OBJECTIVE: N6-methyladenosine (m ⁶A) is a common epigenetic modification in eukaryotes. In this study, we explore the potential impact of m ⁶A-associated single nucleotide polymorphisms (m ⁶A-SNPs) on heart failure (HF). METHODS: Data from genome-wide association studies (GWAS) investigating HF in humans and from m ⁶A-SNPs datasets were used to identify HF-associated m ⁶A-SNPs. Their functions were explored using expression quantitative trait locus (eQTL), gene expression, and gene enrichment analyses. Mediation protein quantitative trait locus (pQTL)-Mendelian randomization (MR) was used to investigate the potential mechanism between critical protein levels and risk factors for HF. RESULTS: We screened 44 HF-associated m ⁶A-SNPs, including 10 m ⁶A-SNPs that showed eQTL signals and differential expressions in HF. The SNP rs1801270 in CDKN1A showed the strongest association with HF ( P = 7.75 × 10 ^-6). Additionally, MR verified the genetic association between the CDKN1A protein and HF, as well as the mediating effect of blood pressure (BP) in this pathway. Higher circulating level of CDKN1A was associated with a lower risk of HF (odds ratio [ OR] = 0.82, 95% confidence interval [ CI]: 0.69 to 0.99). The proportions of hypertension, systolic BP, and diastolic BP were 48.10%, 28.94%, and 18.02%, respectively. Associations of PDIA6 ( P = 1.30 × 10 ^-2) and SMAD3 ( P = 4.80 × 10 ^-2) with HF were also detected. CONCLUSION Multiple HF-related m ⁶A-SNPs were identified in this study. Genetic associations of CDKN1A and other proteins with HF and its risk factors were demonstrated, providing new ideas for further exploration of the molecular mechanisms of HF.
Humans ; Polymorphism, Single Nucleotide ; Heart Failure/genetics* ; Mendelian Randomization Analysis ; Genome-Wide Association Study ; Cyclin-Dependent Kinase Inhibitor p21/metabolism* ; Quantitative Trait Loci ; Adenosine/metabolism* ; Male ; Female ; Genetic Predisposition to Disease

Background::Genome-wide association studies (GWAS) have identified more than a thousand loci for blood pressure (BP). Functional genes in these loci are cell-type specific. The aim of this study was to elucidate potentially functional genes associated with BP in the aorta through the utilization of RNA modification-associated single-nucleotide polymorphisms (RNAm-SNPs).Methods::Utilizing large-scale genetic data of 757,601 individuals from the UK Biobank and International Consortium of Blood Pressure consortium, we identified associations between RNAm-SNPs and BP. The association between RNAm-SNPs, gene expression, and BP were examined.Results::A total of 355 RNAm-SNPs related to m 6A, m 1A, m 5C, m 7G, and A-to-I modification were associated with BP. The related genes were enriched in the pancreatic secretion pathway and renin secretion pathway. The BP GWAS signals were significantly enriched with m 6A-SNPs, highlighting the potential functional relevance of m 6A in physiological processes influencing BP. Notably, m 6A-SNPs in CYP11B1, PDE3B, HDAC7, ACE, SLC4A7, PDE1A, FRK, MTHFR, NPPA, CACNA1D, and HDAC9 were identified. Differential methylation and differential expression of the BP genes in FTO-overexpression and METTL14-knockdown vascular smooth muscle cells were detected. RNAm-SNPs were associated with ascending and descending aorta diameter and the genes showed differential methylation between aortic dissection (AD) cases and controls. In scRNA-seq study, we identified ARID5A, HLA-DPB1, HLA-DRA, IRF1, LINC01091, MCL1, MLF1, MLXIPL, NAA16, NADK, RERG, SRM, and USP53 as differential expression genes for AD in aortic cells. Conclusion::The present study identified RNAm-SNPs in BP loci and elucidated the associations between the RNAm-SNPs, gene expression, and BP. The identified BP-associated genes in aortic cells were associated with AD.

Objectives::Approximately 20%-25% of the global adult population is affected by metabolic syndrome (MetS), highlighting its status as a major public health concern. This study aims to investigate the predictive value of cardiorenal biomarkers on mortality among patients with MetS, thus optimizing treatment strategies.Methods::Utilizing data from the National Health and Nutrition Examination Survey (NHANES) cycles between 1999 and 2004, we conducted a prospective cohort study involving 2369 participants diagnosed with MetS. We evaluated the association of cardiac and renal biomarkers with all-cause and cardiovascular disease (CVD) mortality, employing weighted Cox proportional hazards models. Furthermore, machine learning models were used to predict mortality outcomes based on these biomarkers.Results::Among 2369 participants in the study cohort, over a median follow-up period of 17.1 years, 774 (32.67%) participants died, including 260 (10.98%) from CVD. The highest quartiles of cardiac biomarkers (N-terminal pro-B-type natriuretic peptide [NT-proBNP]) and renal biomarkers (beta-2 microglobulin, [β2M]) were significantly associated with increased risks of all-cause mortality (hazard ratios [HRs] ranging from 1.94 to 2.06) and CVD mortality (HRs up to 2.86), after adjusting for confounders. Additionally, a U-shaped association was observed between high-sensitivity cardiac troponin T (Hs-cTnT), creatinine (Cr), and all-cause mortality in patients with MetS. Machine learning analyses identified Hs-cTnT, NT-proBNP, and β2M as important predictors of mortality, with the CatBoost model showing superior performance (area under the curve [AUC] = 0.904).Conclusion::Cardiac and renal biomarkers are significant predictors of mortality in MetS patients, with Hs-cTnT, NT-proBNP, and β2M emerging as crucial indicators. Further research is needed to explore intervention strategies targeting these biomarkers to improve clinical outcomes.

Background::Genome-wide association studies (GWAS) have identified more than a thousand loci for blood pressure (BP). Functional genes in these loci are cell-type specific. The aim of this study was to elucidate potentially functional genes associated with BP in the aorta through the utilization of RNA modification-associated single-nucleotide polymorphisms (RNAm-SNPs).Methods::Utilizing large-scale genetic data of 757,601 individuals from the UK Biobank and International Consortium of Blood Pressure consortium, we identified associations between RNAm-SNPs and BP. The association between RNAm-SNPs, gene expression, and BP were examined.Results::A total of 355 RNAm-SNPs related to m 6A, m 1A, m 5C, m 7G, and A-to-I modification were associated with BP. The related genes were enriched in the pancreatic secretion pathway and renin secretion pathway. The BP GWAS signals were significantly enriched with m 6A-SNPs, highlighting the potential functional relevance of m 6A in physiological processes influencing BP. Notably, m 6A-SNPs in CYP11B1, PDE3B, HDAC7, ACE, SLC4A7, PDE1A, FRK, MTHFR, NPPA, CACNA1D, and HDAC9 were identified. Differential methylation and differential expression of the BP genes in FTO-overexpression and METTL14-knockdown vascular smooth muscle cells were detected. RNAm-SNPs were associated with ascending and descending aorta diameter and the genes showed differential methylation between aortic dissection (AD) cases and controls. In scRNA-seq study, we identified ARID5A, HLA-DPB1, HLA-DRA, IRF1, LINC01091, MCL1, MLF1, MLXIPL, NAA16, NADK, RERG, SRM, and USP53 as differential expression genes for AD in aortic cells. Conclusion::The present study identified RNAm-SNPs in BP loci and elucidated the associations between the RNAm-SNPs, gene expression, and BP. The identified BP-associated genes in aortic cells were associated with AD.

Objectives::Approximately 20%-25% of the global adult population is affected by metabolic syndrome (MetS), highlighting its status as a major public health concern. This study aims to investigate the predictive value of cardiorenal biomarkers on mortality among patients with MetS, thus optimizing treatment strategies.Methods::Utilizing data from the National Health and Nutrition Examination Survey (NHANES) cycles between 1999 and 2004, we conducted a prospective cohort study involving 2369 participants diagnosed with MetS. We evaluated the association of cardiac and renal biomarkers with all-cause and cardiovascular disease (CVD) mortality, employing weighted Cox proportional hazards models. Furthermore, machine learning models were used to predict mortality outcomes based on these biomarkers.Results::Among 2369 participants in the study cohort, over a median follow-up period of 17.1 years, 774 (32.67%) participants died, including 260 (10.98%) from CVD. The highest quartiles of cardiac biomarkers (N-terminal pro-B-type natriuretic peptide [NT-proBNP]) and renal biomarkers (beta-2 microglobulin, [β2M]) were significantly associated with increased risks of all-cause mortality (hazard ratios [HRs] ranging from 1.94 to 2.06) and CVD mortality (HRs up to 2.86), after adjusting for confounders. Additionally, a U-shaped association was observed between high-sensitivity cardiac troponin T (Hs-cTnT), creatinine (Cr), and all-cause mortality in patients with MetS. Machine learning analyses identified Hs-cTnT, NT-proBNP, and β2M as important predictors of mortality, with the CatBoost model showing superior performance (area under the curve [AUC] = 0.904).Conclusion::Cardiac and renal biomarkers are significant predictors of mortality in MetS patients, with Hs-cTnT, NT-proBNP, and β2M emerging as crucial indicators. Further research is needed to explore intervention strategies targeting these biomarkers to improve clinical outcomes.