Pathway and Network Analyses Identify Growth Factor Signaling and MMP9 as Potential Mediators of Mitochondrial Dysfunction in Severe COVID-19.
Ya WangKlaus SchughartTiana Maria PelaiaTracey ChewKaran KimThomas KarvunidisBen KnippenbergSally TeohAmy L PhuKirsty R ShortJonathan IredellIrani ThevarajanJennifer AudsleyStephen Pj MacDonaldJonathon Burchamnull Predict-ConsortiumBenjamin TangAnthony McLeanMaryam ShojaeiPublished in: International journal of molecular sciences (2023)
Patients with preexisting metabolic disorders such as diabetes are at a higher risk of developing severe coronavirus disease 2019 (COVID-19). Mitochondrion, the very organelle that controls cellular metabolism, holds the key to understanding disease progression at the cellular level. Our current study aimed to understand how cellular metabolism contributes to COVID-19 outcomes. Metacore pathway enrichment analyses on differentially expressed genes (encoded by both mitochondrial and nuclear deoxyribonucleic acid (DNA)) involved in cellular metabolism, regulation of mitochondrial respiration and organization, and apoptosis, was performed on RNA sequencing (RNASeq) data from blood samples collected from healthy controls and patients with mild/moderate or severe COVID-19. Genes from the enriched pathways were analyzed by network analysis to uncover interactions among them and up- or downstream genes within each pathway. Compared to the mild/moderate COVID-19, the upregulation of a myriad of growth factor and cell cycle signaling pathways, with concomitant downregulation of interferon signaling pathways, were observed in the severe group. Matrix metallopeptidase 9 ( MMP9) was found in five of the top 10 upregulated pathways, indicating its potential as therapeutic target against COVID-19. In summary, our data demonstrates aberrant activation of endocrine signaling in severe COVID-19, and its implication in immune and metabolic dysfunction.
Keyphrases
- coronavirus disease
- growth factor
- sars cov
- cell cycle
- signaling pathway
- respiratory syndrome coronavirus
- oxidative stress
- early onset
- network analysis
- cell proliferation
- type diabetes
- cardiovascular disease
- genome wide
- dna methylation
- cell death
- epithelial mesenchymal transition
- electronic health record
- single cell
- dendritic cells
- insulin resistance
- high intensity
- long non coding rna
- gene expression
- machine learning
- cell free
- skeletal muscle
- bioinformatics analysis
- circulating tumor cells
- artificial intelligence
- genome wide identification
- deep learning