Evaluation of Plasma Biomarkers for Causal Association With Peripheral Artery Disease

孟德尔随机化 观察研究 混淆 遗传关联 因果推理 全基因组关联研究 医学 疾病 生物标志物 因果关系(物理学) 内科学 生物信息学 病理 生物 遗传学 基因 基因型 遗传变异 物理 量子力学 单核苷酸多态性
作者
Pranav Sharma,Derek Klarin,Benjamin F. Voight,Philip S. Tsao,Michael G. Levin,Scott M. Damrauer
出处
期刊:Arteriosclerosis, Thrombosis, and Vascular Biology [Lippincott Williams & Wilkins]
卷期号:44 (5): 1114-1123 被引量:2
标识
DOI:10.1161/atvbaha.124.320674
摘要

BACKGROUND: Hundreds of biomarkers for peripheral artery disease (PAD) have been reported in the literature; however, the observational nature of these studies limits causal inference due to the potential of reverse causality and residual confounding. We sought to evaluate the potential causal impact of putative PAD biomarkers identified in human observational studies through genetic causal inference methods. METHODS: Putative circulating PAD biomarkers were identified from human observational studies through a comprehensive literature search based on terms related to PAD using PubMed, Cochrane, and Embase. Genetic instruments were generated from publicly available genome-wide association studies of circulating biomarkers. Two-sample Mendelian randomization was used to test the association of genetically determined biomarker levels with PAD using summary statistics from a genome-wide association study of 31 307 individuals with and 211 753 individuals without PAD in the Veterans Affairs Million Veteran Program and replicated in data from FinnGen comprised of 11 924 individuals with and 288 638 individuals without PAD. RESULTS: We identified 204 unique circulating biomarkers for PAD from the observational literature, of which 173 were genetically instrumented using genome-wide association study results. After accounting for multiple testing (false discovery rate, <0.05), 10 of 173 (5.8%) biomarkers had significant associations with PAD. These 10 biomarkers represented categories including plasma lipoprotein regulation, lipid homeostasis, and protein-lipid complex remodeling. Observational literature highlighted different pathways including inflammatory response, negative regulation of multicellular organismal processes, and regulation of response to external stimuli. CONCLUSIONS: Integrating human observational studies and genetic causal inference highlights several key pathways in PAD pathophysiology. This work demonstrates that a substantial portion of biomarkers identified in observational studies are not well supported by human genetic evidence and emphasizes the importance of triangulating evidence to understand PAD pathophysiology. Although the identified biomarkers offer insights into atherosclerotic development in the lower limb, their specificity to PAD compared with more widespread atherosclerosis requires further study.
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