Evidence map›Paper›PMID 40301426›Full record

ArticleScientific reports2025

Identification of immune phenotypes and diagnostic biomarkers in active and latent tuberculosis infections.

Tongtong Shao, Li Yang, Ge Wu, Xiaobo Lu, Rongjiong Zheng

Abstract read
In one paragraph

Article in Scientific reports, 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.

Tongtong ShaoLiver Disease Center of Infectious Disease, The First Affiliated Hospital of Xinjiang Medical University, No. 137 Liyushan South Road, Urumqi, 830054, Xinjiang, China.
Li YangLiver Disease Center of Infectious Disease, The First Affiliated Hospital of Xinjiang Medical University, No. 137 Liyushan South Road, Urumqi, 830054, Xinjiang, China.
Ge WuTumor Center, The First Affiliated Hospital of Xinjiang Medical University, No. 137 Liyushan South Road, Urumqi, 830054, Xinjiang, China.
Xiaobo LuLiver Disease Center of Infectious Disease, The First Affiliated Hospital of Xinjiang Medical University, No. 137 Liyushan South Road, Urumqi, 830054, Xinjiang, China. xjykdluxiaobo@126.com.
Rongjiong ZhengLiver Disease Center of Infectious Disease, The First Affiliated Hospital of Xinjiang Medical University, No. 137 Liyushan South Road, Urumqi, 830054, Xinjiang, China. zhengrongjiong@163.com.

Funding

Immunological mechanisms and diagnostic applications of activation of latent tuberculosis infection in special populations SKL-HIDCA-2021-JH12
6 · The paper itself

Abstract

The diagnosis and treatment of tuberculosis rely on a deep understanding of the pathobiology and immune responses. This study aimed to identify potential immune response mechanisms by integrating gene expression analysis with immune cell distribution profiling to characterize the immune phenotypes of active tuberculosis (ATB) and latent tuberculosis infection (LTB). Differentially expressed genes (DEGs) between ATB or LTB and controls were identified using the GSE19491 and GSE107994 datasets. A total of 273 and 105 immune-related DEGs were identified in ATB and LTB through ImmProt database, respectively. Immune-related DEGs specific to LTB were mainly enriched in the MAPK signaling pathway, Ras signaling pathway. Furthermore, random forest analysis identified HLA-DRB5 and IRF1 as showing diagnostic potential in ATB, LCN10, SHC1, IKBKG, RETN, and SOS1 showed importance in LTB. Flow cytometry detected significantly higher levels of macrophages M0 in ATB compared to LTB and controls, while other types of immune cells showed significant increases in LTB. The levels of marker genes were validated by RT-qPCR and Western blot, as well as single-cell data in ATB and LTB. The findings of this study provide potential biomarkers for the diagnosis of tuberculosis and may facilitate the development of more effective treatment strategies.

Indexed as

BiomarkersLatent TuberculosisTuberculosisGene Expression ProfilingHumansMacrophagesPhenotypeBiomarkersActive tuberculosisBiomarkersImmune-related genesLatent tuberculosis infection

Identifiers

PMID40301426
PMCPMC12041371

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.