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Graves’ Disease and Its Related Single Nucleotide Polymorphisms and Genes

Authors: Yuhong Lu

Abstract:

Graves’ Disease (GD), an autoimmune health condition caused by the over reactiveness of the thyroid, affects about 1 in 200 people worldwide. GD is not caused by one specific single nucleotide polymorphism (SNP) or gene mutation, but rather determined by multiple factors, each differing from each other. Malfunction of the genes in Human Leukocyte Antigen (HLA) family tend to play a major role in autoimmune diseases, but other genes, such as LOC101929163, have functions that still remain ambiguous. Currently, little studies were done to study GD, resulting in inconclusive results. This study serves not only to introduce background knowledge about GD, but also to organize and pinpoint the major SNPs and genes that are potentially related to the occurrence of GD in humans. Collected from multiple sources from genome-wide association studies (GWAS) Central, the potential SNPs related to the causes of GD are included in this study. This study has located the genes that are related to those SNPs and closely examines a selected sample. Using the data from this study, scientists will then be able to focus on the most expressed genes in GD patients and develop a treatment for GD.

Keywords: CTLA4, Graves’ Disease, HLA, single nucleotide polymorphism, SNP.

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References:


[1] Bucci, Ines et al. Thyroid-Stimulating Hormone Receptor Antibodies in Pregnancy: Clinical Relevance. Frontiers in endocrinology vol. 8 137. 30 Jun. 2017, doi:10.3389/fendo.2017.00137
[2] Database, GeneCards Human Gene. “GeneCards®: The Human Gene Database.” GeneCards, www.genecards.org/.
[3] Graves disease - Genetics Home Reference - NIH. (n.d.). Retrieved August 27, 2020, from https://ghr.nlm.nih.gov/condition/graves-disease
[4] Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using Bioinformatics Resources. Nature Protoc. 2009;4(1):44-57.
[5] Huang DW, Sherman BT, Lempicki RA. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 2009;37(1):1-13.
[6] Jacobson, Eric M, and Yaron Tomer. “The CD40, CTLA-4, thyroglobulin, TSH receptor, and PTPN22 gene quintet and its contribution to thyroid autoimmunity: back to the future.” Journal of autoimmunity vol. 28,2-3 (2007): 85-98. doi:10.1016/j.jaut.2007.02.006
[7] Kent WJ, Sugnet CW, Furey TS, Roskin KM, Pringle TH, Zahler AM, Haussler D. The human genome browser at UCSC. Genome Res. 2002 Jun;12(6):996-1006.
[8] Lee CM, Barber GP, Casper J, et al. UCSC Genome Browser enters 20th year. Nucleic Acids Res. 2020;48(D1):D756-D761. doi:10.1093/nar/gkz1012
[9] Leemans C, van der Zwalm MCH, Brueckner L, et al. Promoter-Intrinsic and Local Chromatin Features Determine Gene Repression in LADs. Cell. 2019;177(4):852-864.e14. doi:10.1016/j.cell.2019.03.009
[10] Li J, Teng W, Yu Y, Hou X, Shan Z. Linkage Analysis of the Chromosome 5q31-33 Region Identifies JAKMIP2 as a Risk Factor for Graves' Disease in the Chinese Han Population. Medical Science Monitor: International Medical Journal of Experimental and Clinical Research. 2019 Feb;25:1439-1451. DOI: 10.12659/msm.911489.
[11] National Center for Biotechnology Information (NCBI)(Internet). Bethesda (MD): National Library of Medicine (US), National Center for Biotechnology Information; (1988) – (cited 2021 Jul 06). Available from: https://www.ncbi.nlm.nih.gov/
[12] PCAWG Transcriptome Core Group, Calabrese C, Davidson NR, et al. Genomic basis for RNA alterations in cancer. Nature. 2020;578(7793):129-136. doi:10.1038/s41586-020-1970-0
[13] Ross DS, et al. 2016 American Thyroid Association guidelines for diagnosis and management of hyperthyroidism and other causes of thyrotoxicosis. Thyroid. 2016; doi:10.1089/thy.2016.0229
[14] SNP Annotation Tool, www.snp-nexus.org/v4/.
[15] Szklarczyk D, Gable AL, Lyon D, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47(D1):D607-D613. doi:10.1093/nar/gky1131
[16] Szumilas M. Explaining odds ratios (published correction appears in J Can Acad Child Adolesc Psychiatry. 2015 Winter;24(1):58). J Can Acad Child Adolesc Psychiatry. 2010;19(3):227-229.
[17] Tai X, Van Laethem F, Pobezinsky L, et al. Basis of CTLA-4 function in regulatory and conventional CD4(+) T cells. Blood. 2012 May;119(22):5155-5163. DOI: 10.1182/blood-2011-11-388918.
[18] Beck, T., T. Shorter, and A. J. Brookes. "Nucleic Acids Research." GWAS Central: A Comprehensive Resource for the Discovery and Comparison of Genotype and Phenotype Data from Genome-wide Association Studies. 2020. Web. 07 July 2021.
[19] Zhang W, Bojorquez-Gomez A, Velez DO, et al. A global transcriptional network connecting noncoding mutations to changes in tumor gene expression. Nat Genet. 2018;50(4):613-620. doi:10.1038/s41588-018-0091-2