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Bioinformatics analysis of key genes and pathways in Hashimoto thyroiditis tissues
Hashimoto thyroiditis (HT) is one of the most common autoimmune diseases, and the incidence of HT continues to increase. Long-term, uncontrollable HT results in thyroid dysfunction and even increases carcinogenesis risks. Since the origin and development of HT involve many complex immune processes,...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Portland Press Ltd.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374273/ https://www.ncbi.nlm.nih.gov/pubmed/32662826 http://dx.doi.org/10.1042/BSR20200759 |
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author | Zheng, Long Dou, Xiaojie Song, Huijia Wang, Pengwei Qu, Wei Zheng, Xianghong |
author_facet | Zheng, Long Dou, Xiaojie Song, Huijia Wang, Pengwei Qu, Wei Zheng, Xianghong |
author_sort | Zheng, Long |
collection | PubMed |
description | Hashimoto thyroiditis (HT) is one of the most common autoimmune diseases, and the incidence of HT continues to increase. Long-term, uncontrollable HT results in thyroid dysfunction and even increases carcinogenesis risks. Since the origin and development of HT involve many complex immune processes, there is no effective therapy for HT on a pathogenesis level. Although bioinformatics analysis has been utilized to seek key genes and pathways of thyroid cancer, only a few bioinformatics studies that focus on HT pathogenesis and mechanisms have been reported. In the present study, the Gene Expression Omnibus dataset (GSE29315) containing 6 HT and 8 thyroid physiological hyperplasia samples was downloaded, and differentially expressed gene (DEG) analysis, Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, protein–protein interaction analysis, and gene set enrichment analysis were performed. In total, 85 DEGs, containing 76 up-regulated and 9 down-regulated DEGS, were identified. The DEGs were mainly enriched in immune and inflammatory response, and the signaling pathways were involved in cytokine interaction and cytotoxicity. Moreover, ten hub genes were identified, and IFN-γ, IFN-α, IL6/JAK/STAT3, and inflammatory pathways may promote the origin and progression of HT. The present study indicated that exploring DEGs and pathways by bioinformatics analysis has important significance in understanding the molecular mechanisms of HT and providing potential targets for the prevention and treatment of HT. |
format | Online Article Text |
id | pubmed-7374273 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Portland Press Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73742732020-08-04 Bioinformatics analysis of key genes and pathways in Hashimoto thyroiditis tissues Zheng, Long Dou, Xiaojie Song, Huijia Wang, Pengwei Qu, Wei Zheng, Xianghong Biosci Rep Bioinformatics Hashimoto thyroiditis (HT) is one of the most common autoimmune diseases, and the incidence of HT continues to increase. Long-term, uncontrollable HT results in thyroid dysfunction and even increases carcinogenesis risks. Since the origin and development of HT involve many complex immune processes, there is no effective therapy for HT on a pathogenesis level. Although bioinformatics analysis has been utilized to seek key genes and pathways of thyroid cancer, only a few bioinformatics studies that focus on HT pathogenesis and mechanisms have been reported. In the present study, the Gene Expression Omnibus dataset (GSE29315) containing 6 HT and 8 thyroid physiological hyperplasia samples was downloaded, and differentially expressed gene (DEG) analysis, Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, protein–protein interaction analysis, and gene set enrichment analysis were performed. In total, 85 DEGs, containing 76 up-regulated and 9 down-regulated DEGS, were identified. The DEGs were mainly enriched in immune and inflammatory response, and the signaling pathways were involved in cytokine interaction and cytotoxicity. Moreover, ten hub genes were identified, and IFN-γ, IFN-α, IL6/JAK/STAT3, and inflammatory pathways may promote the origin and progression of HT. The present study indicated that exploring DEGs and pathways by bioinformatics analysis has important significance in understanding the molecular mechanisms of HT and providing potential targets for the prevention and treatment of HT. Portland Press Ltd. 2020-07-21 /pmc/articles/PMC7374273/ /pubmed/32662826 http://dx.doi.org/10.1042/BSR20200759 Text en © 2020 The Author(s). https://creativecommons.org/licenses/by/4.0/ This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY). |
spellingShingle | Bioinformatics Zheng, Long Dou, Xiaojie Song, Huijia Wang, Pengwei Qu, Wei Zheng, Xianghong Bioinformatics analysis of key genes and pathways in Hashimoto thyroiditis tissues |
title | Bioinformatics analysis of key genes and pathways in Hashimoto thyroiditis tissues |
title_full | Bioinformatics analysis of key genes and pathways in Hashimoto thyroiditis tissues |
title_fullStr | Bioinformatics analysis of key genes and pathways in Hashimoto thyroiditis tissues |
title_full_unstemmed | Bioinformatics analysis of key genes and pathways in Hashimoto thyroiditis tissues |
title_short | Bioinformatics analysis of key genes and pathways in Hashimoto thyroiditis tissues |
title_sort | bioinformatics analysis of key genes and pathways in hashimoto thyroiditis tissues |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374273/ https://www.ncbi.nlm.nih.gov/pubmed/32662826 http://dx.doi.org/10.1042/BSR20200759 |
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