A combined transcriptomics and proteomics approach reveals S100A4 as a potential biomarker for Graves’ orbitopathy - Chng, Chiaw-Ling; Lai, Oi Fah; Seah, Lay-Leng; Yong, Kai-Ling; Chung, Yvonne Hsi-Wei; Goh, Rochelle; Lim, Che Kang (Frontiers in Genetics, 2024)
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.