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Transcriptomic studies revealed pathophysiological impact of COVID-19 to predominant health conditions

Zulkar Nain¹, Shital K Barman², Md Moinuddin Sheam¹

¹Department of Biotechnology and Genetic Engineering, Islamic University, Bangladesh.

Briefings in Bioinformatics

|June 2, 2021

Insights

This study reveals key genes and pathways linking coronavirus disease 2019 (COVID-19) with diabetes mellitus and lung cancer. Findings illuminate shared pathogenesis and identify potential therapeutic targets for these interconnected diseases.

Area of Science:

Genomics
Molecular Biology
Computational Biology

Background:

The precise molecular mechanisms linking prevalent health conditions to COVID-19 severity are not fully understood.
Investigating shared genetic factors and pathways is crucial for understanding disease progression and developing targeted therapies.

Purpose of the Study:

To elucidate the molecular interplay between COVID-19 and comorbidities like diabetes mellitus (DM) and lung cancer (LC).
To identify shared dysregulated genes, signaling pathways, and potential therapeutic targets through network-based gene expression analysis.

Main Methods:

Network-based gene expression analysis of COVID-19 and associated comorbidities.
Identification of shared upregulated and downregulated genes between COVID-19 and DM, LC, myocardial infarction, and hypertension.
Analysis of shared signaling pathways, regulatory factors (transcription factors, microRNAs), and potential drug candidates.

Main Results:

COVID-19 involves significant upregulation of 93 genes and downregulation of 15 genes.
Shared genes identified between COVID-19 and DM (28 genes), LC (17 genes), myocardial infarction (6 genes), and hypertension (7 genes).
Key shared upregulated genes (MX2, IRF7, ADAM8) and downregulated genes (PPARGC1A, METTL7A) were identified, primarily involving inflammatory responses. Six potential biomarkers and drug candidates (captopril, rilonacept, canakinumab) were highlighted. Concomitant COVID-19 may worsen lung cancer prognosis.

Conclusions:

This study provides a molecular basis for COVID-19 progression influenced by comorbidities, particularly DM and LC.
Shared genetic determinants and inflammatory pathways underscore the intricate association between COVID-19 and other diseases.
Identified biomarkers and drug candidates offer potential avenues for therapeutic development in managing complex disease interactions.

Read full analysis

Abstract:

Despite the association of prevalent health conditions with coronavirus disease 2019 (COVID-19) severity, the disease-modifying biomolecules and their pathogenetic mechanisms remain unclear. This study aimed to understand the influences of COVID-19 on different comorbidities and vice versa through network-based gene expression analyses. Using the shared dysregulated genes, we identified key genetic determinants and signaling pathways that may involve in their shared pathogenesis. The COVID-19 showed significant upregulation of 93 genes and downregulation of 15 genes. Interestingly, it shares 28, 17, 6 and 7 genes with diabetes mellitus (DM), lung cancer (LC), myocardial infarction and hypertension, respectively. Importantly, COVID-19 shared three upregulated genes (i.e. MX2, IRF7 and ADAM8) with DM and LC. Conversely, downregulation of two genes (i.e. PPARGC1A and METTL7A) was found in COVID-19 and LC. Besides, most of the shared pathways were related to inflammatory responses. Furthermore, we identified six potential biomarkers and several important regulatory factors, e.g. transcription factors and microRNAs, while notable drug candidates included captopril, rilonacept and canakinumab. Moreover, prognostic analysis suggests concomitant COVID-19 may result in poor outcome of LC patients. This study provides the molecular basis and routes of the COVID-19 progression due to comorbidities. We believe these findings might be useful to further understand the intricate association of these diseases as well as for the therapeutic development.

Keywords:

COVID-19 pandemic RNA-Seq SARS-CoV-2 comorbidities hypertension microarray

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