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Identification of two potential immune-related biomarkers of Graves’ disease based on integrated bioinformatics analyses

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Abstract

Background

Graves’ disease (GD) is an autoimmune disease, the incidence of which is increasing yearly. GD requires long-life therapy. Therefore, the potential immune-related biomarkers of GD need to be studied.

Method

In our study, differentially expressed genes (DEGs) were derived from the online Gene Expression Omnibus (GEO) microarray expression dataset GSE71956. Protein‒protein interaction (PPI) network analyses were used to identify hub genes, which were validated by qPCR. GSEA was used to screen potential pathways and related immune cells. Next, CIBERSORT analysis was used to further explore the immune subtype distribution pattern among hub genes. ROC curves were used to analyze the specificity and sensitivity of hub genes.

Result

44 DEGs were screened from the GEO dataset. Two hub genes, EEF1A1 and EIF4B, were obtained from the PPI network and validated by qPCR (p < 0.05). GSEA was conducted to identify potential pathways and immune cells related to these the two hub genes. Immune cell subtype analysis revealed that hub genes had extensive associations with many different types of immune cells, particularly resting memory CD4+ T cells. AUCs of ROC analysis were 0.687 and 0.733 for EEF1A1 and EIF4B, respectively.

Conclusion

Our study revealed two hub genes, EEF1A1 and EIF4B, that are associated with resting memory CD4+ T cells and potential immune-related molecular biomarkers and therapeutic targets of GD.

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Acknowledgements

Throughout the writing of this dissertation, I have received a great deal of support and assistance. I would first like to thank my supervisor, H.X., whose expertise was invaluable in formulating the research questions and methodology. Your insightful feedback pushed me to sharpen my thinking and brought my work to a higher level. I would particularly like to acknowledge my colleagues J.W., H.Z., B.L., Y.C., F.Q., and J.L. for their wonderful collaboration and patient support.

Funding

This work has been in part supported by the National Natural Science Foundation of China (81773741 and 81973329) and Natural Science Foundation Project of Shanghai (19ZR1440800).

Author information

Author notes

  1. These authors contributed equally: Yihan Zhang, Jia Wei

Authors and Affiliations

  1. Department of Endocrinology and Metabolism, Center for Microbiota and Immunological Diseases, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Haining Road, Shanghai, 200080, China

    Yihan Zhang, Hong Zhou, Bingxin Li, Ying Chen & Huanbai Xu

  2. Wenzhou Medical University, Wenzhou, Zhejiang, 325035, China

    Jia Wei

  3. Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, School of Pharmacy, Shanghai Jiao Tong University, Shanghai, 200240, China

    Feng Qian & Jingting Liu

  4. Department of Endocrinology and Metabolism, Shanghai Traditional Chinese and Medicine Integrated Hospital, 18 Baoding Road, Hongkou District, Shanghai, 200080, China

    Xin Xie

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  1. Yihan Zhang
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Contributions

Y.Z., X.X. and H.X. conceived of and designed the project. J.W., B.L. and F.Q. acquired the data, and Y.C., B.L. and H.Z. analyzed and interpreted the data. Y.Z. and J.W. wrote the paper.

Corresponding authors

Correspondence to Xin Xie or Huanbai Xu.

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Conflict of interest

The authors declare no competing interests.

Ethical approval

This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethical Committee of Shanghai General Hospital (Date 2018-2-27/No 2018KY088).

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Zhang, Y., Wei, J., Zhou, H. et al. Identification of two potential immune-related biomarkers of Graves’ disease based on integrated bioinformatics analyses. Endocrine 78, 306–314 (2022). https://doi.org/10.1007/s12020-022-03156-y

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  • DOI: https://doi.org/10.1007/s12020-022-03156-y

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