Detection of Clinically Relevant Genetic Variants in Autism Spectrum Disorder by Whole-Genome Sequencing

Yong-hui Jiang, Ryan K.C. Yuen, Xin Jin, Mingbang Wang, Nong Chen, Xueli Wu, Jia Ju, Junpu Mei, Yujian Shi, Mingze He, Guangbiao Wang, Jieqin Liang, Zhe Wang, Dandan Cao, Melissa T. Carter, Christina Chrysler, Irene E. Drmic, Jennifer L. Howe, Lynette Lau, Christian R. Marshall, Daniele Merico, Thomas Nalpathamkalam, Bhooma Thiruvahindrapuram, Ann Thompson, Mohammed Uddin, Susan Walker, Jun Luo, Evdokia Anagnostou, Lonnie Zwaigenbaum, Robert H. Ring, Jian Wang, Clara Lajonchere, Jun Wang, Andy Shih, Peter Szatmari, Huanming Yang, Geraldine Dawson, Yingrui Li, Stephen W. Scherer

Autism Spectrum Disorder (ASD) demonstrates high heritability and familial clustering, yet the genetic causes remain only partially understood as a result of extensive clinical and genomic heterogeneity. Whole-genome sequencing (WGS) shows promise as a tool for identifying ASD risk genes as well as unreported mutations in known loci, but an assessment of its full utility in an ASD group has not been performed. We used WGS to examine 32 families with ASD to detect de novo or rare inherited genetic variants predicted to be deleterious (loss-of-function and damaging missense mutations). Among ASD probands, we identified deleterious de novo mutations in six of 32 (19%) families and X-linked or autosomal inherited alterations in ten of 32 (31%) families (some had combinations of mutations). The proportion of families identified with such putative mutations was larger than has been previously reported; this yield was in part due to the comprehensive and uniform coverage afforded by WGS. Deleterious variants were found in four unrecognized, nine known, and eight candidate ASD risk genes. Examples include CAPRIN1 and AFF2 (both linked to FMR1, which is involved in fragile X syndrome), VIP (involved in social-cognitive deficits), and other genes such as SCN2A and KCNQ2 (linked to epilepsy), NRXN1, and CHD7, which causes ASD-associated CHARGE syndrome. Taken together, these results suggest that WGS and thorough bioinformatic analyses for de novo and rare inherited mutations will improve the detection of genetic variants likely to be associated with ASD or its accompanying clinical symptoms.