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Integration of heterogeneous expression data sets extends the role of the retinol pathway in diabetes and insulin resistance
Motivation: Type 2 diabetes is a chronic metabolic disease that involves both environmental and genetic factors. To understand the genetics of type 2 diabetes and insulin resistance, the DIabetes Genome Anatomy Project (DGAP) was launched to profile gene expression in a variety of related animal mod...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2778339/ https://www.ncbi.nlm.nih.gov/pubmed/19786482 http://dx.doi.org/10.1093/bioinformatics/btp559 |
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author | Park, Peter J. Kong, Sek Won Tebaldi, Toma Lai, Weil R. Kasif, Simon Kohane, Isaac S. |
author_facet | Park, Peter J. Kong, Sek Won Tebaldi, Toma Lai, Weil R. Kasif, Simon Kohane, Isaac S. |
author_sort | Park, Peter J. |
collection | PubMed |
description | Motivation: Type 2 diabetes is a chronic metabolic disease that involves both environmental and genetic factors. To understand the genetics of type 2 diabetes and insulin resistance, the DIabetes Genome Anatomy Project (DGAP) was launched to profile gene expression in a variety of related animal models and human subjects. We asked whether these heterogeneous models can be integrated to provide consistent and robust biological insights into the biology of insulin resistance. Results: We perform integrative analysis of the 16 DGAP data sets that span multiple tissues, conditions, array types, laboratories, species, genetic backgrounds and study designs. For each data set, we identify differentially expressed genes compared with control. Then, for the combined data, we rank genes according to the frequency with which they were found to be statistically significant across data sets. This analysis reveals RetSat as a widely shared component of mechanisms involved in insulin resistance and sensitivity and adds to the growing importance of the retinol pathway in diabetes, adipogenesis and insulin resistance. Top candidates obtained from our analysis have been confirmed in recent laboratory studies. Contact: Isaac_kohane@harvard.edu |
format | Text |
id | pubmed-2778339 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-27783392009-11-18 Integration of heterogeneous expression data sets extends the role of the retinol pathway in diabetes and insulin resistance Park, Peter J. Kong, Sek Won Tebaldi, Toma Lai, Weil R. Kasif, Simon Kohane, Isaac S. Bioinformatics Original Papers Motivation: Type 2 diabetes is a chronic metabolic disease that involves both environmental and genetic factors. To understand the genetics of type 2 diabetes and insulin resistance, the DIabetes Genome Anatomy Project (DGAP) was launched to profile gene expression in a variety of related animal models and human subjects. We asked whether these heterogeneous models can be integrated to provide consistent and robust biological insights into the biology of insulin resistance. Results: We perform integrative analysis of the 16 DGAP data sets that span multiple tissues, conditions, array types, laboratories, species, genetic backgrounds and study designs. For each data set, we identify differentially expressed genes compared with control. Then, for the combined data, we rank genes according to the frequency with which they were found to be statistically significant across data sets. This analysis reveals RetSat as a widely shared component of mechanisms involved in insulin resistance and sensitivity and adds to the growing importance of the retinol pathway in diabetes, adipogenesis and insulin resistance. Top candidates obtained from our analysis have been confirmed in recent laboratory studies. Contact: Isaac_kohane@harvard.edu Oxford University Press 2009-12-01 2009-09-28 /pmc/articles/PMC2778339/ /pubmed/19786482 http://dx.doi.org/10.1093/bioinformatics/btp559 Text en © The Author(s) 2009. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Papers Park, Peter J. Kong, Sek Won Tebaldi, Toma Lai, Weil R. Kasif, Simon Kohane, Isaac S. Integration of heterogeneous expression data sets extends the role of the retinol pathway in diabetes and insulin resistance |
title | Integration of heterogeneous expression data sets extends the role of the retinol pathway in diabetes and insulin resistance |
title_full | Integration of heterogeneous expression data sets extends the role of the retinol pathway in diabetes and insulin resistance |
title_fullStr | Integration of heterogeneous expression data sets extends the role of the retinol pathway in diabetes and insulin resistance |
title_full_unstemmed | Integration of heterogeneous expression data sets extends the role of the retinol pathway in diabetes and insulin resistance |
title_short | Integration of heterogeneous expression data sets extends the role of the retinol pathway in diabetes and insulin resistance |
title_sort | integration of heterogeneous expression data sets extends the role of the retinol pathway in diabetes and insulin resistance |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2778339/ https://www.ncbi.nlm.nih.gov/pubmed/19786482 http://dx.doi.org/10.1093/bioinformatics/btp559 |
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