Sex-stratified genome-wide association and transcriptome-wide Mendelian randomization studies reveal drug targets of heart failure

Identification of biomarkers related to iron death in diabetic kidney disease based on machine learning algorithms

BACKGROUND

While ferroptosis has been recognised for its key role in tumour development, its involvement in DKD is not well understood. Identifying differentially expressed ferroptosis-related genes (DEIRGs) could help improve early diagnosis and treatment strategies for DKD.

AIM

Diabetic kidney disease (DKD) is a complication of diabetes that can progress to end-stage renal disease. Early diagnosis and identification of biomarkers related to its pathogenesis are crucial. This study aims to investigate the role of ferroptosis, a type of programmed cell death, in DKD, which remains largely unexplored.

OBJECTIVE

The objective of this study was to screen for diagnosis-related DEIRGs (DDEIRGs) in DKD and construct a diagnostic model with high accuracy.

METHOD

We intersected differentially expressed genes in the DKD dataset with ferroptosis-related genes to obtain DEIRGs. Gene importance was ranked using the random forest and Adaboost algorithms, and DDEIRGs were identified by intersecting results. A diagnostic model was constructed using logistic regression, and its accuracy was evaluated. Additionally, the immune landscape of DDEIRGs was analysed, and RT-qPCR was used to validate gene expression levels.

RESULTS

The diagnostic model constructed with logistic regression demonstrated high diagnostic accuracy for DKD. Immune landscape analysis of DDEIRGs provided further insights into their potential roles. RT-qPCR confirmed the differential expression of diagnosis-related genes.

CONCLUSION

This study successfully identified diagnosis-related ferroptosis genes in DKD and constructed an accurate diagnostic model. These findings enhance our understanding of the role of ferroptosis in DKD and may contribute to the development of new diagnostic and therapeutic approaches.

Cardiac Fibrosis in the Multi-Omics Era: Implications for Heart Failure

Cardiac fibrosis, a hallmark of heart failure and various cardiomyopathies, represents a complex pathological process that has long challenged therapeutic intervention. High-throughput omics technologies have begun revolutionizing our understanding of the molecular mechanisms driving cardiac fibrosis and are providing unprecedented insights into its heterogeneity and progression. This review provides a comprehensive analysis of how techniques-encompassing genomics, epigenomics, transcriptomics, proteomics, and metabolomics-are providing insight into our understanding of cardiac fibrosis. Genomic studies have identified novel genetic variants and regulatory networks associated with fibrosis susceptibility and progression, and single-cell transcriptomics has unveiled distinct cardiac fibroblast subpopulations with unique molecular signatures. Epigenomic profiling has revealed dynamic chromatin modifications controlling fibroblast activation states, and proteomic analyses have identified novel biomarkers and potential therapeutic targets. Metabolomic studies have uncovered important alterations in cardiac energetics and substrate utilization during fibrotic remodeling. The integration of these multi-omic data sets has led to the identification of previously unrecognized pathogenic mechanisms and potential therapeutic targets, including cell-type-specific interventions and metabolic modulators. We discuss how these advances are driving the development of precision medicine approaches for cardiac fibrosis while highlighting current challenges and future directions in translating multi-omic insights into effective therapeutic strategies. This review provides a systems-level perspective on cardiac fibrosis that may inform the development of more effective, personalized therapeutic approaches for heart failure and related cardiovascular diseases.

Integrated Mendelian randomization and single-cell RNA-sequencing analyses identified OAS1 as a novel therapeutic target for erectile dysfunction via targeting fibroblasts

Clinically, phosphodiesterase type 5 inhibitors (PDE5-Is) remain the first-line therapy for erectile dysfunction (ED) patients; however, approximately 35% of these patients are still failing to respond to the therapeutic effects. So, urgent needs are required to identify novel therapeutic targets for ED. Hence, in this report, it was the first time for us to integrate single-cell RNA-sequencing (scRNA-Seq), mendelian randomization (MR) analysis with expression quantitative trait loci (eQTL), and protein quantitative trait loci (pQTL) data to find new treatment targets for ED. Disease-causing changes were revealed by MR analysis, and it showed that the OAS1 eQTL/cis-eQTL/cis-pQTL was causally related to ED, significantly reducing its risks (all P < 0.05). Disease-induced changes were revealed by scRNA-Seq, and it suggested that OAS1 mainly played its role in ED via targeting fibroblasts. We further concluded that the positive regulation of OAS1 gene expression could lead to the vicious circle of ED. As a result, drugs targeting OAS1 in the future might provide more potential opportunities and flexibility for treating ED. In conclusion, our study identified OAS1 as a gene of interest in the context of ED via targeting fibroblasts through integrated MR and scRNA-Seq analyses. While these findings highlighted the potential of OAS1 as a therapeutic target, further experimental and clinical studies were still required to validate its functional role and therapeutic relevance in ED pathology.

Vericiguat in patients with heart failure across the spectrum of left ventricular ejection fraction: a patient-level, pooled meta-analysis of VITALITY-HFpEF and VICTORIA

Vericiguat, the newest soluble guanylate cyclase (sGC) drug, is potentially beneficial in treating heart failure (HF). However, most studies have only confirmed the significant impact of sGC in patients with reduced left ventricular ejection fraction (LVEF). Therefore, the main objective of this meta-analysis was to comparatively analyze the effects of Vericiguat in the entire LVEF range based on previous studies. According to PubMed, Web of Science, Cochrane, and Embase databases, randomized controlled studies in the full LVEF stage range were screened, and two extensive clinical studies on Vericiguat, namely VICTORIA (LVEF<45%) and VITALITY-HFpEF (LVEF≥45%) were identified for analysis and systematic evaluation. We separately assessed the rates of primary outcomes, cardiovascular death, and serious adverse events in both studies. The results of our research confirmed that although the criteria for the primary outcome were not the same in the two extensive studies, it was evident that there was no difference in the primary outcome between the experimental Vericiguat group and the placebo group in the VITALITY-HFpEF (LVEF≥45%) (P=0.45), whereas the primary outcome of VICTORIA (LVEF<45%) was significantly improved with the administration of Vericiguat showing a significant improvement (RR 0.93; 95% CI 0.87 to 1.00), but the effect of Vericiguat on cardiovascular mortality was not significant across the full range of LVEF (RR 0.97; 95% CI 0.86 to 1.09), and the incidence of total serious adverse events did not differ significantly between the two studies (RR 0.96; 95% CI 0.89 to 1.03). Surprisingly, partial subgroups analysis of serious adverse events found that vericiguat treatment reduced the incidence of all-cause death, Cardiac disorders, Hypotension, and Hypertension in patients with LVEF<45%, with a particular effect on the incidence of Cardiac disorders. Taken together, Vericiguat had a significant benefit in HF patients with LVEF<45%, especially in patients with LVEF<24%; it had a less pronounced effect in HF patients with LVEF ≥45%, but no adverse effects were observed.