Polygenic Risk Scores for Predicting Adverse Outcomes After Coronary Revascularization

  • Jenni Aittokallio
  • Anni Kauko
  • Felix Vaura
  • Veikko Salomaa
  • Tuomas Kiviniemi
  • FinnGen
  • Renate B Schnabel
  • Teemu Niiranen

Related Research units

Abstract

Coronary procedures predispose patients to adverse events. To improve our understanding of the genetic factors underlying postoperative prognosis, we studied the association of polygenic risk scores (PRSs) with postprocedural complications in coronary patients who underwent revascularization. The study sample comprised 8,296, 6,132, and 13,082 patients who underwent percutaneous coronary intervention, coronary artery bypass grafting, or any revascularization, respectively. We genotyped all subjects and identified adverse events during follow-up of up to 30 years by record linkage with nationwide healthcare registers. We computed PRSs for each postoperative adverse outcome (atrial fibrillation [AF], myocardial infarction, stroke, and bleeding complications) for all participants. Cox proportional hazards models were used to examine the association between PRSs and outcomes. A 1-SD increase in AF-PRS was associated with greater risk of postoperative AF with hazard ratios of 1.22 (95% confidence interval [CI] 1.16 to 1.28), 1.15 (95% CI 1.10 to 1.20) and 1.18 (95% CI 1.14 to 1.22) after percutaneous coronary intervention, coronary artery bypass grafting, and any revascularization, respectively. In contrast, the association of each PRSs with other postoperative complications was nonexistent to marginal. Inclusion of the AF-PRS in a model with a clinical risk score resulted in significant model improvement (increase in model c-statistic 0.0059 to 0.0098 depending on procedure; p <0.0002 for all). In conclusion, our results demonstrate that PRS can be used for AF risk-prediction in patients who underwent revascularization. The AF-PRS could potentially be used to improve AF prevention and outcomes in patients who underwent revascularization.

Bibliographical data

Original languageEnglish
ISSN0002-9149
DOIs
Publication statusPublished - 15.03.2022

Comment Deanary

Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.

PubMed 34998506