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Updated: Nov 29, 2025

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
Published on: March 1, 2024
Computational gene expression profiling in the exploration of biomarkers, non-coding functional RNAs and drug
S Aishwarya1,2, K Gunasekaran2, A Anita Margret3
1Department of Bioinformatics, Stella Maris College, Chennai, Tamil Nadu, India.
Abstract:
The coronavirus disease, caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is a global health crisis that is being endured with an increased alarm of transmission each day. Though the pandemic has activated innumerable research attention to decipher an antidote, fundamental understanding of the molecular mechanisms is necessary to halt the disease progression. The study focused on comparison of the COVID-19 infected lung tissue gene expression datasets -GSE155241 and GSE150316 with the GEO2R-limma package. The significant up- and downregulated genes were annotated. Further evaluation of the enriched pathways, transcription factors, kinases, noncoding RNAs and drug perturbations revealed the significant molecular mechanisms of the host response. The results revealed a surge in mitochondrial respiration, cytokines, neurodegenerative mechanisms and deprived oxygen, iron, copper, and glucose transport. Hijack of ubiquitination by SARS-CoV-2, hox gene differentiation, histone modification, and miRNA biogenesis were the notable molecular mechanisms inferred. Long non-coding RNAs such as C058791.1, TTTY15 and TPTEP1 were predicted to be efficient in regulating the disease mechanisms. Drugs-F-1566-0341, Digoxin, Proscillaridin and Linifanib that reverse the gene expression signatures were predicted from drug perturbations analysis. The binding efficiency and interaction of proscillaridin and digoxin as obtained from the molecular docking studies confirmed their therapeutic potential. Two overlapping upregulated genes MDH1, SGCE and one downregulated gene PFKFB3 were appraised as potential biomarkers candidates. The upregulation of PGM5, ISLR and ANK2 as measured from their expressions in normal lungs affirmed their possible prognostic biomarker competence. The study explored significant insights for better diagnosis, and therapeutic options for COVID-19. Communicated by Ramaswamy H. Sarma.
Insights
This study analyzes gene expression in COVID-19 lungs, revealing altered metabolism and host responses. It identifies potential biomarkers and drugs like Digoxin and Proscillaridin for therapeutic intervention against SARS-CoV-2.
Area of Science:
- Genomics
- Molecular Biology
- Virology
Background:
- The COVID-19 pandemic, caused by SARS-CoV-2, necessitates a deeper understanding of molecular mechanisms for effective treatment.
- Current research focuses on finding antivirals, but host response pathways are crucial for halting disease progression.
Purpose of the Study:
- To compare gene expression datasets from COVID-19 infected lung tissues.
- To identify key molecular mechanisms, pathways, and potential therapeutic targets involved in the host response to SARS-CoV-2 infection.
Main Methods:
- Comparative analysis of COVID-19 lung tissue gene expression datasets (GSE155241, GSE150316) using GEO2R-limma.
- Annotation of differentially expressed genes, pathway enrichment analysis, and identification of transcription factors, noncoding RNAs, and drug perturbations.
- Molecular docking studies to validate therapeutic potential of candidate drugs.
Main Results:
- Identified significant alterations in mitochondrial respiration, cytokine signaling, neurodegeneration, and nutrient transport.
- Revealed SARS-CoV-2 hijacking of ubiquitination, histone modification, and miRNA biogenesis.
- Predicted long non-coding RNAs (e.g., TTTY15, TPTEP1) and drugs (e.g., Digoxin, Proscillaridin) with therapeutic potential.
- Proposed MDH1, SGCE, PFKFB3 as diagnostic biomarkers and PGM5, ISLR, ANK2 as prognostic biomarkers.
Conclusions:
- The study provides significant insights into the molecular underpinnings of COVID-19 pathogenesis.
- Identified potential diagnostic and prognostic biomarkers for improved patient management.
- Highlighted therapeutic strategies involving drug repurposing and targeting specific host response pathways.
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