Evidence map›Paper›PMID 38881696›Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2024

Integrated Bioinformatics Analysis Revealed Immune Checkpoint Genes Relevant to Type 2 Diabetes.

Ziteng Zhang, Guoting Sun, Yuying Wang, Ningjian Wang, Yingli Lu, Yi Chen, Fangzhen Xia

Abstract read
In one paragraph

Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Ziteng ZhangInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.
Guoting SunInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.
Yuying WangInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.
Ningjian WangInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.
Yingli LuInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.ORCID 0000-0002-5117-1614
Yi ChenInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.
Fangzhen XiaInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.ORCID 0000-0002-1069-0418

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Chronic low-grade inflammation of the pancreatic islets is the characteristic of type 2 diabetes (T2D), and some of the immune checkpoints may play important roles in the pancreatic islet inflammation. Thus, we aim to explore the immune checkpoint genes (ICGs) associated with T2D, thereby revealing the role of ICGs in the pathogenesis of T2D based on bioinformatic analyses. Methods: Differentially expressed genes (DEGs) and immune checkpoint genes (ICGs) of islets between T2D and control group were screened from datasets of the Gene Expression Omnibus (GEO). A risk model was built based on the coefficients of ICGs calculated by ridge regression. Functional enrichment analysis and immune cell infiltration estimation were conducted. Correlations between ICGs and hub genes, T2D-related disease genes, insulin secretion genes, and beta cell function-related genes were analyzed. Finally, we conducted RT-PCR to verify the expression of these ICGs. Results: In total, pancreatic islets from 19 cases of T2D and 84 healthy subjects were included. We identified 458 DEGs. Six significantly upregulated ICGs (CD44, CD47, HAVCR2, SIRPA, TNFSF9, and VTCN1) in T2D were screened out. These ICGs were significantly correlated with several hub genes and T2D-related genes; furthermore, they were correlated with insulin secretion and β cell function-related genes. The analysis of immune infiltration showed that the concentrations of eosinophils, T cells CD4 naive, and T cells regulatory (Tregs) were significantly higher, but CD4 memory resting T cells and monocytes were lower in islets of T2D patients. The infiltrated immune cells in T2D pancreatic islet were associated with these six ICGs. Finally, the expression levels of four ICGs were confirmed by RT-PCR, and three ICGs were validated in another independent dataset. Conclusion: In conclusion, the identified ICGs may play an important role in T2D. Identification of these differential genes may provide new clues for the diagnosis and treatment of T2D.

Indexed as

bioinformaticsimmune checkpoint genemicroenvironmenttype 2 diabetes

Identifiers

PMID38881696
PMCPMC11179640

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