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...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Oxford University Press
2012
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| Online Access: | http://hdl.handle.net/1721.1/72972 |
| _version_ | 1826191019943657472 |
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| author | Park, Peter J. Kong, Sek Won Tebaldi, Toma Lai, Weil R. Kasif, Simon Kohane, Isaac |
| author2 | Harvard University--MIT Division of Health Sciences and Technology |
| author_facet | Harvard University--MIT Division of Health Sciences and Technology Park, Peter J. Kong, Sek Won Tebaldi, Toma Lai, Weil R. Kasif, Simon Kohane, Isaac |
| author_sort | Park, Peter J. |
| collection | MIT |
| 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. |
| first_indexed | 2024-09-23T08:48:51Z |
| format | Article |
| id | mit-1721.1/72972 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T08:48:51Z |
| publishDate | 2012 |
| publisher | Oxford University Press |
| record_format | dspace |
| spelling | mit-1721.1/729722022-09-30T11:27:51Z 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 Harvard University--MIT Division of Health Sciences and Technology Park, Peter J. Park, Peter J. Kong, Sek Won Kasif, Simon Kohane, Isaac 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. National Institutes of Health (U.S.) (Roadmap for Medical Research, grant U54LM008748) 2012-09-14T18:19:48Z 2012-09-14T18:19:48Z 2009-09 2009-09 Article http://purl.org/eprint/type/JournalArticle 1460-2059 1367-4803 http://hdl.handle.net/1721.1/72972 Park, P. J. et al. “Integration of Heterogeneous Expression Data Sets Extends the Role of the Retinol Pathway in Diabetes and Insulin Resistance.” Bioinformatics 25.23 (2009): 3121–3127. Web. en_US http://dx.doi.org/10.1093/bioinformatics/btp559 Bioinformatics Creative Commons Attribution Non-Commercial http://creativecommons.org/licenses/by-nc/2.5 application/pdf Oxford University Press Oxford |
| spellingShingle | Park, Peter J. Kong, Sek Won Tebaldi, Toma Lai, Weil R. Kasif, Simon Kohane, Isaac 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 |
| url | http://hdl.handle.net/1721.1/72972 |
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