Host blood-based biosignatures for subclinical TB and incipient TB: a prospective study of adult TB household contacts in Southern India.

Abstract Background A large proportion of the global tuberculosis (TB) burden is asymptomatic and not detectable by symptom-based screening, driving the TB epidemic through continued M. tuberculosis transmission. Currently, no validated tools exist to diagnose incipient and subclinical TB. Methods Nested within a large prospective study in household contacts of pulmonary TB cases in Southern India, we assessed 35 incipient TB and 12 subclinical TB cases, along with corresponding household active TB cases (n=11), and household controls (n=39) using high throughput methods for transcriptional and protein profiling. We split the data into training and test sets and applied a support vector machine classifier followed by a Lasso regression model to identify signatures. Results The Lasso regression model identified an 11-gene signature (ABLIM2, C20orf197, CTC-543D15.3, CTD-2503O16.3, HLADRB3, METRNL, RAB11B-AS1, RP4-614C10.2, RNA5SP345, RSU1P1, and UACA) that distinguished subclinical TB from incipient TB with an AUC of 1.00 (95% CI: 0.99 – 1.00), corresponding to a sensitivity of 100.0% (95%CI, 63.1-100.0), specificity of 100.0% (95%CI, 85.2-100.0) and the AUC of 0.90 (95% CI: 0.74 – 1.00), and a sensitivity of 100.0% (95%CI, 39.8-100.0), specificity of 83.3% (95%CI, 51.6-97.9) in the training and test sets, respectively. Further, we identified an 8-protein signature comprising b-FGF, IFNγ, IL1RA, IL7, IL12p70, IL13, PDGF-BB, and VEGF that differentiated subclinical TB from incipient TBs with an AUC of 1.00 (95%CI, 0.99-1.00) and an AUC of 0.75 (95%CI, 0.50-0.99) in the training and test set, respectively. Conclusions The 11-gene signature identified in this study in a population with different genetic and socioeconomic settings with lower TB incidence could also be useful for predicting TB progression. However, validation in other studies is warranted to establish the potential of the immune biosignatures for identifying subclinical TB.