Differential gene expression profiling reveals potential biomarkers and pharmacological compounds against SARS-CoV-2: Insights from machine learning and bioinformatics approaches.

Journal: Frontiers in immunology

Volume: 13

Issue: 

Year of Publication: 2022

Affiliated Institutions:  Department of Gynecology, Obstetrics and Reproductive Health, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, Bangladesh. Bangladesh Council of Scientific & Industrial Research (BCSIR), Dhaka, Bangladesh. Department of Biotechnology and Genetic Engineering, University of Development Alternative, Dhaka, Bangladesh. Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh. Department of Computer Science and Engineering, Islamic University, Kushtia, Bangladesh. National Institute of Laboratory Medicine and Referral Center, Dhaka, Bangladesh. Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Durban, South Africa. Department of Genetic Engineering and Biotechnology, School of Life Sciences, Shahjalal University of Science and Technology, Sylhet, Bangladesh. Department of Immunology, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China. Institute of Biotechnology and Genetic Engineering (IBGE), Bangabandhu Sheikh Mujibur Rahman Agricultural University (BSMRAU), Gazipur, Bangladesh.

Abstract summary 

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.

Authors & Co-authors:  Hoque M Nazmul MN Sarkar Md Murshed Hasan MMH Khan Md Arif MA Hossain Md Arju MA Hasan Md Imran MI Rahman Md Habibur MH Habib Md Ahashan MA Akter Shahina S Banu Tanjina Akhtar TA Goswami Barna B Jahan Iffat I Nafisa Tasnim T Molla Md Maruf Ahmed MMA Soliman Mahmoud E ME Araf Yusha Y Khan M Salim MS Zheng Chunfu C Islam Tofazzal T

Study Outcome 

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Statistics
Citations :  Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. . Clinical features of patients infected with 2019 novel coronavirus in wuhan, China. Lancet (2020) 395(10223):497–506. doi: 10.1016/S0140-6736(20)30183-5
Authors :  18
Identifiers
Doi : 918692
SSN : 1664-3224
Study Population
Male,Female
Mesh Terms
Biomarkers
Other Terms
RNA-seq;SARS-CoV-2;functional enrichment;gene regulatory networks;genomics;therapeutic targets
Study Design
Cross Sectional Study
Study Approach
Country of Study
Publication Country
Switzerland