Peripheral artery disease (PAD) is a significant contributor in cardiovascular morbidity and mortality; However, detection of PAD in a timely manner remains “elusive,” according to a study lead authored by Fudi Wang, MD, PhD, and colleagues from the Stanford University School of Medicine. Dr. Wang and colleagues evaluated genome-wide associations studies (GWAS) to determine if genome-wide polygenic risk scores (PRS), could improve the detection of patients with a high-risk of having PAD. According to their article, published in Vascular Medicine, the use of genome-wide PRSs was able to distinguish risk for PAD, as well as other cardiovascular diseases, in a large dataset.
The investigations used summary statistical data from the largest PAD GWAD in the Million Veteran Program, the study’s authors developed a PRS system based on genomic indicators from the UK Biobank. The primary objective of the study was to evaluate the “clinical utility of adding the best-performing PRS to a PAD clinical risk score.”
The investigation included a total of 5,759 cases of PAD within the full cohort of 487,320 patients. After assigning PRSs to the data, the researchers calculated that patients in the highest decile of PRS had 3.1-times higher odds of carrying PAD compared to patients with the lowest 10% of scores (95% confidence interval [CI], 3.06–3.21), supporting the feasibility of detecting risk for PAD via PRS. Additionally, the authors reported that a PAD PRS was associated with an “increased risk of having coronary artery disease, congestive heart failure, and cerebrovascular disease. The PRS profile also significantly improved a clinical risk model (Net Reclassification Index = 0.07; p <0.001), primarily by lowering the risk ranking of control cases. Lastly, the authors calculated an area under the curve of 0.76 (95% CI, 0.75–0.77) in the PAD detection model.
Overall, the study’s contributors presented their model as a potentially effective improvement in the current detection of risk of PAD. In closing, the authors considered that “adding a PAD PRS to clinical risk models may help improve detection of prevalent, but undiagnosed disease.”