We are analyzing https://link.springer.com/article/10.1007/s42000-025-00668-w.

Title:
Hub genes and key pathways of Graves’ disease: bioinformatics analysis and validation | Hormones
Description:
Objective This study aims to identify hub genes associated with the onset and progression of Graves’ disease (GD) with the goal of developing novel biomarkers to enhance diagnosis and improve patient outcomes. Methods mRNA profiles from thyroid tissue samples (24 GD vs. 24 normal controls) were obtained from GEO (GSE9340), ArrayExpress (E-MEXP-2612), and GTEx (Thyroid dataset). After batch correction via SVA algorithm, 366 differentially expressed genes (DEGs) were identified using limma. Functional enrichment, protein-protein interaction networks, and immune microenvironment analysis were performed. Hub genes were validated in clinical thyroid specimens (3 GD vs. 3 controls) using RT-qPCR. Results A total of 366 DEGs were identified in the diseased and normal groups. Among these, eight hub genes (TYROBP, CSF1R, CD163, ITGAM, CD86, FCGR3B, ITGB2, and IL10RA) showed strong correlations with immune cell content. These genes were predominantly enriched in pathways related to amino acid metabolism, viral protein interactions with cytokines and cytokine receptors, phagosome, chemokine signaling, programmed cell death, NF-κB, and other pathways. Additionally, these hub genes were linked to 39 regulatory factors. mRNA levels of these hub genes were validated in clinical samples through RT-qPCR. It is noteworthy that eight genes were found to be upregulated in GD samples. Conclusion The study highlights the potential impact of ITGB 2, TYROBP, CSF1R, CD163, ITGAM, CD86, FCGR3B, and IL10RA on the development and progression of GD, supporting their role as potential biomarkers.
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pubmed, article, google, scholar, cas, disease, graves, thyroid, central, genes, analysis, zhang, immunol, supplementary, material, hub, study, cell, expression, front, httpsdoiorg, autoimmune, data, pathways, validation, patients, gene, httpsdoiorgs, endocrinol, cells, content, key, access, identification, httpsdoiorgfimmu, chen, privacy, cookies, consent, bioinformatics, manuscript, biomarkers, mrna, gtex, clinical, csfr, cancer, datasets, author, clin,

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electronic supplementary material month download article/chapter protein-protein interaction networks cartilage antibody-induced arthritis anti-neutrophil cytoplasmic antibody studies utilizing pre-existing gene expression omnibus holds exclusive rights key immune-related genes gov/geo/query/acc acc=gse9340 e-mexp-2612 embl-ebi/arrayexpress guidelines full article pdf autoimmune thyroid diseases bioinformatic analysis revealed graves’ ophthalmopathy–support article hormones aims duan-rong zhuang mrna expression characteristic mrna expression profile cardiac calsequestrin gene potential immune-related biomarkers ccl20/ccr6 chemokine signaling privacy choices/manage cookies essential regulatory genes programmed cell death genotype-tissue expression tissue macrophage populations immune cell content article zhuang autoimmune thyroid disease machine learning orbital adipose tissues original studies contributing immune microenvironment analysis papillary thyroid carcinoma thyroid antigen-reactive public dataset usage bioinformatic analysis autoimmune disease genes related subjects thyroid eye disease conditions privacy policy gene polymorphisms protein structure prediction identify hub genes clinical thyroid specimens european economic area showed strong correlations amino acid metabolism

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         description:This study aims to identify hub genes associated with the onset and progression of Graves’ disease (GD) with the goal of developing novel biomarkers to enhance diagnosis and improve patient outcomes. mRNA profiles from thyroid tissue samples (24 GD vs. 24 normal controls) were obtained from GEO (GSE9340), ArrayExpress (E-MEXP-2612), and GTEx (Thyroid dataset). After batch correction via SVA algorithm, 366 differentially expressed genes (DEGs) were identified using limma. Functional enrichment, protein-protein interaction networks, and immune microenvironment analysis were performed. Hub genes were validated in clinical thyroid specimens (3 GD vs. 3 controls) using RT-qPCR. A total of 366 DEGs were identified in the diseased and normal groups. Among these, eight hub genes (TYROBP, CSF1R, CD163, ITGAM, CD86, FCGR3B, ITGB2, and IL10RA) showed strong correlations with immune cell content. These genes were predominantly enriched in pathways related to amino acid metabolism, viral protein interactions with cytokines and cytokine receptors, phagosome, chemokine signaling, programmed cell death, NF-κB, and other pathways. Additionally, these hub genes were linked to 39 regulatory factors. mRNA levels of these hub genes were validated in clinical samples through RT-qPCR. It is noteworthy that eight genes were found to be upregulated in GD samples. The study highlights the potential impact of ITGB 2, TYROBP, CSF1R, CD163, ITGAM, CD86, FCGR3B, and IL10RA on the development and progression of GD, supporting their role as potential biomarkers.
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