The omnigenic model posits that genetic risk for traits with complex heritability involves cumulative effects of peripheral genes on mechanistic “core genes,” suggesting that in a network of genes, those closer to clusters including core genes should have higher GWAS signals. In gene co-expression networks, we confirmed that GWAS signals accumulate in genes more connected to risk-enriched gene clusters, highlighting across-network risk convergence. This was strongest in adult psychiatric disorders, especially schizophrenia (SCZ), spanning 70% of network genes, suggestive of super-polygenic architecture. In snRNA-seq cell type networks, SCZ risk convergence was strongest in L2/L3 excitatory neurons. We prioritized genes most connected to SCZ-GWAS genes, which showed robust association to a CRISPRa measure of PGC3 regulation and were consistently identified across several brain regions. Several genes, including dopamine-associated ones, were prioritized specifically in the striatum. This strategy thus retrieves current drug targets and can be used to prioritize other potential drug targets.

中文翻译：

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基因共表达的全网络风险收敛确定了精神分裂症风险的可重复遗传中心


全基因模型假设具有复杂遗传力的性状的遗传风险涉及外周基因对机械“核心基因”的累积影响，这表明在基因网络中，那些更靠近包括核心基因的簇的基因应该具有更高的 GWAS 信号。在基因共表达网络中，我们证实 GWAS 信号在与风险丰富的基因簇更相关的基因中积累，突出了跨网络风险收敛。这在成人精神疾病中最为强烈，尤其是精神分裂症 （SCZ），跨越 70% 的网络基因，表明超多基因结构。在 snRNA-seq 细胞类型网络中，SCZ 风险收敛在 L2/L3 兴奋性神经元中最强。我们优先考虑与 SCZ-GWAS 基因最相关的基因，这些基因与 PGC3 调节的 CRISPRa 测量显示出强大的关联，并且在多个大脑区域中被一致识别。几个基因，包括多巴胺相关的基因，在纹状体中被特别优先考虑。因此，该策略检索当前的药物靶点，并可用于优先考虑其他潜在的药物靶点。