ArticlePloS one2022
Gene expression profiling identifies candidate biomarkers for new latent tuberculosis infections. A cohort study.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Tryptophan and Its Derived Metabolites as Biomarkers for Tuberculosis Disease: A Systematic ReviewIranian biomedical journal · 2024Pooled it
- Machine-Learning-Derived, Mechanistically Informed Transcriptomic Signature to Diagnose Active Tuberculosis and Guide Host-Directed Therapy.Diagnostics (Basel, Switzerland) · 2026Article
- Advancement in diagnostic approaches for latent tuberculosis: distinguishing recent from remote infections.One health outlook · 2025Review
- Identification and assessment of hub genes and miRNAs coregulatory associated with immune infiltrations and drug interactions in latent tuberculosis based on MicroarrayData analysis, molecular docking, and dynamic simulation.Biochemistry and biophysics reports · 2025Article
- Redox Biomarkers in Asymptomatic Latent Human Tuberculosis: A Comparison With Active Disease.The Journal of infectious diseases · 2024Article
- Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo determine the gene expression profile in individuals with new latent tuberculosis infection (LTBI), and to compare them with people with active tuberculosis (TB) and those exposed to TB but not infected.
designA prospective cohort study. Recruitment and follow-up were conducted between September 2016 to December 2018. Gene expression and data processing and analysis from April 2019 to April 2021.
settingTwo male Colombian prisons.
participants15 new tuberculin skin test (TST) converters (negative TST at baseline that became positive during follow-up), 11 people that continued with a negative TST after two years of follow-up, and 10 people with pulmonary ATB.
main outcome measuresGene expression profile using RNA sequencing from PBMC samples. The differential expression was assessed using the DESeq2 package in Bioconductor. Genes with |logFC| >1.0 and an adjusted p-value < 0.1 were differentially expressed. We analyzed the differences in the enrichment of KEGG pathways in each group using InterMiner.
resultsThe gene expression was affected by the time of incarceration. We identified group-specific differentially expressed genes between the groups: 289 genes in people with a new LTBI and short incarceration (less than three months of incarceration), 117 in those with LTBI and long incarceration (one or more years of incarceration), 26 in ATB, and 276 in the exposed but non-infected individuals. Four pathways encompassed the largest number of down and up-regulated genes among individuals with LTBI and short incarceration: cytokine signaling, signal transduction, neutrophil degranulation, and innate immune system. In individuals with LTBI and long incarceration, the only enriched pathway within up-regulated genes was Emi1 phosphorylation.
conclusionsRecent infection with MTB is associated with an identifiable RNA pattern related to innate immune system pathways that can be used to prioritize LTBI treatment for those at greatest risk for developing active TB.
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