Literature DB >> 34555657

Distinct blood transcriptomic signature of treatment in latent tuberculosis infected individuals at risk of developing active disease.

Julie G Burel1, Akul Singhania1, Paige Dubelko1, Julius Muller2, Rachel Tanner2, Eneida Parizotto2, Martin Dedicoat3, Thomas E Fletcher4, James Dunbar5, Adam F Cunningham6, Cecilia S Lindestam Arlehamn1, Donald G Catanzaro7, Antonino Catanzaro8, Timothy Rodwell8, Helen McShane2, Matthew K O'Shea9, Bjoern Peters10.   

Abstract

Although only a small fraction will ever develop the active form of tuberculosis (ATB) disease, chemoprophylaxis treatment in latent TB infected (LTBI) individuals is an effective strategy to control pathogen transmission. Characterizing immune responses in LTBI upon chemoprophylactic treatment is important to facilitate treatment monitoring, and thus improve TB control strategies. Here, we studied changes in the blood transcriptome in a cohort of 42 LTBI and 8 ATB participants who received anti-TB therapy. Based on the expression of previously published gene signatures of progression to ATB, we stratified the LTBI cohort in two groups and examined if individuals deemed to be at elevated risk of developing ATB before treatment (LTBI-Risk) differed from others (LTBI-Other). We found that LTBI-Risk and LTBI-Other groups were associated with two distinct transcriptomic treatment signatures, with the LTBI-Risk signature resembling that of treated ATB patients. Notably, overlapping genes between LTBI-Risk and ATB treatment signatures were associated with risk of progression to ATB and interferon (IFN) signaling, and were selectively downregulated upon treatment in the LTBI-Risk but not the LTBI-Other group. Our results suggest that transcriptomic reprogramming following treatment of LTBI is heterogeneous and can be used to distinguish LTBI-Risk individuals from the LTBI cohort at large.
Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Blood transcriptomics; Latent tuberculosis; Prophylaxis treatment

Mesh:

Year:  2021        PMID: 34555657      PMCID: PMC8629963          DOI: 10.1016/j.tube.2021.102127

Source DB:  PubMed          Journal:  Tuberculosis (Edinb)        ISSN: 1472-9792            Impact factor:   3.131


  49 in total

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Journal:  J Infect Dis       Date:  2012-08-07       Impact factor: 5.226

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Journal:  Nature       Date:  2018-08-22       Impact factor: 49.962

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Journal:  Cell       Date:  2018-11-15       Impact factor: 41.582

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8.  Diagnosis and follow-up of treatment of latent tuberculosis; the utility of the QuantiFERON-TB Gold In-tube assay in outpatients from a tuberculosis low-endemic country.

Authors:  Anne M Dyrhol-Riise; Gerd Gran; Tore Wentzel-Larsen; Bjørn Blomberg; Christel Gill Haanshuus; Odd Mørkve
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9.  Host blood RNA signatures predict the outcome of tuberculosis treatment.

Authors:  Ethan G Thompson; Ying Du; Stephanus T Malherbe; Smitha Shankar; Jackie Braun; Joe Valvo; Katharina Ronacher; Gerard Tromp; David L Tabb; David Alland; Shubhada Shenai; Laura E Via; James Warwick; Alan Aderem; Thomas J Scriba; Jill Winter; Gerhard Walzl; Daniel E Zak
Journal:  Tuberculosis (Edinb)       Date:  2017-08-12       Impact factor: 3.131

10.  Host transcriptional response to TB preventive therapy differentiates two sub-groups of IGRA-positive individuals.

Authors:  Claire Broderick; Jacqueline M Cliff; Ji-Sook Lee; Myrsini Kaforou; David Aj Moore
Journal:  Tuberculosis (Edinb)       Date:  2020-11-28       Impact factor: 3.131

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Review 2.  Contribution and Future of High-Throughput Transcriptomics in Battling Tuberculosis.

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Journal:  Front Microbiol       Date:  2022-02-24       Impact factor: 5.640

3.  Whole transcriptome sequencing reveals neutrophils' transcriptional landscape associated with active tuberculosis.

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Journal:  Front Immunol       Date:  2022-08-18       Impact factor: 8.786

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