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A protein signature associated with active tuberculosis identified by plasma profiling and network-based analysis.

ABSTRACT: Annually, approximately 10 million people are diagnosed with active tuberculosis (TB), and 1.4 million die of the disease. If left untreated, each person with active TB will infect 10-15 new individuals. The lack of non-sputum-based diagnostic tests leads to delayed diagnoses of active pulmonary TB cases, contributing to continued disease transmission. In this exploratory study, we aimed to identify biomarkers associated with active TB. We assessed the plasma levels of 92 proteins associated with inflammation in individuals with active TB (n = 20), latent TB (n = 14), or healthy controls (n = 10). Using co-expression network analysis, we identified one module of proteins with strong association with active TB. We removed proteins from the module that had low abundance or were associated with non-TB diseases in published transcriptomic datasets, resulting in a 12-protein plasma signature that was highly enriched in individuals with pulmonary and extrapulmonary TB and was further associated with disease severity.

SUBMITTER: Mousavian Z

PROVIDER: S-EPMC9763869 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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A protein signature associated with active tuberculosis identified by plasma profiling and network-based analysis.

Mousavian Zaynab Z Folkesson Elin E Fröberg Gabrielle G Foroogh Fariba F Correia-Neves Margarida M Bruchfeld Judith J Källenius Gunilla G Sundling Christopher C

iScience 20221122 12

Annually, approximately 10 million people are diagnosed with active tuberculosis (TB), and 1.4 million die of the disease. If left untreated, each person with active TB will infect 10-15 new individuals. The lack of non-sputum-based diagnostic tests leads to delayed diagnoses of active pulmonary TB cases, contributing to continued disease transmission. In this exploratory study, we aimed to identify biomarkers associated with active TB. We assessed the plasma levels of 92 proteins associated wit ...[more]

PMID: 36561889

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Project description:Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (M.tb.). Our integrative analysis aims to identify the transcriptional profiling and gene expression signature that distinguish individuals with active TB (ATB) disease, and those with latent tuberculosis infection (LTBI). In the present study, we reanalyzed a microarray dataset (GSE37250) from GEO database and explored the data for differential gene expression analysis between those with ATB and LTBI derived from Malawi and South African cohorts. We used BRB array tool to distinguish DEGs (differentially expressed genes) between ATB and LTBI. Pathway enrichment analysis of DEGs was performed using DAVID bioinformatics tool. The protein-protein interaction (PPI) network of most upregulated genes was constructed using STRING analysis. We have identified 375 upregulated genes and 152 downregulated genes differentially expressed between ATB and LTBI samples commonly shared among Malawi and South African cohorts. The constructed PPI network was significantly enriched with 76 nodes connected to 151 edges. The enriched GO term/pathways were mainly related to expression of IFN stimulated genes, interleukin-1 production, and NOD-like receptor signaling pathway. Downregulated genes were significantly enriched in the Wnt signaling, B cell development, and B cell receptor signaling pathways. The short-listed DEGs were validated in a microarray data from an independent cohort (GSE19491). ROC curve analysis was done to assess the diagnostic accuracy of the gene signature in discrimination of active and latent tuberculosis. Thus, we have derived a seven-gene signature, which included five upregulated genes FCGR1B, ANKRD22, CARD17, IFITM3, TNFAIP6 and two downregulated genes FCGBP and KLF12, as a biomarker for discrimination of active and latent tuberculosis. The identified genes have a sensitivity of 80-100% and specificity of 80-95%. Area under the curve (AUC) value of the genes ranged from 0.84 to 1. This seven-gene signature has a high diagnostic accuracy in discrimination of active and latent tuberculosis.

Dataset Information

A protein signature associated with active tuberculosis identified by plasma profiling and network-based analysis.

Publications

A protein signature associated with active tuberculosis identified by plasma profiling and network-based analysis.

Similar Datasets

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