Identification of diagnostic signature and immune infiltration for ischemic cardiomyopathy based on cuproptosis-related genes through bioinformatics analysis and experimental validation.

BACKGROUND: Ischemic cardiomyopathy (IC) is primarily due to long-term ischemia/hypoxia of the coronary arteries, leading to impaired cardiac contractile or diastolic function. A new form of cell death induced by copper, called "cuproptosis" is related to the development and progression of multiple diseases. The cuproptosis-related gene (CuGs) plays an important role in acute myocardial infarction, while the specific mechanisms of CuGs in ischemic cardiomyopathy remain unclear. METHODS: The expressions of CuGs and their immune characteristics were analyzed with the IC datasets obtained from the Gene Expression Omnibus, namely GSE5406 and GSE57338, identifying core genes associated with IC development. By comparing RF, SVM, GLM and XGB models, the optimal machine learning model was selected. The expression of marker genes was validated based on the GSE57345, GSE48166 and GSE42955 datasets. Construct a CeRNA network based on core genes. Therapeutic chemiacals targeting core genes were acquired using the CTD database, and molecular docking was performed using Autodock vina software. By ligating the left anterior descending (LAD) coronary artery, an IC mouse model is established, and core genes were experimentally validated using Western blot (WB) and immunohistochemistry (IHC) methods. RESULTS: We identified 14 CuGs closely associated with the onset of IC. The SVM model exhibited superior discriminative power (AUC = 0.914), with core genes being DLST, ATP7B, FDX1, SLC31A1 and DLAT. Core genes were validated on the GSE42955, GSE48166 and GSE57345 datasets, showing excellent performance (AUC = 0.943, AUC = 0.800, and AUC = 0.932). The CeRNA network consists of 218 nodes and 264 lines, including 5 core diagnostic genes, 52 miRNAs, and 161 lncRNAs. Chemicals predictions indicated 8 chemicals have therapeutic effects on the core diagnostic genes, with benzo(a)pyrene molecular docking showing the highest affinity (-11.3 kcal/mol). Compared to the normal group, the IC group,which was established by LAD ligation, showed a significant decrease in LVEF as indicated by cardiac ultrasound, and increased fibrosis as shown by MASSON staining, WB results suggest increased expression of DLST and ATP7B, and decreased expression of FDX1, SLC31A1 and DLAT in the myocardial ischemic area (p < 0.05), which was also confirmed by IHC in tissue sections. CONCLUSION: In summary, this study comprehensively revealed that DLST, ATP7B, FDX1, SLC31A1 and DLAT could be identified as potential immunological biomarkers in IC, and validated through an IC mouse model, providing valuable insights for future research into the mechanisms of CuGs and its diagnostic value to IC.

Diagnostic accuracy of the FRAIL scale for frailty screening in community-dwelling older adults with diabetes: A cross-sectional study.

There is limited evidence on the diagnostic accuracy of the FRAIL scale in community-dwelling older adults with diabetes. This study aimed to validate the diagnostic accuracy and determine the optimal cutoff point of the FRAIL scale in community-dwelling older adults with diabetes using the Fried Frailty Phenotype as the reference standard. A total of 489 community-dwelling older adults with diabetes aged 60 or above were recruited in this cross-sectional study. The FRAIL scale showed good diagnostic accuracy for frailty screening. The optimal cutoff point for frailty screening in older adults with diabetes was 2. The agreement between the FRAIL scale and the Fried Frailty Phenotype was substantial. The FRAIL scale classified more participants as frail (29.24%) than the Fried Frailty Phenotype (22.09%). These findings provide evidence that the FRAIL scale is a valid tool that can be applied to community-dwelling older adults with diabetes.

Epicardial fat volume is correlated with coronary lesion and its severity.

OBJECTIVE: To evaluate the correlation of epicardial adipose tissue volume (EATV) with the coronary artery lesion and its severity. METHODS: Inpatients with suspicious stable angina of coronary heart lesion were recruited. For patients with coronary artery lesions in CTA, further coronary angiography (CAG) was performed to evaluate the coronary artery lesion. Gensini scoring system was employed to assess the severity of coronary artery lesions. RESULTS: Patients were classified as coronary heart disease (CHD) group (n = 160). Results showed the mean EATV was 192.57 ± 30.32 cm(3) in CHD group, which was significantly larger than that in control group (138.56 ± 23.18 cm(3); P < 0.01). The coronary artery stenosis was classified as mild, moderate and severe stenosis according to the extent of coronary artery lesions, and results showed marked difference in the EATV among patients with different severities of coronary artery stenosis (P < 0.005). The Gensini score was positively related to EATV (r = 0.285, P = 0.000). The EATV increased with the increase in the number of affected coronary arteries. Multivariate Logistic regression analysis showed EATV was an independent risk factor of CHD after adjusting other confounding factors (OR = 1.023, P = 0.013). CONCLUSION: EATV is closely related to the severity of coronary artery lesions: the larger the EATV, the more severe the coronary artery lesions. Moreover, EATV is an independent risk factor of CHD.