Evaluation of Plasma Biomarkers for Causal Association With Peripheral Artery Disease

Author:

Sharma Pranav1ORCID,Klarin Derek23ORCID,Voight Benjamin F.456ORCID,Tsao Philip S.27ORCID,Levin Michael G.86ORCID,Damrauer Scott M.1496

Affiliation:

1. Department of Surgery, Perelman School of Medicine (P.S., S.M.D.), University of Pennsylvania, Philadelphia.

2. Veterans Affairs Palo Alto Healthcare System, CA (D.K., P.S.T.).

3. Division of Vascular Surgery (D.K.), Stanford University School of Medicine, CA.

4. Department of Genetics (B.F.V., S.M.D.), University of Pennsylvania, Philadelphia.

5. Department of Systems Pharmacology and Translational Therapeutics (B.F.V.), University of Pennsylvania, Philadelphia.

6. Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA (B.F.V., M.G.L., S.M.D.).

7. Division of Cardiovascular Medicine, Department of Medicine (P.S.T.), Stanford University School of Medicine, CA.

8. Division of Cardiovascular Medicine, Department of Medicine, Perelman School of Medicine (M.G.L.), University of Pennsylvania, Philadelphia.

9. Cardiovascular Institute (S.M.D.), University of Pennsylvania, Philadelphia.

Abstract

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.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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