Hirohama Daigoro, Fadista João, Ha Eunji, Liu Hongbo, Abedini Amin, Levinsohn Jonathan, Vassalotti Allison, Zeng Li, Li Chenyu, Mohandes Samer, Vitale Steven, Shungin Dmitry, Nguyen Thao, Niewczas Monika A, Olsson Niclas, McAllister Fiona E, Karihaloo Anil, Susztak Katalin
Department of Medicine, Renal Electrolyte and Hypertension Division, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Institute of Diabetes, Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA.
Nat Med. 2025 Aug 12. doi: 10.1038/s41591-025-03872-8.
Nearly one-third of the global population is affected by cardio-kidney-metabolic (CKM) diseases; however, the molecular mechanisms underlying CKM diseases are poorly understood. Here we show that tissue proteomics provide critical insights not captured by tissue gene expression or blood proteomics information by performing whole-genome and RNA sequencing and proteomics analysis of human kidney samples (n = 337), and we generated a publicly available database. Via Bayesian co-localization and Mendelian randomization analyses of kidney protein quantitative trait loci and 36 CKM genome-wide association studies, we prioritized 89 proteins for CKM traits. We prioritized relationships that could underlie the interconnectedness of CKM traits and discovered multiple and targetable mechanisms for CKM diseases, including the potential role of kidney angiopoietin-like protein 3 (ANGPTL3) in serum lipid levels and kidney function as well as the role of charged multivesicular body protein 1A in kidney function and hypertension. Notably, we identify pathways with confluence of evidence from genetic loci, tissue gene expression and protein levels for CKM traits. In summary, our large-scale kidney proteomics study uncovers proteins and targetable mechanisms prioritized for CKM diseases.
全球近三分之一的人口受到心脏-肾脏-代谢(CKM)疾病的影响;然而,人们对CKM疾病背后的分子机制了解甚少。在这里,我们通过对人类肾脏样本(n = 337)进行全基因组、RNA测序和蛋白质组学分析,表明组织蛋白质组学提供了组织基因表达或血液蛋白质组学信息未捕捉到的关键见解,并且我们生成了一个可供公众使用的数据库。通过对肾脏蛋白质定量性状位点和36项CKM全基因组关联研究进行贝叶斯共定位和孟德尔随机化分析,我们为CKM性状确定了89种蛋白质的优先级。我们确定了可能构成CKM性状相互联系基础的关系,并发现了CKM疾病的多种可靶向机制,包括肾脏血管生成素样蛋白3(ANGPTL3)在血脂水平和肾功能中的潜在作用,以及带电荷多囊泡体蛋白1A在肾功能和高血压中的作用。值得注意的是,我们确定了来自遗传位点、组织基因表达和CKM性状蛋白质水平的证据汇聚的途径。总之,我们的大规模肾脏蛋白质组学研究揭示了为CKM疾病确定优先级的蛋白质和可靶向机制。