Coronary artery disease-associated immune gene RBP1 and its pan-cancer analysis

Comprehensive Analysis Based on Genes Associated With Cuproptosis, Ferroptosis, and Pyroptosis for the Prediction of Diagnosis and Therapies in Coronary Artery Disease

Coronary artery disease (CAD) is a complex condition influenced by genetic factors, lifestyle, and other risk factors that contribute to increased mortality. This study is aimed at evaluating the diagnostic potential of genes associated with cuproptosis, ferroptosis, and pyroptosis (CFP) using network modularization and machine learning methods. CAD-related datasets GSE42148, GSE20680, and GSE20681 were sourced from the GEO database, and genes related to CFP genes were gathered from MsigDB and FerrDb datasets and literature. To identify diagnostic genes linked to these pathways, weighted gene coexpression network analysis (WGCNA) was used to isolate CAD-related modules. The diagnostic accuracy of key genes in these modules was then assessed using LASSO, SVM, and random forest models. Immunity and drug sensitivity correlation analyses were subsequently performed to investigate possible underlying mechanisms. The function of a potential gene, STK17B, was analyzed through western blot and transwell assays. Two CAD-related modules with strong correlations were identified and validated. The SVM model outperformed LASSO and random forest models, demonstrating superior discriminative power (AUC = 0.997 in the blue module and AUC = 1.000 in the turquoise module), with nine key genes identified: CTDSP2, DHRS7, NLRP1, MARCKS, PELI1, RILPL2, JUNB, STK17B, and SLC40A1. Knockdown of STK17B inhibited cell migration and invasion in human umbilical vein endothelial cells. In summary, our findings suggest that CFP genes hold potential as diagnostic biomarkers and therapeutic targets, with STK17B playing a role in CAD progression.

Identification of Disease-Relevant, Sex-Based Proteomic Differences in iPSC-Derived Vascular Smooth Muscle Cells

The prevalence of cardiovascular disease varies with sex, and the impact of intrinsic sex-based differences on vasculature is not well understood. Animal models can provide important insights into some aspects of human biology; however, not all discoveries in animal systems translate well to humans. To explore the impact of chromosomal sex on proteomic phenotypes, we used iPSC-derived vascular smooth muscle cells from healthy donors of both sexes to identify sex-based proteomic differences and their possible effects on cardiovascular pathophysiology. Our analysis confirmed that differentiated cells have a proteomic profile more similar to healthy primary aortic smooth muscle cells than iPSCs. We also identified sex-based differences in iPSC-derived vascular smooth muscle cells in pathways related to ATP binding, glycogen metabolic process, and cadherin binding as well as multiple proteins relevant to cardiovascular pathophysiology and disease. Additionally, we explored the role of autosomal and sex chromosomes in protein regulation, identifying that proteins on autosomal chromosomes also show sex-based regulation that may affect the protein expression of proteins from autosomal chromosomes. This work supports the biological relevance of iPSC-derived vascular smooth muscle cells as a model for disease, and further exploration of the pathways identified here can lead to the discovery of sex-specific pharmacological targets for cardiovascular disease.

The impact of immunity on the risk of coronary artery disease: insights from a multiomics study

BACKGROUND

Immune inflammation is intricately associated with coronary artery disease (CAD) progression, necessitating the pursuit of more efficacious therapeutic strategies. This study aimed to uncover potential therapeutic targets for CAD and myocardial infarction (MI) by elucidating the causal connection between regulatory immune-related genes (RIRGs) and these disorders.

METHODOLOGY

We performed summary data-based Mendelian randomization analysis to assess the therapeutic targets linked to expression quantitative trait loci and methylation quantitative trait loci of RIRGs in relation to CAD and MI. Independent validation cohorts and datasets from coronary artery and left ventricular heart tissue were analyzed. To strengthen causal inference, colocalization analysis and PhenoScanner phenotype scans were employed.

RESULTS

Utilizing multiomics integration, we pinpointed EIF2B2, FCHO1, and DDT as CAD risk genes. Notably, EIF2B2 and FCHO1 displayed significant associations with MI. High EIF2B2 expression, regulated by cg16144293, heightened CAD and MI risk at rs175438. In contrast, enhanced FCHO1 expression, modulated by cg18329931, reduced CAD and MI risk at rs13382133. DDT upregulation influenced by cg11060661 and cg09664220 was associated with decreased CAD risk at rs5760120. Colocalization analysis firmly established these relationships.

CONCLUSION

EIF2B2, FCHO1, and DDT represent risk loci for CAD progression within RIRGs. Our identification of these genes enhances understanding of CAD pathogenesis and directs future drug development efforts.

Identification of Disease-relevant, Sex-based Proteomic Differences in iPSC-derived Vascular Smooth Muscle

The prevalence of cardiovascular disease varies with sex, and the impact of intrinsic sex-based differences on vasculature is not well understood. Animal models can provide important insight into some aspects of human biology, however not all discoveries in animal systems translate well to humans. To explore the impact of chromosomal sex on proteomic phenotypes, we used iPSC-derived vascular smooth muscle cells from healthy donors of both sexes to identify sex-based proteomic differences and their possible effects on cardiovascular pathophysiology. Our analysis confirmed that differentiated cells have a proteomic profile more similar to healthy primary aortic smooth muscle than iPSCs. We also identified sex-based differences in iPSC- derived vascular smooth muscle in pathways related to ATP binding, glycogen metabolic process, and cadherin binding as well as multiple proteins relevant to cardiovascular pathophysiology and disease. Additionally, we explored the role of autosomal and sex chromosomes in protein regulation, identifying that proteins on autosomal chromosomes also show sex-based regulation that may affect the protein expression of proteins from autosomal chromosomes. This work supports the biological relevance of iPSC-derived vascular smooth muscle cells as a model for disease, and further exploration of the pathways identified here can lead to the discovery of sex-specific pharmacological targets for cardiovascular disease.

Significance

In this work, we have differentiated 4 male and 4 female iPSC lines into vascular smooth muscle cells, giving us the ability to identify statistically-significant sex-specific proteomic markers that are relevant to cardiovascular disease risk (such as PCK2, MTOR, IGFBP2, PTGR2, and SULTE1).

Identification of Endoplasmic Reticulum Stress-Related Biomarkers in Coronary Artery Disease

Coronary artery disease (CAD) is caused by atherosclerotic lesions in the coronary vessels. Endoplasmic reticulum stress (ERS) acts in cardiovascular disease, and its role in CAD is not clear. A total of 13 differentially expressed ERS-related genes (DEERSRGs) in CAD were identified. Functional enrichment analysis demonstrated the DEERSRGs were mainly enriched in endoplasmic reticulum (ER)-related pathways. Then, eight genes (RCN2, HRC, DERL2, RNF183, CRH, TMED2, PPP1R15A, and IL1A) were authenticated as ERS-related biomarkers in CAD by least absolute shrinkage and selection operator (LASSO). The receiver operating characteristic (ROC) analysis showed that the LASSO logistic model constructed based on biomarkers had a better diagnostic effect, which was confirmed by the ANN and GSE23561 datasets. Also, ROC results showed that seven of the eight biomarkers had better diagnostic effects. The nomogram model had good predictive power, and biomarkers were mostly enriched in pathways associated with CAD. The biomarkers were significantly associated with 10 immune cells, and RCN2, DERL2, TMED2, and RNF183 were negatively correlated with most chemokines. Eight biomarkers had significant correlations with both immunoinhibitors and immunostimulators. In addition, eight biomarkers were significantly different in both CAD and control samples, CRH and HRC were upregulated in CAD. The quantitative reverse transcription-polymerase chain reaction (qRT-PCR) showed that RCN2, HRC, DERL2, CRH, and IL1A were consistent with the bioinformatics analysis. RCN2, HRC, DERL2, RNF183, CRH, TMED2, PPP1R15A, and IL1A were identified as biomarkers of CAD. Functional enrichment analysis and immunoassays for biomarkers provide new ideas for the treatment of CAD.

Integrative bioinformatics analysis identifies APOB as a critical biomarker in coronary in-stent restenosis

Aim: Coronary artery disease (CAD) is a major contributor to the worldwide prevalence of cardiovascular disease. In-stent restenosis (ISR) is a common complication which can lead to stent implantation failure, necessitating repeated intervention and presenting a significant obstacle for CAD management. Methods: To accurately assess and determine the hub genes associated with ISR, CAD databases from the Gene Expression Omnibus were utilized and weighted gene coexpression network analysis was employed to identify key genes in blood samples. Results: APOB was identified as a risk gene for ISR occurrence. Subsequent correlation analysis of APOB demonstrated a positive association with ISR. Clinical validation further confirmed the predictive value of APOB in ISR detection. Conclusion: We have identified APOB as a critical predictive biomarker for ISR in CAD patients.