Evidence map›Paper›PMID 42712463›Full record

ArticleFrontiers in cellular and infection microbiology2026

CD4

Bingfen Yang, Hongjuan An, Pei Zhao, Zhihong Cao, Jinwen Su, Xiaoou Wang, Yinping Liu, Xinjing Wang, Jing Jiang, Xiaoxing Cheng

Abstract read
In one paragraph

Article in Frontiers in cellular and infection microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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

10 authors.

Bingfen Yang *Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute of Tuberculosis Research, Senior Department of Tuberculosis, the Eighth Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing, China.
Hongjuan An *Tuberculosis Control Team, Senior Department of Tuberculosis, The Eighth Medical Center of PLA General Hospital, Beijing, China.
Pei Zhao *Outpatient Department, Senior Department of Tuberculosis, the Eighth Medical Center of PLA General Hospital, Beijing, China.
Zhihong CaoBeijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute of Tuberculosis Research, Senior Department of Tuberculosis, the Eighth Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing, China.
Jinwen SuInstitute of Research, Beijing Key Laboratory of Organ Transplantation and Immune Regulation, Senior Department of Respiratory and Critical Care Medicine, the Eighth Medical Center of PLA General Hospital, Beijing, China.
Xiaoou WangBeijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute of Tuberculosis Research, Senior Department of Tuberculosis, the Eighth Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing, China.
Yinping LiuBeijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute of Tuberculosis Research, Senior Department of Tuberculosis, the Eighth Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing, China.
Xinjing WangOutpatient Department, Senior Department of Tuberculosis, the Eighth Medical Center of PLA General Hospital, Beijing, China.
Jing JiangIntensive Care Unit, Senior Department of Tuberculosis, the Eighth Medical Center of PLA General Hospital, Beijing, China.
Xiaoxing ChengBeijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute of Tuberculosis Research, Senior Department of Tuberculosis, the Eighth Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Tuberculosis (TB) remains a global public health burden, and how immune cell subsets regulate host anti-TB immunity and disease progression remains incompletely understood. While previous studies have focused on single-positive (SP) T cells (CD4 Methods: A Genome-Wide Association Study (GWAS) was conducted to analyze 731 immune cell traits and a dataset encompassing 895 patients with TB. Subsequently, a cohort including 647 patients with active TB and 632 healthy controls was used to verify the findings of Mendelian randomization (MR). The correlation between the percentage of DP T cells in lymphocytes and TB severity, treatment efficacy, and Results: MR analysis suggested potential causal links between the percentage of DP T cells among peripheral leukocytes and TB status. Clinical sample validation showed that the percentage of peripheral DP T cell among leukocytes was significantly lower in patients with active TB than in healthy controls (P < 0.001), and was inversely correlated with disease severity. Additionally, the percentage of DP T cells in leukocytes was positively correlated with Mtb-specific antigen-stimulated IFN-γ production. Flow cytometric analysis demonstrated that DP T cells had a significantly higher frequency of IFN-γ-expressing cells compared to CD8 Conclusions: Our findings indicate that DP T cells are closely associated with TB severity, and are positively associated with Mtb-specific IFN-γ response. The percentage of peripheral DP T cells in leukocytes could serve as a potential non-invasive biomarker for TB severity stratification.

Indexed as

CD4-Positive T-LymphocytesCD8-Positive T-LymphocytesT-Lymphocyte SubsetsTuberculosisAdultFemaleGenome-Wide Association StudyHumansInterferon-gammaMaleMendelian Randomization AnalysisMiddle AgedMycobacterium tuberculosisPrognosisSeverity of Illness IndexInterferon-gammaDP T cellsIFN-γimmune cellsMendelian randomizationtuberculosis

Identifiers

PMID42712463
PMCPMC13549930

What OpenQuestion holds

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Registered trials

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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.