Novel Biomarkers Distinguishing Active Tuberculosis from Latent Infection Identified by Gene Expression Profile of Peripheral Blood Mononuclear Cells
2011

Identifying Biomarkers for Tuberculosis Diagnosis

Sample size: 95 publication 10 minutes Evidence: high

Author Information

Author(s): Lu Chanyi, Wu Jing, Wang Honghai, Wang Sen, Diao Ni, Wang Feifei, Gao Yan, Chen Jiazhen, Shao Lingyun, Weng Xinhua, Zhang Ying, Zhang Wenhong

Primary Institution: Huashan Hospital, Fudan University, Shanghai, China

Hypothesis

This study aimed to identify immune factors associated with Mycobacterium tuberculosis infection and novel biomarkers that can distinguish active disease from latent infection.

Conclusion

The study identified a combination of three genes, CXCL10, ATP10A, and TLR6, as novel biomarkers for distinguishing active tuberculosis from latent infection.

Supporting Evidence

  • The study identified 506 differentially expressed genes associated with tuberculosis infection.
  • Validation studies confirmed the expression patterns of 81% of the microarray identified genes.
  • The combination of CXCL10, ATP10A, and TLR6 provided a sensitivity of 71% and specificity of 89% in distinguishing TB from LTBI.

Takeaway

Researchers found three genes that can help tell if someone has active tuberculosis or just a latent infection, which is important for treatment.

Methodology

The study used microarray analysis and quantitative real-time PCR to analyze gene expression in peripheral blood mononuclear cells from individuals with tuberculosis, latent tuberculosis infection, and healthy controls.

Potential Biases

Potential bias due to the selection of participants from a BCG-vaccinated population.

Limitations

The study was limited to a specific population and may not be generalizable to all demographics.

Participant Demographics

Participants included 25 TB patients, 36 individuals with latent TB infection, and 22 healthy controls, with a mix of genders and ages ranging from 14 to 86 years.

Statistical Information

P-Value

p<0.001

Statistical Significance

p<0.05

Digital Object Identifier (DOI)

10.1371/journal.pone.0024290

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