Evidence map›Paper›PMID 40787468›Full record

ArticleFrontiers in immunology2025

A comprehensive bioinformatics analysis of pathways and biomarkers shared between type 2 diabetes mellitus and chronic obstructive pulmonary disease.

Tingting Hu, Xiaomei Duan, Jiale Gao, Zheng Li, Dan Xu, Jing Jing, Fengsen Li, Jianbing Ding, Li Ma, Min Jiang and 1 more

Abstract read
In one paragraph

Article in Frontiers in immunology, 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

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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

11 authors.

Tingting Hu *Clinical Laboratory Center, Traditional Chinese Medicine Hospital Affiliated to Xinjiang Medical University, Urumqi, China.
Xiaomei Duan *Xinjiang Laboratory of Respiratory Disease Research, Traditional Chinese Medicine Hospital Affiliated to Xinjiang Medical University, Urumqi, China.
Jiale GaoClinical Laboratory Center, Traditional Chinese Medicine Hospital Affiliated to Xinjiang Medical University, Urumqi, China.
Zheng LiXinjiang Laboratory of Respiratory Disease Research, Traditional Chinese Medicine Hospital Affiliated to Xinjiang Medical University, Urumqi, China.
Dan XuXinjiang Laboratory of Respiratory Disease Research, Traditional Chinese Medicine Hospital Affiliated to Xinjiang Medical University, Urumqi, China.
Jing JingXinjiang Laboratory of Respiratory Disease Research, Traditional Chinese Medicine Hospital Affiliated to Xinjiang Medical University, Urumqi, China.
Fengsen LiXinjiang Laboratory of Respiratory Disease Research, Traditional Chinese Medicine Hospital Affiliated to Xinjiang Medical University, Urumqi, China.
Jianbing DingDepartment of Immunology, College of Basic Medicine, Xinjiang Medical University, Urumqi, China.
Li MaDepartment of Endocrinology, Traditional Chinese Medicine Hospital Affiliated to Xinjiang Medical University, Urumqi, China.
Min JiangXinjiang Laboratory of Respiratory Disease Research, Traditional Chinese Medicine Hospital Affiliated to Xinjiang Medical University, Urumqi, China.
Jing WangXinjiang Laboratory of Respiratory Disease Research, Traditional Chinese Medicine Hospital Affiliated to Xinjiang Medical University, Urumqi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: T2DM and COPD are prevalent and high-burden diseases which are closely related, with poor patient outcomes. In this study, we aimed to identify common diagnostic markers for T2DM and COPD and their therapeutic potential. Methods: Microarray data from the GEO database were analyzed to identify DEGs, whereas WGCNA, co-differential gene analyses were employed to identify co-expression modules and DEGs functions. Diagnostic markers were determined through machine learning and validated with human blood PBMC and single-cell sequencing. Results: A total of 738 and 1391 DEGs were identified for T2DM and COPD, respectively. Among these, 25 key genes and 75 co-differential genes were recognized, predominantly enriched in immune-related pathways, particularly those involving T-cell signaling. Eight diagnostic markers were identified through machine learning approaches. Subsequent validation using human PBMC from three groups (Ctrl, COPD, and T2DM, n=15 each) confirmed PES1 (AUC 0.676 and 0.615), CANX (AUC 0.668 and 0.642), SUMF2 (AUC 0.684 and 0.679), and DCXR (0.625 and 0.606) as shared diagnostic markers. Analysis of single-cell sequencing data from blood and bone marrow and RT-qPCR results from healthy individuals and patients with T2DM combined with COPD showed that only SUMF2 showed a statistically significant difference in expression levels in comorbid patients and was strongly associated with T-cell subpopulations. Conclusion: The T-cell pathway may be involved in the pathogenesis of T2DM and COPD, and SUMF2 may be a potential diagnostic marker, and its high expression in T-cell subsets suggests a possible role in the immunomodulatory mechanisms underlying the two diseases.

Indexed as

BiomarkersComputational BiologyDiabetes Mellitus, Type 2Pulmonary Disease, Chronic ObstructiveDatabases, GeneticFemaleGene Expression ProfilingGene Regulatory NetworksHumansLeukocytes, MononuclearMachine LearningMaleSignal TransductionTranscriptomeBiomarkersChronic Obstructive Pulmonary Diseasemachine learningsingle-cell sequencingSUMF2type 2 diabetes mellitusweighted gene co-expression network analysis

Identifiers

PMID40787468
PMCPMC12331674

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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.