Identification of reduced host transcriptomic signatures for tuberculosis disease and digital PCR-based validation and quantification

Gliddon, H.D.; Kaforou, M.; Alikian, M.; Habgood-Coote, D.; Zhou, C.X.; Oni, T.; Anderson, S.T.; Brent, A.J.; Crampin, A.C.; Eley, B.; Heyderman, R.; Kern, F.; Langford, P.R.; Ottenhoff, T.H.M.; Hibberd, M.L.; French, N.; Wright, V.J.; Dockrell, H.M.; Coin, L.J.; Wilkinson, R.J.; Levin, M.; ILULU Consortium

doi:doi:10.3389/fimmu.2021.637164

Recently, host whole blood gene expression signatures have been identified for diagnosis of tuberculosis (TB). Absolute quantification of the concentrations of signature transcripts in blood have not been reported, but would facilitate diagnostic test development. To identify minimal transcript signatures, we applied a transcript selection procedure to microarray data from African adults comprising 536 patients with TB, other diseases (OD) and latent TB (LTBI), divided into training and test sets. Signatures were further investigated using reverse transcriptase (RT)-digital PCR (dPCR). A four-transcript signature (GBP6, TMCC1, PRDM1, and ARG1) measured using RT-dPCR distinguished TB patients from those with OD (area under the curve (AUC) 93.8% (CI95% 82.2-100%). A three-transcript signature (FCGR1A, ZNF296, and C1QB) differentiated TB from LTBI (AUC 97.3%, CI95%: 93.3-100%), regardless of HIV. These signatures have been validated across platforms and across samples offering strong,...Show moreRecently, host whole blood gene expression signatures have been identified for diagnosis of tuberculosis (TB). Absolute quantification of the concentrations of signature transcripts in blood have not been reported, but would facilitate diagnostic test development. To identify minimal transcript signatures, we applied a transcript selection procedure to microarray data from African adults comprising 536 patients with TB, other diseases (OD) and latent TB (LTBI), divided into training and test sets. Signatures were further investigated using reverse transcriptase (RT)-digital PCR (dPCR). A four-transcript signature (GBP6, TMCC1, PRDM1, and ARG1) measured using RT-dPCR distinguished TB patients from those with OD (area under the curve (AUC) 93.8% (CI95% 82.2-100%). A three-transcript signature (FCGR1A, ZNF296, and C1QB) differentiated TB from LTBI (AUC 97.3%, CI95%: 93.3-100%), regardless of HIV. These signatures have been validated across platforms and across samples offering strong, quantitative support for their use as diagnostic biomarkers for TB.Show less

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Identification of reduced host transcriptomic signatures for tuberculosis disease and digital PCR-based validation and quantification