Evidence map›Paper›PMID 42638626›Full record

ArticleFrontiers in tuberculosis2025

Targeted transcriptomic analyses of tuberculosis treatment response and outcomes in The Gambia.

Ismaila L Manneh, Fatoumatta Darboe, Haddijatou Jobe, Binta Sarr Kuyateh, Ousainou Cham, Olumuyiwa Owolabi, Brezesky Kotanmi, Andrea Rachow, Salome Charalambous, Kathrin Held and 2 more

Abstract read
In one paragraph

Article in Frontiers in tuberculosis, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Ismaila L MannehVaccines and Immunity Theme, Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, Gambia.
Fatoumatta DarboeVaccines and Immunity Theme, Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, Gambia.
Haddijatou JobeVaccines and Immunity Theme, Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, Gambia.
Binta Sarr KuyatehVaccines and Immunity Theme, Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, Gambia.
Ousainou ChamVaccines and Immunity Theme, Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, Gambia.
Olumuyiwa OwolabiVaccines and Immunity Theme, Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, Gambia.
Brezesky KotanmiStatistics and Bioinformatics, Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, Gambia.
Andrea RachowInstitute of Infectious Diseases and Tropical Medicine, Ludwig Maximilian University of Munich University Hospital, Munich, Germany.
Salome CharalambousThe Aurum Institute, Johannesburg, South Africa.
Kathrin HeldInstitute of Infectious Diseases and Tropical Medicine, Ludwig Maximilian University of Munich University Hospital, Munich, Germany.
Hazel M DockrellDepartment of Infection Biology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Jayne S SutherlandVaccines and Immunity Theme, Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, Gambia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Despite availability of effective treatment regimens for drug-susceptible Tuberculosis (TB), some patients still experience poor treatment outcomes. Currently tools for monitoring treatment outcomes are dependent on detection of mycobacteria in sputum, which are slow, expensive and poor at predicting relapse and failure. This study aims to identify new blood-derived markers for predicting treatment response and outcomes. Methods: Whole blood was collected in PAXgene tubes from patients with microbiologically confirmed TB at diagnosis, week 2, and at months 2, 4, and 6. Treatment response and outcomes were determined by culture and gene expression was compared between slow and fast responders; and between patients with good (cured) and poor treatment outcomes (failure and recurrent TB) using targeted RNA gene expression. Gene signatures were developed using random forest classification models. Results: Significant changes in gene expression were detected over the course of the TB treatment. Notably, major gene expression differences were observed at diagnosis between subsequently cured patients and patients who experienced poor treatment outcomes while minimal changes were detected between slow and fast responders among cured patients at diagnosis. A 7-gene end of treatment signature distinguished patients with good outcomes from those with poor treatment outcomes with area under the curve (AUC) of 0.91 (95% CI 0.85-0.99), 0.98 (95% CI 0.96-0.99), and 1.0 (95% CI 0.99-1.00), at baseline, month 2 and 6, respectively. Additionally, a 6-gene month 2 signature discriminates slow from fast responders with AUCs of 0.49 (95% CI 0.33-0.64), 0.58 (95% CI 0.07-1.00), and 0.93 (95% CI 0.78-1.00) at diagnosis, week 2 and month 2, respectively. Conclusion: The study identified genes signatures associated with TB treatment response and outcomes suggesting potential utility for treatment monitoring.

Indexed as

gene expressionMycobacterium tuberculosis diseasetreatment outcometreatment responsetuberculosis

Identifiers

PMID42638626
PMCPMC13489619

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.