Background
Observational analyses have described hundreds of biomarkers for peripheral artery disease (PAD). These studies can be limited by sample size, lack of replication, residual confounding, and reverse causality. To assess this, we performed a systematic review of the literature and leveraged genetic approaches to causal inference.
Methods
We performed a systematic literature review for terms related to PAD and/or biomarkers using PubMed, the Cochrane database, and Embase, followed by manual review to extract biomarkers and their direction of effect. To test for evidence of causality we used two-sample Mendelian randomization. We developed genetic instruments for the biomarkers by mapping them to genome-wide association studies (GWAS) of circulating biomolecules agglomerated in the IEU Open GWAS project. We tested the association of the genetic instruments with PAD using summary statistics from a GWAS of 31,307 individuals with and 211,753 individuals without PAD in the VA Million Veteran Program. We used the Wald ratio or inverse variance weighted Mendelian randomization; weighted median and weighted mode methods were applied as sensitivity analyses.
Results
After manual review, we identified 159 unique papers mentioning 268 unique PAD biomarkers. We mapped 76 biomarkers to genetic data, 19 of which were nominally associated with PAD (P < .05). After accounting for multiple testing (false discovery rate of <0.05), 12 remained significant, of which only 7 had concordant directions of effect with published reports: ApoB, ApoA1, high-density lipoprotein-associated cholesterol, triglycerides, Von Willebrand factor, cadherin-5, and b2-microglobulin.
Conclusions
This systematic review paired with genetic causal inference illuminates key biomarkers causally relevant to PAD, and highlights discrepancies between observational and genetic findings. This highlights the importance of rigorous analysis of observational biomarker data and the opportunity to leverage human genetics to inform these studies.
Article info
Publication history
Published online: June 10, 2022
22-VIRC-529-AHA-VDFootnotes
Author Disclosures: P. Sharma: Nothing to disclose; M. Levin: Nothing to disclose; D. Klarin: Nothing to disclose; B. F. Voight: Other, American Medical Association; S. M. Damrauer: Other, US Patent, Calcio Labs; Research Grant, RenalytixAI
Identification
Copyright
© 2022 Published by Elsevier Inc.
User license
Creative Commons Attribution – NonCommercial – NoDerivs (CC BY-NC-ND 4.0) | How you can reuse
Elsevier's open access license policy

Creative Commons Attribution – NonCommercial – NoDerivs (CC BY-NC-ND 4.0)
Permitted
For non-commercial purposes:
- Read, print & download
- Redistribute or republish the final article
- Text & data mine
- Translate the article (private use only, not for distribution)
- Reuse portions or extracts from the article in other works
Not Permitted
- Sell or re-use for commercial purposes
- Distribute translations or adaptations of the article
Elsevier's open access license policy