Predictive Accuracy of a Polygenic Risk Score for Postoperative Atrial Fibrillation After Cardiac Surgery

Abstract

Background - Postoperative atrial fibrillation (PoAF) remains a significant risk factor for increased morbidity and mortality after cardiac surgery. The ability to accurately identify patients at risk through clinical risk factors is limited. There is growing evidence that polygenic risk contributes significantly to PoAF, and incorporating measures of genetic risk could enhance prediction. Methods - A retrospective cohort study of 1,047 patients of white European ancestry who underwent either coronary artery bypass grafting (CABG) or valve surgery at a tertiary academic center, and were free from a history or persistent preoperative AF. The primary outcome was defined as PoAF based on postoperative ECG reports, medical record documentation, and changes in medication. The exposure was a polygenic risk score (PRS) comprising 2,746 SNPs previously associated with AF risk. The prediction of PoAF risk was assessed using measures of model discrimination, calibration, and net reclassification improvement (NRI). Results - A total of 259 patients (24.7%) developed PoAF. The PRS was significantly associated with a higher risk for PoAF (OR = 1.63 per standard deviation increase in PRS; 95% CI, 1.41-1.90). Addition of PRS to patient- and procedure-related predictors of PoAF significantly increased the C statistic from 0.742 to 0.782 (change in C statistic, 0.040; 95% CI, 0.021-0.060) while maintaining good calibration. The addition of the PRS to patient- and procedure-related predictors of postoperative AF improved model fit (likelihood ratio test p = 2.8 x 10 -15 ) and significantly improved measures of reclassification (NRI, 0.158; 95% CI, 0.066- 0.274). Conclusions - The PRS for PoAF was associated with improved discrimination, calibration, and risk reclassification compared to conventional clinical predictors suggesting that a PoAF PRS may enhance risk prediction of PoAF in patients undergoing CABG or valve surgery.

A Higher Polygenic Risk Score Is Associated with a Higher Recurrence Rate of Atrial Fibrillation in Direct Current Cardioversion-Treated Patients

“…Furthermore, O'Sullivan et al, studying 530,933 SNVs and Pulit et al studying 934 SNVs, found a link between a higher PRS and a higher risk of stroke in AF patients. Additionally, Kertai et al, investigating 2,746 SNVs, detected an association between a higher PRS and a higher risk of developing AF post cardiac surgery [38][39][40]. Similar to this study, multiple studies have observed the trend of significant association of AF recurrence only with a higher PRS and generally not with the SNVs themselves.…”

“…The current consensus is that a PRS should include the maximum number of SNVs possible as the pathogenesis of AF is polygenic and not yet fully understood despite being an area of active research [43]. As such, recent studies have utilized whole-genome sequencing in conjunction with GWAS to permit the calculation of PRS using a far greater number of SNVs [37][38][39][40][44][45][46][47][48]. This has been made possible by the increasing availability of whole-genome sequencing [37,41,42,49].…”

Future of Perioperative Precision Medicine: Integration of Molecular Science, Dynamic Health Care Informatics, and Implementation of Predictive Pathways in Real Time

“…Another example of how genetic predisposition could help identify patients at risk for postoperative complications was highlighted by a recent study of patients who underwent cardiac surgery in whom the prediction of postoperative atrial fibrillation (POAF) was much improved by the addition of polygenic risk score (odds ratio, 1.63 per SD increase in PRS [95% CI, 1.41-1.90]). 34 PO-AKI is another frequent complication. Tseng et al 35 enrolled 671 patients prospectively undergoing cardiac surgery patients to design ML-based algorithms logistic regression, support vector machine, random forest, extreme gradient boosting, and ensemble.…”

“…Another example of how genetic predisposition could help identify patients at risk for postoperative complications was highlighted by a recent study of patients who underwent cardiac surgery in whom the prediction of postoperative atrial fibrillation (POAF) was much improved by the addition of polygenic risk score (odds ratio, 1.63 per SD increase in PRS [95% CI, 1.41–1.90]). 34…”

Methylation risk scores are associated with a collection of phenotypes within electronic health record systems

“…Widespread adoption of electronic health record systems coupled with an increasing interest in hospital biobanking systems has spurred research efforts spanning machine-learning and genomics communities[1–7]. These efforts have produced increasingly accurate imputation (current state) and prediction (future state) of patient phenotypes from medical records [8, 9] and polygenic risk scores [1–3, 10–14], and are already being investigated in translational contexts [15–18]. For example, recent work has shown that machine learning can leverage high-dimensional data to aid in the prediction of a multitude of clinical phenotypes including cardiac function and arrhythmia [19–21], post-operative complications [8, 9], sepsis [22], breast cancer [11, 23], and prostate cancer [24].…”