K M Dupnik1, J M Bean2, M H Lee1, M A Jean Juste3, L Skrabanek4, V Rivera1, C K Vorkas5, J W Pape6, D W Fitzgerald1, M Glickman7. 1. Department of Medicine, Weill Cornell Medical College, New York, New York. 2. Immunology Program, Memorial Sloan Kettering Cancer Center, New York, New York, USA. 3. GHESKIO (Groupe Haitien d'Etude du Sarcome de Kaposi et des Infections Opportunistes) Center, Port au Prince, Haiti. 4. Applied Bioinformatics Core and Department of Physiology and Biophysics, Weill Cornell Medicine, New York, New York. 5. Department of Medicine, Weill Cornell Medical College, New York, New York, Immunology Program, Memorial Sloan Kettering Cancer Center, New York, New York, USA. 6. Department of Medicine, Weill Cornell Medical College, New York, New York, GHESKIO (Groupe Haitien d'Etude du Sarcome de Kaposi et des Infections Opportunistes) Center, Port au Prince, Haiti. 7. Immunology Program, Memorial Sloan Kettering Cancer Center, New York, New York, USA, Division of Infectious Diseases, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Abstract
BACKGROUND: Peripheral blood transcriptome signatures that distinguish active pulmonary tuberculosis (TB) from control groups have been reported, but correlations of these signatures with sputum mycobacterial load are incompletely defined. METHODS: We assessed the performance of published TB transcriptomic signatures in Haiti, and identified transcriptomic biomarkers of TB bacterial load in sputum as measured by Xpert® MTB/RIF molecular testing. People in Port au Prince, Haiti, with untreated pulmonary TB (n = 51) formed the study cohort: 19 people with low and 32 with high sputum Mycobacterium tuberculosis load. Peripheral whole blood transcriptomes were generated using RNA sequencing. RESULTS: Twenty of the differentially expressed transcripts in TB vs. no TB were differentially expressed in people with low vs. high sputum mycobacterial loads. The difference between low and high bacterial load groups was independent of radiographic severity. In a published data set of transcriptomic response to anti-tuberculosis treatment, this 20-gene subset was more treatment-responsive at 6 months than the full active TB signature. CONCLUSION: We identified genes whose transcript levels in the blood distinguish active TB with high vs. low M. tuberculosis loads in the sputum. These transcripts may reveal mechanisms of mycobacterial control of M. tuberculosis during active infection, as well as identifying potential biomarkers for bacterial response to anti-tuberculosis treatment.
BACKGROUND: Peripheral blood transcriptome signatures that distinguish active pulmonary tuberculosis (TB) from control groups have been reported, but correlations of these signatures with sputum mycobacterial load are incompletely defined. METHODS: We assessed the performance of published TB transcriptomic signatures in Haiti, and identified transcriptomic biomarkers of TB bacterial load in sputum as measured by Xpert® MTB/RIF molecular testing. People in Port au Prince, Haiti, with untreated pulmonary TB (n = 51) formed the study cohort: 19 people with low and 32 with high sputum Mycobacterium tuberculosis load. Peripheral whole blood transcriptomes were generated using RNA sequencing. RESULTS: Twenty of the differentially expressed transcripts in TB vs. no TB were differentially expressed in people with low vs. high sputum mycobacterial loads. The difference between low and high bacterial load groups was independent of radiographic severity. In a published data set of transcriptomic response to anti-tuberculosis treatment, this 20-gene subset was more treatment-responsive at 6 months than the full active TB signature. CONCLUSION: We identified genes whose transcript levels in the blood distinguish active TB with high vs. low M. tuberculosis loads in the sputum. These transcripts may reveal mechanisms of mycobacterial control of M. tuberculosis during active infection, as well as identifying potential biomarkers for bacterial response to anti-tuberculosis treatment.
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Authors: Qianjing Xia; Myung Hee Lee; Kathleen F Walsh; Kathrine McAulay; James M Bean; Daniel W Fitzgerald; Kathryn M Dupnik; Warren D Johnson; Jean W Pape; Kyu Y Rhee; Flonza Isa Journal: JCI Insight Date: 2020-09-17