Objective: Acute coronary syndrome (ACS) is currently a leading cause of morbidity and mortality worldwide. This study aimed to screen critical genes and miRNAs involved in ACS.
Materials And Methods: Microarray data (access number GSE19339) was downloaded from Gene Expression Omnibus (GEO) database. After data preprocessing, we screened the differentially expressed genes (DEGs) using limma package and subsequently performed enrichment analysis using DAVID tool. The protein-protein interaction (PPI) network and transcription factor (TF)-miRNA-target gene regulatory network were visualized using Cytoscape software. Finally, the drug-gene interactions were predicted using DGIdb database.
Results: A total of 425 DEGs were identified in ACS samples compared with healthy control samples. Functional enrichment analysis showed that DEGs were mainly involved in angiogenesis, inflammatory response and PI3K-Akt signaling pathway. IL6 and VEGFA were key nodes in PPI network. In addition, hsa-miR-29, hsa-miR-1, NFIC, NFKB1 and RELA were identified as key factors in TF-miRNA-target gene network. Finally, the prediction results revealed that VWF, CXCL8 and IL6 had higher degree than other genes.
Conclusion: IL6 and VEGFA might play major roles in ACS progression. Two miRNAs (hsa-miR-29 and hsa-miR-1) and three TFs (NFIC, NFKB1 and RELA) were critical genes involved in pathological process of ACS. VWF, CXCL8 and IL6 might be potential druggable genes for ACS therapy.
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http://dx.doi.org/10.1016/j.compbiolchem.2019.107125 | DOI Listing |
J Thromb Haemost
December 2024
Department of Pediatrics, Centre Hospitalier Universitaire de Québec - Centre Mère-Enfant Soleil, Quebec City, Quebec, Canada; Centre de Recherche du Centre Hospitalier Universitaire de Québec, Quebec City, Quebec, Canada. Electronic address:
Background: Venous thromboembolism (VTE) is a frequent complication of childhood acute lymphoblastic leukemia (ALL).
Objectives: We aimed to identify molecular markers and signatures of leukemia microenvironment associated with VTE in childhood ALL, by dual-omics approach of gene expression (GEP) and DNA-methylation profiling.
Patients/methods: Eligible children were aged 1-21 years old with newly diagnosed ALL enrolled on the Dana Farber Cancer Institute 16-001 trial with available RNA sequencing data from bone marrow at diagnosis.
Stem Cell Res Ther
September 2024
Department of Stem Cells & Regenerative Medicine, D.Y. Patil Education Society (Deemed to be University), D. Y. Patil Vidyanagar, Kasab Bawada, Kolhapur, 416006, Maharashtra, India.
Front Mol Neurosci
December 2023
Department of Neuroscience Intensive Care Unit, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Stroke is a devastating condition that can lead to significant morbidity and mortality. The aftermath of a stroke, particularly hemorrhagic transformation (HT) and brain edema, can significantly impact the prognosis of patients. Early detection and effective management of these complications are crucial for improving outcomes in stroke patients.
View Article and Find Full Text PDFTrop Anim Health Prod
October 2023
Department of Animal Science, Faculty of Agricultural Science, Payame Noor University, Tehran, 19395-4697, Iran.
Context: Somatic cell count (SCC) is used as an indicator of udder health. The log transformation of SCC is called somatic cell score (SCS).
Aim: Several QTL and genes have been identified that are associated with SCS.
Biomed Res Int
January 2023
Department of Computer Science and Telecommunication Engineering, Noakhali Science and Technology University, Noakhali 3814, Bangladesh.
Several studies have been done to identify comorbidities of COVID-19. In this work, we developed an analytical bioinformatics framework to reveal COVID-19 comorbidities, their genomic associations, and molecular mechanisms accomplishing transcriptomic analyses of the RNA-seq datasets provided by the Gene Expression Omnibus (GEO) database, where normal and infected tissues were evaluated. Using the framework, we identified 27 COVID-19 correlated diseases out of 7,092 collected diseases.
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