Genome-wide prediction and functional characterization of the genetic basis of autism spectrum disorder

Abstract

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with a strong genetic basis. Yet, only a small fraction of potentially causal genes—about 65 genes out of an estimated several hundred—are known with strong genetic evidence from sequencing studies. We developed a complementary machine-learning approach based on a human brain-specific gene network to present a genome-wide prediction of autism risk genes, including hundreds of candidates for which there is minimal or no prior genetic evidence. Our approach was validated in a large independent case–control sequencing study. Leveraging these genomewide predictions and the brain-specific network, we demonstrated that the large set of ASD genes converges on a smaller number of key pathways and developmental stages of the brain. Finally, we identified likely pathogenic genes within frequent autism-associated copy-number variants and proposed genes and pathways that are likely mediators of ASD across multiple copy-number variants. All predictions and functional insights are available at http://asd.princeton.edu.

Exonic Mosaic Mutations Contribute Risk for Autism Spectrum Disorder

“…We evaluated rankings based on gene mutation intolerance (LGD rank, LGD-RVIS average rank) 33 or based on a human brain-specific gene functional interaction network (ASD association). 38 At the population level, we found only nonsignificant increases in LGD-RVIS rankings for proband synonymous and essential missense PMMs in the subcohort of families without any proband NS GDMs (p ¼ 0.029 and p ¼ 0.073, one-sided WRST). We also observed no significant shifts in rankings for missense GDMs.…”

“…Gene set enrichment was evaluated using a binomial test in R binom.test(x, n, p), where x ¼ number of genes impact within set, n ¼ total number of genes impacted, and p ¼ expected mean based on joint coverage. Genome-wide gene rankings generated from two previous studies 33,38 were used to determine whether genes targeted by missense or synonymous mutations in probands showed enrichment for ASD candidate gene rankings. The LGD intolerance ranking is based on the load of LGD mutations observed per gene.…”

“…In probands, we found Recently, several groups have taken different approaches to generate genome-wide ASD candidate risk gene rankings and predict novel gene targets. 33,38 These approaches have largely been validated on LGD GDMs. We explored whether our high-confidence PMM calls showed any shift in ASD candidate gene rankings for probands compared with their unaffected siblings (Table S10).…”

The connectomes of males and females with autism spectrum disorder have significantly different white matter connectivity densities

“…In 2016, Krishnan et al 38. studied ASD-associated genetic changes in the spatiotemporal development of the brain as well as the enrichment of prominent gene expression signatures (sets of genes highly expressed in a certain brain region) in a genome-wide ranking of ASD genes.…”

2017 WONOEP appraisal: Studying epilepsy as a network disease using systems biology approaches

“…22,[68][69][70] Weighted gene coexpression network analysis Not limited by current pathway annotations, but only as robust as the prediction models used to build the networks.…”