Evidence mapPaperPMID 39359477Full record

ArticleFrontiers in genetics2024

A combined transcriptomics and proteomics approach reveals S100A4 as a potential biomarker for Graves' orbitopathy.

Chiaw-Ling Chng, Oi Fah Lai, Lay-Leng Seah, Kai-Ling Yong, Yvonne Hsi-Wei Chung, Rochelle Goh, Che Kang Lim

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Article in Frontiers in genetics, 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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2 citing papers in PubMed.

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5 · Who and what money

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7 authors.

Chiaw-Ling ChngDepartment of Endocrinology, Singapore General Hospital, Singapore, Singapore.
Oi Fah LaiDepartment of Clinical and Translational Research, Singapore General Hospital, Singapore, Singapore.
Lay-Leng SeahOculoplastic Department, Singapore National Eye Centre, Singapore, Singapore.
Kai-Ling YongOculoplastic Department, Singapore National Eye Centre, Singapore, Singapore.
Yvonne Hsi-Wei ChungOculoplastic Department, Singapore National Eye Centre, Singapore, Singapore.
Rochelle GohDepartment of Clinical and Translational Research, Singapore General Hospital, Singapore, Singapore.
Che Kang LimDepartment of Clinical and Translational Research, Singapore General Hospital, Singapore, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: There are no reliable biomarkers to identify Graves' disease patients who will develop severe Graves' orbitopathy (GO). We hypothesize that integrating various omics platforms can enhance our understanding of disease mechanisms and uncover potential biomarkers. This study aimed to (1) elucidate the differential gene expression profile of orbital fibroblasts in GO during early adipogenesis to better understand disease mechanisms and (2) compare tear protein profiles from our earlier study and the transcriptome profiles of orbital fibroblasts (OFs) to identify possible biomarkers of the disease. Methods: OFs were grown from orbital adipose tissue obtained from nine GO patients (three for discovery and six for validation experiments). Total RNA was extracted from OFs on day 0 as the baseline for each sample and from differentiated OFs on days 4 and 8. Protein-protein interaction (PPI) analysis and functional enrichment analysis were also carried out. The differentially expressed genes (DEGs) from the RNA sequencing experiments were then compared to the full tear proteome profile from the author's previous study, which examined the tear protein changes of GO patients based on fold change > 1.6 or < -1.6. FDR < 0.05 was applied within all datasets. Further validation of S100 calcium-binding protein A4 (S100A4) downregulation in GO was performed via quantitative real-time PCR (qPCR). Results: The whole transcriptomic analysis revealed 9 upregulated genes and 15 downregulated genes in common between the discovery and validation experiments. From the PPI network analysis, an interaction network containing six identified DEGs (ALDH2, MAP2K6, MT2A, SOCS3, S100A4, and THBD) was observed. The functional enrichment network analysis identified a set of genes related to oxysterol production. S100A4 was found to be consistently downregulated in both our transcriptome studies and the full-tear proteome profile from the author's previous study. Conclusion: Our study identified several DEGs and potential gene pathways in GO patients, which concurred with the results of other studies. Tear S100A4 may serve as a biomarker for the propensity to develop thyroid eye disease (TED) in patients with autoimmune thyroid disease (AITD) before clinical manifestation and should be confirmed in future studies.

Indexed as

Graves’ ophthalmologyGraves’ orbitopathyS100A4tear biomarkerstranscriptome

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PMID39359477
PMCPMC11445072

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