Identification of m6A regulator-mediated RNA methylation modification patterns and key immune-related genes involved in atrial fibrillation

Unveiling the Molecular Links Between Atrial Fibrillation and Atherosclerosis: Insights into Shared Pathogenesis and Ferroptosis Diagnostic Biomarkers

Objective

Atherosclerosis(AS) is a vascular disease characterized by the development of plaque in the arteries, and atrial fibrillation (AF) is a common heart arrhythmia. These two conditions share several risk factors in common, such as aging, diabetes, obesity, and hypertension. Ferroptosis is a new mode of non-apoptotic cell death that plays a key role in cardiomyocyte death and has been associated with a variety of cardiac diseases. This study aimed to investigate the ferroptosis biomarkers and underlying biological mechanisms associated with AF and AS.

Materials and Methods

The gene expression dataset was obtained from GEO database, differentially expressed genes (DEGs) and ferroptosis expressed genes (FDGs) were obtained by data processing and screening, and then functional enrichment, network construction, transcription factor prediction, identification of biomarkers by LASSO and SVM - RFE algorithms, and also immune infiltration analyses and cellular experiments were performed.

Results

In AF and AS, 1627 and 571 DEGs were identified respectively, and 128 were intersected, and 47 common FDGs were also identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of DEGs revealed that they were associated with biological processes and pathways such as leukocyte immunity, and FDGs were also involved in specific functions and pathways. Fifteen key genes were identified, CSF1R and ITGAM expression differences were verified, and seven transcription factors were predicted to be differentially expressed. Characterized genes were screened to construct models with good diagnostic efficacy, and immune infiltration showed that NUPR1 was associated with altered immune environments, and WB indicated that NUPR1 was highly expressed in the disease model.

Conclusion

Our study demonstrates that the ferroptosis gene NUPR1 plays a role in the pathogenesis of atrial fibrillation and atherosclerosis, and also provides valuable insights into their molecular mechanisms, which may contribute to the development of new targets and strategies for the treatment of these diseases.

Single-cell transcriptomics reveals writers of RNA modification-mediated immune microenvironment and cardiac resident Macro-MYL2 macrophages in heart failure

BACKGROUND

Heart failure (HF), which is caused by cardiac overload and injury, is linked to significant mortality. Writers of RNA modification (WRMs) play a crucial role in the regulation of epigenetic processes involved in immune response and cardiovascular disease. However, the potential roles of these writers in the immunological milieu of HF remain unknown.

METHODS

We comprehensively characterized the expressions of 28 WRMs using datasets GSE145154 and GSE141910 to map the cardiac immunological microenvironment in HF patients. Based on the expression of WRMs, the immunological cells in the datasets were scored.

RESULTS

Single-cell transcriptomics analysis (GSE145154) revealed immunological dysregulation in HF as well as differential expression of WRMs in immunological cells from HF and non-HF (NHF) samples. WRM-scored immunological cells were positively correlated with the immunological response, and the high WRM score group exhibited elevated immunological cell infiltration. WRMs are involved in the differentiation of T cells and myeloid cells. WRM scores of T cell and myeloid cell subtypes were significantly reduced in the HF group compared to the NHF group. We identified a myogenesis-related resident macrophage population in the heart, Macro-MYL2, that was characterized by an increased expression of cardiomyocyte structural genes (MYL2, TNNI3, TNNC1, TCAP, and TNNT2) and was regulated by TRMT10C. Based on the WRM expression pattern, the transcriptomics data (GSE141910) identified two distinct clusters of HF samples, each with distinct functional enrichments and immunological characteristics.

CONCLUSION

Our study demonstrated a significant relationship between the WRMs and immunological microenvironment in HF, as well as a novel resident macrophage population, Macro-MYL2, characterized by myogenesis. These results provide a novel perspective on the underlying mechanisms and therapeutic targets for HF. Further experiments are required to validate the regulation of WRMs and Macro-MYL2 macrophage subtype in the cardiac immunological milieu.

Identification of common mechanisms and biomarkers of atrial fibrillation and heart failure based on machine learning

AIMS

Atrial fibrillation (AF) is the most common arrhythmia. Heart failure (HF) is a disease caused by heart dysfunction. The prevalence of AF and HF were progressively increasing over time. The co-existence of AF and HF presents a significant therapeutic challenge. In order to provide new ideas for the diagnosis of AF and HF, it is necessary to carry out biomarker related studies.

METHODS AND RESULTS

The training set and validation set data of AF and HF patient samples were downloaded from the GEO database, 'limma' was used to compare the differences in gene expression levels between the disease group and the normal group to screen for differentially expressed genes (DEGs). Weighted correlation network analysis (WGCNA) identified the modules with the highest positive correlation with AF and HF. Functional enrichment and PPI network construction of key genes were carried out. Biomarkers were screened by machine learning. The infiltration of immune cells in AF and HF groups was evaluated by R-packet 'CIBERSORT'. The miRNA network was constructed and potential therapeutic agents for biomarker genes were predicted through the drugbank database. Through WGCNA analysis, it was found that the modules most positively correlated with AF and HF were MEturquoise (r = 0.21, P value = 0.09) and MEbrown (r = 0.62, P value = 8e-12), respectively. We screened 25 genes that were highly correlated with both AF and HF. Lasso regression analysis results showed 7 and 20 core genes in AF and HF groups, respectively. The top 20 important genes in AF and HF groups were obtained as core genes by RF model analysis. Four biomarkers were obtained after the intersection of core genes in four groups, namely, GLUL, NCF2, S100A12, and SRGN. The diagnostic efficacy of four genes in AF validation sets was good (AUC: GLUL 0.76, NCF2 0.64, S100A12 0.68, and SRGN 0.76), as well as in the HF validation set (AUC: GLUL 0.76, NCF2 0.84, S100A12 0.92, and SRGN 0.68). The highest correlation with neutrophils was observed for GLUL, NCF2, and S100A12, while SRGN exhibited the strongest correlation with T cells CD4 memory resting in the AF group. GLUL, NCF2, S100A12, and SRGN were most associated with neutrophils in the HF group. A total of 101 miRNAs were predicted by four genes, and GLUL, NCF2, and S100A12 predicted a total of 10 potential therapeutic agents.

CONCLUSIONS

We identified four biological markers that are highly correlated with AF and HF, namely, GLUL, NCF2, S100A12, and SRGN. Our findings provide theoretical basis for the clinical diagnosis and treatment of AF and HF.

Identification and experimental validation of KMO as a critical immune-associated mitochondrial gene in unstable atherosclerotic plaque

BACKGROUND

The heightened risk of cardiovascular and cerebrovascular events is associated with the increased instability of atherosclerotic plaques. However, the lack of effective diagnostic biomarkers has impeded the assessment of plaque instability currently. This study was aimed to investigate and identify hub genes associated with unstable plaques through the integration of various bioinformatics tools, providing novel insights into the detection and treatment of this condition.

METHODS

Weighted Gene Co-expression Network Analysis (WGCNA) combined with two machine learning methods were used to identify hub genes strongly associated with plaque instability. The cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) method was utilized to assess immune cell infiltration patterns in atherosclerosis patients. Additionally, Gene Set Variation Analysis (GSVA) was conducted to investigate the potential biological functions, pathways, and mechanisms of hub genes associated with unstable plaques. To further validate the diagnostic efficiency and expression of the hub genes, immunohistochemistry (IHC), quantitative real-time polymerase chain reaction (RT-qPCR), and enzyme-linked immunosorbent assay (ELISA) were performed on collected human carotid plaque and blood samples. Immunofluorescence co-staining was also utilized to confirm the association between hub genes and immune cells, as well as their colocalization with mitochondria.

RESULTS

The CIBERSORT analysis demonstrated a significant decrease in the infiltration of CD8 T cells and an obvious increase in the infiltration of M0 macrophages in patients with atherosclerosis. Subsequently, two highly relevant modules (blue and green) strongly associated with atherosclerotic plaque instability were identified. Through intersection with mitochondria-related genes, 50 crucial genes were identified. Further analysis employing least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine recursive feature elimination (SVM-RFE) algorithms revealed six hub genes significantly associated with plaque instability. Among them, NT5DC3, ACADL, SLC25A4, ALDH1B1, and MAOB exhibited positive correlations with CD8 T cells and negative correlations with M0 macrophages, while kynurenine 3-monooxygenas (KMO) demonstrated a positive correlation with M0 macrophages and a negative correlation with CD8 T cells. IHC and RT-qPCR analyses of human carotid plaque samples, as well as ELISA analyses of blood samples, revealed significant upregulation of KMO and MAOB expression, along with decreased ALDH1B1 expression, in both stable and unstable samples compared to the control samples. However, among the three key genes mentioned above, only KMO showed a significant increase in expression in unstable plaque samples compared to stable plaque samples. Furthermore, the expression patterns of KMO in human carotid unstable plaque tissues and cultured mouse macrophage cell lines were assessed using immunofluorescence co-staining techniques. Finally, lentivirus-mediated KMO silencing was successfully transduced into the aortas of high-fat-fed ApoE-/- mice, with results indicating that KMO silencing attenuated plaque formation and promoted plaque stability in ApoE-/- mice.

CONCLUSIONS

The results suggest that KMO, a mitochondria-targeted gene associated with macrophage cells, holds promise as a valuable diagnostic biomarker for assessing the instability of atherosclerotic plaques.

Shared genetic architecture and causal relationship between liver and heart disease

This study investigates the relationship and genetic mechanisms of liver and heart diseases, focusing on the liver-heart axis (LHA) as a fundamental biological basis. Through genome-wide association study analysis, we explore shared genes and pathways related to LHA. Shared genetic factors are found in 8 out of 20 pairs, indicating genetic correlations. The analysis reveals 53 loci with pleiotropic effects, including 8 loci exhibiting shared causality across multiple traits. Based on SNP-p level tissue-specific multi-marker analysis of genomic annotation (MAGMA) analysis demonstrates significant enrichment of pleiotropy in liver and heart diseases within different cardiovascular tissues and female reproductive appendages. Gene-specific MAGMA analysis identifies 343 pleiotropic genes associated with various traits; these genes show tissue-specific enrichment primarily in the liver, cardiovascular system, and other tissues. Shared risk loci between immune cells and both liver and cardiovascular diseases are also discovered. Mendelian randomization analyses provide support for causal relationships among the investigated trait pairs.