Evidence map›Paper›PMID 39239096›Full record

ArticleFrontiers in endocrinology2024

T-cell exhaustion-related genes in Graves' disease: a comprehensive genome mapping analysis.

Zhengrong Jiang, Huiyao Cai, Yizhao Lin, Ruhai Lin, Lijun Chen, Huibin Huang

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Zhengrong Jiang *Department of Endocrinology, Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China.
Huiyao Cai *Department of Endocrinology, Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China.
Yizhao LinDepartment of Internal Medicine, Gutian County Hospital of Ningde City, Ningde, Fujian, China.
Ruhai LinDepartment of Endocrinology, Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China.
Lijun ChenDepartment of Endocrinology, Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China.
Huibin Huang *Department of Endocrinology, Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: T-cell exhaustion (Tex) can be beneficial in autoimmune diseases, but its role in Graves' disease (GD), an autoimmune disorder of the thyroid, remains unknown. This study investigated Tex-related gene expression in GD patients to discern the potential contributions of these genes to GD pathogenesis and immune regulation. Methods: Through gene landscape analysis, a protein-protein interaction network of 40 Tex-related genes was constructed. mRNA expression levels were compared between GD patients and healthy control (HCs). Unsupervised clustering categorized GD cases into subtypes, revealing distinctions in gene expression, immune cell infiltration, and immune responses. Weighted gene co-expression network analysis and differential gene expression profiling identified potential therapeutic targets. RT-qPCR validation of candidate gene expression was performed using blood samples from 112 GD patients. Correlations between Tex-related gene expression and clinical indicators were analyzed. Results: Extensive Tex-related gene interactions were observed, with six genes displaying aberrant expression in GD patients. This was associated with atypical immune cell infiltration and regulation. Cluster analysis delineated two GD subtypes, revealing notable variations in gene expression and immune responses. Screening efforts identified diverse drug candidates for GD treatment. The Tex-related gene Conclusion: Tex-related genes modulate GD pathogenesis, and their grouping aids subtype differentiation and exploration of therapeutic targets.

Indexed as

Graves DiseaseAdultCase-Control StudiesChromosome MappingFemaleGene Expression ProfilingGene Regulatory NetworksHumansMaleMiddle AgedProtein Interaction MapsProto-Oncogene Proteins c-cblT-Cell ExhaustionT-LymphocytesProto-Oncogene Proteins c-cblCBLenlargement of thyroid glandGraves’ diseaseT-cell exhaustionweighted gene co-expression network analysis

Identifiers

PMID39239096
PMCPMC11374593

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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.