Wright Sarah N, Yang Jane, Ideker Trey
Department of Medicine, University of California, San Diego, La Jolla, CA 92093, USA.
Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA 92093, USA.
medRxiv. 2025 Jun 28:2025.06.27.25330419. doi: 10.1101/2025.06.27.25330419.
While both common and rare variants contribute to the genetic etiology of complex traits, whether their impacts manifest through the same effector genes and molecular mechanisms is not well understood. Here, we systematically analyze common and rare variants associated with each of 373 phenotypic traits within a large biological knowledge network of gene and protein interactions. While common and rare variants implicate few shared genes, they converge on shared molecular networks for more than 75% of traits. We demonstrate that the strength of this convergence is influenced by core factors such as trait heritability, gene mutational constraints, and tissue specificity. Using neuropsychiatric traits as examples, we show that common and rare variants impact shared functions across multiple levels of biological organization. These findings underscore the importance of integrating variants across the frequency spectrum and establish a foundation for network-based investigations of the genetics of diverse human diseases and phenotypes.
虽然常见变异和罕见变异都对复杂性状的遗传病因有贡献，但它们的影响是否通过相同的效应基因和分子机制表现出来，目前还不太清楚。在这里，我们在一个由基因和蛋白质相互作用组成的大型生物知识网络中，系统地分析了与373种表型性状中的每一种相关的常见变异和罕见变异。虽然常见变异和罕见变异涉及的共享基因很少，但它们在超过75%的性状上汇聚于共享的分子网络。我们证明，这种汇聚的强度受到诸如性状遗传力、基因突变限制和组织特异性等核心因素的影响。以神经精神性状为例，我们表明常见变异和罕见变异在生物组织的多个层面上影响共享功能。这些发现强调了整合不同频率谱变异的重要性，并为基于网络的各种人类疾病和表型遗传学研究奠定了基础。
