Evidence map›Paper›PMID 41852731›Full record

ArticleiScience2026

Plasma protein biomarkers predictive of progression to active tuberculosis among close contacts of patients with tuberculosis.

Yutong Han, Yan Shao, Qiao Liu, Limei Zhu, Cheng Chen, Biao Xu

Abstract read
In one paragraph

Article in iScience, 2026. 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. Review
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

6 authors.

Yutong HanDepartment of Epidemiology, School of Public Health, Fudan University, Shanghai, China.
Yan ShaoDepartment of Chronic Communicable Disease, Center for Disease Control and Prevention of Jiangsu Province, Nanjing, Jiangsu Province, China.
Qiao LiuDepartment of Chronic Communicable Disease, Center for Disease Control and Prevention of Jiangsu Province, Nanjing, Jiangsu Province, China.
Limei ZhuDepartment of Chronic Communicable Disease, Center for Disease Control and Prevention of Jiangsu Province, Nanjing, Jiangsu Province, China.
Cheng ChenDepartment of Chronic Communicable Disease, Center for Disease Control and Prevention of Jiangsu Province, Nanjing, Jiangsu Province, China.
Biao XuDepartment of Epidemiology, School of Public Health, Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A blood-based test capable of predicting progression to active tuberculosis (TB) before symptom onset could reduce numbers needed to treat and mitigate disease transmission. This study evaluated plasma protein as predictors of TB progression within a cohort of close contacts from a university TB outbreak. Plasma from 17 progressors who developed TB within 2 years, 28 interferon-gamma release assay (IGRA)-positive non-progressors, and 33 IGRA-negative healthy controls was profiled using the Olink proteomics platform. Progressors showed broad downregulation of proteins related to immune regulation, cell adhesion, and nucleotide metabolism, while no significant differences were observed between non-progressors and healthy controls. A six-protein panel comprising LRP11, REG4, FLT3LG, CCDC80, ADA, and DPP7 discriminated progressors from others with AUCs exceeding 0.85. Transcriptomic validation in two independent cohorts support consistent downregulation of these markers. These findings highlight a distinct protein signature with potential for risk differentiation of TB progression and inform the development of targeted preventive strategies.

Indexed as

DiseasePublic health

Identifiers

PMID41852731
PMCPMC12992532

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.