Shilong Zhong

Myocardial ischemia is the common etiology of heart failure (HF). However, the precise molecular mechanisms that govern the ischemic myocardium into HF remain poorly defined. Selective accumulation of succinate is a hallmark of ischemia. Succinate is a predominant regulator of protein succinylation modification. The present study unravels the novel role of succinate in ischemia-induced HF via succinylation. A clinical cohort study that was performed on 1554 Chinese patients with coronary artery disease (CAD) indicated that serum succinate levels were positively correlated with the increase of HF biomarker, decrease of left ventricular ejection fraction (LVEF), incidence of HF, and risk of death. In cardiomyocytes deprived of oxygen and glucose (OGD) and in mice subjected to ligation of the left anterior descending coronary artery (LAD), succinate levels and global protein succinylation were elevated. Succinylation proteomic analysis identified the α-subunit of mitochondrial ATP synthase (ATP5A1) as an important succinylated protein, and K531 was identified as the functional succinylation site. Ablation of succinylation by the ATP5A1-K531R mutant ameliorated OGD-induced cardiomyocyte death, mitochondrial dysfunction and energy metabolic dysfunction. K531R delivered by cardiac-specific adeno-associated virus (AAV9) achieved short-term cardioprotective effects against ischemic injury, and exerted prolonged protective effects against HF development. Sirtuin 5 was confirmed as a desuccinylase of ATP5A1, whereas carnitine palmitoyltransferase 1A (CPT1A) was recognized as a trans-succinylase. Mechanistically, succinylation of ATP5A1-K531 impeded the assembly of ATP synthase and impaired its activity. Elevated succinate potentially serves as a risk predictor of HF. Targeting desuccinylation of ATP5A1-K531 might be a promising therapeutic strategy.

Adverse outcomes including myocardial infarction (MI) and stroke render coronary artery disease (CAD) a leading cause of death worldwide. DNA methylation markers may alert such adversity ahead of the events. We profiled DNA methylation of blood leukocytes in 933 Chinese CAD patients with up-to-13-year follow-up from three centers, identifying 70 differentially methylated sites (DMPs) associated with future death. These DMPs correlated with inflammation markers, left ventricular functions and high-density lipoprotein cholesterol, and impacted gene expression in immune response and cellular scenesence. Notably, cg25563198 and cg25114611 were discovered to regulate FKBP5, whose upregulation persisted during MI and stroke. Fkbp5 knockout in male mice partially rescued MI by reducing infarct size and improving heart function, confirming its critical function. Finally, our prognostic model of 10 methylation sites and 5 clinical features outperformed clinical models. Our study highlights the value of DNA methylation in predicting prognosis in CAD and provides tools for clinical translation.

In the realm of cellular biochemistry, mitochondria have been increasingly recognized for their critical role in both cellular metabolism and the etiology of various diseases. Mitochondrial transporters (MTs) are essential for maintaining cellular energy dynamics and metabolic fluxes by facilitating the bidirectional transfer of metabolites across mitochondrial membranes. Dysregulation of these transporters, such as the mitochondrial pyruvate carrier (MPC), citrate carrier (SLC25A1), and voltage-dependent anion channel (VDAC), disrupts energy metabolism, redox balance, and cellular signaling, contributing to the pathogenesis of neurodegenerative diseases (NDDs), cardiovascular diseases (CVDs), type 2 diabetes (T2D), and cancer. In NDDs, impaired transporters exacerbate oxidative stress and neuronal death, while in CVDs, they lead to energy deficits and heart failure. In T2D, dysfunctional transporters like MPC and carnitine palmitoyltransferase (CPT) systems drive insulin resistance and metabolic dysregulation. In cancer, upregulated transporters such as citrate carrier (SLC25A1), and dicarboxylate carrier (SLC25A10) as well as metabolic shifts like the Warburg effect support tumor growth and survival. Targeting MTs and metabolic reprogramming (MR) offers significant therapeutic potential. Preclinical studies have demonstrated the efficacy of mitochondrial-targeted therapies (MTT), such as adenosine monophosphate-activated protein kinase (AMPK) activators and antioxidants, in restoring metabolic homeostasis and reducing disease pathology. In cancer, inhibitors of glutamine transporters and VDAC1 are being explored to disrupt tumor metabolism. Several therapies are advancing to clinical trials, including mitochondrial-targeted drugs for NDDs and metabolic modulators for T2D and cancer, highlighting their translational potential. Despite notable individual achievements and isolated reviews in this field, there remains a lack of comprehensive syntheses that integrate these advancements. This review seeks to combine the prevailing scientific evidence and outline prospective research trajectories. The gathered data robustly support the significant potential of targeting MTs as a groundbreaking approach in the treatment of complex diseases, with the potential to significantly improve health outcomes and mitigate disease progression.

The association between rosuvastatin (RST) and the risk of new-onset diabetes mellitus (NODM) is controversial. Although the link between RST and NODM is still debated, there is a lack of effective strategies to predict and prevent potential RST-induced NODM in clinical practice. This study aimed to determine the association between plasma exposure to RST and the risk of developing NODM in patients with cardiovascular disease and to establish predictive models for the early detection of RST-induced NODM. We included 704 patients with cardiovascular disease and without diabetes who had been on RST for > 4 months. We used ultra-performance liquid chromatography–tandem mass spectrometry to detect the concentration of RST and its metabolites. We then used machine learning (ML) to analyze the impact of plasma exposure to RST and patient characteristics on NODM and established four risk prediction models for RST-induced NODM. The optimal model was determined using the receiver-operating-characteristic (ROC) curve (AUC) and the Shapley algorithm (SHAP) interpretation. Our findings indicated that high plasma exposure to RST was an independent risk factor for NODM. In terms of NODM, the Random Forest model demonstrated the highest AUC value (0.7310) in the testing set and was validated as the best performing model. The SHAP analysis identified high triglyceride levels, advanced age, and high RST plasma exposure as the top three predictors of NODM. In addition, low total cholesterol and LDL-cholesterol levels were also associated with an increased risk of NODM. The study findings revealed high plasma exposure of RST as an independent risk factor for NODM in patients without diabetes who are on RST, which may relate to “on-target” effects of RST. In addition, ML interpreted using SHAP provide valuable tools for early prediction and personalized management of RST-induced NODM.

Coronary heart disease (CHD) remains a global health threat. As antiplatelet therapy constitutes the cornerstone of CHD management, ticagrelor has been universally endorsed as a first-line agent in major clinical guidelines. However, the therapeutic efficacy of ticagrelor is compromised by interindividual variability in bleeding risk. Notably, while inherited genetic variations account for part of this heterogeneity, the dynamic regulatory role of modifiable epigenetic mechanisms-particularly DNA methylation in mediating platelet reactivity-remains inadequately characterized, presenting a critical knowledge gap in optimizing precision antiplatelet strategies. We utilized the 850k methylation array to measure DNA methylation levels in blood samples from 47 healthy controls and 93 patients with CHD. Subsequently, epigenome-wide association study (EWAS), summary data-based Mendelian randomization (SMR), and heterogeneity in dependent instruments (HEIDI) analyses were applied to pinpoint critical methylation sites that influence gene expression, platelet function recovery, and bleeding risk. After developing a targeted cellular model using the CRISPR-dCas9-DNMT3A/Tet1CD-U6-sgRNA system and integrating with transcriptomic sequencing data, we conducted mechanistic cellular experiments to elucidate how these methylation sites affect platelet function recovery and bleeding risk. The findings were further validated through animal studies. Integrated analysis of EWAS and SMR-HEIDI revealed that hypermethylation at CpG site cg03230175 within the GPD2 gene promoter region was significantly associated with decreased GPD2 gene expression (P = 1.76E-18), delayed platelet functional recovery (P = 9.02 × 10^-3), and elevated hemorrhagic risk (P = 2.71 × 10^-2). Transcriptomic studies indicated that GPD2 gene (cg03230175) methylation affects mitochondrial function, nuclear factor kappa B (NF-κB) signaling pathway, reactive oxygen species metabolic process, and G protein-coupled receptor (GPCR) ligand binding. Cellular experiments demonstrated that the GPD2 gene (cg03230175) methylation inhibits coagulation function by suppressing reactive oxygen species (ROS) production, NF-κB activation, and P2Y12 gene expression (P2Y12 receptor plays a pivotal role in platelet activation, thrombus formation, and the pathogenesis of thrombotic disorders). The animal study results confirmed that GPD2 enzyme inhibition can indeed prolong the clotting time in mice. GPD2 gene (cg03230175) methylation resulted in reduced gene expression levels, inhibited mitochondrial energy metabolism, decreased ROS levels, and affected P2Y12 gene expression through the NF-κB pathway, ultimately leading to inhibition of coagulation function. Registry: The Impact of Genotype on Pharmacokinetics and Antiplatelet Effects of Ticagrelor in Healthy Chinese (IGPPT). NCT03092076. Date of Registration: 09 March 2017, retrospectively registered. URL of trial registry record: https://clinicaltrials.gov/ct2/show/NCT03092076 .

Atherosclerosis serves as the main pathological basis of numerous cardiovascular diseases and begins with endothelial cell activation. The traditional Chinese medicine Rhizoma Corydalis has garnered significant attention for its efficacy in treating cardiovascular conditions. However, its specific molecular mechanism remains unclear. This research sought to systematically explore the effects of levo-corydalmine (l-CDL) on endothelial proinflammatory activation and the related mechanisms. Network pharmacology combined with molecular docking assays was employed to construct a compound-target-pathway network and determine the optimal binding affinities between the compounds and atherosclerosis-related targets. Additionally, experimental studies were conducted to validate the regulatory effects of l-CDL on endothelial proinflammatory activation and vascular tension. Network pharmacology and molecular docking analysis revealed that l-CDL exhibited strong binding affinities for several core atherosclerosis-related targets. The results of the CCK-8, qRT-PCR, western blot, SA-β-gal staining, and fluorescence assays revealed that l-CDL suppressed ox-LDL-induced endothelial cell activation by increasing cell viability, alleviating inflammatory and senescence marker levels, and upregulating endothelial nitric oxide synthase (eNOS) in endothelial cells. A vascular ring assay further demonstrated that l-CDL promoted endothelium-dependent vasodilation under both physiological and ox-LDL-induced pathological conditions. Mechanistically, RNA sequencing and luciferase reporter gene analyses revealed that l-CDL inhibited the transcriptional activity of DNA damage inducible transcript 3 (DDIT3) and subsequently promoted eNOS expression, and these effects can be reversed by overexpression of DDIT3. This study revealed that l-CDL enhances eNOS expression by inhibiting DDIT3 expression, thereby suppressing ox-LDL-induced endothelial cell activation and improving vasodilatation. These findings indicate that l-CDL could be a potential therapeutic agent for preventing and treating endothelial proinflammatory activation and atherosclerosis. Graphical Abstract

Aims Long-term statin use has been linked to increased diabetes risk. Iron metabolism disruption may explain this association. The objective of this study was to identify the co-expression gene modules and the iron metabolism-related gene (IMG) linking statin administration and diabetes, making the hunt for novel therapeutic targets necessary. Methods Weighted gene co-expression network analysis (WGCNA) was applied to the GSE130991 dataset to detect co-expressed gene modules. Enrichment analysis and single sample gene set enrichment analysis (ssGSEA) were conducted to characterize the biological processes and iron metabolism differences, respectively. Candidate IMGs were identified by intersecting WGCNA hub genes, differentially expressed genes (DEGs) from the statin-using and non-using obese individuals within the GSE130991 liver tissue dataset, and IMGs from Molecular Signatures Database Molecular Signatures Database (MisgDB). Mediation analysis was utilized to identify the definitive IMG. Expression validation was conducted through reverse transcription quantitative PCR (RT-qPCR) experiments and cross-referencing with additional datasets. Results A shared gene module was identified between statin-users and diabetes patients, with functional enrichment analysis indicating involvement in iron ion binding. ssGSEA revealed differentially expressed iron metabolism in both statin-users and diabetes patients. Five IMG genes (CYP51A1, SC5D, MSMO1, SCD, and FLVCR1) were shortlisted, with FLVCR1 emerging as the key intermediary biomarker. FLVCR1 was positively correlated with insulin resistance and demonstrated robust predictive capabilities for diabetes. An increase in FLVCR1 mRNA levels was observed following statin treatment, as confirmed by RT-qPCR experiments and the GSE24188 dataset. Elevated FLVCR1 mRNA was also noted in diabetes patients across datasets GSE130991, GSE23343, and GSE95849. Conclusion In this study, bioinformatics evidence supporting the association between statin use and diabetes was presented. FLVCR1 was identified as the iron metabolism-related mediator gene implicated in this relationship. Overall, our findings provide a theoretical foundation for new directions for future research exploring the complex interplay between statin treatment, iron metabolism regulation, and diabetes pathogenesis.

Liver hepatocellular carcinoma (LIHC) is a highly heterogeneous disease, necessitating the discovery of novel biomarkers to enhance individualized treatment approaches. Recent research has shown the significant involvement of ubiquitin-related genes (UbRGs) in the progression of LIHC. However, the prognostic value of UbRGs in LIHC has not been investigated. In this study, the mRNA expression profiles and clinical data were obtained from public databases of LIHC patients. The least absolute shrinkage and selection operator Cox regression model was employed to construct a multigene signature in the TCGA cohort. Our results showed that a twelve UbRGs signature was developed to categorize patients into two risk groups, with significant differences in expression between LIHC and normal tissues. Patients in the high-risk group exhibited significantly reduced overall survival (OS) and progression-free survival compared to those in the low-risk group. The risk score was identified as an independent predictor for OS in multivariate Cox regression analyses. Receiver operating characteristic curve analysis confirmed the predictive capacity of the signature. Functional analysis revealed enrichment of immune-related pathways and differences in immune status between the two risk groups. The risk score was correlated with 35 transcription factors and 26 eRNA enhancers, and positively associated with tumor mutation burden. Patients in the high-risk group demonstrated decreased sensitivity to targeted and chemotherapeutic drugs than those in the low-risk group. In conclusion, our study identified a twelve UbRGs signature that may serve as a prognostic predictor for LIHC patients and and provide valuable insights for cancer treatment.