Proteomic insights into the associations between obesity, lifestyle factors, and coronary artery disease

医学 冠状动脉疾病 全基因组关联研究 生物信息学 孟德尔随机化 内科学 连锁不平衡 遗传关联 遗传学 单核苷酸多态性 生物 等位基因 单倍型 基因 基因型 遗传变异
作者
Fangkun Yang,Fengzhe Xu,Han Zhang,Dipender Gill,Susanna C. Larsson,Xue Li,Hanbin Cui,Shuai Yuan
出处
期刊:BMC Medicine [Springer Nature]
卷期号:21 (1)
标识
DOI:10.1186/s12916-023-03197-8
摘要

Abstract Background We aimed to investigate the protein pathways linking obesity and lifestyle factors to coronary artery disease (CAD). Methods Summary-level genome-wide association statistics of CAD were obtained from the CARDIoGRAMplusC4D consortium (60,801 cases and 123,504 controls) and the FinnGen study (R8, 39,036 cases and 303,463 controls). Proteome-wide Mendelian randomization (MR) analysis was conducted to identify CAD-associated blood proteins, supplemented by colocalization analysis to minimize potential bias caused by linkage disequilibrium. Two-sample MR analyses were performed to assess the associations of genetically predicted four obesity measures and 13 lifestyle factors with CAD risk and CAD-associated proteins’ levels. A two-step network MR analysis was conducted to explore the mediating effects of proteins in the associations between these modifiable factors and CAD. Results Genetically predicted levels of 41 circulating proteins were associated with CAD, and 17 of them were supported by medium to high colocalization evidence. PTK7 (protein tyrosine kinase-7), RGMB (repulsive guidance molecule BMP co-receptor B), TAGLN2 (transgelin-2), TIMP3 (tissue inhibitor of metalloproteinases 3), and VIM (vimentin) were identified as promising therapeutic targets. Several proteins were found to mediate the associations between some modifiable factors and CAD, with PCSK9, C1S, AGER (advanced glycosylation end product-specific receptor), and MST1 (mammalian Ste20-like kinase 1) exhibiting highest frequency among the mediating networks. Conclusions This study suggests pathways explaining the associations of obesity and lifestyle factors with CAD from alterations in blood protein levels. These insights may be used to prioritize therapeutic intervention for further study.
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