Dataset Information

Genome-wide rare variant score associates with morphological subtypes of autism spectrum disorder.

ABSTRACT: Defining different genetic subtypes of autism spectrum disorder (ASD) can enable the prediction of developmental outcomes. Based on minor physical and major congenital anomalies, we categorize 325 Canadian children with ASD into dysmorphic and nondysmorphic subgroups. We develop a method for calculating a patient-level, genome-wide rare variant score (GRVS) from whole-genome sequencing (WGS) data. GRVS is a sum of the number of variants in morphology-associated coding and non-coding regions, weighted by their effect sizes. Probands with dysmorphic ASD have a significantly higher GRVS compared to those with nondysmorphic ASD (P = 0.03). Using the polygenic transmission disequilibrium test, we observe an over-transmission of ASD-associated common variants in nondysmorphic ASD probands (P = 2.9 × 10^-3). These findings replicate using WGS data from 442 ASD probands with accompanying morphology data from the Simons Simplex Collection. Our results provide support for an alternative genomic classification of ASD subgroups using morphology data, which may inform intervention protocols.

SUBMITTER: Chan AJS

PROVIDER: S-EPMC9617891 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Genome-wide rare variant score associates with morphological subtypes of autism spectrum disorder.

Chan Ada J S AJS Engchuan Worrawat W Reuter Miriam S MS Wang Zhuozhi Z Thiruvahindrapuram Bhooma B Trost Brett B Nalpathamkalam Thomas T Negrijn Carol C Lamoureux Sylvia S Pellecchia Giovanna G Patel Rohan V RV Sung Wilson W L WWL MacDonald Jeffrey R JR Howe Jennifer L JL Vorstman Jacob J Sondheimer Neal N Takahashi Nicole N Miles Judith H JH Anagnostou Evdokia E Tammimies Kristiina K Zarrei Mehdi M Merico Daniele D Stavropoulos Dimitri J DJ Yuen Ryan K C RKC Fernandez Bridget A BA Scherer Stephen W SW

Nature communications 20221029 1

Defining different genetic subtypes of autism spectrum disorder (ASD) can enable the prediction of developmental outcomes. Based on minor physical and major congenital anomalies, we categorize 325 Canadian children with ASD into dysmorphic and nondysmorphic subgroups. We develop a method for calculating a patient-level, genome-wide rare variant score (GRVS) from whole-genome sequencing (WGS) data. GRVS is a sum of the number of variants in morphology-associated coding and non-coding regions, wei ...[more]

PMID: 36309498

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Project description:BackgroundThe heterogeneity inherent in autism spectrum disorder (ASD) presents a substantial challenge to diagnosis and precision treatment. Heterogeneity across biological etiologies, genetics, neural systems, neurocognitive attributes and clinical subtypes or phenotypes has been observed across individuals with ASD.MethodsIn this study, we aim to investigate the heterogeneity in ASD from a multimodal brain imaging perspective. The Autism Diagnostic Observation Schedule (ADOS) was used as a reference to guide functional and structural MRI fusion. DSM-IV-TR diagnosed Asperger's disorder (n = 79), pervasive developmental disorder-not otherwise specified [PDD-NOS] (n = 58) and Autistic disorder (n = 92) from ABIDE II were used as discovery cohort, and ABIDE I (n = 400) was used for replication.ResultsDorsolateral prefrontal cortex and superior/middle temporal cortex are the primary common functional-structural covarying cortical brain areas shared among Asperger's, PDD-NOS and Autistic subgroups. Key differences among the three subtypes are negative functional features within subcortical brain areas, including negative putamen-parahippocampus fractional amplitude of low-frequency fluctuations (fALFF) unique to the Asperger's subtype; negative fALFF in anterior cingulate cortex unique to PDD-NOS subtype; and negative thalamus-amygdala-caudate fALFF unique to the Autistic subtype. Furthermore, each subtype-specific brain pattern is correlated with different ADOS subdomains, with social interaction as the common subdomain. The identified subtype-specific patterns are only predictive for ASD symptoms manifested in the corresponding subtypes, but not the other subtypes.ConclusionsAlthough ASD has a common neural basis with core deficits linked to social interaction, each ASD subtype is strongly linked to unique brain systems and subdomain symptoms, which may help to better understand the underlying mechanisms of ASD heterogeneity from a multimodal neuroimaging perspective.LimitationsThis study is male based, which cannot be generalized to the female or the general ASD population.

Dataset Information

Genome-wide rare variant score associates with morphological subtypes of autism spectrum disorder.

Publications

Genome-wide rare variant score associates with morphological subtypes of autism spectrum disorder.

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