Whole-exome sequencing studies have been useful for identifying genes that, when mutated, affect risk for autism spectrum disorder (ASD). Nonetheless, the association signal primarily arises from de novo protein-truncating variants, as opposed to the more common missense variants. Despite their commonness in humans, determining which missense variants affect phenotypes and how remains a challenge. We investigate the functional relevance of de novo missense variants, specifically whether they are likely to disrupt protein interactions, and nominate novel genes in risk for ASD through integrated genomic, transcriptomic, and proteomic analyses. Utilizing our previous interactome perturbation predictor, we identify a set of missense variants that are likely disruptive to protein–protein interactions. For genes encoding the disrupted interactions, we evaluate their expression patterns across developing brains and within specific cell types, using both bulk and inferred cell-type-specific brain transcriptomes. Connecting all disrupted pairs of proteins, we construct an “ASD disrupted network.” Finally, we integrate protein interactions and cell-type-specific co-expression networks together with published association data to implicate novel genes in ASD risk in a cell-type-specific manner. Extending earlier work, we show that de novo missense variants that disrupt protein interactions are enriched in individuals with ASD, often affecting hub proteins and disrupting hub interactions. Genes encoding disrupted complementary interactors tend to be risk genes, and an interaction network built from these proteins is enriched for ASD proteins. Consistent with other studies, genes identified by disrupted protein interactions are expressed early in development and in excitatory and inhibitory neuronal lineages. Using inferred gene co-expression for three neuronal cell types—excitatory, inhibitory, and neural progenitor—we implicate several hundred genes in risk (FDR $$\le \hspace{0.17em}$$ 0.05), ~ 60% novel, with characteristics of genuine ASD genes. Across cell types, these genes affect neuronal morphogenesis and neuronal communication, while neural progenitor cells show strong enrichment for development of the limbic system. Some analyses use the imperfect guilt-by-association principle; results are statistical, not functional. Disrupted protein interactions identify gene sets involved in risk for ASD. Their gene expression during brain development and within cell types highlights how they relate to ASD.

中文翻译：

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从头错义变异破坏蛋白质-蛋白质相互作用，通过神经元细胞类型中的基因共表达和蛋白质网络影响自闭症风险


全外显子组测序研究对于识别突变后影响自闭症谱系障碍 (ASD) 风险的基因非常有用。尽管如此，关联信号主要来自从头蛋白质截短变体，而不是更常见的错义变体。尽管错义变异在人类中很常见，但确定哪些错义变异影响表型以及如何影响表型仍然是一个挑战。我们研究了从头错义变异的功能相关性，特别是它们是否可能破坏蛋白质相互作用，并通过综合基因组、转录组和蛋白质组分析提名有 ASD 风险的新基因。利用我们之前的相互作用组扰动预测器，我们识别出一组可能破坏蛋白质-蛋白质相互作用的错义变异。对于编码被破坏的相互作用的基因，我们使用大量和推断的细胞类型特异性大脑转录组来评估它们在发育中的大脑和特定细胞类型内的表达模式。连接所有被破坏的蛋白质对，我们构建了一个“ASD 破坏网络”。最后，我们将蛋白质相互作用和细胞类型特异性共表达网络与已发表的关联数据整合在一起，以细胞类型特异性的方式暗示新基因与 ASD 风险有关。扩展早期的工作，我们发现破坏蛋白质相互作用的从头错义变异在患有自闭症谱系障碍的个体中丰富，通常影响中枢蛋白质并破坏中枢相互作用。编码被破坏的互补相互作用子的基因往往是风险基因，并且由这些蛋白质构建的相互作用网络富含 ASD 蛋白质。 与其他研究一致，通过破坏蛋白质相互作用鉴定出的基因在发育早期以及兴奋性和抑制性神经元谱系中表达。使用三种神经元细胞类型（兴奋性细胞、抑制性细胞和神经祖细胞）的推断基因共表达，我们发现数百个基因存在风险（FDR $$\le \hspace{0.17em}$$ 0.05），约 60% 是新颖的，真正的 ASD 基因的特征。在不同的细胞类型中，这些基因影响神经元形态发生和神经元通讯，而神经祖细胞显示出对边缘系统发育的强烈富集。一些分析使用了不完善的关联有罪原则；结果是统计性的，而不是功能性的。蛋白质相互作用中断可识别与 ASD 风险相关的基因组。它们在大脑发育过程中和细胞类型内的基因表达突显了它们与自闭症谱系障碍的关系。