Genome-wide Rare Variant Score Associates with Morphological Subtypes of Autism Spectrum Disorder

Overview

Journal Nat Commun

Specialty Biology

Date 2022 Oct 30

PMID 36309498

Authors

Ada J S Chan

Worrawat Engchuan

Miriam S Reuter

Zhuozhi Wang

Bhooma Thiruvahindrapuram

Brett Trost

Thomas Nalpathamkalam

Carol Negrijn

Sylvia Lamoureux

Giovanna Pellecchia

Rohan V Patel

Wilson W L Sung

Jeffrey R MacDonald

Jennifer L Howe

Jacob Vorstman

Neal Sondheimer

Nicole Takahashi

Judith H Miles

Evdokia Anagnostou

Kristiina Tammimies

Mehdi Zarrei

Daniele Merico

Dimitri J Stavropoulos

Ryan K C Yuen

Bridget A Fernandez

Stephen W Scherer

Affiliations

Soon will be listed here.

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). 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.

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