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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...

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Autores principales: Park, Peter J., Kong, Sek Won, Tebaldi, Toma, Lai, Weil R., Kasif, Simon, Kohane, Isaac S.
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2009
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
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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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