Project description:Background: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and post-operative atrial fibrillation (POAF) is a major healthcare burden, contributing to an increased risk of stroke, kidney failure, heart attack and death. Genetic studies have identified associations with AF, but no molecular diagnostic exists to predict POAF based on pre-operative measurements. Such a tool would be of great value for perioperative planning to improve patient care and reduce healthcare costs. In this pilot study of epigenetic precision medicine in the perioperative period, we carried out bisulfite sequencing to measure DNA methylation status in blood collected from patients prior to cardiac surgery to identify biosignatures of POAF. Methods: We enrolled 221 patients undergoing cardiac surgery in this prospective observational study. DNA methylation measurements were obtained from blood samples drawn from awake patients prior to surgery. After controlling for clinical and methylation covariates, we analyzed DNA methylation loci in the discovery cohort of 110 patients for association with POAF. We also constructed predictive models for POAF using clinical and DNA methylation data. We subsequently performed targeted analyses of a separate cohort of 101 cardiac surgical patients to measure the methylation status solely of significant methylation loci in the discovery cohort. Results: A total of 47 patients in the discovery cohort (42.7%) and 43 patients in the validation cohort (42.6%) developed POAF. We identified 12 CpGs that were statistically significant in the discovery cohort after correcting for multiple hypothesis testing. Of these sites, 6 were amenable to targeted bisulfite sequencing and chr16:24640902 was statistically significant in the validation cohort. In addition, the methylation POAF prediction model had an AUC of 0.79 in the validation cohort. Conclusions: We have identified DNA methylation biomarkers that can predict future occurrence of POAF associated with cardiac surgery. This research demonstrates the use of precision medicine to develop models combining epigenomic and clinical data to predict disease.

Project description:Post-operative (POP) atrial fibrillation (AF) is frequent in patients who undergo cardiac surgery. However, its prognostic impact in the long term remains unclear. We followed 1386 patients who underwent cardiac surgery for an average of 10 ± 3 years. According to clinical history of AF before and after surgery, four subgroups were identified: (1) patients with no history of AF and without episodes of AF during the first 30 days after surgery (control or Group 1, n = 726), (2) patients with no history of AF before surgery in whom new-onset POP AF was detected during the first 30 days after surgery (new-onset POP AF or Group 2, n = 452), (3) patients with a history of paroxysmal/persistent AF before cardiac surgery (Group 3, n = 125, including 87 POP AF patients and 38 who did not develop POP AF), and (4) patients with permanent AF at the time of cardiac surgery (Group 4, n = 83). All-cause mortality was the primary outcome of the study. We tested the associations of potential determinants with all-cause mortality using univariable and multivariable statistical analyses. Overall, 473 patients (34%) died during follow-up. After adjustment for multiple confounders, new-onset POP AF (hazard ratio (HR) = 1.31, 95% confidence interval (CI): 0.90-1.89; p = 0.1609), history of paroxysmal/persistent AF before cardiac surgery (HR = 1.33, 95% CI: 0.71-2.49; p = 0.3736), and permanent AF (Group 4) (HR = 1.55, 95% CI 0.82-2.95; p = 0.1803) were not associated with a significantly increased risk of mortality when compared with Group 1 (patients with no history of AF and without episodes of AF during the first 30 days after surgery). In new-onset POP AF patients, oral anticoagulation was not associated with mortality (HR = 1.13, 95% CI: 0.83-1.54; p = 0.4299). In this cohort of patients who underwent different types of heart surgery, POP AF was not associated with an increased risk of mortality. In this setting, the role of long-term anticoagulation remains unclear.

Project description:BackgroundAtrial fibrillation (AF) is the most common sustained cardiac arrhythmia and post-operative atrial fibrillation (POAF) is a major healthcare burden, contributing to an increased risk of stroke, kidney failure, heart attack and death. Genetic studies have identified associations with AF, but no molecular diagnostic exists to predict POAF based on pre-operative measurements. Such a tool would be of great value for perioperative planning to improve patient care and reduce healthcare costs. In this pilot study of epigenetic precision medicine in the perioperative period, we carried out bisulfite sequencing to measure DNA methylation status in blood collected from patients prior to cardiac surgery to identify biosignatures of POAF.MethodsWe enrolled 221 patients undergoing cardiac surgery in this prospective observational study. DNA methylation measurements were obtained from blood samples drawn from awake patients prior to surgery. After controlling for clinical and methylation covariates, we analyzed DNA methylation loci in the discovery cohort of 110 patients for association with POAF. We also constructed predictive models for POAF using clinical and DNA methylation data. We subsequently performed targeted analyses of a separate cohort of 101 cardiac surgical patients to measure the methylation status solely of significant methylation loci in the discovery cohort.ResultsA total of 47 patients in the discovery cohort (42.7%) and 43 patients in the validation cohort (42.6%) developed POAF. We identified 12 CpGs that were statistically significant in the discovery cohort after correcting for multiple hypothesis testing. Of these sites, 6 were amenable to targeted bisulfite sequencing and chr16:24640902 was statistically significant in the validation cohort. In addition, the methylation POAF prediction model had an AUC of 0.79 in the validation cohort.ConclusionsWe have identified DNA methylation biomarkers that can predict future occurrence of POAF associated with cardiac surgery. This research demonstrates the use of precision medicine to develop models combining epigenomic and clinical data to predict disease.

Dataset Information

Post-operative atrial fibrillation after cardiac surgery: Challenges throughout the patient journey.

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Post-operative atrial fibrillation after cardiac surgery: Challenges throughout the patient journey.

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