Objective:To explore the predictive value of triglyceride-glucose (TyG) index combined with low-density lipoprotein cholesterol (LDL-C) for major adverse cardiovascular events (MACE) in patients with coronary heart disease (CHD) complicated by type 2 diabetes mellitus (T2DM).Methods:A total of 248 patients with CHD and T2DM admitted to the First Affiliated Hospital of Xinjiang Medical University from July 2022 to January 2024 were retrospectively enrolled. All patients were followed up for 2 years and divided into MACE group (43 cases) and non-MACE group (205 cases) according to the occurrence of MACE. Indicators such as TyG index and LDL-C were compared between the two groups, and their correlations with MACE were analyzed. Multivariate logistic regression was used to screen the risk factors for MACE in patients with CHD and T2DM. Receiver operating characteristic (ROC) curve was used to evaluate the predictive value of TyG index, LDL-C, and their combination for MACE in these patients.Results:Compared with the non-MACE group, the MACE group had significantly higher LDL-C [2.63(2.23, 2.95)mmol/L vs 1.99(1.60, 2.66)mmol/L, P<0.001] and TyG index [9.30(8.80, 9.87) vs 8.60(8.09, 9.15), P<0.001]. Multivariate logistic regression showed that TyG index was an independent risk factor for MACE in patients with CHD and T2DM ( OR=10.49, P<0.001). ROC curve results indicated that the area under the curve (AUC) of TyG index and LDL-C for predicting MACE were 0.731 and 0.686, respectively. The combined AUC of the two indicators for predicting MACE was 0.769(95% CI: 0.698-0.840), showing better predictive performance. Conclusions:TyG index combined with LDL-C has high predictive value for the risk of MACE in patients with CHD complicated by T2DM.

Objective:To explore the predictive value of triglyceride-glucose (TyG) index combined with low-density lipoprotein cholesterol (LDL-C) for major adverse cardiovascular events (MACE) in patients with coronary heart disease (CHD) complicated by type 2 diabetes mellitus (T2DM).Methods:A total of 248 patients with CHD and T2DM admitted to the First Affiliated Hospital of Xinjiang Medical University from July 2022 to January 2024 were retrospectively enrolled. All patients were followed up for 2 years and divided into MACE group (43 cases) and non-MACE group (205 cases) according to the occurrence of MACE. Indicators such as TyG index and LDL-C were compared between the two groups, and their correlations with MACE were analyzed. Multivariate logistic regression was used to screen the risk factors for MACE in patients with CHD and T2DM. Receiver operating characteristic (ROC) curve was used to evaluate the predictive value of TyG index, LDL-C, and their combination for MACE in these patients.Results:Compared with the non-MACE group, the MACE group had significantly higher LDL-C [2.63(2.23, 2.95)mmol/L vs 1.99(1.60, 2.66)mmol/L, P<0.001] and TyG index [9.30(8.80, 9.87) vs 8.60(8.09, 9.15), P<0.001]. Multivariate logistic regression showed that TyG index was an independent risk factor for MACE in patients with CHD and T2DM ( OR=10.49, P<0.001). ROC curve results indicated that the area under the curve (AUC) of TyG index and LDL-C for predicting MACE were 0.731 and 0.686, respectively. The combined AUC of the two indicators for predicting MACE was 0.769(95% CI: 0.698-0.840), showing better predictive performance. Conclusions:TyG index combined with LDL-C has high predictive value for the risk of MACE in patients with CHD complicated by T2DM.

Objective:To explore the relationship between the polymorphisms of AHNAK2 gene rs12882641,rs28583515 and rs2582497 loci and coronary heart disease(CHD)in the population of Xinjiang.Materials:This study used a case-control method,a total of 602 patients who were hospitalized and underwent coronary angiogra-phy(CAG)at ourheart center from Jan 2019 to Dec 2021 were selected.According toCAG results,the patients were divided into CHD group(n=301)and non-CHD group(n=301).The AHNAK2 gene rs12882641,rs28583515 and rs2582497 loci were genotyped using the improved multiple ligase detection reaction(iMLDR)technique,and the relationship between AHNAK2 gene polymorphisms and CHD was analyzed.Results:Compared with non-CHD group,there was significant rise in the distribution frequencies of AC+CC genotypes(52.8%vs.61.1%,P= 0.040)at rs2582497 locus of the AHNAK2 gene under the dominant model;there was significant reduction in distri-bution frequency of the CC genotype(65.8%vs.53.8%)at the rs28583515 locus of the AHNAK2 gene,and signif-icant rise in distribution frequencies of CT+TT(34.2%vs.46.2%)under the dominant model,TT under the re-cessive model(0.7%vs.3.0%)and CT under the additive model(33.6%vs.43.2%)in CHD group,P＜0.05 or＜0.01.After adjusting for confounding factors,logistic regression analysis indicated that the dominant model of the rs28583515 locus remained an independent risk factor for CHD(OR=1.509,P=0.036).Conclusion:The AH-NAK2 gene rs28583515 locus is closely related to the occurrence and development of CHD in the Xinjiang popula-tion.The dominant model of the AHNAK2 gene rs28583515 locus is an independent risk factor for CHD.

Objective: To explore the clinical implication of tissue-related biomarkers in patients with acute aortic dissection (AAD). Methods: It was a cross-sectional study. Ten Stanford Type A AAD patients, who were diagnosed and surgically treated in the Department of Cardiology, First Affiliated Hospital of Xinjiang Medical University, from December 2018 to August 2019, were selected as the case group. Meanwhile, 10 patients with atherosclerotic heart disease, who underwent coronary artery bypass grafting (CABG), were selected as control group. The ascending aorta tissue specimens from patients of the two groups were collected during the operation. Four-dimensional non-standard quantitative proteomics technology (4D-LFQ) was used to detect the protein profile of ascending aorta tissue specimens of the two groups and to screen out differentially expressed proteins and analyze their biological functions. Precise quantification of the selected target proteins was achieved by parallel response monitoring (PRM). Results: A total of 3 985 proteins were identified by 4D-LFQ technology, among which 3 350 proteins could be quantified. There were 39 proteins were significantly upregulated and 47 proteins were significantly downregulated in AAD group. The results of biological function analysis showed that most of the differentially expressed proteins were located in the extracellular, and their functions were mainly involved in cell migration and proliferation, inflammatory cell activation, cell contraction, and muscle organ development. The 15 selected proteins underwent precise quantification by PRM, and the results showed that integrin α-Ⅱb (ITGA2B), integrin α-M (ITGAM), integrin β-2 (ITGB2), integrin β-3 (ITGB3) were significantly upregulated in the ascending aorta tissue of AAD patients. Conclusion: ITGA2B, ITGAM, ITGB2, and ITGB3 are highly expressed in aortic tissues of patients with AAD, which may be used as biomarkers for the diagnosis of AAD patients.
Aneurysm, Dissecting ; Aorta ; Biomarkers ; Coronary Artery Bypass ; Cross-Sectional Studies ; Humans