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Phenotypic Subtyping and Re-analyses of Existing Transcriptomic Data from Autistic Probands in Simplex Families Reveal Differentially Expressed and ASD Trait-Associated Genes.

ABSTRACT: Autism spectrum disorder (ASD) describes a collection of neurodevelopmental disorders characterized by core symptoms that include social communication deficits and repetitive, stereotyped behaviors often coupled with restricted interests. Primary challenges to understanding and treating ASD are the genetic and phenotypic heterogeneity of cases that complicates all omics analyses as well as a lack of information on relationships among genes, pathways, and autistic traits. In this study, we re-analyze existing transcriptomic data from simplex families by subtyping individuals with ASD according to multivariate cluster analyses of clinical ADI-R scores that encompass a broad range of behavioral symptoms. We also correlate multiple ASD traits, such as deficits in verbal and non-verbal communication, play and social skills, ritualistic behaviors, and savant skills, with expression profiles using Weighted Gene Correlation Network Analyses (WGCNA). Our results show that subtyping greatly enhances the ability to identify differentially expressed genes involved in specific canonical pathways and biological functions associated with ASD within each phenotypic subgroup. Moreover, using WGCNA, we identify gene modules that correlate significantly with specific ASD traits. Network prediction analyses of the genes in these modules reveal canonical pathways as well as neurological functions and disorders relevant to the pathobiology of ASD. Finally, we compare the WGCNA-derived data on autistic traits in simplex families with analogous data from multiplex families using transcriptomic data from our previous studies. The comparison reveals overlapping trait-associated pathways as well as upstream regulators of the module-associated genes that may serve as useful targets for a precision medicine approach to ASD.

SUBMITTER: Hu VW

PROVIDER: S-EPMC7689346 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Phenotypic Subtyping and Re-analyses of Existing Transcriptomic Data from Autistic Probands in Simplex Families Reveal Differentially Expressed and ASD Trait-Associated Genes.

Hu Valerie W VW Bi Chongfeng C

Frontiers in neurology 20201112

Autism spectrum disorder (ASD) describes a collection of neurodevelopmental disorders characterized by core symptoms that include social communication deficits and repetitive, stereotyped behaviors often coupled with restricted interests. Primary challenges to understanding and treating ASD are the genetic and phenotypic heterogeneity of cases that complicates all omics analyses as well as a lack of information on relationships among genes, pathways, and autistic traits. In this study, we re-ana ...[more]

PMID: 33281715

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Project description:BACKGROUND:Younger siblings of children with autism spectrum disorder (ASD) are at increased likelihood of receiving an ASD diagnosis and exhibiting other developmental concerns. It is unknown how quantitative variation in ASD traits and broader developmental domains in older siblings with ASD (probands) may inform outcomes in their younger siblings. METHODS:Participants included 385 pairs of toddler siblings and probands from the Infant Brain Imaging Study. ASD probands (mean age 5.5?years, range 1.7 to 15.5?years) were phenotyped using the Autism Diagnostic Interview-Revised (ADI-R), the Social Communication Questionnaire (SCQ), and the Vineland Adaptive Behavior Scales, Second Edition (VABS-II). Siblings were assessed using the ADI-R, VABS-II, Mullen Scales of Early Learning (MSEL), and Autism Diagnostic Observation Schedule (ADOS) and received a clinical best estimate diagnosis at 24?months using DSM-IV-TR criteria (n?=?89 concordant for ASD; n?=?296 discordant). We addressed two aims: (1) to determine whether proband characteristics are predictive of recurrence in siblings and (2) to assess associations between proband traits and sibling dimensional outcomes at 24?months. RESULTS:Regarding recurrence risk, proband SCQ scores were found to significantly predict sibling 24-month diagnostic outcome (OR for a 1-point increase in SCQ?=?1.06; 95% CI?=?1.01, 1.12). Regarding quantitative trait associations, we found no significant correlations in ASD traits among proband-sibling pairs. However, quantitative variation in proband adaptive behavior, communication, and expressive and receptive language was significantly associated with sibling outcomes in the same domains; proband scores explained 9-18% of the variation in cognition and behavior in siblings with ASD. Receptive language was particularly strongly associated in concordant pairs (ICC?=?0.50, p?<?0.001). CONCLUSIONS:Proband ASD symptomology, indexed by the SCQ, is a predictor of familial ASD recurrence risk. While quantitative variation in social communication and restricted and repetitive behavior were not associated among sibling pairs, standardized ratings of proband language and communication explained significant variation in the same domains in the sibling at 24?months, especially among toddlers with an ASD diagnosis. These data suggest that proband characteristics can alert clinicians to areas of developmental concern for young children with familial risk for ASD.

Project description:Autism Spectrum Disorder (ASD) is a complex neurological and developmental disorder characterized by behavioral and social impairments as well as multiple co-occurring conditions, such as gastrointestinal abnormalities, dental/periodontal diseases, and allergies. The etiology of ASD likely involves interaction between genetic and environmental factors. Recent studies suggest that oral and gut microbiome play important roles in the pathogenesis of inflammation, immune dysfunction, and disruption of the gut-brain axis, which may contribute to ASD pathophysiology. The majority of previous studies used unrelated neurotypical individuals as controls, and they focused on the gut microbiome, with little attention paid to the oral flora. In this pilot study, we used a first degree-relative matched design combined with high fidelity 16S rRNA (ribosomal RNA) gene amplicon sequencing in order to characterize the oral and gut microbiotas of patients with ASD compared to neurotypical individuals, and explored the utility of microbiome markers for ASD diagnosis and subtyping of clinical comorbid conditions. Additionally, we aimed to develop microbiome biomarkers to monitor responses to a subsequent clinical trial using probiotics supplementation. We identified distinct features of gut and salivary microbiota that differed between ASD patients and neurotypical controls. We next explored the utility of some differentially enriched markers for ASD diagnosis and examined the association between the oral and gut microbiomes using network analysis. Due to the tremendous clinical heterogeneity of the ASD population, we explored the relationship between microbiome and clinical indices as an attempt to extract microbiome signatures assocociated with clinical subtypes, including allergies, abdominal pain, and abnormal dietary habits. The diagnosis of ASD currently relies on psychological testing with potentially high subjectivity. Given the emerging role that the oral and gut microbiome plays in systemic diseases, our study will provide preliminary evidence for developing microbial markers that can be used to diagnose or guide treatment of ASD and comorbid conditions. These preliminary results also serve as a starting point to test whether altering the oral and gut microbiome could improve co-morbid conditions in patients with ASD and further modify the core symptoms of ASD.

Project description:BackgroundTraits and characteristics qualitatively similar to those seen in diagnosed autism spectrum disorder can be found to varying degrees in the general population. To measure these traits and facilitate their use in autism research, several questionnaires have been developed that provide broad measures of autistic traits [e.g. Autism-Spectrum Quotient (AQ), Broad Autism Phenotype Questionnaire (BAPQ)]. However, since their development, our understanding of autism has grown considerably, and it is arguable that existing measures do not provide an ideal representation of the trait dimensions currently associated with autism. Our aim was to create a new measure of autistic traits that reflects our current understanding of autism, the Comprehensive Autism Trait Inventory (CATI).MethodsIn Study 1, 107 pilot items were administered to 1119 individuals in the general population and exploratory factor analysis of responses used to create the 42-item CATI comprising six subscales: Social Interactions, Communication, Social Camouflage, Repetitive Behaviours, Cognitive Rigidity, and Sensory Sensitivity. In Study 2, the CATI was administered to 1068 new individuals and confirmatory factor analysis used to verify the factor structure. The AQ and BAPQ were administered to validate the CATI, and additional autistic participants were recruited to compare the predictive ability of the measures. In Study 3, to validate the CATI subscales, the CATI was administered to 195 new individuals along with existing valid measures qualitatively similar to each CATI subscale.ResultsThe CATI showed convergent validity at both the total-scale (r ≥ .79) and subscale level (r ≥ .68). The CATI also showed superior internal reliability for total-scale scores (α = .95) relative to the AQ (α = .90) and BAPQ (α = .94), consistently high reliability for subscales (α > .81), greater predictive ability for classifying autism (Youden's Index = .62 vs .56-.59), and demonstrated measurement invariance for sex.LimitationsAnalyses of predictive ability for classifying autism depended upon self-reported diagnosis or identification of autism. The autistic sample was not large enough to test measurement invariance of autism diagnosis.ConclusionsThe CATI is a reliable and economical new measure that provides observations across a wide range of trait dimensions associated with autism, potentially precluding the need to administer multiple measures, and to our knowledge, the CATI is also the first broad measure of autistic traits to have dedicated subscales for social camouflage and sensory sensitivity.

Project description:BackgroundResearch suggests that families' knowledge and cultural perceptions of autism spectrum disorder (ASD), and beliefs about its etiology and prognosis, can affect parents' recognition of the first signs of autism in their children and influence help seeking and treatment decisions.ObjectiveThis study investigated explanatory models of autism among parents of young children with ASD in the multicultural context of Sweden.MethodSeventeen parents from diverse cultural, ethnic and linguistic backgrounds participated in semi-structured interviews. A deductive approach to qualitative content analysis was used to analyze data. Five domains of the Explanatory Model supplementary module of the Cultural Formulation Interview (CFI) were used as coding categories, operationalized as 'Parents' understanding of autism'; 'Autism prototypes'; 'Causal explanations'; 'Course of autism', and 'Help seeking and treatment expectations'.ResultsThe results showed that parents' prior knowledge of autism and experience of young children's typical developmental trajectories, as well as the opinions of children's grandparents and preschool teachers, affected symptom recognition and help seeking. There were differences in parents' explanatory models before and after ASD diagnosis. Initial interpretations of the disorder included medical conditions and reaction to environmental influences, while genetic, supernatural/religious factors, and vaccinations were mentioned as definite causes after obtaining a clinical diagnosis. Parents also held multiple explanatory models, influenced by the views of family members and information obtained from media or from health care professionals. Parents' treatment decisions included use of available state-funded support services, and complementary and alternative treatments.ConclusionThe results demonstrate the utility of the CFI's Explanatory Model supplementary module in autism research. Implications for clinical practice are discussed.

Dataset Information

Phenotypic Subtyping and Re-analyses of Existing Transcriptomic Data from Autistic Probands in Simplex Families Reveal Differentially Expressed and ASD Trait-Associated Genes.

Publications

Phenotypic Subtyping and Re-analyses of Existing Transcriptomic Data from Autistic Probands in Simplex Families Reveal Differentially Expressed and ASD Trait-Associated Genes.

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