Plasma Olink Proteomics Reveals Novel Biomarkers for Prediction and Diagnosis in Dilated Cardiomyopathy with Heart Failure.

In this study, we utilized the Olink Cardiovascular III panel to compare the expression levels of 92 cardiovascular-related proteins between patients with dilated cardiomyopathy combined with heart failure (DCM-HF) (n = 20) and healthy normal people (Normal) (n = 18). The top five most significant proteins, including SPP1, IGFBP7, F11R, CHI3L1, and Plaur, were selected by Olink proteomics. These proteins were further validated using ELISA in plasma samples collected from an additional cohort. ELISA validation confirmed significant increases in SPP1, IGFBP7, F11R, CHI3L1, and Plaur in DCM-HF patients compared to healthy controls. GO and KEGG analysis indicated that NT-pro BNP, SPP1, IGFBP7, F11R, CHI3L1, Plaur, BLM hydrolase, CSTB, Gal-4, CCL15, CDH5, SR-PSOX, and CCL2 were associated with DCM-HF. Correlation analysis revealed that these 13 differentially expressed proteins have strong correlations with clinical indicators such as LVEF and NT-pro BNP, etc. Additionally, in the GEO-DCM data sets, the combined diagnostic value of these five core proteins AUC values of 0.959, 0.773, and 0.803, respectively indicating the predictive value of the five core proteins for DCM-HF. Our findings suggest that these proteins may be useful biomarkers for the diagnosis and prediction of DCM-HF, and further research is prompted to explore their potential as therapeutic targets.

Association of TyG index with aortic valve calcification in valvular heart disease patients.

BACKGROUND: In recent years, triglyceride glucose (TyG) index, as a popular metabolic index, has been proposed as an alternative index of insulin resistance, and it has been proved to be associated with many cardiovascular diseases, but the relationship between it and aortic valve calcification is still unknown. METHODS: A total of 450 aortic valve disease patients were enrolled in this study, including 361 patients with aortic valve calcification (AVC) (calcification group) and 89 patients without (control group). According to the severity of AVC, patients with AVC included severe calcification, moderate calcification and low calcification. The TyG index was calculated based on fasting triglyceride and fasting blood glucose levels. RESULTS: The TyG index in the calcification group was significantly higher than that in the control group (P < .05), and with the increase of the degree of calcification, the TyG index showed an increasing trend. The univariate and multivariate logistic regression analysis showed TyG index has a high predictive value for the presence of AVC (OR (95% CI): 1.743 (1.036-2.933)) and severe AVC (OR (95% CI): 1.608 (1.143-2.262)). In assessing the predictive value of the TyG index distribution width for AVC, with the first quartile as a reference, the last quartile of the TyG index had significant predictive value for the presence of AVC and severe AVC. CONCLUSIONS: TyG index was significantly associated with the presence and severity of AVC, suggesting that TyG index may be a valid predictor of AVC.

Advances in Ion Channel, Non-Desmosomal Variants and Autophagic Mechanisms Implicated in Arrhythmogenic Cardiomyopathy.

Arrhythmogenic cardiomyopathy (ACM) is a heterogeneous disorder characterized by the replacement of cardiac myocytes with fibro-fatty tissues, leading to abnormal excitation-contraction (EC) coupling and a range of malignant events, such as ventricular tachycardia (VT), sudden cardiac death/arrest (SCD/A) and heart failure (HF). The concept of ACM has recently been ex-tended to include right ventricular cardiomyopathy (ARVC), left ventricular cardiomyopathy (ALVC) and biventricular cardiomyopathy. ARVC is generally seen as the most common type of ACM. The pathogenesis of ACM involves mutation variants in desmosomal or non-desmosomal gene loci, as well as various external factors, such as intense exercise, stress and infections. Ion channel alterations, autophagy and non-desmosomal variants are also important components in the development of ACM. As clinical practice enters the era of precision therapy, it is important to review recent studies on these topics to better diagnose and treat the molecular phase of ACM.

A Mendelian analysis of the relationships between immune cells and breast cancer.

Background: Emerging evidence showed immune cells were associated with the development of breast cancer. Nonetheless, the causal link between them remains uncertain. Consequently, the objective of this study was to investigate the causal connection between immune traits and the likelihood of developing breast cancer. Methods: A two-sample Mendelian randomization (MR) analysis was conducted to establish the causal relationship between immune cells and breast cancer in this study. Utilizing publicly accessible genetic data, we investigated causal connections between 731 immune cells and the occurrence of breast cancer. The primary approach for exploring this relationship was the application of the inverse-variance-weighted (IVW) method. Furthermore, sensitivity analyses, encompassing the leave-one-out analysis, Cochran Q test, and Egger intercept test were performed to validate the reliability of the Mendelian randomization results. Finally, we used Bayesian Weighted Mendelian Randomization (BWMR) approach to test the results of MR study. Results: According to the Bonferroni correction, no immune trait was identified with a decreased or increased risk of overall breast cancer risk. As for the ER+ breast cancer, 6 immune trait was identified after the Bonferroni method. the IVW method results showed that CD45RA- CD4+ %CD4+ (p-value:1.37×10-6), CD8dim %T cell (p-value:4.62×10-43), BAFF-R on IgD+ CD38- unsw mem (p-value:6.93×10-5), CD27 on PB/PC (p-value:2.72×10-18) lowered the risk of breast cancer. However, CD19 on IgD- CD38br (p-value:1.64×10-6), CD25 on IgD+ CD38dim (p-value: - ∞) were associated with a higher risk of developing breast cancer. As for the CX3CR1 on CD14+ CD16- monocyte (p-value: 1.15×10-166), the IVW method clearly demonstrated a protective effect against ER- breast cancer. For the above positive results, BAFF-R on IgD+ CD38- unsw mem was the sole association linked to reduced breast cancer risk using the BWMR method. The intercept terms' p-values in MR-Egger regression all exceeded 0.05, indicating the absence of potential horizontal pleiotropy. Conclusion: Through genetic approaches, our study has illustrated the distinct correlation between immune cells and breast cancer, potentially paving the way for earlier diagnosis and more efficient treatment alternatives.

Generation of an integration-free induced pluripotent stem cell (iPSC) line (SDHI001-A) from a 65-year old adult mitral valve prolapse (MVP) patient.

Human iPSC line, SDHi001-A, was generated from 65-year-old male patient with mitral valve prolapse, using non-integrative reprogramming method. This cell line shows pluripotency both in vitro and in vivo, and has a normal karyotype.

Molecular subtypes of ischemic heart disease based on circadian rhythm.

Coronary atherosclerotic heart disease (CAD) is among the most prevalent chronic diseases globally. Circadian rhythm disruption (CRD) is closely associated with the progression of various diseases. However, the precise role of CRD in the development of CAD remains to be elucidated. The Circadian rhythm disruption score (CRDscore) was employed to quantitatively assess the level of CRD in CAD samples. Our investigation revealed a significant association between high CRDscore and adverse prognosis in CAD patients, along with a substantial correlation with CAD progression. Remarkably distinct CRDscore distributions were also identified among various subtypes. In summary, we have pioneered the revelation of the relationship between CRD and CAD at the single-cell level and established reliable markers for the development, treatment, and prognosis of CAD. A deeper understanding of these mechanisms may offer new possibilities for incorporating "the therapy of coronary heart disease based circadian rhythm" into personalized medical treatment regimens.

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.

Association between AGTR1 (c.1166 A>C) Polymorphisms and Kidney Injury in Hypertension.

BACKGROUND: High blood pressure is the main cause of cardiovascular diseases. Kidney damage is one of the most common organ secondary damage to hypertension. The study of hypertension gene polymorphisms is an important means of precision treatment of primary hypertension. OBJECTIVES: The objective of this study was to explore the relationship between AGTR1 (c.1166 A>C) gene polymorphisms and hypertension combined with kidney damage, while exploring the relationship between codominant, dominant and recessive gene model and hypertension with kidney injury and the susceptibility of different genotypes to hypertension with kidney injury. METHODS: The distribution of AGTR1 polymorphism in the AGTR1 in hypertensive patients (hypertension group, 292 patients) and hypertension with kidney injury patients (44 patients) were detected and compared by PCR-melting curve method. RESULTS: The genotype distribution of hypertension and combined groups met Hardy-Weinberg equilibrium (p > 0.05); the distribution difference between the three genotypes was statistically significant (p < 0.05), the codominant, dominant and recessive distribution frequency of genotypes (p < 0.05), and no difference between A allele and C allele (p > 0.05). CONCLUSIONS: Our study identified the relationship of AGTRA (c.1166 A>C) with hypertension combined with renal injury, and compared the susceptibility of different genetic models, which may provide novel targets for precision gene therapy of hypertension. CLINICAL TRIAL REGISTRATION: URL: https://www.chictr.org.cn/indexEN.html; Unique identifier: ChiCTR2100051472.