DNA Methylation-Based Prediction of Post-operative Atrial Fibrillation

Machine learning in the prediction and detection of new-onset atrial fibrillation in ICU: a systematic review

Atrial fibrillation (AF) stands as the predominant arrhythmia observed in ICU patients. Nevertheless, the absence of a swift and precise method for prediction and detection poses a challenge. This study aims to provide a comprehensive literature review on the application of machine learning (ML) algorithms for predicting and detecting new-onset atrial fibrillation (NOAF) in ICU-treated patients. Following the PRISMA recommendations, this systematic review outlines ML models employed in the prediction and detection of NOAF in ICU patients and compares the ML-based approach with clinical-based methods. Inclusion criteria comprised randomized controlled trials (RCTs), observational studies, cohort studies, and case-control studies. A total of five articles published between November 2020 and April 2023 were identified and reviewed to extract the algorithms and performance metrics. Reviewed studies sourced 108,724 ICU admission records form databases, e.g., MIMIC. Eight prediction and detection methods were examined. Notably, CatBoost exhibited superior performance in NOAF prediction, while the support vector machine excelled in NOAF detection. Machine learning algorithms emerge as promising tools for predicting and detecting NOAF in ICU patients. The incorporation of these algorithms in clinical practice has the potential to enhance decision-making and the overall management of NOAF in ICU settings.

CDK5R1, GSE1, HSPG2 and WDFY3 as indirect epigenetic-sensitive genes in atrial fibrillation

BACKGROUND

Although mounting evidence supports that aberrant DNA methylation occurs in the hearts of patients with atrial fibrillation (AF), noninvasive epigenetic characterization of AF has not yet been defined.

METHODS

We investigated DNA methylome changes in peripheral blood CD4+ T cells isolated from 10 patients with AF relative to 11 healthy subjects (HS) who were enrolled in the DIANA clinical trial (NCT04371809) via reduced-representation bisulfite sequencing (RRBS).

RESULTS

An atrial-specific PPI network revealed 18 hub differentially methylated genes (DMGs), wherein ROC curve analysis revealed reasonable diagnostic performance of DNA methylation levels found within CDK5R1 (AUC = 0.76; p = 0.049), HSPG2 (AUC = 0.77; p = 0.038), WDFY3 (AUC = 0.78; p = 0.029), USP49 (AUC = 0.76; p = 0.049), GSE1 (AUC = 0.76; p = 0.049), AIFM1 (AUC = 0.76; p = 0.041), CDK5RAP2 (AUC = 0.81; p = 0.017), COL4A1 (AUC = 0.86; p < 0.001), SEPT8 (AUC = 0.90; p < 0.001), PFDN1 (AUC = 0.90; p < 0.01) and ACOT7 (AUC = 0.78; p = 0.032). Transcriptional profiling of the hub DMGs provided a significant overexpression of PSDM6 (p = 0.004), TFRC (p = 0.01), CDK5R1 (p < 0.001), HSPG2 (p = 0.01), WDFY3 (p < 0.001), USP49 (p = 0.004) and GSE1 (p = 0.021) in AF patients vs HS.

CONCLUSIONS

CDK5R1, GSE1, HSPG2 and WDFY3 resulted the best discriminatory genes both at methylation and gene expression level. Our results provide several candidate diagnostic biomarkers with the potential to advance precision medicine in AF.

Atrial fibrillation: pathophysiology, genetic and epigenetic mechanisms

Atrial fibrillation (AF) is the most common supraventricular arrhythmia affecting up to 1% of the general population. Its prevalence dramatically increases with age and could reach up to ∼10% in the elderly. The management of AF is a complex issue that is object of extensive ongoing basic and clinical research, it depends on its genetic and epigenetic causes, and it varies considerably geographically and also according to the ethnicity. Mechanistically, over the last decade, Genome Wide Association Studies have uncovered over 100 genetic loci associated with AF, and have shown that European ancestry is associated with elevated risk of AF. These AF-associated loci revolve around different types of disturbances, including inflammation, electrical abnormalities, and structural remodeling. Moreover, the discovery of epigenetic regulatory mechanisms, involving non-coding RNAs, DNA methylation and histone modification, has allowed unravelling what modifications reshape the processes leading to arrhythmias. Our review provides a current state of the field regarding the identification and functional characterization of AF-related genetic and epigenetic regulatory networks, including ethnic differences. We discuss clear and emerging connections between genetic regulation and pathophysiological mechanisms of AF.

Epigenetic MicroRNAs as Prognostic Markers of Postoperative Atrial Fibrillation: A Systematic Review

Postoperative atrial fibrillation (POAF) is a common complication after cardiac surgery, increasing the risk for adverse outcomes such as perioperative and long-term mortality, stroke, myocardial infarction, and other thromboembolic events. Epigenetic biomarkers show promise as prognostic tools for POAF. Epigenetic changes, such as DNA methylation, histone modification, and microRNAs (miRNA), can result in altered gene expression and the development of various pathological conditions. This systematic review aims to present the current literature on the association between various epigenetic markers and the development of POAF following cardiac surgery. Here, an electronic literature search was performed using MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, ClinicalTrials.gov, and Google Scholar to identify studies that reported the role of epigenetic markers in the development of POAF. Five of the 6 studies focused on miRNAs and their association with POAF. In POAF patients, the expression of miR-1 and miR-483-5p were upregulated in the right atrial appendage (RAA), while the levels of miR-133A, miR-208a, miR-23a, miR-26a, miR-29a, miR-29b, and miR-29c were decreased in the RAA and venous blood. One study examined cytosines followed by guanines (CpGs) as DNA methylation markers. Across all studies, 488 human subjects who had undergone cardiac surgery were investigated, and 195 subjects (39.9%) developed new-onset POAF. The current literature suggests that miRNAs may play a role in predicting the development of atrial fibrillation after cardiac surgery. However, more robust clinical data are required to justify their role in routine clinical practice.

DNA Methylation and Telomeres-Their Impact on the Occurrence of Atrial Fibrillation during Cardiac Aging

Atrial fibrillation (AF) is the most common arrhythmia in humans. AF is characterized by irregular and increased atrial muscle activation. This high-frequency activation obliterates the synchronous work of the atria and ventricles, reducing myocardial performance, which can lead to severe heart failure or stroke. The risk of developing atrial fibrillation depends largely on the patient's history. Cardiovascular diseases are considered aging-related pathologies; therefore, deciphering the role of telomeres and DNA methylation (mDNA), two hallmarks of aging, is likely to contribute to a better understanding and prophylaxis of AF. In honor of Prof. Elizabeth Blackburn's 75th birthday, we dedicate this review to the discovery of telomeres and her contribution to research on aging.

Gene modules and genes associated with postoperative atrial fibrillation: weighted gene co-expression network analysis and circRNA-miRNA-mRNA regulatory network analysis

Background

Atrial fibrillation (AF) is the most common complication in patients undergoing cardiac surgery. However, the pathogenesis of postoperative AF (POAF) is elusive, and research related to this topic is sparse. Our study aimed to identify key gene modules and genes and to conduct a circular RNA (circRNA)-microRNA (miRNA)-messenger RNA (mRNA) regulatory network analysis of POAF on the basis of bioinformatic analysis.

Methods

The GSE143924 and GSE97455 data sets from the Gene Expression Omnibus (GEO) database were analyzed. Weighted gene co-expression network analysis (WGCNA) was used to identify the key gene modules and genes related to POAF. A circRNA-miRNA-mRNA regulatory network was also built according to differential expression analysis. Functional enrichment analysis was further performed according to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis.

Results

WGCNA identified 2 key gene modules and 44 key genes that were significantly related to POAF. Functional enrichment analysis of these key genes implicated the following important biological processes (BPs): endosomal transport, protein kinase B signaling, and transcription regulation. The circRNA-miRNA-mRNA regulatory network suggested that KLF10 may take critical part in POAF. Moreover, 2 novel circRNAs, hsa_circRNA_001654 and hsa_circRNA_005899, and 2 miRNAs, hsa-miR-19b-3p and hsa-miR-30a-5p, which related with KLF10, were involved in the network.

Conclusions

Our study provides foundational expression profiles following POAF based on WGCNA. The circRNA-miRNA-mRNA network offers insights into the BPs and underlying mechanisms of POAF.

Gut Microbiota in Patients with Postoperative Atrial Fibrillation Undergoing Off-Pump Coronary Bypass Graft Surgery

BACKGROUND

Post-operative atrial fibrillation (POAF) is one of the most common complications of cardiac surgery. However, the underlying mechanism is not well understood. Alterations in the gut microbiota are associated with the development of atrial fibrillation (AF). The aim of this study was to explore the relationship between gut microbiota and POAF.

METHODS

Fecal samples were collected before surgery from 45 patients who underwent coronary artery bypass grafting with POAF and 90 matched patients without POAF (1:2). 16S rRNA sequencing was used to detect the microbiome profiles of 45 POAF patients and 89 matched patients (one sample in the no-POAF group was deleted owing to low quality after sequencing). Plasma 25-hydroxy vitamin D level was measured by ELISA.

RESULTS

Compared to the patients without POAF, gut microbiota composition was remarkably changed in the patients with POAF, with an increase in Lachnospira, Acinetobacter, Veillonella and Aeromonas, and a decrease in Escherichia-Shigella, Klebsiella, Streptococcus, Brevundimonas and Citrobacter. Furthermore, plasma 25-hydroxy vitamin D levels were decreased in POAF patients and negatively correlated with an abundance of Lachnospira.

CONCLUSIONS

The gut microbiota composition between patients with and without POAF is significantly different, implying that gut microbiota may play a role in the pathogenesis of POAF. Further studies are needed to fully clarify the role of gut microbiota in the initiation of AF.

Longitudinal profiling in patients undergoing cardiac surgery reveals postoperative changes in DNA methylation

BACKGROUND

Cardiac surgery and cardiopulmonary bypass induce a substantial immune and inflammatory response, the overactivation of which is associated with significant pulmonary, cardiovascular, and neurologic complications. Commensurate with the immune and inflammatory response are changes in the heart and vasculature itself, which together drive postoperative complications through mechanisms that are poorly understood. Longitudinal DNA methylation profiling has the potential to identify changes in gene regulatory mechanisms that are secondary to surgery and to identify molecular processes that predict and/or cause postoperative complications. In this study, we measure DNA methylation in preoperative and postoperative whole blood samples from 96 patients undergoing cardiac surgery on cardiopulmonary bypass.

RESULTS

While the vast majority of DNA methylation is unchanged by surgery after accounting for changes in cell-type composition, we identify several loci with statistically significant postoperative changes in methylation. Additionally, two of these loci are associated with new-onset postoperative atrial fibrillation, a significant complication after cardiac surgery. Paired statistical analysis, use of FACS data to support sufficient control of cell-type heterogeneity, and measurement of IL6 levels in a subset of patients add rigor to this analysis, allowing us to distinguish cell-type variability from actual changes in methylation.

CONCLUSIONS

This study identifies significant changes in DNA methylation that occur immediately after cardiac surgery and demonstrates that these acute alterations in DNA methylation have the granularity to identify processes associated with major postoperative complications. This research also establishes methods for controlling for cell-type variability in a large human cohort that may be useful to deploy in other longitudinal studies of epigenetic marks in the setting of acute and chronic disease.

Immune-associated pivotal biomarkers identification and competing endogenous RNA network construction in post-operative atrial fibrillation by comprehensive bioinformatics and machine learning strategies

Background

Atrial fibrillation (AF) is the most common arrhythmia. Previous studies mainly focused on identifying potential diagnostic biomarkers and treatment strategies for AF, while few studies concentrated on post-operative AF (POAF), particularly using bioinformatics analysis and machine learning algorithms. Therefore, our study aimed to identify immune-associated genes and provide the competing endogenous RNA (ceRNA) network for POAF.

Methods

Three GSE datasets were downloaded from the GEO database, and we used a variety of bioinformatics strategies and machine learning algorithms to discover candidate hub genes. These techniques included identifying differentially expressed genes (DEGs) and circRNAs (DECs), building protein-protein interaction networks, selecting common genes, and filtering candidate hub genes via three machine learning algorithms. To assess the diagnostic value, we then created the nomogram and receiver operating curve (ROC). MiRNAs targeting DEGs and DECs were predicted using five tools and the competing endogenous RNA (ceRNA) network was built. Moreover, we performed the immune cell infiltration analysis to better elucidate the regulation of immune cells in POAF.

Results

We identified 234 DEGs (82 up-regulated and 152 down-regulated) of POAF via Limma, 75 node genes were visualized via PPI network, which were mainly enriched in immune regulation. 15 common genes were selected using three CytoHubba algorithms. Following machine learning selection, the nomogram was created based on the four candidate hub genes. The area under curve (AUC) of the nomogram and individual gene were all over 0.75, showing the ideal diagnostic value. The dysregulation of macrophages may be critical in POAF pathogenesis. A novel circ_0007738 was discovered in POAF and the ceRNA network was eventually built.

Conclusion

We identified four immune-associated candidate hub genes (C1QA, C1R, MET, and SDC4) for POAF diagnosis through the creation of a nomogram and evaluation of its diagnostic value. The modulation of macrophages and the ceRNA network may represent further therapy methods.