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Transcriptional subtyping explains phenotypic variability in genetic subtypes of autism spectrum disorder.

ABSTRACT: Autism spectrum disorder (ASD) is a common neurodevelopmental disorder characterized by deficits in social communication and presence of restricted, repetitive behaviors, and interests. However, individuals with ASD vary significantly in their challenges and abilities in these and other developmental domains. Gene discovery in ASD has accelerated in the past decade, and genetic subtyping has yielded preliminary evidence of utility in parsing phenotypic heterogeneity through genomic subtypes. Recent advances in transcriptomics have provided additional dimensions with which to refine genetic subtyping efforts. In the current study, we investigate phenotypic differences among transcriptional subtypes defined by neurobiological spatiotemporal co-expression patterns. Of the four transcriptional subtypes examined, participants with mutations to genes typically expressed highly in all brain regions prenatally, and those with differential postnatal cerebellar expression relative to other brain regions, showed lower cognitive and adaptive skills, higher severity of social communication deficits, and later acquisition of speech and motor milestones, compared to those with mutations to genes highly expressed during the postnatal period across brain regions. These findings suggest higher-order characterization of genetic subtypes based on neurobiological expression patterns may be a promising approach to parsing phenotypic heterogeneity among those with ASD and related neurodevelopmental disorders.

SUBMITTER: Trinh S

PROVIDER: S-EPMC7709958 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Transcriptional subtyping explains phenotypic variability in genetic subtypes of autism spectrum disorder.

Trinh Sandy S Arnett Anne A Kurtz-Nelson Evangeline E Beighley Jennifer J Picoto Marta M Bernier Raphael R

Development and psychopathology 20201001 4

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder characterized by deficits in social communication and presence of restricted, repetitive behaviors, and interests. However, individuals with ASD vary significantly in their challenges and abilities in these and other developmental domains. Gene discovery in ASD has accelerated in the past decade, and genetic subtyping has yielded preliminary evidence of utility in parsing phenotypic heterogeneity through genomic subtypes. Rec ...[more]

PMID: 32912353

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Project description:Approximately one-fourth of autism spectrum disorder (ASD) cases are associated with a disruptive genetic variant. Many of these ASD genotypes have been described previously, and are characterized by unique constellations of medical, psychiatric, developmental, and behavioral features. Development of precision medicine care for affected individuals has been challenging due to the phenotypic heterogeneity that exists even within each genetic subtype. In the present study, we identify developmental milestones that predict cognitive and adaptive outcomes for five of the most common ASD genotypes. Sixty-five youth with a known pathogenic variant involving ADNP, CHD8, DYRK1A, GRIN2B, or SCN2A genes participated in cognitive and adaptive testing. Exploratory linear regressions were used to identify developmental milestones that predicted cognitive and adaptive outcomes within each gene group. We hypothesized that the earliest and most predictive milestones would vary across gene groups, but would be consistent across outcomes within each genetic subtype. Within the ADNP group, age of walking predicted cognitive outcomes, while age of first words predicted adaptive behaviors. Age of phrases predicted adaptive functioning in the CHD8 group, but cognitive outcomes were not clearly associated with early developmental milestones. Verbal milestones were the strongest predictors of cognitive and adaptive outcomes for individuals with mutations to DYRK1A, GRIN2B, or SCN2A. These trends inform decisions about treatment planning and long-term expectations for affected individuals, and they add to the growing body of research linking molecular genetic function to brain development and phenotypic outcomes. LAY SUMMARY: Researchers have found many genetic causes of autism including mutations to ADNP, CHD8, DYRK1A, GRIN2B, and SCN2A genes. We found that each genetic cause had different early developmental milestones that explained the overall functioning of the children when they were older. Depending on the genetic cause, the age that a child first starts walking and/or talking may help to better understand and support a child's development who has a mutation to one of the above genes. Autism Res 2020, 13: 1659-1669. © 2020 International Society for Autism Research and Wiley Periodicals LLC.

Project description:Interest in autonomic arousal in autism spectrum disorder (ASD) is increasing; however, reliability of these measures in ASD is unknown, and previously reported associations with social and cognitive abilities are inconsistent. This study assesses heart rate (HR) and HR variability (HRV) in preschoolers with ASD or typical development (TD) while they passively watched naturalistic videos. Measurement reliability, group differences, and the relationship with social and cognitive abilities were evaluated. Seventy one ASD and 66 TD children (2-4 years) provided cardiac data from two sessions. Test-retest intraclass correlations of HR and HRV over a 3-week period were moderate to good in both groups. Groups did not differ in mean level of HR or HRV. Intra-individual variability of HR between video segments within a session was higher in the ASD group, but intraclass correlations of this metric were low. Higher HR related to better language skills in TD children, but not after accounting for age and nonverbal ability. Higher HRV related to better expressive and receptive language in ASD children after controlling for age and nonverbal ability. HR/HRV were not related to social or executive functioning skills and did not explain any additional variance in abilities at a 12-month follow-up visit. In summary, variation in language abilities is associated with HR in the TD group and HRV in the ASD group. While preliminary, these results are promising for consideration of autonomic control as a biomarker for individual differences in ASD and may help us understand the mechanisms that contribute to communication skills. Autism Research 2019, 12: 39-52. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Cardiac activity, such as heart rate and heart rate variability, is linked to a wide range of psychological functions. This study shows that there is an association between heart rate and heart rate variability and language skills in young children with autism spectrum disorder (ASD). These results may help us understand what underlies individual differences in developmental abilities in young children with ASD.

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.

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Transcriptional subtyping explains phenotypic variability in genetic subtypes of autism spectrum disorder.

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Transcriptional subtyping explains phenotypic variability in genetic subtypes of autism spectrum disorder.

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