Objective: To screen specific biomarkers for latent tuberculosis infection by comparing the plasma proteomic profiling between latent tuberculosis infection and healthy controls.
Methods: The plasma proteins from 15 cases with latent tuberculosis infection and 15 healthy controls were detected by the label-free quantitative proteomic technology. Differential expressed proteins were analyzed by GO, KEGG, and BiNGO analysis. Student's t test was used to analyze the differential expression between 2 groups.
Results: Twenty-three candidate proteins were identified, among which 15 proteins were downregulated (<0.5-fold at P<0.05) and 8 proteins were upregulated (>2.0-fold at P<0.05) in the latent tuberculosis infection group. Bioinformatic analysis revealed 3 proteins AAT, C3 and C4A to be the most significant.
Conclusion: There were differential plasma protein profiles between latent tuberculosis infection and healthy controls. Candidate proteins AAT, C3 and C4A were promising biomarkers for discriminating cases with latent tuberculosis infection from healthy persons.