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Related Concept Videos

Pulmonary Tuberculosis IV01:26

Pulmonary Tuberculosis IV

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Tuberculosis, more commonly referred to as TB, is an infectious disease stemming from Mycobacterium tuberculosis. While it primarily impacts the lungs, TB can also affect other body areas. Given its severity and global impact, timely and accurate diagnosis is crucial for controlling its spread and improving patient outcomes.
Several diagnostic approaches are used to detect TB. The conventional method is the Tuberculin Skin Test (TST), also known as the Mantoux test. However, this method has...
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Pulmonary Tuberculosis III01:31

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Tuberculosis (TB) is a contagious infection primarily affecting the lung parenchyma but which can also affect other body parts. TB can be classified based on disease development, presentation, and the affected anatomical site.
The first classification is based on the development of the disease, and it includes the following categories:
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Pulmonary Tuberculosis II01:28

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Tuberculosis, or TB, is a bacterial infectious disease caused by Mycobacterium tuberculosis. While its primary impact is on the lungs, leading to pulmonary tuberculosis, it can also affect various other organs, a condition referred to as extrapulmonary tuberculosis.
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Transmission: The process begins when a person inhales droplet nuclei containing M. tuberculosis. These are typically released into the air when an individual with pulmonary or...
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Pulmonary Tuberculosis V01:28

Pulmonary Tuberculosis V

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Medical management of tuberculosis (TB) patients involves a comprehensive approach that includes diagnosis, treatment, and monitoring. The specific strategies can vary depending on the type of tuberculosis (latent or active), the patient's overall health status, and other considerations.
Latent tuberculosis infection occurs when TB bacteria are present in a person's body, but are not causing illness or symptoms. It is not contagious, and preventive treatment is crucial to avoid the...
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Pulmonary Tuberculosis I01:29

Pulmonary Tuberculosis I

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Tuberculosis, often called TB, is a contagious illness primarily caused by Mycobacterium tuberculosis. It mainly affects the lung parenchyma but can also impact other body parts.
Causative Organism
The primary infectious agent causing tuberculosis is Mycobacterium tuberculosis, a slow-growing, acid-fast, aerobic rod that exhibits sensitivity to heat and ultraviolet light. Instances of Mycobacterium bovis and Mycobacterium avium contributing to the development of TB infection are rare.
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Identification of Gene Expression Biomarkers Predictive of Latent Tuberculosis Infection Using Machine Learning

Youssra Boumait1, Boutaina Ettetuani2, Manal Chrairi1

  • 1Biology Molecular Unit, Life and Health Sciences Laboratory, Faculty of Medicine and Pharmacy, Abdelmalek Essaâdi University, Tangier 93000, Morocco.

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|June 26, 2025
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Summary

This study identifies novel gene expression biomarkers for latent tuberculosis infection (LTBi) using bioinformatics and machine learning. CCL2 and CXCL10 show promise for improved LTBi detection.

Keywords:
bioinformaticsbiomarkersgene expressionlatent tuberculosis infectionmachine learningtranscriptomic

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Area of Science:

  • Genomics
  • Bioinformatics
  • Immunology

Background:

  • Latent tuberculosis infection (LTBi) impacts a significant portion of the global population.
  • Current diagnostic tools for LTBi suffer from limitations in sensitivity and specificity.
  • There is a critical need for more accurate and reliable methods for LTBi diagnosis.

Purpose of the Study:

  • To identify robust gene expression biomarkers for latent tuberculosis infection (LTBi).
  • To leverage an integrative bioinformatics framework and machine learning for biomarker discovery.
  • To improve the accuracy and efficiency of LTBi detection.

Main Methods:

  • Analysis of four public transcriptomic datasets from peripheral blood mononuclear cells (PBMCs).
  • Identification of differentially expressed genes (DEGs) and application of gene ontology (GO) enrichment.
  • Utilized machine learning, miRNA interaction analysis, semantic similarity, and ROC curve analysis for biomarker prioritization.

Main Results:

  • Identified key candidate biomarkers, CCL2 and CXCL10, with high diagnostic potential (AUC > 0.85).
  • Demonstrated the effectiveness of an integrative bioinformatics approach in uncovering LTBi-associated genes.
  • Refined gene lists through multi-step analysis including functional clustering and pathway enrichment.

Conclusions:

  • The study highlights the potential of combining transcriptomic data with machine learning for novel LTBi biomarker discovery.
  • Candidate biomarkers CCL2 and CXCL10 warrant further experimental validation for clinical application.
  • This approach provides a foundation for developing improved diagnostic strategies for latent tuberculosis infection.