Transcriptomic studies revealed pathophysiological impact of COVID-19 to predominant health conditions.
Zulkar NainShital K BarmanMohammad Moinuddin SheamShifath Bin SyedAbdus SamadJulian M W QuinnMohammad Minnatul KarimMahbubul Kabir HimelRajib Kanti RoyMohammad Ali MoniSudhangshu Kumar BiswasPublished in: Briefings in bioinformatics (2021)
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.
Keyphrases
- coronavirus disease
- sars cov
- genome wide
- gene expression
- respiratory syndrome coronavirus
- healthcare
- public health
- signaling pathway
- genome wide identification
- transcription factor
- cell proliferation
- bioinformatics analysis
- simultaneous determination
- type diabetes
- oxidative stress
- adipose tissue
- newly diagnosed
- emergency department
- end stage renal disease
- chronic kidney disease
- insulin resistance
- peritoneal dialysis
- metabolic syndrome
- poor prognosis
- social media
- prognostic factors
- pi k akt
- data analysis
- adverse drug