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Meta- and cross-species analyses of insulin resistance based on gene expression datasets in human white adipose tissues
Ample evidence indicates that insulin resistance (IR) is closely related to white adipose tissue (WAT), but the underlying mechanisms of IR pathogenesis are still unclear. Using 352 microarray datasets from seven independent studies, we identified a meta-signature which comprised of 1,413 genes. Our...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829071/ https://www.ncbi.nlm.nih.gov/pubmed/29487289 http://dx.doi.org/10.1038/s41598-017-18082-7 |
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author | Jung, Junghyun Kim, Go Woon Lee, Woosuk Mok, Changsoo Chung, Sung Hyun Jang, Wonhee |
author_facet | Jung, Junghyun Kim, Go Woon Lee, Woosuk Mok, Changsoo Chung, Sung Hyun Jang, Wonhee |
author_sort | Jung, Junghyun |
collection | PubMed |
description | Ample evidence indicates that insulin resistance (IR) is closely related to white adipose tissue (WAT), but the underlying mechanisms of IR pathogenesis are still unclear. Using 352 microarray datasets from seven independent studies, we identified a meta-signature which comprised of 1,413 genes. Our meta-signature was also enriched in overall WAT in in vitro and in vivo IR models. Only 12 core enrichment genes were consistently enriched across all IR models. Among the meta-signature, we identified a drug signature made up of 211 genes with expression levels that were co-regulated by thiazolidinediones and metformin using cross-species analysis. To confirm the clinical relevance of our drug signature, we found that the expression levels of 195 genes in the drug signature were significantly correlated with both homeostasis model assessment 2-IR score and body mass index. Finally, 18 genes from the drug signature were identified by protein-protein interaction network cluster. Four core enrichment genes were included in 18 genes and the expression levels of selected 8 genes were validated by quantitative PCR. These findings suggest that our signatures provide a robust set of genetic markers which can be used to provide a starting point for developing potential therapeutic targets in improving IR in WAT. |
format | Online Article Text |
id | pubmed-5829071 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-58290712018-03-01 Meta- and cross-species analyses of insulin resistance based on gene expression datasets in human white adipose tissues Jung, Junghyun Kim, Go Woon Lee, Woosuk Mok, Changsoo Chung, Sung Hyun Jang, Wonhee Sci Rep Article Ample evidence indicates that insulin resistance (IR) is closely related to white adipose tissue (WAT), but the underlying mechanisms of IR pathogenesis are still unclear. Using 352 microarray datasets from seven independent studies, we identified a meta-signature which comprised of 1,413 genes. Our meta-signature was also enriched in overall WAT in in vitro and in vivo IR models. Only 12 core enrichment genes were consistently enriched across all IR models. Among the meta-signature, we identified a drug signature made up of 211 genes with expression levels that were co-regulated by thiazolidinediones and metformin using cross-species analysis. To confirm the clinical relevance of our drug signature, we found that the expression levels of 195 genes in the drug signature were significantly correlated with both homeostasis model assessment 2-IR score and body mass index. Finally, 18 genes from the drug signature were identified by protein-protein interaction network cluster. Four core enrichment genes were included in 18 genes and the expression levels of selected 8 genes were validated by quantitative PCR. These findings suggest that our signatures provide a robust set of genetic markers which can be used to provide a starting point for developing potential therapeutic targets in improving IR in WAT. Nature Publishing Group UK 2018-02-27 /pmc/articles/PMC5829071/ /pubmed/29487289 http://dx.doi.org/10.1038/s41598-017-18082-7 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Jung, Junghyun Kim, Go Woon Lee, Woosuk Mok, Changsoo Chung, Sung Hyun Jang, Wonhee Meta- and cross-species analyses of insulin resistance based on gene expression datasets in human white adipose tissues |
title | Meta- and cross-species analyses of insulin resistance based on gene expression datasets in human white adipose tissues |
title_full | Meta- and cross-species analyses of insulin resistance based on gene expression datasets in human white adipose tissues |
title_fullStr | Meta- and cross-species analyses of insulin resistance based on gene expression datasets in human white adipose tissues |
title_full_unstemmed | Meta- and cross-species analyses of insulin resistance based on gene expression datasets in human white adipose tissues |
title_short | Meta- and cross-species analyses of insulin resistance based on gene expression datasets in human white adipose tissues |
title_sort | meta- and cross-species analyses of insulin resistance based on gene expression datasets in human white adipose tissues |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829071/ https://www.ncbi.nlm.nih.gov/pubmed/29487289 http://dx.doi.org/10.1038/s41598-017-18082-7 |
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