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Differential gene expression profiling reveals potential biomarkers and pharmacological compounds against SARS-CoV-2: Insights from machine learning and bioinformatics approaches.
Hoque, M Nazmul; Sarkar, Md Murshed Hasan; Khan, Md Arif; Hossain, Md Arju; Hasan, Md Imran; Rahman, Md Habibur; Habib, Md Ahashan; Akter, Shahina; Banu, Tanjina Akhtar; Goswami, Barna; Jahan, Iffat; Nafisa, Tasnim; Molla, Md Maruf Ahmed; Soliman, Mahmoud E; Araf, Yusha; Khan, M Salim; Zheng, Chunfu; Islam, Tofazzal.
  • Hoque MN; Department of Gynecology, Obstetrics and Reproductive Health, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, Bangladesh.
  • Sarkar MMH; Bangladesh Council of Scientific & Industrial Research (BCSIR), Dhaka, Bangladesh.
  • Khan MA; Department of Biotechnology and Genetic Engineering, University of Development Alternative, Dhaka, Bangladesh.
  • Hossain MA; Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh.
  • Hasan MI; Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh.
  • Rahman MH; Department of Computer Science and Engineering, Islamic University, Kushtia, Bangladesh.
  • Habib MA; Department of Computer Science and Engineering, Islamic University, Kushtia, Bangladesh.
  • Akter S; Bangladesh Council of Scientific & Industrial Research (BCSIR), Dhaka, Bangladesh.
  • Banu TA; Bangladesh Council of Scientific & Industrial Research (BCSIR), Dhaka, Bangladesh.
  • Goswami B; Bangladesh Council of Scientific & Industrial Research (BCSIR), Dhaka, Bangladesh.
  • Jahan I; Bangladesh Council of Scientific & Industrial Research (BCSIR), Dhaka, Bangladesh.
  • Nafisa T; Bangladesh Council of Scientific & Industrial Research (BCSIR), Dhaka, Bangladesh.
  • Molla MMA; National Institute of Laboratory Medicine and Referral Center, Dhaka, Bangladesh.
  • Soliman ME; National Institute of Laboratory Medicine and Referral Center, Dhaka, Bangladesh.
  • Araf Y; Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Durban, South Africa.
  • Khan MS; Department of Genetic Engineering and Biotechnology, School of Life Sciences, Shahjalal University of Science and Technology, Sylhet, Bangladesh.
  • Zheng C; Department of Immunology, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
  • Islam T; Bangladesh Council of Scientific & Industrial Research (BCSIR), Dhaka, Bangladesh.
Front Immunol ; 13: 918692, 2022.
Article in English | MEDLINE | ID: covidwho-2022707
ABSTRACT
The COVID-19 pandemic, caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has created an urgent global situation. Therefore, it is necessary to identify the differentially expressed genes (DEGs) in COVID-19 patients to understand disease pathogenesis and the genetic factor(s) responsible for inter-individual variability and disease comorbidities. The pandemic continues to spread worldwide, despite intense efforts to develop multiple vaccines and therapeutic options against COVID-19. However, the precise role of SARS-CoV-2 in the pathophysiology of the nasopharyngeal tract (NT) is still unfathomable. This study utilized machine learning approaches to analyze 22 RNA-seq data from COVID-19 patients (n = 8), recovered individuals (n = 7), and healthy individuals (n = 7) to find disease-related differentially expressed genes (DEGs). We compared dysregulated DEGs to detect critical pathways and gene ontology (GO) connected to COVID-19 comorbidities. We found 1960 and 153 DEG signatures in COVID-19 patients and recovered individuals compared to healthy controls. In COVID-19 patients, the DEG-miRNA, and DEG-transcription factors (TFs) interactions network analysis revealed that E2F1, MAX, EGR1, YY1, and SRF were the highly expressed TFs, whereas hsa-miR-19b, hsa-miR-495, hsa-miR-340, hsa-miR-101, and hsa-miR-19a were the overexpressed miRNAs. Three chemical agents (Valproic Acid, Alfatoxin B1, and Cyclosporine) were abundant in COVID-19 patients and recovered individuals. Mental retardation, mental deficit, intellectual disability, muscle hypotonia, micrognathism, and cleft palate were the significant diseases associated with COVID-19 by sharing DEGs. Finally, the detected DEGs mediated by TFs and miRNA expression indicated that SARS-CoV-2 infection might contribute to various comorbidities. Our results provide the common DEGs between COVID-19 patients and recovered humans, which suggests some crucial insights into the complex interplay between COVID-19 progression and the recovery stage, and offer some suggestions on therapeutic target identification in COVID-19 caused by the SARS-CoV-2.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: MicroRNAs / COVID-19 / COVID-19 Drug Treatment Type of study: Prognostic study Topics: Vaccines Limits: Humans Language: English Journal: Front Immunol Year: 2022 Document Type: Article Affiliation country: Fimmu.2022.918692

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Full text: Available Collection: International databases Database: MEDLINE Main subject: MicroRNAs / COVID-19 / COVID-19 Drug Treatment Type of study: Prognostic study Topics: Vaccines Limits: Humans Language: English Journal: Front Immunol Year: 2022 Document Type: Article Affiliation country: Fimmu.2022.918692