蛋白质组范围内孟德尔随机化确定心血管疾病的候选致病蛋白

Chen Li, Nicolas De Jay, Shan-Shan Zhang, Xin Fang, Supriya Sharma, Katrina A. Catalano, Venkatesh Sridharan, Zhaoqing Wang, Lei Zhao, Joseph D. Szustakowski, Ching-Pin Chang, Joseph C. Maranville, Emily R. Holzinger, Erika M. Kvikstad
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引用次数: 0

摘要

跨不同祖先的人类基因组学和其他组学的整合为目标识别提供了新颖、经济、系统的方法。我们使用孟德尔随机化方法来揭示2940种循环蛋白与19种心血管疾病之间的因果关系。我们发现218个蛋白通过正向MR影响一种或多种CVD的风险(106个和182个分别使用顺式pqtl和顺式+反式pqtl),其中107个先前报道与CVD或CVD相关性状相关。有102个蛋白被复制(FDR <;使用FinnGen Olink数据,53例仅为顺式pqtl, 88例为顺式+ trans- pqtl。BTN3A2被认为是缺血性脑卒中的一个新的候选基因,提示免疫调节与脑卒中发病机制之间存在相互作用。单细胞整合优先考虑稳定型心绞痛和室性心律失常的PAM和外周动脉疾病的LPL,其转录表达在心肌细胞中富集。正向和反向MR发现大部分不重叠的蛋白质(只有2个重叠:LGALS4和MMP12),提示CVD的不同蛋白质组原因和后果。我们的研究为新的候选基因提供了基于人类遗传学的证据,为全面的基于人类生物学的心血管疾病药物发现奠定了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Proteome-Wide Mendelian Randomization Identifies Candidate Causal Proteins for Cardiovascular Diseases

Proteome-Wide Mendelian Randomization Identifies Candidate Causal Proteins for Cardiovascular Diseases

Integration of human genomics and other omics across different ancestries provides novel, affordable, and systematic approach for target identification. We used Mendelian randomization approaches to unravel causal associations between 2,940 circulating proteins and 19 CVD. We found 218 proteins that impacted risk of one or more CVDs through forward MR (106 and 182 using cis-pQTLs only and cis- + trans-pQTLs, respectively), among which 107 were previously reported as associated with CVD or CVD-related traits. There were 102 proteins replicated (FDR < 5%, 53 with cis-pQTLs only and 88 with cis- + trans-pQTLs) using the FinnGen Olink data. BTN3A2 was highlighted as a novel candidate gene for ischemic stroke, suggesting a crosstalk between immune modulation and stroke pathogenesis. Single cell integration prioritized PAM for stable angina pectoris and ventricular arrhythmia and LPL for peripheral artery disease, whose transcriptional expressions were enriched in cardiomyocytes. Forward and reverse MR found largely non-overlapping proteins (only 2 overlapped: LGALS4 and MMP12), suggesting distinct proteomic causes and consequences of CVD. Our study provides human genetics-based evidence of novel candidate genes, a foundational step towards full-scale causal human biology-based drug discovery for CVD.

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