OPA1, a molecular regulator of dilated cardiomyopathy.

Dilated cardiomyopathy (DCM) is a disease with no specific treatment, poor prognosis and high mortality. During DCM development, there is apoptosis, mitochondrial dynamics imbalance and changes in cristae structure. Optic atrophy 1 (OPA1) appears at high frequency in these three aspects. DCM LMNA (LaminA/C) gene mutation can activate TP53, and the study of P53 shows that P53 affects OPA1 through Bak/Bax and OMA1 (a metalloprotease). OPA1 can be considered the missing link between DCMp53 and DCM apoptosis, mitochondrial dynamics imbalance and changes in cristae structure. OPA1 regulates apoptosis by regulating the release of cytochrome c from the mitochondrial matrix through CJs (crisp linkages, located in the inner mitochondrial membrane) and unbalances mitochondrial fusion and fission by affecting mitochondrial inner membrane (IM) fusion. OPA1 is also associated with the formation and maintenance of mitochondrial cristae. OPA1 is not the root cause of DCM, but it is an essential mediator in P53 mediating the occurrence and development of DCM, so OPA1 also becomes a molecular regulator of DCM. This review discusses the implication of OPA1 for DCM from three aspects: apoptosis, mitochondrial dynamics and ridge structure.

Association of triglyceride glucose index with all-cause and cardiovascular mortality in the general population.

OBJECTIVE: The Triglyceride-glucose (TyG) index, a novel indicator of insulin resistance, has been associated with mortality from coronary artery diseases, ischemic stroke, and heart failure. In recent years, much emphasis has been placed on the relationship between the TyG index and mortality in the general population. However, the impact of age on the association between TyG and all-cause and cardiovascular mortality remains controversial. This study investigated the link between the TyG index and all-cause and cardiovascular mortality, emphasizing differences between older and non-older populations. METHODS: Data from the National Health and Nutrition Examination Survey (2009-2018), encompassing 20,194 participants, were analyzed. The baseline TyG index was calculated as Ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2]. Multivariate Cox proportional hazards regression models with restricted cubic splines and trend tests were employed to explore the association between the TyG index and all-cause and cardiovascular mortality, with emphasis on age-specific analysis. Subgroup analysis was conducted to examine whether the TyG index's association with mortality varied across different subgroups. Additionally, receiver operating characteristic curves were used to compare the predictive ability of the TyG index with the homeostasis model assessment of insulin resistance (HOMA-IR) for all-cause and cardiovascular mortality. RESULTS: Over a median follow-up period of 105 months, all-cause mortality accounted for 13.345% of cases, and cardiovascular mortality accounted for 3.387%. Kaplan-Meier curves showed a significant increase in all-cause and cardiovascular mortality with higher TyG index values (both P for log-rank test < 0.001). However, during Cox proportional hazards regression analysis, no linear trend was observed between the TyG index and all-cause or cardiovascular mortality after adjusting for confounding factors (all-cause mortality: P for trend = 0.424; cardiovascular mortality: P for trend = 0.481). Restricted cubic splines revealed a non-linear association between the baseline TyG index and all-cause and cardiovascular mortality in the overall population (all-cause mortality: Non-linear P = 0.003; cardiovascular mortality: Non-linear P = 0.034). The effect of the TyG index was consistent across most subgroups in terms of all-cause and cardiovascular mortality, with no significant interaction with randomized factors (all-cause mortality: P for interaction = 0.077-0.940, cardiovascular mortality: P for interaction = 0.173-0.987), except for the age subgroup (all-cause mortality: P for interaction < 0.001, cardiovascular mortality: P for interaction < 0.001). Further age-specific analysis revealed that the association between the TyG index and all-cause and cardiovascular mortality remained significant in patients aged < 65 but not in those aged ≥ 65. Interestingly, a non-linear association was observed between the TyG index and all-cause mortality in individuals aged < 65 (Non-linear P = 0.011), while a linear relationship was observed with cardiovascular mortality, showing an upward trend (Non-linear P = 0.742, P for trend = 0.010). Further stratification according to age yielded similar results only in patients aged 45-64 (all-cause mortality: Non-linear P = 0.001 and cardiovascular mortality: Non-linear P = 0.902, P for trend = 0.015). Compared to HOMA-IR, the TyG index demonstrated superior predictive performance for all-cause and cardiovascular mortality (all-cause mortality: 0.620 vs. 0.524, P < 0.001; cardiovascular mortality: 0.623 vs. 0.537, P < 0.001). CONCLUSIONS: This study established a significant association between the TyG index and all-cause and cardiovascular mortality in the general population, particularly among individuals aged < 65. Notably, a non-linear association with all-cause mortality was observed in those aged < 65, while a linear relationship with cardiovascular mortality was found.

Association between monocyte to high-density lipoprotein cholesterol ratio and multi-vessel coronary artery disease: a cross-sectional study.

BACKGROUND: Patients with multi-vessel coronary artery disease (MV-CAD) have poorer clinical outcomes than those with single-vessel coronary artery disease (SV-CAD). Solid evidence underlines that high-density lipoprotein cholesterol (HDL-C) plays a protective role and monocyte plays a negative role in coronary artery disease (CAD). However, the monocyte to high-density lipoprotein ratio (MHR) has not been studied in relation to MV-CAD. METHODS: In this study, 640 patients underwent coronary angiography, of whom 225 had severe coronary artery disease. Then divide the above two groups of patients into three groups based on the MHR tertiles, respectively. Logistic regression and subgroup analysis were carried out to estimate the association between MHR and MV-CAD. The receiver operating characteristic (ROC) curve analysis was constructed by combining classic CAD risk factors with MHR in response to MV-CAD. In addition, the mediating effect of MHR between smoking and MV-CAD in suspected CAD Patients was analyzed. RESULTS: Among the three MHR groups, a statistically discrepant was observed in the number of patients with CAD, Severe-CAD and MV-CAD (PCAD < 0.001; PSevere-CAD < 0.001; PMV-CAD = 0.001) in suspected CAD patients. Furthermore, the number of patients with MV-CAD (P < 0.001) was different in Severe-CAD patients among three MHR groups. Non-CAD and CAD patients showed statistically discrepant in MHR levels (P < 0.001), and this difference also was observed between SV-CAD and MV-CAD patients (P < 0.001). In the analysis of suspected CAD patients, a significantly positive relationship was found between MHR and CAD, Severe-CAD, and MV-CAD (P for trend < 0.001). The effect of MHR on MV-CAD was consistent across all subgroups, with no significant randomized factor-by-subgroup interaction (P-interaction = 0.17-0.89). ROC analysis showed that the model constructed with MHR and classic influencing factors of CAD was superior to the model constructed solely based on classic influencing factors of CAD (0.742 vs.0.682, P = 0.002). In the analysis of Severe-CAD patients, patients with higher MHR levels had a higher risk of MV-CAD [OR (95%CI): 2.90 (1.49, 5.62), P for trend = 0.002] compared to patients with lower MHR. The trends persisted after adjusting for demographic (P for trend = 0.004) and classic influencing factors of CAD (P for trend = 0.009). All subgroup factors for patients with MV-CAD had no interaction with MHR (P-interaction = 0.15-0.86). ROC analysis showed that the model combining MHR and classic influencing factors of CAD was superior to the one including only the classic influencing factors of CAD (0.716 vs.0.650, P = 0.046). Assuming that MHR played a mediating effect between smoking and MV-CAD in suspected CAD patients. The results indicated that MHR played a partial mediating effect of 0.48 (P < 0.001). CONCLUSION: A higher MHR was mainly associated with multi-vessel coronary artery disease and MHR partially mediated the association between smoking and MV-CAD.