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Coexpression Network Analysis-Based Identification of Critical Genes Differentiating between Latent and Active
Liang Chen1, Jie Hua2, Xiaopu He3
1Department of Infectious Diseases, Nanjing Lishui People's Hospital, Zhongda Hospital Lishui Branch, Southeast University, Nanjing, China.
Disease Markers
|November 22, 2022
Summary
Five hub genes were identified as potential biomarkers to differentiate active tuberculosis (ATB) from latent tuberculosis infection (LTBI). These genes show diagnostic accuracy and correlate with immune cell activity, offering insights into tuberculosis immunopathology.
Area of Science:
- Genomics
- Immunology
- Biomarker Discovery
Background:
- Tuberculosis remains a significant global health challenge.
- Differentiating active tuberculosis (ATB) from latent tuberculosis infection (LTBI) is crucial for effective treatment and disease management.
- Identifying reliable biomarkers for ATB and LTBI is an ongoing area of research.
Purpose of the Study:
- To identify novel gene expression biomarkers capable of distinguishing between active tuberculosis (ATB) and latent tuberculosis infection (LTBI).
- To assess the diagnostic accuracy of identified hub genes.
- To investigate the relationship between hub gene expression and immune cell infiltration in tuberculosis.
Main Methods:
- Utilized three Gene Expression Omnibus (GEO) microarray datasets (GSE19491, GSE98461, GSE152532).
- Employed differential expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA) to identify hub genes from a merged training dataset.
- Validated diagnostic accuracy using Receiver Operating Characteristic (ROC) curves on a separate test dataset.
- Assessed immune cell infiltration via single-sample gene set enrichment analysis (ssGSEA).
Main Results:
- Identified five hub genes (FBXO6, ATF3, GBP1, GBP4, GBP5) with potential as biomarkers for LTBI progression to ATB.
- These hub genes demonstrated high diagnostic accuracy, with Area Under the ROC Curve (AUC) values ranging from 0.8 to 0.9 in the test dataset.
- ssGSEA revealed negative correlation with lymphocyte activity and positive correlation with myeloid and inflammatory cell activity.
Conclusions:
- The identified five hub genes may play a significant role in tuberculosis-related immunopathology.
- These genes hold promise as novel biomarkers for differentiating between latent tuberculosis infection (LTBI) and active tuberculosis (ATB).
- Further research into these biomarkers could lead to improved diagnostic strategies for tuberculosis.
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