Identification and interaction analysis of molecular markers in myocardial infarction by bioinformatics and next-generation sequencing data analysis DOI Creative Commons
Basavaraj Vastrad, Chanabasayya Vastrad

Egyptian Journal of Medical Human Genetics, Год журнала: 2024, Номер 25(1)

Опубликована: Окт. 14, 2024

Abstract Background Cardiovascular diseases are prevalent worldwide with any age, and it is characterized by sudden blockage of blood flow to heart permanent damage the muscle, whose cause underlying molecular mechanisms not fully understood. This investigation aimed explore identify essential genes signaling pathways that contribute progression MI. Methods The aim this was use bioinformatics next-generation sequencing (NGS) data analysis differentially expressed (DEGs) diagnostic therapeutic potential in NGS dataset (GSE132143) downloaded from Gene Expression Omnibus (GEO) database. DEGs between MI normal control samples were identified using DESeq2 R bioconductor tool. gene ontology (GO) REACTOME pathway enrichment analyses performed g:Profiler. Next, four kinds algorithms protein–protein interaction (PPI) novel biomarkers. miRNA-hub regulatory network TF-hub constructed miRNet NetworkAnalyst database, Cytoscape software. Finally, effectiveness hub predicted receiver operator characteristic curve (ROC) AUC more than 0.800 considered as having capability diagnose excellent specificity sensitivity. Results A total 958 identified, consisting 480 up-regulated 478 down-regulated genes. enriched GO terms include immune system, neuronal response stimulus multicellular organismal process. Ten (namely cftr, cdk1, rps13, rps15a, rps27, notch1, mrpl12, nos2, ccdc85b atn1 ) obtained via results. MiRNA-hub showed hsa-mir-409-3p , hsa-mir-3200-3p creb1 tp63 might play an important role Conclusions Analysis combined global information validation presents a successful approach uncover risk prognostic markers Our risk- prognostic-related signatures, including . sets new perspective improve diagnostic, prognostic, outcomes

Язык: Английский

NQO1 polymorphism and susceptibility to ischemic stroke in a Chinese population DOI Creative Commons
Min Wang, Ying Shen, Yuan Gao

и другие.

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Апрель 19, 2024

Abstract Background Ischemic stroke (IS) is a major cause of death and disability worldwide. Genetic factors are important risk for the development IS. The quinone oxidoreductase 1 gene (NQO1) has antioxidant, anti-inflammatory, cytoprotective properties. Thus, in this study, we investigated relationship between NQO1 polymorphism Methods Peripheral blood was collected from 143 patients with IS 124 healthy controls Yunnan, China, NQO1 rs2917673, rs689455, rs1800566 were genotyped. Logistic regression used to analyze three loci susceptibility. difference expression levels control groups verified using public databases enzyme-linked immunosorbent assay. Results rs2917673 locus increased by 2.375 times TT genotype carriers under co-dominance model compared CC statistically associated (P = 0.046). In recessive model, 2.407 CC/CT 0.033). Conclusions significantly Mutant

Язык: Английский

Процитировано

0

Identification of core genes shared by ischemic stroke and myocardial infarction using an integrated approach DOI Creative Commons
Min Wang, Yuan Gao, Huaqiu Chen

и другие.

Medicine, Год журнала: 2024, Номер 103(27), С. e38877 - e38877

Опубликована: Июль 5, 2024

Background: Both ischemic stroke (IS) and myocardial infarction (MI) are caused by vascular occlusion that results in ischemia. While there may be similarities their mechanisms, the potential relationship between these 2 diseases has not been comprehensively analyzed. Therefore, this study explored commonalities pathogenesis of IS MI. Methods: Datasets for (GSE58294, GSE16561) MI (GSE60993, GSE61144) were downloaded from Gene Expression Omnibus database. Transcriptome data each 4 datasets analyzed using bioinformatics, differentially expressed genes (DEGs) shared identified subsequently visualized a Venn diagram. A protein–protein interaction (PPI) network was constructed Interacting Retrieval Tool database, identification key core performed CytoHubba. Ontology (GO) term annotation Kyoto Encyclopedia Genes Genomes (KEGG) pathway enrichment analysis DEGs conducted prediction methods, functions hub determined Metascape. Results: The revealed 116 1321 datasets, respectively. Of 75 MI, 56 upregulated 19 downregulated. Furthermore, 15 – S100a12, Hp, Clec4d, Cd163, Mmp9, Ormdl3, Il2rb, Orm1, Irak3, Tlr5, Lrg1, Clec4e, Clec5a, Mcemp1, Ly96 identified. GO showed they mainly involved biological neutrophil degranulation, activation during immune response, cytokine secretion. KEGG pathways pertaining to Salmonella infection, Legionellosis, inflammatory bowel disease. Finally, gene–transcription factor, gene–microRNA, small-molecule relationships predicted. Conclusion: These provide novel theoretical basis diagnosis treatment

Язык: Английский

Процитировано

0

NQO1 polymorphism and susceptibility to ischemic stroke in a Chinese population DOI Creative Commons
Min Wang, Ying Shen, Yuan Gao

и другие.

BMC Medical Genomics, Год журнала: 2024, Номер 17(1)

Опубликована: Авг. 22, 2024

Abstract Background Ischemic stroke (IS) is a major cause of death and disability worldwide. Genetic factors are important risk for the development IS. The quinone oxidoreductase 1 gene ( NQO1 ) has antioxidant, anti-inflammatory, cytoprotective properties. Thus, in this study, we investigated relationship between polymorphism Methods Peripheral blood was collected from 143 patients with IS 124 control groups Yunnan, China, rs2917673, rs689455, rs1800566 were genotyped. Logistic regression used to analyze three loci susceptibility. difference expression levels verified using public databases enzyme-linked immunosorbent assay. Results rs2917673 locus increased by 2.375 times TT genotype carriers under co-dominance model compared CC statistically associated (OR = 2.375, 95% CI 1.017–5.546, P 0.046). In recessive model, 2.407 CC/CT 2.407, 1.073–5.396, 0.033). Conclusions significantly Mutant

Язык: Английский

Процитировано

0

Identification and interaction analysis of molecular markers in myocardial infarction by bioinformatics and next-generation sequencing data analysis DOI Creative Commons
Basavaraj Vastrad, Chanabasayya Vastrad

Egyptian Journal of Medical Human Genetics, Год журнала: 2024, Номер 25(1)

Опубликована: Окт. 14, 2024

Abstract Background Cardiovascular diseases are prevalent worldwide with any age, and it is characterized by sudden blockage of blood flow to heart permanent damage the muscle, whose cause underlying molecular mechanisms not fully understood. This investigation aimed explore identify essential genes signaling pathways that contribute progression MI. Methods The aim this was use bioinformatics next-generation sequencing (NGS) data analysis differentially expressed (DEGs) diagnostic therapeutic potential in NGS dataset (GSE132143) downloaded from Gene Expression Omnibus (GEO) database. DEGs between MI normal control samples were identified using DESeq2 R bioconductor tool. gene ontology (GO) REACTOME pathway enrichment analyses performed g:Profiler. Next, four kinds algorithms protein–protein interaction (PPI) novel biomarkers. miRNA-hub regulatory network TF-hub constructed miRNet NetworkAnalyst database, Cytoscape software. Finally, effectiveness hub predicted receiver operator characteristic curve (ROC) AUC more than 0.800 considered as having capability diagnose excellent specificity sensitivity. Results A total 958 identified, consisting 480 up-regulated 478 down-regulated genes. enriched GO terms include immune system, neuronal response stimulus multicellular organismal process. Ten (namely cftr, cdk1, rps13, rps15a, rps27, notch1, mrpl12, nos2, ccdc85b atn1 ) obtained via results. MiRNA-hub showed hsa-mir-409-3p , hsa-mir-3200-3p creb1 tp63 might play an important role Conclusions Analysis combined global information validation presents a successful approach uncover risk prognostic markers Our risk- prognostic-related signatures, including . sets new perspective improve diagnostic, prognostic, outcomes

Язык: Английский

Процитировано

0