Evidence map›Paper›PMID 39906693›Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2025

Integrated Approach for Biomarker Discovery and Mechanistic Insights into the Co-Pathogenesis of Type 2 Diabetes Mellitus and Non-Hodgkin Lymphoma.

Yidong Zhu, Jun Liu, Bo Wang

Abstract read
In one paragraph

Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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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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

2 citing papers in PubMed.

  1. Article
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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

3 authors.

Yidong Zhu *Department of Traditional Chinese Medicine, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, People's Republic of China.ORCID 0000-0002-8505-8257
Jun Liu *Department of Traditional Chinese Medicine, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, People's Republic of China.
Bo WangDepartment of Endocrinology, Yangpu Hospital, Tongji University School of Medicine, Shanghai, 200090, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Type 2 diabetes mellitus (T2DM) is associated with an increased risk of non-Hodgkin lymphoma (NHL), but the underlying mechanisms remain unclear. This study aimed to identify potential biomarkers and elucidate the molecular mechanisms underlying the co-pathogenesis of T2DM and NHL. Methods: Microarray datasets of T2DM and NHL were downloaded from the Gene Expression Omnibus database. Subsequently, a protein-protein interaction network was constructed based on the common differentially expressed genes (DEGs) between T2DM and NHL to explore regulatory interactions. Functional analyses were performed to explore underlying mechanisms. Topological analysis and machine learning algorithms were applied to refine hub gene selection. Finally, quantitative real-time polymerase chain reaction was performed to validate hub genes in clinical samples. Results: Intersection analysis of DEGs from the T2DM and NHL datasets identified 81 shared genes. Functional analyses suggested that immune-related pathways played a significant role in the co-pathogenesis of T2DM and NHL. Topological analysis and machine learning identified three hub genes: Conclusion: This study suggested the pivotal role of immune dysregulation in the co-pathogenesis of T2DM and NHL and identified and validated three hub genes as key contributors. These findings provide insight into the complex interplay between T2DM and NHL.

Indexed as

immunitymachine learningmicroarray analysisnon-Hodgkin lymphomatype 2 diabetes mellitus

Identifiers

PMID39906693
PMCPMC11793108

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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.