Analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods

Construction of ferroptosis-related prediction model for pathogenesis, diagnosis and treatment of ruptured abdominal aortic aneurysm

Abdominal aortic aneurysm (AAA) is a dangerous cardiovascular disease, which often brings great psychological burden and economic pressure to patients. If AAA rupture occurs, it is a serious threat to patients' lives. Therefore, it is of clinical value to actively explore the pathogenesis of ruptured AAA and prevent its occurrence. Ferroptosis is a new type of cell death dependent on lipid peroxidation, which plays an important role in many cardiovascular diseases. In this study, we used online data and analysis of ferroptosis-related genes to uncover the formation of ruptured AAA and potential therapeutic targets. We obtained ferroptosis-related differentially expressed genes (Fe-DEGs) from GSE98278 dataset and 259 known ferroptosis-related genes from FerrDb website. Enrichment analysis of differentially expressed genes (DEGs) was performed by gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG). Receiver Operating characteristic (ROC) curve was employed to evaluate the diagnostic abilities of Fe-DEGs. Transcription factors and miRNAs of Fe-DEGs were identified through PASTAA and miRDB, miRWalk, TargetScan respectively. Single-sample gene set enrichment analysis (ssGSEA) was used to observe immune infiltration between the stable group and the rupture group. DGIdb database was performed to find potential targeted drugs of DEGs. GO and KEGG enrichment analysis found that DEGs mainly enriched in "cellular divalent inorganic cation homeostasis," "cellular zinc ion homeostasis," "divalent inorganic cation homeostasis," "Mineral absorption," "Cytokine - cytokine receptor interaction," "Coronavirus disease - COVID-19." Two up-regulated Fe-DEGs MT1G and DDIT4 were found to further analysis. Both single and combined applications of MT1G and DDIT4 showed good diagnostic efficacy (AUC = 0.8254, 0.8548, 0.8577, respectively). Transcription factors STAT1 and PU1 of MT1G and ARNT and MAX of DDIT4 were identified. Meanwhile, has_miR-548p-MT1G pairs, has_miR-53-3p/has_miR-181b-5p/ has_miR-664a-3p-DDIT4 pairs were found. B cells, NK cells, Th2 cells were high expression in the rupture group compared with the stable group, while DCs, Th1 cells were low expression in the rupture group. Targeted drugs against immunity, GEMCITABINE and INDOMETHACIN were discovered. We preliminarily explored the clinical significance of Fe-DEGs MT1G and DDIT4 in the diagnosis of ruptured AAA, and proposed possible upstream regulatory transcription factors and miRNAs. In addition, we also analyzed the immune infiltration of stable and rupture groups, and found possible targeted drugs for immunotherapy.

Catabolic/Anabolic Imbalance Is Accompanied by Changes of Left Ventricular Steroid Nuclear Receptor Expression in Tachycardia-Induced Systolic Heart Failure in Male Pigs

BACKGROUND

Steroid hormones play an important role in heart failure (HF) pathogenesis, and clinical data have revealed disordered steroidogenesis in male patients with HF. However, there is still a lack of studies on steroid hormones and their receptors during HF progression. Therefore, a porcine model of tachycardia-induced cardiomyopathy corresponding to HF was used to assess steroid hormone concentrations in serum and their nuclear receptor levels in heart tissue during the consecutive stages of HF.

METHODS AND RESULTS

Male pigs underwent right ventricular pacing and developed a clinical picture of mild, moderate, or severe HF. Serum concentrations of dehydroepiandrosterone, testosterone, dihydrotestosterone, estradiol, aldosterone, and cortisol were assessed by enzyme-linked immunosorbent assay. Androgen receptor, estrogen receptor alpha, mineralocorticoid receptor, and glucocorticoid receptor messenger RNA levels in the left ventricle were determined by qPCR.The androgen level decreased in moderate and severe HF animals, while the corticosteroid level increased. The estradiol concentration remained stable. The quantitative real-time polymerase chain reaction revealed the downregulation of androgen receptor in consecutive stages of HF and increased expression of mineralocorticoid receptor messenger RNA under these conditions.

CONCLUSIONS

In the HF pig model, deteriorated catabolic/anabolic balance, manifested by upregulation of aldosterone and cortisol and downregulation of androgen signaling on the ligand level, was augmented by changes in steroid hormone receptor expression in the heart tissue.

Identification of target genes in cardiomyopathy with fibrosis and cardiac remodeling

Background

Identify genes probably associated with chronic heart failure and predict potential target genes for dilated cardiomyopathy using bioinformatics analyses.

Methods

Gene expression profiles (series number GSE3585 and GSE42955) of cardiomyopathy patients and healthy controls were downloaded from the Expression Omnibus Gene (GEO) database. Differential expression of genes (DEGS) between the two groups of total 14 cardiomyopathy patients and 10 healthy controls were subsequently identified by limma package of R. Database for Annotation, Visualization, and Integrated Discovery (DAVID Tool), which is an analysis of enriched biological processes. Search Tool for the Retrieval Interacting Genes (STRING) was used as well for the analysis of protein-protein interaction network (PPI). Prediction of the potential drugs was suggested based on the preliminarily identified genes using Connectivity Map (CMap).

Results

Eighty-nine DEGs were identified (57 up-regulated and 32 down-regulated). The most enrichment Gene Ontology (GO) terms (P < 0.05) contain genes involved in extracellular matrix (ECM) and biological adhesion signal pathways (P < 0.05, ES > 1.5) such as ECM-receptors, focal adhesion and transforming growth factor beta (TGF-β), etc. Fifty-one differentially expressed genes were found to encode interacting proteins. Eleven key genes along with related transcription factors were identified including CTGF, POSTN, CORIN, FIGF, etc.

Conclusion

Bioinformatics-based analyses reveal the targeted genes probably associated with cardiomyopathy, which provide clues for pharmacological therapies aiming at the targets.