Evidence map›Paper›PMID 40359654›Full record

ArticleTuberculosis (Edinburgh, Scotland)2025

Analysis of the cross-study replicability of tuberculosis gene signatures using 49 curated human transcriptomic datasets.

Xutao Wang, Katie Harper, Pranay Sinha, W Evan Johnson, Prasad Patil

Abstract read
In one paragraph

Article in Tuberculosis (Edinburgh, Scotland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Xutao WangDepartment of Biostatistics, Boston University School of Public Health, Boston, USA.
Katie HarperDivision of Computational Biomedicine, Boston University School of Medicine, Boston, USA.
Pranay SinhaSection of Infectious Diseases, Department of Medicine, Boston University School of Medicine, Boston, USA.
W Evan JohnsonDivision of Infectious Disease, Center for Data Science, Rutgers New Jersey Medical School, New Jersey, USA.
Prasad PatilDepartment of Biostatistics, Boston University School of Public Health, Boston, USA. Electronic address: patil@bu.edu.

Funding

FEND for TB supplement to accelerate BLINK X developmentU01AI152084 · NIAID · RUTGERS BIOMEDICAL AND HEALTH SCIENCES · PI ALLAND, DAVID, DORMAN, SUSAN E · 2020 to 2024
$20.0M
Novel and Optimized Diagnostics for Pediatric TBR01AI152159 · NIAID · RUTGERS BIOMEDICAL AND HEALTH SCIENCES · PI ALLAND, DAVID, ELLNER, JERROLD J. · 2020 to 2024
$6.0M
Removing batch effects in high-throughput biomedical studiesR01GM127430 · NIGMS · RUTGERS BIOMEDICAL AND HEALTH SCIENCES · PI William Evan Johnson · 2018 to 2026
$2.4M
Signature of profiling and staging the progression of TB from infection to disease.R21AI154387 · NIAID · BOSTON UNIVERSITY MEDICAL CAMPUS · PI JOHNSON, WILLIAM EVAN · 2020 to 2021
$468k
NIAID NIH HHS R01 AI152159NIAID NIH HHS R21 AI154387NIAID NIH HHS U01 AI152084NIGMS NIH HHS R01 GM127430
6 · The paper itself

Abstract

backgroundTuberculosis (TB) is the leading cause of infectious disease mortality worldwide. Numerous host blood-based gene expression signatures have been proposed in the literature as alternative tools for diagnosing TB infection. However, the generalizability of these signatures to different patient contexts is not well-characterized. There is a pressing need for a well-curated database of TB gene expression studies for the systematic assessment of existing and newly developed TB gene signatures.

resultsWe built curatedTBData, a manually-curated database of 49 human TB transcriptomic studies. This data resource is freely available through GitHub and as an R Bioconductor package that allows users to validate new and existing biomarkers without the challenges of harmonizing heterogeneous studies. We demonstrate the use of this data resource with cross-study comparisons for 72 human host blood-based TB gene signatures. For the comparison of subjects with active TB from healthy controls, 19 gene signatures had weighted mean AUC of 0.90 or greater, with the highest result of 0.94. In active TB disease versus latent TB infection, 7 gene signatures had weighted mean AUC of 0.90 or greater, with a maximum of 0.93.

conclusionsThe curatedTBData data package offers a comprehensive resource of curated human blood-based gene expression and clinically annotated data. This resource will facilitate the development of new signatures that are generalizable across cohorts or more applicable to specific subsets of patients.

Indexed as

Databases, GeneticGene Expression ProfilingLatent TuberculosisMycobacterium tuberculosisTranscriptomeTuberculosisCase-Control StudiesHost-Pathogen InteractionsHumansPredictive Value of TestsReproducibility of ResultsGene set scoring methodsGene signatureTranscriptomic dataTuberculosis

Identifiers

PMID40359654
PMCPMC12158633

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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.