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DNA Methylation-Based Prediction of Post-Operative Atrial Fibrillation I

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE194154 | GEO | 2022/05/05

REPOSITORIES: GEO

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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:Background On-pump cardiac surgery provokes a predictable perioperative myocardial ischaemia–reperfusion injury which is associated with poor clinical outcomes. We determined the occurrence of time-of-the-day variation in perioperative myocardial injury in patients undergoing aortic valve replacement and its molecular mechanisms. Methods We studied the incidence of major adverse cardiac events in a prospective observational single-centre cohort study of patients with severe aortic stenosis and preserved left ventricular ejection fraction (>50%) who were referred to our cardiovascular surgery department at Lille University Hospital (Lille, France) for aortic valve replacement and underwent surgery in the morning or afternoon. Patients were matched into pairs by propensity score. We also did a randomised study, in which we evaluated perioperative myocardial injury and myocardial samples of patients randomly assigned (1:1) via permuted block randomisation (block size of eight) to undergo isolated aortic valve replacement surgery either in the morning or afternoon. We also evaluated human and rodent myocardium in ex-vivo hypoxia–reoxygenation models and did a transcriptomic analysis in myocardial samples from the randomised patients to identify the signalling pathway(s) involved. The primary objective of the study was to assess whether myocardial tolerance of ischaemia–reperfusion differed depending on the timing of aortic valve replacement surgery (morning vs afternoon), as measured by the occurrence of major adverse cardiovascular events (cardiovascular death, myocardial infarction, and admission to hospital for acute heart failure). The randomised study is registered with ClinicalTrials.gov, number NCT02812901. Findings In the cohort study (n=596 patients in matched pairs who underwent either morning surgery [n=298] or afternoon surgery [n=298]), during the 500 days following aortic valve replacement, the incidence of major adverse cardiac events was lower in the afternoon surgery group than in the morning group: hazard ratio 0·50 (95% CI 0·32–0·77; p=0·0021). In the randomised study, 88 patients were randomly assigned to undergo surgery in the morning (n=44) or afternoon (n=44); perioperative myocardial injury assessed with the geometric mean of perioperative cardiac troponin T release was significantly lower in the afternoon group than in the morning group (estimated ratio of geometric means for afternoon to morning of 0·79 [95% CI 0·68–0·93; p=0·0045]). Ex-vivo analysis of human myocardium revealed an intrinsic morning–afternoon variation in hypoxia–reoxygenation tolerance, concomitant with transcriptional alterations in circadian gene expression with the nuclear receptor Rev-Erbα being highest in the morning. In a mouse Langendorff model of hypoxia–reoxygenation myocardial injury, Rev-Erbα gene deletion or antagonist treatment reduced injury at the time of sleep-to-wake transition, through an increase in the expression of the ischaemia–reperfusion injury modulator CDKN1a/p21. Interpretation Perioperative myocardial injury is transcriptionally orchestrated by the circadian clock in patients undergoing aortic valve replacement, and Rev-Erbα antagonism seems to be a pharmacological strategy for cardioprotection. Afternoon surgery might provide perioperative myocardial protection and lead to improved patient outcomes compared with morning surgery.

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DNA Methylation-Based Prediction of Post-Operative Atrial Fibrillation I

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