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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.
2022-05-05 | GSE194155 | GEO
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.
2022-05-05 | GSE194154 | GEO
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.
| S-EPMC9127230 | biostudies-literature
Project description:DNA Methylation-Based Prediction of Post-Operative Atrial Fibrillation
| PRJNA799328 | ENA
Project description:DNA Methylation-Based Prediction of Post-Operative Atrial Fibrillation I
| PRJNA799332 | ENA
Project description:DNA Methylation-Based Prediction of Post-Operative Atrial Fibrillation II
| PRJNA799335 | ENA
Project description:Atrial fibrillation (AF) is the most common sustained arrhythmia with increased risk of stroke and congestive heart failure. AF is a highly genetic heterogeneous disease, but a large proportion of AF cannot be explained by genetic variants only. Some risk factors of AF, tendentious heritable phenomenon, potentially reversible conditions and some subtypes without DNA sequence variation all indicate the participation of DNA methylation in the pathogenesis of AF.
2014-10-28 | GSE62727 | GEO
Project description:Development of post-operative atrial fibrillation (POAF) following open-heart surgery is a significant clinical and economic burden. Despite advancements in medical therapies, the incidence of POAF remains elevated at 25-40%. Early work focused on detecting arrhythmias from electrocardiograms as well as identifying pre-operative risk factors from medical records. However, further progress has been stagnant, and a deeper understanding of pathogenesis and significant influences is warranted. With the advent of more complex machine learning (ML) algorithms and high-throughput sequencing, we have an unprecedented ability to capture and predict POAF in real-time. Integration of multimodal heterogeneous data and application of ML can generate a paradigm shift for diagnosis and treatment. This will require a concerted effort to consolidate and streamline real-time data. Herein, we will review the current literature and emerging opportunities aimed at predictive targets and new insights into the mechanisms underlying long-term sequelae of POAF.
| S-EPMC7330352 | biostudies-literature
Project description: Not available
| S-EPMC9885901 | biostudies-literature
Project description:AimsPost-operative atrial fibrillation (POAF) is associated with stroke and mortality. It is unknown if POAF is associated with subsequent heart failure (HF) hospitalization. This study aims to examine the association between POAF and incident HF hospitalization among patients undergoing cardiac and non-cardiac surgeries.Methods and resultsA retrospective cohort study was conducted using all-payer administrative claims data that included all non-federal emergency department visits and acute care hospitalizations across 11 states in the USA. The study population included adults aged at least 18 years hospitalized for surgery without a prior diagnosis of HF. Cox proportional hazards regression models were used to examine the association between POAF and incident HF hospitalization after making adjustment for socio-demographics and comorbid conditions. Among 76 536 patients who underwent cardiac surgery, 14 365 (18.8%) developed incident POAF. In an adjusted Cox model, POAF was associated with incident HF hospitalization [hazard ratio (HR) 1.33; 95% confidence interval (CI) 1.25-1.41]. In a sensitivity analysis excluding HF within 1 year of surgery, POAF remained associated with incident HF hospitalization (HR 1.15; 95% CI 1.01-1.31). Among 2 929 854 patients who underwent non-cardiac surgery, 23 763 (0.8%) developed incident POAF. In an adjusted Cox model, POAF was again associated with incident HF hospitalization (HR 2.02; 95% CI 1.94-2.10), including in a sensitivity analysis excluding HF within 1 year of surgery (HR 1.49; 95% CI 1.38-1.61).ConclusionsPost-operative atrial fibrillation is associated with incident HF hospitalization among patients without prior history of HF undergoing both cardiac and non-cardiac surgeries. These findings reinforce the adverse prognostic impact of POAF and suggest that POAF may be a marker for identifying patients with subclinical HF and those at elevated risk for HF.
| S-EPMC9890619 | biostudies-literature