Real-time PCR for the rapid identification of latent tuberculosis infection using host-serum biomarkers

<title>Abstract</title> <p> Background Latent tuberculosis infection (LTBI) is a major health challenge globally, which constitutes a large reservoir for future active disease and transmission. Currently, diagnostic tests, including the tuberculin skin test and interferon-γ release assays, have limited ability to distinguish LTBI from active disease and to predict disease progression. Therefore, this study aimed to evaluate host-derived serum biomarkers using a real-time qPCR assay for the rapid identification of LTBI. Methods The study population consisted of 143 individuals, including the primary study population (n = 93), which was categorized into 3 groups: active tuberculosis (n = 20), latent tuberculosis infection (n = 54), and contact tracing (n = 19), and an additional 50 individuals from close contacts of ATB for further validation of the study results. Serum samples were separated, and total RNA was extracted, followed by cDNA synthesis. The analysis of five host gene expression ( <italic>CXCL10</italic> , <italic>L6</italic> , <italic>CVIL</italic> , <italic>LIMD2</italic> , and <italic>ARSA1</italic> ) was done using SYBR Green-based real-time qPCR, with <italic>B2M</italic> as the housekeeping reference gene for normalization. Relative gene expression was calculated using the 2^−ΔΔCt method, and statistical analyses were performed based on data distribution. Results <italic>CXCL10</italic> was the most highly detected gene among the three study groups (ATB: 100%, CT: 89.5%, LTBI: 92.6%) and the most consistently detected gene across the independent validation cohort (n = 50). Significant differential expression was observed for <italic>CXCL10</italic> (p = 0.019), <italic>L6</italic> (p = 0.001), and <italic>CVIL</italic> (p = 0.001) genes for the LTBI and ATB groups. <italic>CXCL10</italic> , <italic>L6</italic> , and <italic>CVIL</italic> were upregulated in LTBI and downregulated in ATB, suggesting their potential to distinguish infection states. <italic>LIMD2</italic> and <italic>ARSA1</italic> did not show consistent or statistically significant differences. Conclusions This study uses a molecular-based RT-qPCR assay to identify potential biomarkers that accurately differentiate LTBI and ATB patients. The genes, including <italic>CXCL10</italic> , <italic>L6</italic> , and <italic>CVIL</italic> , showed significant differences between the ATB and LTBI groups, suggesting that these genes could serve as potential biomarkers for early identification of LTBI. These results indicate that host biomarkers could serve as potential markers for developing a rapid, minimally invasive approach, particularly in resource-limited settings. </p>