Single-gene transcripts for subclinical TB: an individual participant data meta-analysis

Abstract

AbstractBackgroundTranslation of blood RNA signatures may be accelerated by identifying more parsimonious biomarkers. We tested the hypothesis that single-gene transcripts provide comparable accuracy for detection of subclinical TB to multi-gene signatures and benchmarked their clinical utility to interferon-y release assays (IGRAs).MethodsWe identified datasets where participants underwent RNA sampling and at least 12 months of follow-up for progression to TB. We performed a one-stage individual participant data meta-analysis to compare multi-gene signatures against single-gene transcripts to detect subclinical TB, defined as asymptomatic prevalent or incident TB (diagnosed ≥21 days from enrolment, irrespective of symptoms) over a 12-month interval. We performed decision curve analysis to evaluate the net benefit of using RNA biomarkers and IGRA, alone or in combination, compared to treating all or no individuals with preventative treatment.ResultsWe evaluated 80 single-genes and eight multi-gene signatures in a pooled analysis of four RNAseq and three qPCR datasets, comprising 6544 total samples and including 283 samples from 214 individuals with subclinical TB. Five single-gene transcripts were equivalent to the best-performing multi-gene signature over 12 months, with areas under the receiver operating characteristic curves ranging from 0.75-0.77, but none met the WHO minimum target product profile (TPP) for a TB progression test. IGRA demonstrated much lower specificity in higher burden settings, while sensitivity and specificity of RNA biomarkers were consistent across settings. In higher burden settings, RNA biomarkers had greater net benefit than IGRA, which offered little clinical utility over treating all with preventative therapy. In low burden settings, IGRA approximated the TPP and offered greater clinical utility than RNA biomarkers, but combining both tests provided the highest net benefit for services aiming to treat <50 people to prevent a single case.InterpretationSingle-gene transcripts are equivalent to multi-gene signatures for detection of subclinical TB, with consistent performance across settings. Single transcripts demonstrate potential clinical utility to stratify treatment, particularly when used in combination with IGRA in low burden settings.