Nature GeneticsGenetic & Genomic MedicinePeer-reviewed journal article
Genetic correlates of phenotypic heterogeneity in autism
Varun WarrieriD, Xinhe ZhangiD, Patrick Reed, Alexandra HavdahliD, Tyler M. MooreiD, Freddy CliquetiD, Claire S. LeblondiD, Thomas RollandiD, Anders RosengreniD, EU-AIMS LEAP, Antonia San José CáceresiD, Hannah HaywardiD, Daisy CrawleyiD, Jessica FaulkneriD, Jessica Sabet, Claire L. EllisiD, Bethany F. M. OakleyiD, Eva LothiD, Tony CharmaniD, Declan MurphyiD, Rosemary HoltiD, Jack Waldman, Jessica Upadhyay, Nicola Gunby, Meng‐Chuan LaiiD, , Simon Baron‐CoheniD
Abstract
The substantial phenotypic heterogeneity in autism limits our understanding of its genetic aetiology. To address this gap, we investigated genetic differences between autistic individuals (Nmax = 12,893) based on core (i.e., social communication difficulties, and restricted and repetitive behaviours) and associated features of autism, co-occurring developmental disabilities (e.g. language, motor, and intellectual developmental disabilities and delays), and sex. We conducted a comprehensive factor analysis of core autism features in autistic individuals and identified six factors. Common genetic variants including autism polygenic scores (PGS) were associated with the core factors but de novo variants were not, even though the latent factor structure was similar between carriers and non-carriers of de novo variants. We identify that increasing autism PGS decrease the likelihood of co- occurring developmental disabilities in autistic individuals, which reflects both a true protective effect and additivity between rare and common variants. Furthermore in autistic individuals without co-occurring intellectual disability (ID), autism PGS are overinherited by autistic females compared to males. Finally, we observe higher SNP heritability for males and autistic individuals without ID, but found no robust differences in SNP heritability by the level of core autism features. Deeper phenotypic characterisation will be critical to determining how the complex underlying genetics shapes cognition, behaviour, and co- occurring conditions in autism.
- organism: human
- assay: GWAS summary statistics
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 152
- FWCI
- 17.40
- Field percentile
- top 1%
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