Evidence map›Paper›PMID 40022006›Full record

ArticleBMC immunology2025

Identification of BTK as an immune-related biomarker for Hashimoto's thyroiditis by integrated bioinformatic analysis.

Yingzhao Liu, Zhangwei Zhu, Qian Xu, Juan Xu, Jie Xing, Shengjun Wang, Huiyong Peng

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PubMed Full text at PMC Publisher
In one paragraph

Article in BMC 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

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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

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5 · Who and what money

Authors and funding

7 authors.

Yingzhao Liu *Department of Endocrinology, The Affiliated People's Hospital of Jiangsu University, Zhenjiang Medical School of Nanjing Medical University, Zhenjiang, 212002, China.
Zhangwei Zhu *Department of Endocrinology, The Affiliated People's Hospital of Jiangsu University, Zhenjiang Medical School of Nanjing Medical University, Zhenjiang, 212002, China.
Qian Xu *Department of Endocrinology, The Affiliated People's Hospital of Jiangsu University, Zhenjiang Medical School of Nanjing Medical University, Zhenjiang, 212002, China.
Juan XuDepartment of Critical Care Medicine, The Affiliated People's Hospital of Jiangsu University, Zhenjiang Medical School of Nanjing Medical University, Zhenjiang, 212002, China.
Jie XingDepartment of Laboratory Medicine, The Affiliated People's Hospital of Jiangsu University, Zhenjiang Medical School of Nanjing Medical University, Zhenjiang, 212002, China.
Shengjun WangDepartment of Laboratory Medicine, The Affiliated People's Hospital of Jiangsu University, Zhenjiang Medical School of Nanjing Medical University, Zhenjiang, 212002, China. sjwjs@ujs.edu.cn.
Huiyong PengDepartment of Laboratory Medicine, The Affiliated People's Hospital of Jiangsu University, Zhenjiang Medical School of Nanjing Medical University, Zhenjiang, 212002, China. penghuiyong33815@163.com.

Funding

Jiangsu Provincial Medical Key Discipline Cultivation Unit JSDW202241Research Project of Jiangsu Commission of Health H2023053Research Project of Jiangsu Commission of Health ZD2021049Science and Technology Planning Social Development Project of Zhenjiang City SH2023006Science and Technology Planning Social Development Project of Zhenjiang City SH2023008
6 · The paper itself

Abstract

backgroundHashimoto's thyroiditis (HT) is one of the most common autoimmune disorders characterized by diffuse enlargement of the thyroid gland, lymphocyte infiltration, and thyroid-specific autoantibodies. Cellular and humoral immune disorders have been implicated in the development of HT. However, little is known regarding the role of immune-related molecules in HT. This study was aimed to identify key immune-related biomarkers in HT by using bioinformatic analysis.

methodIntegration of the sequencing data from HT and normal control (NC) in the GSA and GTEx databases yielded a dataset named NGS. The GSE138198 dataset from the GEO database was downloaded as a validation set. WGCNA analysis was performed to identify key modules associated with HT. Lasso regression analysis (LASSO) and random forest (RF) were performed to determine potential diagnostic biomarkers. The potential value was assessed by using receiver operating characteristic (ROC) curve analysis. CIBERSORT algorithm was used to evaluate the infiltration of immune cells in HT and NC samples. The transcript levels of verified genes from expanded samples were detected by quantitative real-time PCR.

resultsA total of 1,401 differentially expressed genes (DEGs) were identified in HT patients. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses indicated that these DEGs were predominantly enriched in immune-related pathways. Furthermore, 192 immune-related genes were identified in HT through the intersection of WGCNA modules, DEGs, and the IRGs. Among them, two upregulated genes ((Bruton's tyrosine kinase, BTK) and CD19) showed the potential diagnostic value for HT by using machine learning. The ROC curve analysis revealed that BTK had a higher diagnostic value than CD19 across two datasets. Intriguingly, only BTK expression was upregulated in the peripheral blood mononuclear cells of HT patients, and was significantly positively correlated with the serum levels of thyroid autoantibodies. Further studies confirmed a significant positive correlation between BTK and increased proportions of plasma cells in HT patients.

conclusionThis study identified BTK was significantly increased in HT patients, which might be the involved in the pathogenesis of HT by regulating plasma cells and represented a potential immune-related biomarker of HT.

Indexed as

Agammaglobulinaemia Tyrosine KinaseHashimoto DiseaseBiomarkersComputational BiologyDatabases, GeneticGene Expression ProfilingGene Regulatory NetworksHumansROC CurveAgammaglobulinaemia Tyrosine KinaseBiomarkersBTK protein, humanBioinformatics analysisBTKHashimoto’s thyroiditisImmune cellsImmune-related biomarkerMachine learning

Identifiers

PMID40022006
PMCPMC11869739

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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.