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:Delirium is a common postoperative complication among older patients with many adverse outcomes. Due to lack of validated biomarkers, prediction and monitoring of delirium by biological testing is not currently feasible. Circulating proteins in cerebrospinal fluid (CSF) may reflect biological processes causing delirium. Our goal was to discover and investigate candidate protein biomarkers in preoperative CSF that were associated with development of postoperative delirium in older surgical patients. We employed a nested case–control study design coupled with high multiplex affinity proteomics analysis to measure 1305 proteins in preoperative CSF. Twenty-four matched delirium cases and non-delirium controls were selected from the Healthier Postoperative Recovery (HiPOR) cohort and the associations between preoperative protein levels and postoperative delirium were assessed using t-test statistics with further analysis by systems biology to elucidate delirium pathophysiology. Proteomics analysis identified 32 proteins in preoperative CSF that significantly associate with delirium (t-test p<0.05). Due to the limited sample size these proteins did not remain significant by multiple hypothesis testing using the Benjamini-Hochberg correction and q-value method. Three algorithms were applied to separate delirium cases from non-delirium controls. Hierarchical clustering classified 40/48 case-control samples correctly, principal components analysis separated 43/48. The receiver operating characteristic curve yielded an area under the curve [95% confidence interval] of 0.91 [0.80-0.97]. Systems biology analysis identified several key pathways associated with risk of delirium: inflammation, immune cell migration, apoptosis, angiogenesis, synaptic depression and neuronal cell death. Proteomics analysis of preoperative CSF identifies 32 proteins that might discriminate individuals who subsequently develop postoperative delirium from matched control samples. These proteins are potential candidate biomarkers for delirium and may play a role in its pathophysiology.

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Hematopoietic somatic mosaicism is associated with an increased risk of postoperative atrial fibrillation

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