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In Silico Approach to Identify the Relationships between COVID-19 and Coronary Artery Disease/Rheumatoid Arthritis    
Yazarlar (2)
Dr. Öğr. Üyesi Sevinç AKÇAY Dr. Öğr. Üyesi Sevinç AKÇAY
Kırşehir Ahi Evran Üniversitesi, Türkiye
Dilek Pirim
Türkiye
Devamını Göster
Özet
Global public has been threatened by the coronavirus disease 2019 (COVID-19) pandemic which led to nearly 15 million deaths around the world. People with complex and chronic diseases usually have more severe COVID-19 symptoms than the general population. Mounting evidence indicates individuals with coronary artery disease (CAD) and rheumatoid arthritis (RA) have worse COVID-19 outcomes yet the underlying mechanism still needs to be explored. The aim of our study is to reveal in silico evidence for the molecular mechanisms shared by COVID-19, CAD and RA pathogenesis which may aggravate the COVID-19 disease severity. Public datasets (GSE164805 and GSE23561) were downloaded from the Gene Expression Omnibus (GEO) database and analyzed for differential expression analysis (DEG). Identified differential expressed genes (DEGs) were further analyzed to find common DEGs, common pathways, hub genes, transcription factors (TFs) and microRNAs (miRNAs). Our study identified common hub genes, miRNAs, TFs and shared mechanisms in both mild and severe COVID-19-CAD patients and mild and severe COVID-19-RA patients. We also uncovered that mild and severe forms of COVID-19 differ in potential biomarkers, mechanisms, miRNAs and TFs in both CAD and RA patients. Our study is the first study investigating the potential shared mechanisms, biomarkers, TFs and miRNAs between COVID-19 and CAD patients and COVID-19 and RA patients. Our results could shed on light to the patient management strategies with CAD with COVID-19 and patients with RA with COVID-19 based on the severity of …
Anahtar Kelimeler
COVID-19 | coronary artery disease | rheumatoid arthritis | differentially expressed genes | bioinformatics | transcription factors | microRNAs
Makale Türü Özgün Makale
Makale Alt Türü SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale
Dergi Adı Brazilian Archives of Biology and Technology
Dergi ISSN 1678-4324 Wos Dergi Scopus Dergi
Dergi Tarandığı Indeksler SCI-Expanded
Dergi Grubu Q3
Makale Dili İngilizce
Basım Tarihi 10-2023
Cilt No 66
Doi Numarası 10.1590/1678-4324-2023220722
Makale Linki file:///Users/sevinc/Downloads/In_Silico_Approach_to_Identify_the_Relationships_b.pdf