SummaryThe genetic architecture of autism spectrum disorder involves the interplay of common and rare variation and their impact on hundreds of genes. Using exome sequencing, analysis of rare coding variation in 3,871 autism cases and 9,937 ancestry-matched or parental controls implicates 22 autosomal genes at a false discovery rate (FDR) < 0.05, and a set of 107 autosomal genes strongly enriched for those likely to affect risk (FDR < 0.30). These 107 genes, which show unusual evolutionary constraint against mutations, incur de novo loss-of-function mutations in over 5% of autistic subjects. Many of the genes implicated encode proteins for synaptic, transcriptional, and chromatin remodeling pathways. These include voltage-gated ion channels regulating propagation of action potentials, pacemaking, and excitability-transcription coupling, as well as histone-modifying enzymes and chromatin remodelers, prominently histone post-translational modifications involving lysine methylation/demethylation.
Supplemental Figure 1 Method: All MS runs were compared and clustered using standard artMS ( https://github.com/biodavidjm/artMS ) procedures on observed feature intensities computed by MaxQuant. Supplemental Figure 1 shows all Pearson's pairwise correlations between MS runs, and are clustered according to similar correlation patterns. Supplemental Figure 2 Method: See main text. Supplemental Figure 3 Method: PFAM domain enrichment analysis. The enrichment of individual PFAM domains (or PFAM clans) 1 was calculated with a hypergeometric test where success is defined as number of domains, and the number of trials is the number of individual preys pulled-down with each viral bait. The population values were the numbers of individual PFAM domains and clans in the human proteome.To make sure that the p-values that signify enrichment were meaningful, we only considered PFAM domains that have been pulled-down at least three times with any SARS-CoV-2 protein, and which occur in the human proteome at least five times. In SI Figure 3 we show PFAM domains/clans with the lowest p-value for a given viral bait protein.
Highlights d 102 genes implicated in risk for autism spectrum disorder (ASD genes, FDR % 0.1) d Most are expressed and enriched early in excitatory and inhibitory neuronal lineages d Most affect synapses or regulate other genes; how these roles dovetail is unknown d Some ASD genes alter early development broadly, others appear more specific to ASD
Autism spectrum disorder (ASD) risk is influenced by common polygenic and de novo variation.We aimed to clarify the influence of polygenic risk for ASDs and to identify subgroups of ASD cases, including those with strong acting de novo variants, in which polygenic risk is relevant.Using a novel approach called the polygenic transmission disequilibrium test, and data from 6,454 families with a child with ASD, we show that polygenic risk for ASDs, schizophrenia, and greater educational attainment is over transmitted to children with ASDs. These findings hold independent of proband IQ. We find that polygenic variation contributes additively to risk in ASD cases who carry a strong acting de novo variant. Lastly, we show that elements of polygenic risk are independent and differ in their relationship with phenotype. These results confirm that ASDs' genetic influences are additive and suggest they create risk through at least partially distinct etiologic pathways.
Almost all genetic risk factors for autism spectrum disorders (ASDs) can be found in the general population, but the effects of that risk are unclear in people not ascertained for neuropsychiatric symptoms. Using several large ASD consortia and population based resources, we find genetic links between ASDs and typical variation in social behavior and adaptive functioning. This finding is evidenced through both inherited and de novo variation, indicating that multiple types of genetic risk for ASDs influence a continuum of behavioral and developmental traits, the severe tail of which can result in an ASD or other neuropsychiatric disorder diagnosis. A continuum model should inform the design and interpretation of studies of neuropsychiatric disease biology.
Competing Interests B.M.N. is on the Scientific Advisory Board at Deep Genomics and Camp4 Therapeutics Corporation, and on the Biogen Genomics Advisory Panel. M.F. is an employee of Verily Life Sciences. Accession codes Data included in this manuscript have been deposited in the database of Genotypes and Phenotypes (dbGaP) under accession number phs001196.v1. Data collection and analysis were not performed blind to the conditions of the experiments. Data availability Data included in this manuscript have been deposited in the database of Genotypes and Phenotypes (dbGaP) under accession number phs001196.v1. Data collection and analysis were not performed blind to the conditions of the experiments.
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