Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA; Department of Medicine, New York University Grossman School of Medicine, New York, New York, USA.
Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA; Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany.
Kidney Int. 2022 Nov;102(5):1167-1177. doi: 10.1016/j.kint.2022.07.005. Epub 2022 Jul 21.
Investigations into the causal underpinnings of disease processes can be aided by the incorporation of genetic information. Genetic studies require populations varied in both ancestry and prevalent disease in order to optimize discovery and ensure generalizability of findings to the global population. Here, we report the genetic determinants of the serum proteome in 466 African Americans with chronic kidney disease attributed to hypertension from the richly phenotyped African American Study of Kidney Disease and Hypertension (AASK) study. Using the largest aptamer-based protein profiling platform to date (6,790 proteins or protein complexes), we identified 969 genetic associations with 900 unique proteins; including 52 novel cis (local) associations and 379 novel trans (distant) associations. The genetic effects of previously published cis-protein quantitative trait loci (pQTLs) were found to be highly reproducible, and we found evidence that our novel genetic signals colocalize with gene expression and disease processes. Many trans- pQTLs were found to reflect associations mediated by the circulating cis protein, and the common trans-pQTLs are enriched for processes involving extracellular vesicles, highlighting a plausible mechanism for distal regulation of the levels of secreted proteins. Thus, our study generates a valuable resource of genetic associations linking variants to protein levels and disease in an understudied patient population to inform future studies of drug targets and physiology.
对疾病发生机制的因果关系进行研究，可以借助遗传信息。遗传研究需要在祖先和常见疾病方面具有多样性的人群，以优化发现并确保研究结果能够推广到全球人群。在这里，我们报告了来自表型丰富的高血压致慢性肾脏病的非裔美国人研究（AASK）研究的 466 名非裔美国人的血清蛋白质组的遗传决定因素。利用迄今为止最大的基于适体的蛋白质分析平台（6790 种蛋白质或蛋白质复合物），我们鉴定出了 969 个与 900 种独特蛋白质相关的遗传关联；其中包括 52 个新的顺式（局部）关联和 379 个新的反式（远距离）关联。先前发表的顺式蛋白数量性状基因座（cis-pQTL）的遗传效应被发现具有高度可重复性，我们发现证据表明，我们新的遗传信号与基因表达和疾病过程存在共定位。许多反式-pQTL 被发现反映了由循环顺式蛋白介导的关联，而常见的反式-pQTL 富含涉及细胞外囊泡的过程，这突出了对分泌蛋白水平进行远距离调节的合理机制。因此，我们的研究生成了一个有价值的遗传关联资源，将变体与蛋白水平和疾病联系起来，为未来的药物靶点和生理学研究提供信息。
