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Host transcriptional biosignatures for TB progression in Indian household contactsBlood test signatures may help predict TB in household contacts

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Key Takeaway
Consider that host transcriptional biosignatures show modest, non-significant predictive performance for TB progression in Indian household contacts.

This was a prospective observational cohort study in India involving 525 household contacts of TB patients. The study evaluated several host transcriptional biosignatures (RISK6, Sweeney3, INDIA10, GBP2, FCGR1B, SERPING1) adapted to a microfluidic RT-qPCR platform for predicting TB progression during a 12-month follow-up period.

Over the 12-month follow-up, 12 of 525 contacts progressed to TB, with 6 cases in children aged 5–14 years. Five cases progressed at 6 months and 7 at 12 months. The predictive performance of the RISK6 signature showed an AUC of 0.61 (95% CI 0.41–0.82) for TB progression. The Sweeney3 signature also had an AUC of 0.61 (95% CI 0.41–0.80), and the INDIA10 signature had an AUC of 0.59 (95% CI 0.46–0.72).

At 75% sensitivity, the specificity for RISK6 was 0.49 (95% CI 0.41–0.56), for Sweeney3 was 0.32 (95% CI 0.25–0.39), and for INDIA10 was 0.42 (95% CI 0.35–0.50). The FCGR1B and GBP2 signatures also showed significant AUCs for TB progression, with specificities of 0.56 (95% CL 0.49–0.64) and 0.50 (95% CL 0.43–0.58), respectively. Safety and tolerability data were not reported.

Key limitations include the lack of prior evaluation in Asian populations, limited sensitivity and specificity of the biosignatures in all populations, and a 5.7% failure rate for the INDIA10 signature due to one failed gene. The study supports the generalizability of RNA technology for TB prediction in the Indian population but warrants exploration of integrated diagnostic algorithms. This is an observational study; associations are reported, not causation.

Researchers studied 525 Indian household contacts of tuberculosis patients to see if blood-based gene signatures could predict who might develop TB over a year. The study used a microfluidic platform to test several signatures, including RISK6, Sweeney3, and INDIA10.

During 12 months of follow-up, 12 people (about 2%) progressed to TB, including 6 children aged 5–14 years. The predictive performance of the signatures was modest, with AUC values around 0.59 to 0.61, meaning they were not strong predictors. Specificity at a fixed sensitivity level was also low, ranging from 0.32 to 0.56.

No safety issues were reported, as the study only involved blood draws. The main reason to be careful is that this is an observational cohort study, so it shows links but not cause-and-effect, and the results are based on one group in India.

The realistic takeaway is that these signatures show some promise for TB prediction in this population, but they are not ready for clinical use and need more research in larger, diverse groups.

What this means for you:
Blood gene signatures show modest promise for predicting TB in Indian household contacts, but more research is needed.

Study Details

Study typeCohort
EvidenceLevel 3
PublishedApr 2026
View Original Abstract ↓
Achieving the goal of the End TB Strategy depends on new tools, preferably blood-based point-of-care (POC) tests, to identify individuals at risk of progression from M. tuberculosis infection to subclinical or clinical tuberculosis (TB). A decade of signature discovery and validation has resulted in several transcriptional signatures with promising capacity for predicting TB progression within the next 3–6 months, but evaluation of signature performance in Asian populations is lacking. Nested within a prospective observational cohort study of Indian household contacts (HHC study), we adapted the RISK6 and Sweeney3 along with our locally derived INDIA11 signature to the microfluidic RT-qPCR platform (Fluidigm) and evaluated their capacity to predict TB progression during a 12-month follow-up in a head-to-head comparison. As readily available in our dataset, the recently published single-gene signatures GBP2, FCGR1B, and SERPING1 were also assessed. Of the 525 recruited household contacts, 12 (6 cases in children aged 5–14 years) progressed to TB (5 at 6 months, 7 at 12 months) as defined by growth of M. tuberculosis in respiratory specimens. RISK6 and Sweeney3 were successfully adapted to the Fluidigm platform. One gene in the INDIA11 assay failed, resulting in the INDIA10 signature with an overall failure rate of 5.7%. RISK6, Sweeney3, and INDIA10 demonstrated comparable but statistically non-significant predictive performance for TB progression, with AUCs: RISK6 0.61 (95%CI 0.41–0.82), Sweeney3 0.61 (95%CI 0.41–0.80), INDIA10 0.59 (95%CI 0.46–0.72). Applying a fixed value of sensitivity 75% corresponding to the WHO minimum target for TB prediction resulted in the corresponding specificities RISK6 0.49 (95%CI 0.41–0.56), Sweeney3 0.32 (95%CI 0.25–0.39), and INDIA10 0.42 (95%CI 0.35–0.50). Of single-gene signatures, the AUCs of FCGR1B and GBP2 were significant with specificities of FCGR1B 0.56 (95%CL 0.49–0.64) and GBP 0.50 (95%CL 0.43–0.58). The expression of interferon-gamma–inducible gene signatures were able to discriminate between TB progressors and non-progressors in an hitherto underexplored Indian population, supporting the generalizability of RNA technology to this setting. Given the limited sensitivity and specificity of current biosignatures in all populations, exploration of integrated diagnostic algorithms relying on established and novel tools in a multidisciplinary approach is warranted.
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