinical genetic testing is recommended and can provide information regarding medical interventions or work up that might be necessary and help with family planning ( 96 ). The American College of Medical Genetics and Genomics (ACMGG) guidelines currently recommend chromosomal microarray for all children, fragile X testing in males, and additional gene sequencing, including PTEN and MECP2 , in certain patients as first tier genetic testing in the work up of ASD ( 97 ). High resolution G-banded karyotype, once recommended for all patients with ASD, is no longer routinely indicated based on recent consensus recommendations, but might still be performed in patients with a family or reproductive history suggestive of chromosomal rearrangements or specific syndromes such as sex chromosome anomalies or Trisomy 21 ( 96 - 98 ). Several professional societies recommend genetic testing for ASD, including the American Academy of Neurology, the AAP, ACMGG, and the American Academy of Child and Adolescent Psychiatry, and a child may require further referral to a geneticist and/or genetic counselor, depending on results of testing ( 25 , 28 , 97 , 99 ). As the field of genetics continues to advance rapidly, recent publications suggest whole exome sequencing may become the preferred method for clinical genetic testing in individuals with ASD ( 100 , 101 ).

Aside from genetic testing, no other laboratory work up is routinely recommended for every patient with a diagnosis of ASD. However, further evaluation may be appropriate for patients with particular findings or risk factors. Metabolic work-up should be considered in patients with any of the following concerning symptoms or signs: a history of clear developmental regression including loss or plateau of motor skills; hypotonia; recurrent episodes of vomiting, lethargy or hypoglycemia; microcephaly or poor growth; concern for other organ involvement; coarse features; or concern for seizures or ataxia. Based on the patient’s history and presentation, components of a metabolic laboratory evaluation could include complete blood count (CBC), liver and renal function tests, lactate, pyruvate, carnitine, amino acids, an acylcarnitine profile, urine organic acids and/or urine glycosaminoglycans ( 97 , 102 ). Children with a history of pica should have a lead level measured ( 28 , 103 ). In a child with significantly restricted food intake, one should consider a laboratory evaluation of nutritional status. Sleep symptoms may warrant a referral for a possible sleep study, and if restless sleep symptoms are present, an evaluation for iron deficiency is not unreasonable, particularly if dietary rigidity limits iron intake ( 104 ).

Neuroimaging is not routinely recommended for every patient with ASD ( 28 , 99 ), but may be appropriate in patients with a suspicion for TSC or other neurocutaneous disorders, microcephaly, or an abnormal neurologic exam (spasticity, severe hypotonia, unilateral findings). Patients with suspected seizures should have an electroencephalography (EEG) obtained ( 102 ). If accessible, it might be appropriate to immediately refer children with concern for further genetic, metabolic or neurologic conditions to a specialist who can then obtain and interpret the aforementioned testing. At this time there is inadequate evidence to recommend routine testing for celiac disease, immunologic or neurochemical markers, mitochondrial disorders, allergy testing, hair analysis, intestinal permeability studies, erythrocyte glutathione peroxidase studies, stool analysis, urinary peptides or vitamin and mineral deficiencies without a history of severe food selectivity.

ASD is a neurodevelopmental disorder characterized by deficits in social communication and the presence of restricted interests and repetitive behaviors. Recent changes to the diagnostic criteria occurred with the transition to the new diagnostic manual (DSM-5) and will likely impact prevalence, which currently stands at 1 in 59 children in the US. ASD is a neurobiological disorder influenced by both genetic and environmental factors affecting the developing brain. Research continues to reveal factors that correlate with ASD risk and these findings may guide further etiologic investigation, but no final causal pathway has been elucidated. Clinical evaluation begins with developmental screening of the general pediatric population to identify at-risk children, followed by referral to a specialist for a definitive diagnosis and comprehensive neuropsychological assessment. Children with ASD should also be screened for common co-morbid diagnoses. While no clear biomarkers or diagnostic measures exist, clinical genetic testing is recommended as part of the initial medical evaluation. Further medical work up or subspecialist referrals may be pursued based on specific patient characteristics.

Acknowledgments

Funding: None.

Ethical Statement : The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Conflicts of Interest : The authors have no conflicts of interest to declare.

ORIGINAL RESEARCH article

Autism spectrum disorder research: knowledge mapping of progress and focus between 2011 and 2022.

• 1 National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
• 2 Translational Medicine Center of Chinese Institute for Brain Research, Beijing, China
• 3 Guangdong Key Laboratory of Mental Health and Cognitive Science, Institute for Brain Research and Rehabilitation (IBRR), South China Normal University, Guangzhou, China

Background: In recent years, a large number of studies have focused on autism spectrum disorder (ASD). The present study used bibliometric analysis to describe the state of ASD research over the past decade and identify its trends and research fronts.

Methods: Studies on ASD published from 2011 to 2022 were obtained from the Web of Science Core Collection (WoSCC). Bibliometrix, CiteSpace, and VOSviewer were used for bibliometric analysis.

Results: A total of 57,108 studies were included in the systematic search, and articles were published in more than 6,000 journals. The number of publications increased by 181.7% (2,623 in 2011 and 7,390 in 2021). The articles in the field of genetics are widely cited in immunology, clinical research, and psychological research. Keywords co-occurrence analysis revealed that “causative mechanisms,” “clinical features,” and “intervention features” were the three main clusters of ASD research. Over the past decade, genetic variants associated with ASD have gained increasing attention, and immune dysbiosis and gut microbiota are the new development frontiers after 2015.

Conclusion: This study uses a bibliometric approach to visualize and quantitatively describe autism research over the last decade. Neuroscience, genetics, brain imaging studies, and gut microbiome studies improve our understanding of autism. In addition, the microbe-gut-brain axis may be an exciting research direction for ASD in the future. Therefore, through visual analysis of autism literature, this paper shows the development process, research hotspots, and cutting-edge trends in this field to provide theoretical reference for the development of autism in the future.

Introduction

Autism spectrum disorder (ASD) refers to a group of early-onset, lifelong, heterogeneous neurodevelopmental conditions with complex mechanisms of emergence ( 1 ). The prevalence of ASD has increased from 1 in 69 by 2012 to 1 in 44 by 2018, as reported by the Centers for Disease Control and Prevention for 2012–2018 ( 2 , 3 ). Recent research estimates the male-to-female ratio is closer to 2:1 or 3:1, indicating a higher diagnostic prevalence of autism in males compared to females ( 4 – 6 ). Some studies have shown a high heritability of 80–93% in ASD and reported hundreds of risk gene loci ( 7 ).

Specific autistic characteristics usually appear before the age of 3 years, and some children on the spectrum may have limited nonverbal and verbal communication by the age of 18–24 months ( 8 , 9 ). The diagnosis of ASD is based on the core features of social communication impairment and unusual and repetitive sensory-motor behavior ( 10 ). Some autistic individuals can be definitively diagnosed with autism as early as 2–3 years of age and the mean age of diagnosis for autistic children is still 4–5 years ( 1 , 11 ). It is important to stress that more adults are getting assessed for possible autism ( 5 ). As autism is increasingly diagnosed, multidisciplinary involvement can help have a positive impact on the well-being and quality of life for both children and adults on the spectrum ( 12 ). Several mental diseases also affect autistic individuals, increasing the diagnosis complexity ( 13 ).

Over the past decade, researchers have struggled to explain the neurological etiology, and great progress has been made in the genetics, epigenetics, neuropathology, and neuroimaging of ASD ( 9 ). However, there is a lack of systematic review of field research and discussion of future research hotspots. Bibliometrics ( 14 ) belongs to interdisciplinary research, which has been widely used in science by analyzing highly cited papers, field keyword clustering, and the internal cooperation links of countries, thus providing a comprehensive interpretation of the development process of autism research field ( 15 ).

In some of the previous bibliometrics studies on ASD, a single software was used to focus on a specific field or research aspect of the autism ( 16 – 18 ), and the trend in the past decade has not yet been displayed. The present study comprehensively combines Bibliometrix package, CiteSpace, and VOSviewer to (1) dynamically assess quantitative indicators of ASD research publications and use different index indicators to measure the quality of research; (2) further identify the most contributing countries, institutions, journals, and authors; (3) analyze the citation network architecture; (4) determine the top 100 most cited papers; (5) conduct keyword analysis. Subsequently, bibliometrics was used to understand the current hotspots and trends in the field of ASD research for further in-depth investigation.

Materials and methods

Data collection and search strategies.

We comprehensively searched the Web of Science Core Collection (WoSCC) database from 2011 to 2022. WoSCC is a daily updated database covering an abstract index of multidisciplinary literature that exports complete citation data, maintained by Thomson Reuters (New York, NY, USA) ( 19 ). The articles’ data were independently searched by two researchers on May 29, 2022, to avoid bias caused by database updates. The scientometric retrieval process is illustrated in Figure 1 . A total of 68,769 original articles in English language were retrieved, excluding 11,661 irrelevant articles, such as meeting abstracts, editorial materials, corrections, and letters. A total of 57,108 documents were exported, and the retrieved documents would be exported in the form of all records and references.

Figure 1 . Flowchart of the screening process.

Grey prediction model

Grey models (GM) are used to construct differential prediction models with limited and incomplete data ( 20 ). The GM (1,1) model, with high accuracy and convenient calculations, is extensively utilized in the energy and medical industries ( 21 ). We used the standard GM (1,1) model to forecast the annual publication volume over the next 5 years. The operation of GM (1,1) model was done by using Python software.

Bibliometric analysis and visualization

The records of the retrieved publications were exported to Bibliometrix, CiteSpace, and VOSviewer for further bibliometric analysis.

Bibliometrix package (running on R4.0.3) was utilized to capture and extract the bibliographic information on selected publications, including topic, author, keywords, and country distribution ( 22 ). The productivity of authors/journals in the field was measured by the number of publications (Np) and assessing metrics, such as the number of citations, publication h-index value, and m-index value. The h-index is used to quantify the scientific output and measure the citation impact, and two people with similar h-index may have a similar impact in the scientific field, even if the total number of papers or total citations are different ( 23 ). The m-index can be used to compare the influence of scholars with different academic career years. The number of citations of a document is a measure of its scientific impact to a certain extent ( 24 ). Bibliometrix package was also used to screen the top 100 articles and explore research trends and hotspots.

VOSviewer is a free computer program to visualize bibliometric maps ( 25 ). The keyword co-occurrence network was constructed using VOSviewer. CiteSpace is based on the Java environment and uses methods, such as co-occurrence analysis and cluster analysis, for the visualization of scientific literature research data in specific disciplines. The visual knowledge maps were constructed using the procedural steps of CiteSpace ( 26 ), including time slicing, threshold, pruning, merging, and mapping; then, the contribution of countries and institutions of ASD over the past decade was assessed based on centrality scores. The co-citation network and dual-map of references were constructed by CiteSpace. A dual-map ( 27 ) overlay is a bipartite overlay analysis method by CiteSspace, which uses the distribution map cited journals in the WoS database as the base map, and the map generated by the cited literature data as the overlay map.

Annual publications

A total of 57,108 articles were included in this study, consisting of 46,574 articles, 2,643 conference papers, and 7,891 reviews. From 2011 to 2022, the number of publications maintained a steady growth rate ( Figure 2A ), and the grey prediction model predicted the trend of increasing publication volume in the next 5 years ( Figure 2B ). The main information for all publications is shown in Supplementary Table S1 .

Figure 2 . Global trends in publications of ASD research. (A) Single-year publication output over the past decade. (B) Model forecast curves for publication growth trends.

Distribution of countries and institutions

Autism-related research has been conducted by researchers from a variety of countries and institutions, and articles in this field have been cited 1,231,588 times ( Tables 1 , 2 ). CiteSpace visualizes collaborative networks between institutions and countries ( Figures 3A , B ). As shown in the international collaborations network of autism research ( Figure 3C ), the USA and UK are the leading countries working closely with other countries.

Table 1 . Publications in top 10 most productive countries.

Table 2 . Publications in top 10 most productive Institutions.

Figure 3 . The distribution of countries and institutions. Map of countries (A) and institutions (B) contributed to publications related to ASD research. (C) Network diagram showing international collaborations involved in ASD research. The nodes represent the countries and institutions; the color depth and size of the circle are positively correlated to the number of posts. The thickness of the curved connecting lines represents the strength of collaboration in the countries and institutions.

Analysis of journals

The h-index combines productivity and impact; typically, a high h-index means a high recognition. As presented in Table 3 , the Journal of Autism and Developmental Disorders, PLOS One, and Molecular Psychiatry were among the top three of the 20 journals with the highest h-index. The Journal of Autism and Developmental Disorders has the highest number of articles (3478) and cited number of publications (90308). Among the top 20, four journals with impact factors >10 include Molecular Psychiatry (IF: 13.437), Biological Psychiatry (IF: 12.810), Proceedings of the National Academy of Sciences of the United States of America (IF: 12.779), Journal of the American Academy of Child and Adolescent Psychiatry (IF: 13.113), which have been cited more than 10,000 times. In addition, 75% of journals belong to Q1 ( Table 3 ). The cited journals provided the knowledge base of the citing journals. The yellow paths illustrate that studies published in “molecular, biology, immunology” journals tended to cite journals primarily in the domains of “molecular, biology, genetics,” and “psychology, education, social.” The paths colored with grass-green paths illustrate that studies published in “medicine, medical, clinical” journals tended to cite journals primarily in the domains of “molecular, biology, and genetics.” The pale blue paths showcase that research published in “psychology, education, health” journals preferred to quote journals mostly in the domains of “molecular, biology, genetics,” “health, nursing, medicine,” and “psychology, education, social ( Figure 4 ).”

Table 3 . Top 20 journals ranked by h_index.

Figure 4 . A dual-map overlay of journals that published work related to ASD. A presentation of citation paths at a disciplinary level on a dual-map overlay. The width of the paths is proportional to the z-score-scale citation frequency. The labels on the map represent the research subjects covered by the journals, and the wavy curve connects the citing articles on the left side of the map and the cited articles on the right side of the map.

Analysis of authors

The top 10 most effective authors who have contributed to autism research are listed in Table 4 . The g-index and m-index are derivatives of the h-index, and if scientists publish at least 10 articles, of which 7 papers have been cited cumulatively 51 (>49), the g-index is 7; the m-index is related to the academic age of the scientists. The large g-index, h-index, and m-index indicate a great influence on the scholar’s academic influence and high academic achievement. Professor Catherine Lord from the USA is ranked first and has made outstanding contributions to autism research over the past 10 years. In terms of the number of publications, Simon Baron-Cohen was the most productive author ( n  = 278), followed by Tony Charman ( n  = 212) and Christopher Gillberg ( n  = 206). In terms of citations in this field, Daniel H. Geschwind was ranked first (18,127 citations), followed by Catherine Lord (14,830 citations) and Joseph D. Buxbaum (14,528 citations).

Table 4 . Top 10 most effective authors contributing to autism research.

Analysis of reference

The co-citation analysis network of 1,056,125 references ( Figure 5A ) showed that two articles appear simultaneously in the bibliography of the third cited document. The top 20 co-cited references (over the past decade) summarized in ASD studies are listed in Supplementary Table S2 . Most of this highly cited literature focuses on the genetic field, discovering genetic risk loci and associated mutations, constructing mutation networks highly associated with autism, and identifying genes associated with autism synaptic destruction. Some studies indicated that de novo mutations in ASD might partially explain the etiology. Multiple studies have revealed genetic variants associated with ASD, such as rare copy number variants (CNVs), de novo likely gene-disrupting (LGD) mutations, missense or nonsense de novo variants, and de novo duplications. In the cluster network graph, different colors represent varied clusters, and each node represents a cited paper, displaying the distribution of topics in the field ( Figure 5B ). The network is divided into 25 co-citation clusters ( Figure 5B ), primarily related to the diagnosis, etiology, and intervention of autism. The etiological studies include five clusters, de novo mutation, inflammation, gut microbiota, mitochondrial dysfunction, and mouse model. Intervention literature focuses on early intensive behavioral intervention, intranasal oxytocin, video modeling, and multisensory integration. The diagnostic aspects of ASD include neuroimaging functional connectivity and Diagnostic and Statistical Manual of Mental Disorders (DSM-5). In addition, some of the references focus on gender/sex differences and sleep problems. Coronavirus disease 2019 (COVID-19) is a new cluster for autism research.

Figure 5 . Mapping on co-cited references. (A) A network map showing the co-cited references. (B) Co-cited clusters with cluster labels.

Co-occurrence analysis of keywords

The co-occurrence analysis of keywords in ASD research articles was performed using VOSviewer software; the keywords that occurred ≥200 times were analyzed after being grouped into four clusters of different colors ( Figure 6A ); the temporal distribution of keywords is summarized in Figure 6B . This map identifies various categories of research: Etiological mechanisms (red), Clinical features (green), Intervention features (blue), and the Asperger cluster (yellow). In the “Etiological mechanisms” cluster, the research includes brain structure and function, genetics, and neuropathology. In the “Clinical features” cluster, the common keywords were “symptoms,” “diagnosis,” “prevalence,” and its comorbidities, including “anxiety” and “sleep.” In the “Intervention features” cluster, the research population of ASD is concentrated in “young children,” “intervention,” and “communication.” These interventions improve the learning and social skills through the involvement of parents and schools.

Figure 6 . Keywords co-occurrence network. (A) Cluster analysis of keywords. There are four clusters of keywords: red indicates Cluster 1 ( n  = 145), green indicates Cluster 2 ( n  = 104), blue indicates Cluster 3 ( n  = 78), yellow indicates Cluster 4 ( n  = 80). (B) Evolution of keyword frequency. A minimum number of occurrences of a keyword = 200. Overall, 407 keywords met the threshold criteria. The yellow keywords appear later than purple keywords.

The 100 top-cited publications

The screening of the 100 most cited publications on ASD between 2011 and 2022 by Bibliometrix software package, each with >500 citations. The detailed evaluation index information for countries, institutions, journals, and authors ( Supplementary Tables S3 – S6 ).

Taken together, the results indicated that the United States is the country that publishes the most highly cited articles ( n  = 64), including single-country publications ( n  = 37) and multiple-country publications ( n  = 27); most articles are from academic institutions within the USA ( Figures 7A , B ).

Figure 7 . Analysis of the 100 top-cited publications Characteristics of 100 top-cited publications. The most relevant countries (A) , affiliations (B) , journals (C) and authors (D) . Trend topics (E) and thematic evolution (F) of 100 top-cited publication. Coupling Map (G) : the coupled analysis of the article, references and keywords is carried out, the centrality of the x -axis is displayed, the y -axis is the impact, and the confidence (conf%) is calculated.

The 100 top-cited ASD publications were published in 48 journals; 17 articles were published in Nature ( n  = 17), making it the highest h-index journal in this list ( Supplementary Table S5 ). In addition, 10 articles were published in Cell, and 7 articles were published in Nature Genetics ( Figure 7C ). When considering the individual authors’ academic contributions, Bernie Devlin provided 13 publications, followed by Kathryn Roeder and Stephan J Sanders, with 11 publications each ( Figure 7D ). The details of the top 10 top-cited papers are summarized in Table 5 . An article titled “A general framework for estimating the relative pathogenicity of human genetic variants” published by Martin Kircher in Nature Genetics, received the highest number of citations ( n  = 3,353).

Table 5 . Detail of top 10 citation paper.

The 100 top-cited ASD articles encompassed a range of keywords ( Figure 7E ) and displayed the main cluster of themes through specific periods (2011–2022) by analyzing those in the selected literature. The Sankey diagrams of thematic evolution explain the topics that evolved throughout the years ( Figure 7F ). In summary, the core topics of the ASD field in 2011–2014 consisted of the risk of childhood ASD and further developed into the field of human genetic variants, such as CNV and de novo mutations. In the subperiod 2015–2020, the further expansion of studies in this field leads to new clusters, such as “immune system,” “brain development,” and “fecal microbiota.” Genome research in the upper right quadrant, including mutations and risk, is a major and evolving theme. The coupled map showing the brain-gut axis field, including intestinal microbiota and chain fatty acids, located in the lower right corner is crucial for autism research but is not yet well-developed ( Figure 7G ). The research on autism, including animal models, schizophrenia, is a well-developed field, but that on high-functioning autism and diagnosis is a marginal field.

This study used various bibliometric tools and software to analyze the published articles on ASD based on the WoSCC database from 2011 to 2022. By 2022, the annual number of publications and citations of ASD-related research showed an overall upward trend, reflecting the sustained interest and the diversity of areas.

General information

In terms of regional distribution, researchers from different countries and regions have participated in autism research, and international cooperation has been relatively close over the past decade. The scientific research is supported by several countries and institutions, as well as by large-scale international cooperation ( 28 , 29 ). The USA has the highest collaboration performance, especially with UK, Canada, Australia and China. In addition to the limitations of financial aid, ethical, cultural, and racial issues are complex constraints that should be overcome for more diversity in autism research ( 30 , 31 ). We speculated that further collaboration between institutions and countries could promote autism research.

Among the top 20 academic journals, most of the papers were in the Journal of Autism and Developmental Disorders. The frequent publishing of ASD-related papers indicates the interest of readers and journal editors in Autism. Also, substantial studies have been carried out on ASDs, autism, and molecular autism. These journals are ascribed to the field of ASD, focusing on autism research and communication ASD science. However, the analysis of the 10 most cited publications revealed that they were published in such as Nature, Cell, Lancet; these ASD studies were all from high-impact journals.

From the perspective of authors, some of them have made outstanding contributions to global ASD research. Professor Catherine Lord, the top rank for h-index, m-index analysis conducted by the author, and who developed the two gold standards for autism diagnosis ( 32 , 33 ), are the most influencing factors in the field. ASD is a disease with complex genetic roots. Dr. Catherine Lord has conducted multiple studies using genome-wide association study (GWAS) and gene set analysis to identify variant signatures in autism ( 34 ). A recent meta-analysis showed that 74–93% of ASD risk is heritable, with an analysis of CNVs that highlights the key role of rare and de novo mutations in the etiology of ASD ( 35 ). Variation-affected gene clusters on networks associated with synaptic transmission, neuronal development, and chromatin regulation ( 36 , 37 ). The identification of the cross-disorder genetic risk factors found by assessing SNP heritability in five psychiatric disorders ( 38 ). Five of the top 10 cited papers in Table 5 focus on genetic variation, suggesting that over the past decade, research has shifted from a general concept of genetic risk to the different types of genetic variations associated with autism.

Simon Baron-Cohen of the Autism Research Center at the University of Cambridge was the most published author between 2011 and 2021. He contributed to the mind-blindness hypothesis of autism, developed the autism spectrum quotient (AQ) screening tool for autism, and focused on gender differences in autism ( 39 – 41 ). There are gender/sex differences in the volume and tissue density of brain regions, including the amygdala, hippocampus, and insula, and the heart-blind hypothesis links emotional recognition in individuals with autism to deficits in the amygdala ( 41 – 43 ). Then, Simon et al. backed up the “extreme male brain” theory of autism in a study of 36,000 autistic individuals aged 16–89 ( 44 ). Recently, an increasing number of studies from different perspectives have focused on how sex/gender differences are related to autism ( 4 , 5 , 45 ). In the future, studies of neural dimorphism in brain development in autism need to be conducted across the lifespan to reduce age-induced biases ( 41 ).

Hotspots and Frontiers

Keyword analysis was a major indicator for research trends and hotspot analysis. This study shows that keywords for autism research include etiological mechanism, clinical characteristics, and intervention characteristics. Genetic, environmental, epigenetic, brain structure, neuropathological, and immunological factors have contributed to studying its etiological mechanism ( 46 , 47 ). The studies on the abnormal cortical development in ASD have reported early brain overgrowth ( 48 ), reduced resting cerebral blood flow in the medial PFC and anterior cingulate ( 49 ), focal disruption of neuronal migration ( 50 ), and transcriptomic alterations in the cerebral cortex of autism ( 51 ). Genomics studies have identified several variants and genes that increase susceptibility to autism, affecting biological pathways related to chromatin remodeling, regulation of neuronal function, and synaptic development ( 51 – 54 ). In addition, many autism-related genes are enriched in cortical glutamatergic neurons, and mutations in the genes encoding these proteins result in neuronal excitation-inhibitory balance ( 51 , 55 ). A recent study using single-cell sequencing of the developing human cerebral cortex found strong cell-type-specific enrichment of noncoding mutations in ASD ( 56 ). Interestingly, genes interact with the environment; some studies have shown that environmental exposure during pregnancy is a risk factor for brain development ( 57 ), and there are changes in DNA methylation in the brains of ASD patients, reflecting an underlying epigenetic dysregulation.

Presently, the diagnosis of ASD is mainly based on symptoms and behaviors, but the disease has a high clinical heterogeneity, and the individual differences between patients are obvious ( 58 ). In this study, the keywords of the intervention cluster show the importance of early individualized intervention. Patient data are multidimensional, and individualized diagnoses could be made at multiple levels, such as age, gender, clinical characteristics, and genetic characteristics ( 59 ). Early individual genetic diagnosis aids clinical evaluation, ranging from chromosomal microarray (CMA) to fragile X genetic testing ( 60 ). However, the results of genetic research cannot guide the treatment. Notably, the treatment of autism is dominated by educational practices and behavioral interventions ( 61 ). Medication may address other co-occurring conditions, such as sleep disturbances, epilepsy, and gastrointestinal dysfunction ( 9 ). Professor Catherine Lord pointed out that the future of autism requires coordinated, large-scale research to develop affordable, individualized, staged assessments and interventions for people with ASD ( 62 ). Professor Baron-Cohen noted that increasing the sample size and collecting data from the same individual multiple times could reduce heterogeneity ( 58 ). In addition, screening for objective and valid biomarkers in the future would help to stratify diagnosis and reduce heterogeneity.

According to the keyword trend analysis of 100 highly cited documents, the genetic risk of autism was determined as the hot focus of research, and immune dysregulation and gut microbiome are the new development frontiers after 2015. Patients with ASD have altered immune function, microglia activation was observed in postmortem brain samples, and increased production of inflammatory cytokines and chemokines was observed in cerebrospinal fluid. The microglia are involved in synaptic pruning, and cytokines also affect neuronal migration and axonal projections ( 63 – 65 ). In addition, abnormal peripheral immune responses during pregnancy might affect the developing brain, increasing likelihood of autism ( 66 ). Several studies have pointed to abnormalities in immune-related genes in the brain and peripheral blood of autistic patients ( 51 , 67 , 68 ). Immune dysfunction is involved in the etiology of ASD and mediates the accompanying symptoms of autism. The patients have multiple immune-related diseases, asthma, allergic rhinitis, Crohn’s disease, and gastrointestinal dysfunction ( 69 – 71 ). Children with frequent gastrointestinal symptoms, such as abdominal pain, gas, constipation, or diarrhea, had pronounced social withdrawal and stereotyped behavior ( 70 – 72 ). Several studies suggested that these autism-related gastrointestinal problems might be related to intestinal microbiota composition ( 72 – 74 ). Accumulating evidence suggested that the microbiota-gut-brain axis influences human neurodevelopment, a complex system involving immune, metabolic, and vagal pathways in which bacterial metabolites directly affect the brain by disrupting the gut and blood–brain barrier ( 75 – 78 ). Fecal samples from children with autism contained high Clostridium species and low Bifidobacterium species ( 79 , 80 ). Probiotics can modulate gut microbiota structure and increase the relative abundance of Bifidobacteria , and clinical studies have shown that supplementation with probiotic strains improves attention problems in children with autism ( 81 , 82 ). Recent clinical trials have shown that microbiota transfer therapy improves gastrointestinal symptoms and autism-like behaviors in children with ASD ( 83 , 84 ).

This scientometric study comprehensively analyzes about a decade of global autism research. Research in the field of autism is increasing, with the United States making outstanding contributions, while neuroscience, genetics, brain imaging studies, or studies of the gut microbiome deepen our understanding of the disorder. The study of the brain-gut axis elucidates the mechanism of immunology in autism, and immunological research may be in the renaissance. The current data serve as a valuable resource for studying ASD. However, the future of autism needs further development. In the future, relevant research should be included for a complete representation of the entire autism population, and further collaboration between individuals, institutions, and countries is expected to accelerate the development of autism research.

Data availability statement

The original contributions presented in the study are included in the article/ Supplementary material , further inquiries can be directed to the corresponding authors.

Author contributions

MJ, DZ, JL, and LW conceived and designed the study. MJ, TL, XL, KY, and LZ contributed to data collection and data analysis. MJ wrote the original manuscript. DZ, JL, and LW revised the article and contributed to the final version of the manuscript. All authors contributed to the article and approved the submitted version.

This work was supported by grants from the Key-Area Research and Development Program of Guangdong Province (2019B030335001) and the National Natural Science Foundation of China (grant numbers 82171537, 81971283, 82071541, and 81730037).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1096769/full#supplementary-material

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Keywords: autism spectrum disorder, bibliometric study, CiteSpace, VOSviewer, research frontiers

Citation: Jiang M, Lu T, Yang K, Li X, Zhao L, Zhang D, Li J and Wang L (2023) Autism spectrum disorder research: knowledge mapping of progress and focus between 2011 and 2022. Front. Psychiatry . 14:1096769. doi: 10.3389/fpsyt.2023.1096769

Received: 16 November 2022; Accepted: 10 April 2023; Published: 25 April 2023.

Reviewed by:

Copyright © 2023 Jiang, Lu, Yang, Li, Zhao, Zhang, Li and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Jun Li, [email protected] ; Lifang Wang, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Heterogeneity of Autism Characteristics in Genetic Syndromes: Key Considerations for Assessment and Support

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• Published: 09 May 2023
• Volume 10 , pages 132–146, ( 2023 )

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• Lauren Jenner 1 ,
• Caroline Richards   ORCID: orcid.org/0000-0002-5444-4147 2 ,
• Rachel Howard 1 &
• Joanna Moss 1  

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Purpose of Review

Elevated prevalence of autism characteristics is reported in genetic syndromes associated with intellectual disability. This review summarises recent evidence on the behavioural heterogeneity of autism in the following syndromes: Fragile X, Cornelia de Lange, Williams, Prader-Willi, Angelman, Down, Smith-Magenis, and tuberous sclerosis complex. Key considerations for assessment and support are discussed.

Recent Findings

The profile and developmental trajectory of autism-related behaviour in these syndromes indicate some degree of syndrome specificity which may interact with broader behavioural phenotypes (e.g. hypersociability), intellectual disability, and mental health (e.g. anxiety). Genetic subtype and co-occurring epilepsy within syndromes contribute to increased significance of autism characteristics. Autism-related strengths and challenges are likely to be overlooked or misunderstood using existing screening/diagnostic tools and criteria, which lack sensitivity and specificity within these populations.

Autism characteristics are highly heterogeneous across genetic syndromes and often distinguishable from non-syndromic autism. Autism diagnostic assessment practices in this population should be tailored to specific syndromes. Service provisions must begin to prioritise needs-led support.

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Introduction

People with genetic syndromes associated with intellectual disability (ID) are more likely to evidence clinically significant autism characteristics compared to people in the general population [ 1 ]. For many people with genetic syndromes associated with ID, characteristics related to the ‘core’ diagnostic criteria of autism are evident [ 2 ••]. However, detailed analyses consistently indicate that the profile and developmental trajectory of autism characteristics across these groups are highly heterogeneous, in ways which indicate some degree of syndrome specificity (e.g. in Fragile X syndrome; 3). Furthermore, there is a tendency for people within these populations to demonstrate profiles of autism characteristics that are phenotypically distinct, in subtle and specific ways, from that of non-syndromic Footnote 1 autism [ 4 ]. The picture is further complicated by the fact that ID is a primary characteristic of these genetic syndromes. The extent to which associated ID contributes to the heterogeneity of autism characteristics in people with genetic syndromes has not been clearly established and is likely to be variable across syndrome groups [ 1 ]. Furthermore, differential diagnosis, particularly in those with severe to profound ID, is challenging [ 5 ••], both conceptually and practically. Together, these complexities confer significant challenges for assessment and diagnosis of autism in people with genetic syndromes and likely explain the substantially reduced and delayed recognition of autism in clinical practice for these individuals and their families [ 6 , 7 ••]. Further delineation of these factors within and between genetic syndrome groups, alongside greater precision of assessment of autism for this population as whole, will be critical to address the extant gap between research reported rates of autism characteristics and the interpretation and application of these findings within clinical practice.

In this paper, we first review recent work on autism in genetic syndromes associated with ID, with an emphasis on raising awareness and understanding of phenotypic heterogeneity of autism characteristics within specific genetic syndromes. We then highlight the need to advance developments in diagnostic assessment tools and autism-related support for people with genetic syndromes.

Prevalence of Autism in Genetic Syndromes

Research over recent years has indicated significantly elevated rates of autism and related characteristics in several genetic syndromes associated with ID [ 1 , 2 ••]. Prevalence estimates within the general population indicate rates of autism of at least 1% [ 8 ]. However, people with a genetic syndrome associated with ID are reported to be at least ten times more likely to show autism characteristics than the general population [ 1 ]. Yet application of these findings in clinical diagnostic services is somewhat limited [ 6 ], with reports of significantly delayed and reduced access to autism diagnostic pathways in these populations. For example, the age of autism diagnosis in individuals with Sturge-Weber syndrome is over the age of 8 years old, with 94% of individuals being diagnosed in a Tier 3 specialist service [ 7 ••].

In some cases, this research has challenged existing stereotypes of particular syndrome groups. For instance, individuals with Down syndrome have historically been characterised as having social communication skills that directly contrast with the diagnostic characteristics of autism [ 9 ]. However, reported prevalence rates of autism in Down syndrome have increased from 5 to 42% in the past 20 years [ 10 , 11 ]. A similar trend has also been documented in Williams syndrome [ 12 ]. The apparent increase in the reported prevalence of autism within these populations may reflect an improved understanding and awareness of the co-occurrence of autism in genetic syndromes. However, these and other prevalence data continue to be drawn from an application of cut-off scores from diagnostic autism measures, which have been developed and normed in the general population, where there will be limited representation of syndromic autism. As such, these prevalence data assume a similar constellation of autism characteristics that contribute to scoring at diagnostic threshold to that seen in non-syndromic autism; this assumption may mask important syndrome-specific profiles of autism characteristics.

Heterogeneous Profiles of Characteristics

Autism is widely understood as a complex condition, with variation in terms of sex-specific factors, intellectual ability, and co-occurring conditions [ 13 ]. Detailed analyses that have considered the specific patterns of autism characteristics within individual syndrome groups show that the profiles of autism characteristics are highly heterogeneous between different syndrome groups [ 14 ••], even when individuals score above clinical cut-off scores on autism assessment tools. In many cases, the profile of autism characteristics is reported to be subtly different, both qualitatively and quantitatively from non-syndromic autism. For example, some syndrome groups evidence a profile of characteristics which includes significant repetitive behaviours and/or interests (RRBIs) alongside differences in social communication that are similar to that of autistic people who do not have a genetic syndrome, combined with comparatively heightened social motivation (e.g. Rubinstein-Taybi syndrome [ 14 ••], Sturge-Weber syndrome [ 7 ••]). For other syndromes, both social interaction and communication differences evidence similarities with non-syndromic autism, while RRBIs may be less apparent in the syndrome or may present differently to those described in autistic people without a syndrome (e.g., Phelan-McDermid syndrome [ 15 ], Sotos [ 16 ]). In Fragile X syndrome, which has been understood to be the leading monogenic cause of autism over the past 30 years [ 18 ], a deep phenotyping approach is now commonly adopted, leading researchers to argue that the profile of autism characteristics present are not captured fully by categorical diagnosis alone [ 19 , 20 , 21 , 22 •]. Such variation is not necessarily indicative of reduced presence of autism characteristics in these populations. Rather, they suggest that there are unique autism-related strengths and challenges in people with genetic syndromes. These may differ from that of non-syndromic autism and may differ between syndromes. These similarities and differences need to be recognised to ensure that people receive the most appropriate support.

Developmental Trajectories and Changes with Age

In the general population, subgroup differences (e.g., sex-specific) in the longitudinal heterogeneity of autism characteristics reveal fractionable trajectories which are not clearly related to the development of language and functioning [ 23 ]. Longitudinal heterogeneity of autism characteristics is also variable across and within different genetic syndromes. In Cornelia de Lange syndrome, autism characteristics are reported to become more evident with age, specifically in relation to social interaction skills [ 24 ••]. A similar increase in autism characteristics from childhood to adulthood has also been reported in Sotos syndrome [ 25 ]. However, there is a question surrounding whether these differences are attributable to age or changes in context. For instance, in Sotos syndrome, autism characteristics were reported to increase during the COVID-19 pandemic, a change not seen in age- and IQ-matched autistic children [ 26 ]. It can also be difficult to distinguish an increase in autism characteristics from other changes which commonly co-occur with age in syndromes, particularly the emergence of mental health conditions such as psychosis (e.g., 22q11.2 deletion syndrome, [ 26 ], Prader-Willi syndrome [ 27 ]) and anxiety (e.g., Fragile X syndrome; 20). Improved understanding of these trajectories and interacting factors is critical to ensure people receive the timeliest support and provide clarity in diagnostic classifications at all ages.

Broader Phenotypic Characteristics

One explanation for the so-called atypical profiles of autism in genetic syndromes might be that broader phenotypic behaviours associated with a given syndrome interact with the profile of autism characteristics, resulting in a syndrome-specific signature of autism-related strengths and challenges which vary across the lifespan. Disentangling autism characteristics from the broader phenotypic characteristics of the syndrome is therefore incredibly complex. There are several implications of such heterogeneity within clinical practice. First, the presence of the syndrome may lead to diagnostic overshadowing [ 6 ], resulting in delayed assessment and diagnosis [ 7 ••]. Second, an autism diagnosis is given, but without clear understanding of the unique profile of strengths and challenges for that person—information which should guide more tailored support. Finally, although perhaps less likely, individuals with rare syndromes may meet diagnostic threshold for autism as a result of concomitant syndrome- or ID -related characteristics, and the autism diagnosis may in fact be less appropriate.

In the following sections, we outline recent evidence which highlights the key considerations for understanding the heterogeneity of autism characteristics in genetic syndromes. As it is beyond the scope of this paper to review all syndromes systematically, we have selected eight syndromes which have relatively large bodies of empirical evidence in relation to autism characteristics. Each provides examples of key considerations for clinicians and researchers seeking to understand autism in these populations. The presentation of autism characteristics in these syndromes should be interpreted within the context of the broader behavioural phenotype associated with each genetic syndrome, summarised in Table 1 .

Fragile X Syndrome (FXS)

In FXS, half of males and nearly 20% of females meet DSM-5 criteria for autism spectrum disorder Footnote 2 (ASD; 29). Social anxiety is characteristic of FXS and overlaps behaviourally with autism characteristics [ 21 ], together impacting day-to-day functioning [ 30 ]. Studies have indicated that autism is a distinct condition in FXS that can be dissociated from the broader behavioural phenotype. From infancy, differences in reactions to strangers [ 31 ], social avoidance [ 32 ], reduced eye contact [ 21 , 31 ], behavioural inflexibility [ 33 ], and behaviours that challenge [ 29 ], distinguish individuals with FXS who score above threshold for autism. In fact, more similarities are seen between those with non-syndromic autism and FXS (+ autism Footnote 3 ) than between those with FXS (+ autism) and FXS-alone [ 33 ]. However, reliance on current diagnostic algorithms masks heterogeneity inherent to the behavioural phenotype. For instance, young males with FXS who score above threshold on the Autism Diagnostic Inventory-Revised (ADI-R; 34) present with qualitatively different characteristics than age-matched males with non-syndromic autism, such as increased social smiling and complex mannerisms [ 36 ]. On the Autism Diagnostic Observational Schedule (ADOS; 39), increased repetitive speech, stereotyped behaviours, and hyperarousal are reported to distinguish those with FXS from non-syndromic autism [ 36 ]. These findings highlight the need to look beyond prescriptive algorithms, even when the behaviour presented appears distinct within the syndrome, and similar to non-syndromic autism. Furthermore, the onset of autism characteristics and their developmental trajectory in males with FXS differs relative to males with non-syndromic autism [ 3 ] due to differences in cognitive ability and expressive language [ 38 ]. Even within FXS, differences in the developmental trajectory of autism characteristics have been evidenced related to impulsivity [ 39 ], the presence of co-occurring attention deficit hyperactivity disorder (ADHD) [ 40 , 41 ], adaptive functioning [ 33 ], and epilepsy [ 29 ]. It is therefore important that the time course of autism characteristics is understood within the context of co-occurring conditions and support addresses these simultaneously across development.

Cornelia de Lange Syndrome (CdLS)

Up to 45% of people with CdLS meet diagnostic cut-off for autism on the ADOS [ 42 ]. Autism characteristics are more prominent among those with greater severity of physical phenotypic features in CdLS (e.g., upper limb differences; 42). Social anxiety distinguishes those with CdLS from non-syndromic autism [ 44 , 45 ] and is positively associated with the prevalence of autism characteristics across the lifespan, independent of IQ [ 46 ]. Intolerance of uncertainty appears to mediate the relationship between autism characteristics and anxiety in CdLS [ 47 ], as described in non-syndromic autism [ 48 ]. During interactions with an unfamiliar adult and when participation is voluntary, individuals with CdLS show heightened social anxiety and lower social motivation, a finding not evidenced in fragile X, Rubinstein Taybi or Down syndromes [ 49 ]. The interplay between social anxiety, autism characteristics, and social context has important implications for the suitability and validity of direct assessment in CdLS (e.g., ADOS-2; 47) and highlights the need for greater precision of assessment in these populations. Age-related differences are also evident, with repetitive behaviours and social withdrawal becoming more prominent among older individuals and increasing over time [ 23 , 40 ]. Notably, several studies have also associated older age with more frequent self-injury and compulsive behaviour, and lower levels of interest and pleasure in CdLS, indicating that additional challenges are coinciding with age-related changes in autism characteristics in this group [ 51 , 52 , 53 ]. The significance of age-related changes experienced by people with CdLS highlights the need to provide additional and/or bespoke support, particularly during the transition to adulthood which is a critical period of change.

Williams Syndrome (WS)

Using the ADOS, estimates of autism in WS range from 30 to 35%, although some behaviours may be better characterised as part of WS, for example, difficulties with imagination/creativity, gesture, and repetitive behaviours, rather than indicative of an additional autism diagnosis [ 54 ]. Hypersociability is considered to be central to the WS phenotype [ 55 ], alongside auditory hypersensitivity [ 56 ] and repetitive behaviours [ 57 ]. People with WS also experience significant anxiety, which increases with age and results in lower social motivation [ 58 , 59 ]. Similarly to autistic individuals and those with CdLS, intolerance of uncertainty mediates the relationship between anxiety and autism characteristics in WS [ 60 •]. However, unlike CdLS, social interactions are not influenced by degree of familiarity with a partner in WS [ 61 ] resulting in increased social vulnerability [ 62 ]. These cross-syndrome comparisons indicate subtle differentiations in the presentation of autism characteristics, which arise from phenotypic differences that are key to consider when delivering support. For example, both groups may benefit from support designed for autistic people which improves tolerance of uncertainty to alleviate heightened anxiety (e.g., Coping with Uncertainty in Everyday Situations [CUES©], 61) but people with WS may additionally benefit from supports to mitigate social vulnerability whilst preserving independence.

Prader-Willi Syndrome (PWS)

In PWS, estimates of autism using the Social Communication Questionnaire (SCQ; 62) can be as high as 29–49%, but when assessed directly by PWS-experts using the ADOS-2, the rate of ASD diagnosis reduces to 12.3% (14 out of 146 children; 63). In this study, people with PWS (+ autism) showed more difficulty with overall rapport and reduced quality in response and overtures compared to those with PWS alone. Insistence on sameness in routines/events and compulsivity were seen in 76–100% of this sample (± autism), appearing related to physiological challenges, including hyperphagia and emotional regulation [ 66 ]. Strong interests described as ‘intense obsessionality’ are more marked in PWS than non-syndromic autism [ 67 ]. Psychiatric conditions also frequently co-occur, the most common being anxiety, expressed through difficulties with transitions, skin picking, and repetitive questioning [ 68 ]. Evidence from PWS demonstrates that syndrome-specific expertise is vital to ensure valid and efficient differential diagnosis. People with PWS also present with social communication differences, such as reduced eye contact, limited range of emotional expressions, and differing quality of social overtures [ 69 ]. Social-cognitive differences in PWS are also reminiscent of those described in autistic individuals [ 70 ]. The nature of social differences can be distinguished between genetic subtypes within PWS, from as young as 3 years old [ 71 ]. When compared to people with deletion subtypes, those with the uniparental disomy or imprinting defect have greater social communication differences and are more likely to be diagnosed with autism [ 72 ]—associated with greater severity of ID [ 73 ]. The apparent fractionation of social communication difficulties from RRBIs within PWS related to genetic subtype speaks to the differing pathways to behavioural autism characteristics. Findings also indicate that differing clinical support may be warranted for different genotypes within syndromes.

Angelman Syndrome (AS)

AS has been considered to be the ‘sister’ syndrome to PWS, with markedly contrasting phenotypes. People with AS present with fewer autism characteristics compared to those with PWS, particularly within the domain of social affect, such as increased shared enjoyment of social interactions [ 69 ]. This difference could be attributed to the strong motivation for social contact seen in AS, characterised by behavioural signatures such as frequent smiling and laughing [ 74 ]. Despite people with AS having few or no words, they demonstrate relative strengths in non-verbal communication, particularly through use of gesture and symbols [ 75 ]. Children with the non-deletion subtypes often have strengths in these communicative abilities and are more responsive to social reinforcement (e.g., eye contact, laughing [74]) than those with a deletion. Correspondingly, autism characteristics are observed more commonly in deletion subtypes (75%) than uniparental disomy or mutations (11%) using the ADOS-2 [ 77 ]. Epilepsy in AS is thought to contribute to the development of autism characteristics to a greater degree than expected from the underlying genetic subtype alone, as those with AS and epilepsy score significantly higher on the SCQ than those without epilepsy [ 78 ]. Age-related decline in social motivation [ 74 ] and the onset of autism characteristics should be explored further in relation to epilepsy.

Down Syndrome (DS)

A ‘friendly stereotype’—that individuals are overly sociable—is also associated with DS. The prevalence of co-occurring autism in DS is estimated to be 16–41% [ 11 , 79 ]. Though some relative strengths in reciprocal social interaction (e.g., social smiling, offering comfort, social overtures) are reported among those with DS who meet screening criteria for autism relative to those with non-syndromic autism [ 80 ], broad composite scores are similar across social and non-social diagnostic domains [ 81 , 82 ]. The majority of people with DS who score highly on the SCQ [ 9 ] and ADOS-2 [ 79 ] have more severe ID than individuals with DS alone. Specifically, children with DS and clinically significant autism characteristics are more likely to acquire language later and be less likely to communicate using phrases and sentences than children with DS alone [ 83 ]. Notably, there is evidence of subgroups of people with DS and severe ID who are not autistic [ 84 ], suggesting that the presentation of autism in DS cannot solely be accounted for severity of ID. It has been hypothesised that individuals with DS overcome functional difficulties by adapting to social environments [ 85 ]. This may explain why co-occurring DS and autism is associated with greater manifestation of behaviours that challenge relative to non-syndromic autism [ 86 ] and DS alone [ 9 , 83 ]. Recognising autism characteristics in DS could be useful for prioritising and tailoring particular support (e.g., Speech and Language Therapy [86]).

Smith-Magenis Syndrome (SMS)

The behavioural phenotype of SMS includes sleep disturbances, self-injurious and maladaptive behaviours, stereotypies, and sensory difficulties [ 88 ]. When compared to those with DS, children with SMS show social motivation associated with more negative behavioural outcomes such as self-injury and behaviours that challenge, due to high demand for individualised attention from adults [ 89 ]. In contrast with high levels of social motivation, individuals also present with clinically significant difficulties on the SCQ across domains of social-communication and RRBIs (72% [ 55 ]). Though behavioural and emotional difficulties decrease with age, social communication difficulties and repetitive behaviours persist [ 90 ]. The sex ratio commonly cited in non-syndromic autism is 4:1 and 3:1 (male:female), and this proportion reduces to 2:1 in non-syndromic ID [ 91 ]. However, there is a reversed sex difference in SMS, with three females scoring above the threshold on the SCQ per male [ 92 •]. These sex differences are not seen for IQ, adaptive functioning, and behavioural or emotional difficulties and indicate a sex-specific pathway to behavioural autism characteristics in SMS, which may require tailored clinical support.

Tuberous Sclerosis Complex (TSC)

Epilepsy is the most common feature of TSC and has been identified as related to autism characteristics [ 93 •]. Seizure onset before age 1 year and greater severity of infantile spasms are positively correlated with autism characteristics [ 94 ], although the cause-effect nature of these relationships is not clear [ 95 , 96 , 97 ]. Up to 66% of infants with TSC meet the criteria for autism on the ADOS [ 98 ] and demonstrate a profile of social communication differences which are highly similar to that observed in non-syndromic autism [ 99 , 100 ]. Social communication differences, including reduced eye contact, social babbling, and reciprocal smiling, are more frequently reported than RRBIs in infancy [ 101 , 102 ]. By 36 months, early seizure onset, higher seizure frequency, and delayed language development distinguish those with TSC (+ autism) than TSC-alone [ 103 ]. As early-onset and severe epilepsy are also associated with greater severity of ID, effective treatment and prevention of epilepsy are considered vital for long-term outcomes in TSC [ 104 ].

Key Considerations for Assessment and Support

Re-conceptualisation of autism as a ‘spectrum’ condition in the DSM-5 [ 105 ] has resulted in a single diagnosis encompassing vast behavioural heterogeneity. Furthermore, DSM criteria now state that a diagnosis of autism should only be made if social communication difficulties cannot be better explained by ID [ 102 ]. However, diagnostic guidance does not indicate when or how ID may ‘explain’’ autism-specific difficulties. A modified version on the DSM-5, the Diagnostic Manual—Intellectual Disability (DM-ID-2; 103), highlights that it can be challenging to distinguish autism from ID but does not provide guidance beyond the requirement that ‘deficits’ must exceed general delay.

Since the modification of these criteria, referrals to autism diagnostic services include a significant proportion of individuals without ID [ 5 ••]. Likewise, individuals with ID are commonly excluded from autism research [ 107 •]. Together, this has downstream effects on clinical expertise and resources. Distinguishing autism-specific difficulties in genetic syndromes poses additional challenges. Clinicians are not only presented with the difficult task of determining when characteristics may be attributable to a person’s ID but also must consider factors associated with the behavioural phenotype and longitudinal heterogeneity of the syndrome, which are not accurately captured under classification systems. To provide valid differential diagnosis, clinicians must have sufficient understanding of not only the clinical manifestation of autism in the context of ID, but also syndrome-specific profiles of autism characteristics and co-occurring diagnoses as described above. Where there is a lack of specialism, people are likely to be misdiagnosed or precluded from access to diagnostic pathways/assessment when it is appropriate.

The validity of autism specific assessments for use within genetic syndrome populations generates a significant challenge that impacts widely across this field of research and consequently impedes clinical diagnosis. Autism assessment tools are primarily developed with non-ID populations [ 108 , 109 ]. As a result, screening measures have reduced sensitivity and specificity for persons with ID, particularly for use in people with specific genetic syndromes [ 110 ••]. This can lead to an autism diagnosis being made when this is not wholly relevant to the individual and result in implementation of generic autism support which may not support individual’s needs. Importantly, this may also lead to dismissal of a diagnosis or reluctance to pursue a full autism assessment in situations where it would be appropriate and autism specific support would be beneficial. Reliance on clinical cut-off scores, which are based on a single facet of autism and have limited normative data, may mask syndrome-specific associated profiles of autism characteristics and thus compound the issue of misclassification [ 111 ]. Given this, when screening tools are used as part of a standard, clinical triage for autism assessment, a score below threshold for a person with a genetic syndrome, and ID should not be used as the sole criteria to prevent a full autism assessment. As outlined above, evidence also points towards variability within and between genetic syndrome groups regarding the emergence of autistic characteristics and related trajectories of development (e.g. 23, 24). This heterogeneity requires additional consideration regarding the timing of clinical assessment of autism in these groups.

Diagnostic observational assessments, such as the ADOS-2, have further practical limitations when used with people with ID. For instance, ADOS-2 Modules 3 and 4 require verbal fluency and measure higher-level social communication skills (e.g., reporting of event), yet verbal fluency does not always parallel cognitive ability. Modules 1 and 2 are designed for use with young children; thus, the materials and activities (e.g., playing with dolls) are not engaging or appropriate for most adults. Diagnostic algorithms are a further limitation. Authors have cautioned against interpreting scores on the ADOS-2 and ADI-R when a person has a mental age of 18–24 months [ 35 , 112 ]. Fortunately, researchers have begun to explore how screening tools can be tailored and standardised in samples with ID [ 113 ] and suggested modifications to diagnostic assessment that are more appropriate for those with few and no words [ 114 •, 115 ]. Though this is a step forward, an unintended consequence of focusing on ID broadly is that we are still limited in the ability to conceptualise syndrome-specific profiles of autism.

As explored above, prescriptive algorithms normed in non-syndromic populations are likely to lead to score differences which fail to represent the true nature of strengths and challenges within and across genetic syndromes. Taking a deep phenotyping approach, where an extensive battery of multiple measures is used, allows us to better understand the significance and presentation of autism characteristics in the context of specific syndromes. For instance, Roberts and colleagues [ 22 •] accounted for cognitive abilities, adaptive functioning, anxiety, and ADHD to understand autism in pre-schoolers with FXS. This enabled them to consider differential diagnoses and establish a high degree of confidence in diagnostic determinations. As such, it is important to look beyond autism screening and diagnostic measures to understand and describe autism-related behaviours to facilitate appropriate supports. Triangulation of tools that measure social motivation/avoidance and broader quality of social abilities (e.g., Sociability Questionnaire for People with Intellectual Disability [ 43 ]; Child Sociability Rating Scale [ 114 •]), restricted/repetitive behaviours (e.g., Repetitive Behaviour Questionnaire [ 117 ]) and sensory sensitivity (e.g., Sensory Experiences Questionnaire [ 118 ]) with standard autism screening and diagnostic tools will also lead to a more comprehensive picture of an individuals’ strengths and needs, and may overcome some of the limitations of the current autism screening tools. It is also important to develop an understanding of those who score below threshold for autism within genetic syndrome populations, especially where the profile of need sits within one or two of the autism diagnostic domains, but not across all domains. It is plausible that these individuals may benefit from relevant components of autism-specific support and interventions. Together, these research and clinical recommendations would support efforts to develop syndrome-sensitive algorithms and cut-off scores, which could inform operationalisation of autism diagnostic criteria in the DSM-5 (and other classification systems). We also suggest researchers develop large-scale, open-source data sets, enabling cross-syndrome comparisons both concurrently and over-time to improve the precision and replicability of autism phenotyping.

Specifically in clinical practice, scores on existing algorithms should be used in tandem with sufficient understanding of a person with a genetic syndrome. For instance, context is needed regarding their developmental level, but also differences related to the physical and behavioural phenotypes, which are likely to contribute to their overall presentation. These should be understood in relation to the developmental trajectory of autism characteristics and age-related changes associated with the syndrome—especially as older individuals are more likely to be encountered by diagnostic services, given the reported delays in access to assessment [ 6 , 7 ••]. Assessment of potential co-occurring conditions (e.g., ADHD, social anxiety) would also support differential diagnosis. If co-occurring conditions are present, then it is important to consider how it may influence the validity of autism diagnostic assessment and, if possible, consult relevant professionals.

Though much of this review has focused on differential diagnosis, we finish by emphasising the urgent need for change in service provision to value need over diagnosis. People with genetic syndromes who present with ‘atypical’ profiles of autism characteristics may still benefit from clinical and educational support strategies primarily developed for autistic people who do not have a genetic syndrome. Depending on the country, health service provision, and national guidelines, clinical services differ in terms of eligibility criteria and funding. Yet it is often the case that autism services are perceived as being more comprehensive than those available for other neurodevelopmental conditions [ 119 ] but also somewhat disconnected from other diagnostic and disability services. Given the high rates of co-occurrence across neurodevelopmental conditions, greater convergence of clinical services and support would be beneficial [ 120 ••]. Understandably, these practical factors may motivate caregivers and professionals working with an individual to seek a diagnosis to support access to such provisions. Amassing an evidence base for differential diagnosis in each syndrome is an ambitious goal, and if services wait for this goal to be achieved, immediate support for people with these syndromes will be precluded or significantly delayed. As such, researchers argue that a needs-led approach may be the better alternative to a categorical diagnosis [ 5 ••]. Where it is possible and appropriate to translate findings from the non-syndromic autism literature to people with genetic syndromes, clinical services should seek to do so, to accelerate the progress of practice-based evidence and improve real-world outcomes and support for people with genetic syndromes.

Conclusions

The behavioural and longitudinal heterogeneity of autism-related behaviours within and across genetic syndromes indicate some degree of syndrome specificity, as illustrated in the examples provided above. Current classification systems and diagnostic assessment tools do not provide clear guidance on how to disentangle these differences from associated ID and broader phenotypic characteristics. Therefore, differential diagnosis relies on the development of syndrome-sensitive assessment practices, alongside access to comprehensive clinical expertise, to establish strengths and challenges as a baseline. However, access to support should not be dependent on diagnostic categorisation. Autism characteristics in genetic syndromes demand attention across time and circumstance, to evidence and support related changes in need.

In most cases, autism is diagnosed in people who do not have a known genetic syndrome. In this paper, we have used the term ‘non-syndromic autism’ to reflect such cases.

The term autism has been chosen over the diagnostic term autism spectrum disorder (ASD) wherever possible to reflect the view that autism is a difference rather than a dysfunction [ 137 ]). This is consistent with the neurodiversity perspective [ 138 ] and the deficit-as-difference conception of autism [ 139 ]. However, where essential to maintain precision in reporting, the diagnostic term ‘ASD’ is used. The identity-first phrasing ‘autistic people’ is also used, as it is the preferred term by the UK autism community [ 140 ].

‘ + autism’ is used to distinguish people within a genetic syndrome group who have received a clinical diagnosis of autism.

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Jenner, L., Richards, C., Howard, R. et al. Heterogeneity of Autism Characteristics in Genetic Syndromes: Key Considerations for Assessment and Support. Curr Dev Disord Rep 10 , 132–146 (2023). https://doi.org/10.1007/s40474-023-00276-6

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Study of different autism types finds shared mechanism that may respond to drugs

Researchers detect similar disruptions in the neural development of genetic and unexplained autism.

An analysis of how brains with different forms of autism develop has revealed common underlying mechanisms that may respond to existing medications.

For the study, Rutgers Health researchers used a technique called induced pluripotent stem cells to transform the blood cells of people with both genetic and unexplained (or idiopathic) autism spectrum disorder (ASD) into early brain cells called neural precursor cells. As the precursor cells from both groups matured in the lab, defects in a common signaling pathway that controls structural proteins led them to struggle with an important step in cell differentiation, the growth of neurites, and the cell migration needed for proper brain architecture.

Although some cell lines exhibited too much activity in this mTOR pathway, while others exhibited too little, the researchers could correct both problems and spur better cell differentiation with existing drugs that either stimulate or inhibit the activity of mTOR (mechanistic target of rapamycin).

"Cells in a dish are not fully human cells that have developed in a fetus and functioned in a person, but they are a lot closer than mouse cells," said Emanuel DiCicco-Bloom, a professor of neuroscience and cell biology/pediatrics at Robert Wood Johnson Medical School and senior author of the study in eLife.

"This finding is particularly interesting because the process of growing new synaptic spines when people learn things is completely analogous to the processes we observed in the cells we used for this experiment: growing axons and migrating during fetal development," DiCicco-Bloom said. "So even though this experiment mimicked a process you'd see during early to mid-pregnancy, the same process involving structural proteins is happening right now in you and me, which means that if we took cells from people with autism and found this abnormal regulation of mTOR in their cells in a dish, those people might be candidates as adults for mTOR regulating drugs to improve their function."

The visible symptoms of ASD vary widely but typically feature some repetitive behaviors and some impairment in communication and social interaction. The condition's incidence has increased from about 1 in 150 children in 2000 to 1 in 36 children in 2020, according to the

Centers for Disease Control and Prevention. Roughly 10 to 15 percent of people with ASD have genes that are known to elevate their risk for ASD. Other cases are idiopathic, meaning they are unexplained.

Rutgers Health researchers began the study with blood from three unrelated people with idiopathic ASD, ages 4 to 14 years, with the expectation of finding person-specific differences in the processes occurring during development in utero. When the researchers used the pluripotent stem cell technique to transform blood cells into the sort of neuron precursors typically found in fetal brains, they unexpectedly found many similarities, including abnormalities in the mTOR pathway, which regulates cell creation, metabolism, neurite growth, remodeling and destruction, among many other functions.

The researchers then gained access to blood cells from another three patients with ASD caused by a particular genetic abnormality associated with about 1 percent of ASD, deletion of genes on chromosome 16, called 16p11.2 deletion. They performed the same experiment and found the same disruptions in neuron development.

Subsequent analysis showed that the mTOR signaling disruptions in some patients stemmed from excessive amounts of a particular molecule, while the disruptions in others stemmed from insufficient amounts. In either case, the researchers could use existing medications approved for use in other conditions to correct the problem and stimulate normal development.

The study team has already begun a follow-up investigation to see if people with ASD stemming from other genetic causes exhibit similar disruptions in mTOR activity during development. If mTOR signaling disruption proves a common feature of ASD, tests of mTOR function could help clinicians diagnose the condition more accurately and differentiate it from other conditions with similar effects.

"A couple of very rare genetic types of autism have already been linked to the mTOR pathway, but this is the first to connect mTOR with genes in the 16p11.2 area, which does not have mTOR on it, and with three presumably different types of idiopathic autism from three unrelated people," said Smrithi Prem, lead author of the study and a psychiatry resident at Penn Medicine who led the study as an MD/PhD student at Robert Wood Johnson Medical School.

"These findings also echo something that has appeared in studies of other conditions, that not all people with mTOR dysregulation have excessive activation that needs inhibition," Prem said. "There are two kinds of mTOR dysregulation, but most trials we've run on people with mTOR dysregulation have only used inhibitors. Our findings showed that cells from two of the people we studied needed more mTOR, not less, and that may spur trials that give different types of mTOR treatment to different individual patients."

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Materials provided by Rutgers University . Original written by Andrew Smith. Note: Content may be edited for style and length.

Journal Reference :

• Smrithi Prem, Bharati Dev, Cynthia Peng, Monal Mehta, Rohan Alibutud, Robert J Connacher, Madeline St Thomas, Xiaofeng Zhou, Paul Matteson, Jinchuan Xing, James H Millonig, Emanuel DiCicco-Bloom. Dysregulation of mTOR signaling mediates common neurite and migration defects in both idiopathic and 16p11.2 deletion autism neural precursor cells . eLife , 2024; 13 DOI: 10.7554/eLife.82809

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Autism May Have 'Unnoticed' Driver, Say Stanford Neuroscientists

Neuroscientists at Stanford University have proposed a new theory for a key driving force of autism spectrum disorder.

Roughly one in 100 children worldwide has autism, according to data from the World Health Organization. The term refers to a diverse group of conditions characterized by some degree of difficulty with social interaction and communication.

There are many potential causes of autism spectrum disorders, which include both environmental and genetic factors. However, we still know very little about the specific causes of the condition.

In a new comment paper, published in the journal Molecular Psychiatry , researchers from Stanford University, led by Karen Parker, have highlighted a potential key driver of this condition in certain individuals, providing a possible pathway to improving social abilities in some children with autism.

The theory focuses on a hormone called vasopressin, also known as antidiuretic hormone. This hormone is known to play a diverse range of functions in the human body, hence its multiple different names.

Antidiuretic hormone is most commonly used to describe its essential roles in regulating blood pressure, kidney function and concentrations of water in the blood. But it also plays an important role in modulating social communication and pair bonding behaviors, a context in which it is usually known as the previously mentioned vasopressin.

Because of its role in social interactions, Parker's lab have previously investigated the effects of vasopressin treatment in children with autism. While human trials have so far been limited to a small sample size, children who received this nasally introduced treatment showed significant improvements in social abilities as well as reduced anxiety and repetitive behaviors.

However, to demonstrate that autism is a direct result of vasopressin deficiency, rather than something that can simply be masked by introducing the hormone, the scientists said they needed to look at the other roles it has and how they might be impacted in people with autism.

The researchers said that a deficiency in vasopressin would likely be associated with difficulties controlling the body's water content. For example, they might see individuals with autism also experiencing excessive thirst, excessive urine production, or a condition called central diabetes insipidus which results from an inability to control the body's water balance.

• Scientists reveal hidden factor that may boost child's brain development
• Watching TV linked to abnormal behavior in toddlers, parents warned
• Neuroscientists make "unexpected" discovery over cause of childhood autism

Unfortunately, there are very few studies that explore the links between autism and these conditions. Several studies have shown that people with autism are more likely to experience excessive thirst compared to neurotypical individuals, and compared to those with different neurodevelopmental diagnoses, indicating that this thirst is not simply correlated with intellectual disabilities.

Children with autism also have significantly higher rates of urinary incontinence and bedwetting, which may be a symptom of excessive urine production.

"The emerging evidence reviewed above is consistent with decreased brain [vasopressin] production in at least some individuals with autism spectrum disorder," the authors write.

"However, given a lack of awareness of [vasopressin's] diverse functions, these symptoms may be subtle enough to go unnoticed or, if prominent, may be misattributed to other causes."

More research is now needed to identify whether there is indeed a clear link between water balance-related medical conditions and autism spectrum disorders, as well as determining whether a positive relationship exists between vasopressin deficiency and the severity of social symptoms in individuals with autism.

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Pandora Dewan is a Newsweek Science Reporter based in London, UK. Her focus is reporting on science, health and technology. Pandora joined Newsweek in 2022 and previously worked as the Head of Content for the climate change education start-up, ClimateScience and as a Freelance writer for content creators such as Dr Karan Rajan and Thoughty2. She is a graduate in Biological Sciences from the University of Oxford. Languages: English.

You can get in touch with Pandora by emailing [email protected]. or on Twitter @dewanpandora.

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Psychology Major’s Research Empowers Families with Autism

Mackenzie Fowler ’24 has a passion for helping parents of children with autism. As a psychology major with minors in applied behavior analysis (ABA) and art, she plans to work as a board-certified behavior analyst in school environments. Mackenzie’s undergraduate research, study abroad experience and campus job taught her to apply textbook knowledge in the real world and deepened her commitment to the field of psychology.

A required introductory course sparked Mackenzie’s interest in psychology, and a subsequent ABA class introduced her to the science of therapy. She later applied for an internship with a local clinic, C.A.B.S. Autism & Behavior Specialists, where she became a registered behavior technician and began focusing on early intervention with families and parents.

Awarded the psychology department’s George Scholar grant, Mackenzie asked her professor and advisor, Assistant Professor of Psychology Miguel Ampuero, to partner with her on a project. Their research supports parents teaching communication skills to their children with autism. Mackenzie is investigating how much training parents need and how to make it faster and more efficient. Younger psychology students have joined the project, growing undergraduate research opportunities at Berry while giving Mackenzie more mentoring practice.

Her job as the student director of the alumni center also reinforces her supervisory skills: “This role is less focused on discovery and more on professional management experiences such as event planning and building schedules. Here, I’m learning how to manage a work environment and growing professionally in a different way.”

Mackenzie also pursued a summer international program in Peru, saying it was a significant step out of her comfort zone and her most formative college experience. Each year, Berry professors accompany students abroad as they navigate special topics classes and engage in related cultural and professional work. The program coordinators assigned Mackenzie’s group to autism clinics and a special needs school implementing new behavior intervention plans in the classroom.

“If C.A.B.S. helped affirm that I wanted to work in behavior analysis, this trip really solidified it,” she says. “It was amazing to see the basics of the clinics were similar but with cultural differences. It was also neat to see the new program taking shape.”

Recalling how her learning and career possibilities expanded throughout college, Mackenzie is grateful for the ways Ampuero helped shape her future.

“Dr. Ampuero has guided me in so many areas,” says Mackenzie. “He taught several of my classes at Berry, then led me through coursework and practical, real-world experiences in Peru. He also acts as my research advisor, and we plan to publish a paper on our work. He has supported me through every step of my academic and professional decisions in psychology.”

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FCAI Deputy Director Dave Caudel Discusses the Strengths and Challenges of Neurodiversity in New Talk

Posted by stasikjs on Saturday, March 30, 2024 in FCAI News , News , Presentations .

Last week, FCAI Deputy Director Dave Caudel spoke for a Disability @ Work session hosted by the UNC Charlotte Career Center.

Caudel discussed the strengths and challenges of neurodiversity, and these undeserved and underutilized members of our society. You can view the video below or on YouTube  here .

Every spring, the UNC Career Center offers programming that centers on disabled community members, their professional development, and their rights in the workforce.

The theme this year is The Future of the Neurodiverse Workforce.

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Link Between Autism, ADHD, and a Common Plastic Ingredient Identified by Researchers

I n an effort to unravel the complexities of autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD), rates of which have surged in recent times, scholars have been investigating potential causative factors.

Recent research has uncovered that children diagnosed with autism or ADHD exhibit a distinct metabolic response in dealing with bisphenol A (BPA), a widespread plastic additive, when compared to non-ASD/ADHD children.

Common among various plastic products and their manufacturing, BPA is additionally found lining the insides of cans containing food and beverages. Prior studies have connected BPA with various health complications, notably those affecting hormonal functioning such as breast cancer and issues with fertility.

A collaborative effort by scientists from Rowan University and Rutgers University in the United States analyzed urine samples from three child cohorts: 66 with autism, 46 with ADHD, and 37 typically developing children. The focus of the study was on glucuronidation , a bodily detoxification process that helps eliminate toxins from the bloodstream.

Their findings suggested children with ASD and ADHD were less effective at expelling BPA and a related chemical, Diethylhexyl Phthalate (DEHP), which could result in prolonged exposure to their harmful effects.

The researchers identified a detoxification impairment for these plastic-origin substances in children with ASD and ADHD, which exposes their tissues to heightened levels of these chemicals, as noted in their research paper .

While efficiency in expelling BPA was significantly lower by roughly 11 percent in ASD-affected kids and 17 percent in those with ADHD compared to the control group, not every child with neurodevelopmental disorders had issues with BPA clearance, suggesting there are also other contributing factors.

The paper speculates that gene mutations might be influencing the body’s capacity to process BPA effectively, possibly resulting in neuronal development and functionality damage.

As ASD and ADHD are believed to arise from both genetic and environmental interactions, this study merges these aspects. However, it remains unclear whether BPA exposure is causal for these disorders.

Scientists continue working to pinpoint the precise developmental processes of ASD and ADHD—whether they occur in the womb or post-birth—as the evidence linking environmental pollutants such as plasticizers to neurodevelopmental disorders strengthens.

According to the bulk of epidemiological data , there is a significant correlation between neurodevelopmental disorders and environmental contaminants, particularly plasticizers. The exact magnitude of this correlation on the prevalence of these disorders, however, is still undetermined.

The detailed findings from this study are presented in the journal PLOS ONE .

This story was initially published in October 2023.

FAQ Section

What is BPA?

BPA, or bisphenol A, is a chemical commonly used in the production of plastic products and epoxy resins, which can be found in various consumer goods such as water bottles and food container linings.

How might BPA affect children with ASD or ADHD differently?

Children with ASD and ADHD may have a reduced ability to metabolize and excrete BPA through glucuronidation, leading to potentially longer periods of exposure to its harmful effects.

What is glucuronidation?

Glucuronidation is a metabolic pathway in the body that attaches glucuronic acid to substances for detoxification and facilitates their excretion through urine.

Does BPA exposure cause ASD or ADHD?

Currently, there is not enough evidence to definitively claim that BPA exposure causes ASD or ADHD. The relationship between exposure to environmental pollutants like BPA and neurodevelopmental disorders is complex and likely to involve multiple genetic and environmental factors.

Where can I find the research study?

The study is published in the peer-reviewed journal PLOS ONE .

The recent study highlights a significant environmental health concern and underscores the intricate interplay between genetics and environmental exposures in the context of neurodevelopmental disorders such as ASD and ADHD. Although conclusive proof of causation is still absent, the findings emphasize the importance of examining the potential impacts of common substances such as BPA on vulnerable populations like children. The continued research in this area not only broadens our understanding of ASD and ADHD but also points to the need for further investigation into the safety and regulation of synthetic chemicals in our environment.