DNA Methylation-Based Prediction of Post-Operative Atrial Fibrillation II
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA799335 | ENA |
REPOSITORIES: ENA
Similar Datasets
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: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:To identify pathway and mechanism undergoing post operative atrial fibrillation, we check transcriptomic expression of patients with and without post operative atrial fibrillation development and compare up and down regulated genes and their pathways. Right atrial appendage were obtained from patients undergoing cardiac surgery.
2017-10-30 | GSE62871 | GEO
Project description:This study will report the incidence of atrial fibrillation after elective colorectal cancer resection in the over 65 age group. This will be used to validate a risk model for the development of post-operative atrial fibrillation.
Eligible patients will undergo electrocardiogram based screening for atrial fibrillation, as well as brain natriuretic peptide tests prior to surgery. They will undergo 24 hour holter monitor prior to surgery, and at 30 and 90 days following surgery.
The primary outcome will be occurrence of atrial fibrillation within 90 days of surgery. Secondary outcomes include quality of life change, use of hospital services for atrial fibrillation, and complications of atrial fibrillation. This will be used to validate the pre-existing model for prediction of atrial fibrillation.
| 2312263 | ecrin-mdr-crc
Project description:This SuperSeries is composed of the SubSeries listed below.
2022-05-05 | GSE194156 | GEO
Project description:Analysis for early diagnosis of atrial fibrillation by finding changes in miRNA in the urine of patients with atrial fibrillation
2021-12-16 | GSE190898 | GEO
Project description:Electrical and structural remodeling processes are contributors to the self-perpetuating nature of atrial fibrillation (AF). However, their correlation has not been clarified. In this study, human atrial tissues from the patients with rheumatic mitral valve disease in either sinus rhythm or persistent AF were analyzed using a combined transcriptomic and proteomic approach. An up-regulation in chloride intracellular channel (CLIC) 1, 4, 5 and a rise in type IV collagen were revealed. Combined with the results from immunohistochemistry and electron microscope analysis, the distribution of type IV collagen and effects of fibrosis on myocyte membrane indicated the possible interaction between CLIC and type IV collagen, confirmed by protein structure prediction and co-immunoprecipitation. These results indicate that CLICs play an important role in the development of atrial fibrillation and that CLICs and structural type IV collagen may interact on each other to promote the development of AF in rheumatic mitral valve disease.
2018-11-22 | PXD006911 | Pride
Project description:Regional differential expression of atrial fibrillation risk genes in the left atrium and pulmonary veins is not well studied, but may yield insights into atrial fibrillation pathogenesis. We tested the hypothesis that there is significant regional differential expression in left atrium structures. RNAseq was performed in 25 regions within the pulmonary veins (n=12), left atrial body (n=10), and left atrial appendage (n=3) from a 75 year old male with hypertension and atrial fibrillation who died of a stroke. These data show that genes involved in atrial fibrillation pathogenesis have substantial regional expression heterogeneity, particularly when comparing the left atrial body, pulmonary veins and left atrial appendage.
2020-11-14 | GSE161450 | GEO