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Updated: Oct 22, 2025
High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
Published on: March 5, 2022
Comprehensive Analysis of the Systemic Transcriptomic Alternations and Inflammatory Response during the Occurrence
Shaocong Mo1, Leijie Dai1, Yulin Wang1
1Shanghai Medical College, Fudan University, Shanghai, China.
Insights
This study identifies 31 key genes in COVID-19 patients
Area of Science:
- Immunology
- Genomics
- Computational Biology
Background:
- The COVID-19 pandemic highlights gaps in understanding host responses at molecular and cellular levels.
- Effective therapies for COVID-19 are urgently needed, necessitating deeper insights into disease mechanisms.
Purpose of the Study:
- To identify key genes and immune cell alterations associated with COVID-19 severity and prognosis.
- To explore potential therapeutic strategies by analyzing gene signatures and drug interactions.
Main Methods:
- Integrated analysis of three COVID-19 gene expression datasets (GSE152641, GSE161777, GSE157103).
- Utilized MCODE, ssGSEA, CIBERSORT, WGCNA, GO, KEGG, NMF, submap, and DGIdb for network and pathway analysis.
- Identified a 31-gene signature in peripheral blood associated with hospital-free days.
Main Results:
- Identified 314 differentially expressed genes, predominantly linked to neutrophil degranulation and cell division.
- Revealed significant alterations in immune cell abundance, highlighting the roles of neutrophils and T cells.
- Established a 31-gene peripheral blood signature predictive of COVID-19 patient prognosis.
Conclusions:
- The study elucidates the intricate relationship between inflammatory responses and COVID-19 disease progression.
- Identified potential therapeutic targets and strategies for COVID-19 treatment based on gene signatures.
- Provides a comprehensive molecular and cellular understanding to guide future COVID-19 therapeutic development.
Abstract:
The pandemic of the coronavirus disease 2019 (COVID-19) has posed huge threats to healthcare systems and the global economy. However, the host response towards COVID-19 on the molecular and cellular levels still lacks full understanding and effective therapies are in urgent need. Here, we integrate three datasets, GSE152641, GSE161777, and GSE157103. Compared to healthy people, 314 differentially expressed genes were identified, which were mostly involved in neutrophil degranulation and cell division. The protein-protein network was established and two significant subsets were filtered by MCODE: ssGSEA and CIBERSORT, which comprehensively revealed the alternation of immune cell abundance. Weighted gene coexpression network analysis (WGCNA) as well as GO and KEGG analyses unveiled the role of neutrophils and T cells during the progress of the disease. Based on the hospital-free days after 45 days of follow-up and statistical methods such as nonnegative matrix factorization (NMF), submap, and linear correlation analysis, 31 genes were regarded as the signature of the peripheral blood of COVID-19. Various immune cells were identified to be related to the prognosis of the patients. Drugs were predicted for the genes in the signature by DGIdb. Overall, our study comprehensively revealed the relationship between the inflammatory response and the disease course, which provided strategies for the treatment of COVID-19.
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