Dataset Information

Investigating the genetic pathways of insomnia in Autism Spectrum Disorder.

ABSTRACT:

Background

Sleep problems are common in children with autism spectrum disorder (autism). There is sparse research to date to examine whether insomnia in people with autism is related to autism genetics or insomnia genetics. Moreover, there is a lack of research examining whether circadian-rhythm related genes share potential pathways with autism.

Aims

To address this research gap, we tested whether polygenic scores of insomnia or autism are related to risk of insomnia in people with autism, and whether the circadian genes are associated with insomnia in people with autism.

Methods and procedures

We tested these questions using the phenotypically and genotypically rich MSSNG dataset (N = 1049) as well as incorporating in the analyses data from the Vanderbilt University Biobank (BioVU) (N = 349).

Outcomes and results

In our meta-analyzed sample, there was no evidence of associations between the polygenic scores (PGS) for insomnia and a clinical diagnosis of insomnia, or between the PGS of autism and insomnia. We also did not find evidence of a greater burden of rare and disruptive variation in the melatonin and circadian genes in individuals with autism and insomnia compared to individuals with autism without insomnia.

Conclusions and implications

Overall, we did not find evidence for strong effects of genetic scores influencing sleep in people with autism, however, we cannot rule out the possibility that smaller genetic effects may play a role in sleep problems. Our study indicated the need for a larger collection of data on sleep problems and sleep quality among people with autism.

SUBMITTER: Niarchou M

PROVIDER: S-EPMC10068748 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Investigating the genetic pathways of insomnia in Autism Spectrum Disorder.

Niarchou Maria M Singer Emily V EV Straub Peter P Malow Beth A BA Davis Lea K LK

Research in developmental disabilities 20220709

<h4>Background</h4>Sleep problems are common in children with autism spectrum disorder (autism). There is sparse research to date to examine whether insomnia in people with autism is related to autism genetics or insomnia genetics. Moreover, there is a lack of research examining whether circadian-rhythm related genes share potential pathways with autism.<h4>Aims</h4>To address this research gap, we tested whether polygenic scores of insomnia or autism are related to risk of insomnia in people wi ...[more]

PMID: 35820265

Similar Datasets

Project description:BackgroundEarly identification and treatment of individuals with autism spectrum disorder (ASD) improves outcomes, but specific evidence needed to individualize treatment recommendations is lacking. Biomarkers that could be routinely measured within the clinical setting could potentially transform clinical care for patients with ASD. This demonstration project employed collection of biomarker data during regular autism specialty clinical visits and explored the relationship of biomarkers with clinical ASD symptoms.MethodsEighty-three children with ASD, aged 5-10 years, completed a multi-site feasibility study integrating the collection of biochemical (blood serotonin, urine melatonin sulfate excretion) and clinical (head circumference, dysmorphology exam, digit ratio, cognitive and behavioral function) biomarkers during routine ASD clinic visits. Parents completed a demographic survey and the Aberrant Behavior Checklist-Community. Cognitive function was determined by record review. Data analysis utilized Wilcoxon two-sample tests and Spearman correlations.ResultsParticipants were 82% male, 63% White, 19% Hispanic, with a broad range of functioning. Group means indicated hyperserotonemia. In a single regression analysis adjusting for race and median household income, higher income was associated with higher levels of blood serotonin and urine melatonin sulfate excretion levels (p = 0.004 and p = 0.04, respectively). Melatonin correlated negatively with age (p = 0.048) and reported neurologic problems (p = 0.02). Dysmorphic status correlated with higher reported stereotyped behavior (p = 0.02) and inappropriate speech (p = 0.04).ConclusionThis demonstration project employed collection of multiple biomarkers, allowed for examination of associations between biochemical and clinical measures, and identified several findings that suggest direction for future studies. This clinical research model has promise for integrative biomarker research in individuals with complex, heterogeneous neurodevelopmental disorders such as ASD.

Project description:BackgroundAutism spectrum disorder (ASD) is a neurodevelopmental condition characterized by atypical patterns of social functioning and repetitive/restricted behaviors. ASD commonly co-occurs with ADHD and, despite their clinical distinctiveness, the two share considerable genetic overlap. Given their shared genetic liability, it is unclear which genetic pathways increase the likelihood of ASD independently of ADHD.MethodsWe applied Genomic Structural Equation Modeling (SEM) to GWAS summary statistics for ASD and childhood-diagnosed ADHD, decomposing the genetic variance for ASD into that which is unique to ASD (uASD) and that which is shared with ADHD. We computed genetic correlations between uASD and 83 external traits to estimate genetic overlap between uASD and other clinically relevant phenotypes. We went on to apply Stratified Genomic SEM to identify classes of genes enriched for uASD. Finally, we implemented Transcriptome-Wide SEM (T-SEM) to explore patterns of gene-expression associated with uASD.ResultsWe observed positive genetic correlations between uASD and several external traits, most notably those relating to cognitive/educational outcomes and internalizing psychiatric traits. Stratified Genomic SEM showed that heritability for uASD was significantly enriched in genes involved in evolutionarily conserved processes, as well as for a histone mark in the germinal matrix. T-SEM revealed 83 unique genes with expression associated with uASD, 34 of which were novel with respect to univariate analyses. These genes were overrepresented in skin-related pathologies.LimitationsOur study was limited by summary statistics derived exclusively from individuals of European ancestry. Additionally, using data based on a general ASD diagnosis limits our ability to understand genetic factors contributing to the pronounced clinical heterogeneity in ASD.ConclusionsOur findings delineate the unique genetic underpinnings of ASD that are independent of ADHD at the genome-wide, functional, and gene expression level of analysis. In addition, we identify novel associations previously masked by their diametric effects on ADHD. Collectively, these results provide insight into the processes that make ASD biologically unique.

Dataset Information

Investigating the genetic pathways of insomnia in Autism Spectrum Disorder.

Background

Aims

Methods and procedures

Outcomes and results

Conclusions and implications

Publications

Investigating the genetic pathways of insomnia in Autism Spectrum Disorder.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets