Use of Genome-Wide Expression Data to Mine the "Gray Zone" of GWA Studies Leads to Novel Candidate Obesity Genes
To get beyond the “low-hanging fruits” so far identified by genome-wide association (GWA) studies, new methods must be developed in order to discover the numerous remaining genes that estimates of heritability indicate should be contributing to complex human phenotypes, such as obesity. Here we desc...
| Main Authors: | , , , , , , , , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Public Library of Science
2011
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| Online Access: | http://hdl.handle.net/1721.1/60388 |
| _version_ | 1826190042564919296 |
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| author | Peltonen, Leena Naukkarinen, Jussi Surakka, Ida Pietiläinen, Kirsi H. Rissanen, Aila Salomaa, Veikko Ripatti, Samuli Yki-Järvinen, Hannele van Duijn, Cornelia M. Wichmann, H.-Erich Kaprio, Jaakko Taskinen, Marja-Riitta ENGAGE Consortium |
| author2 | Broad Institute of MIT and Harvard |
| author_facet | Broad Institute of MIT and Harvard Peltonen, Leena Naukkarinen, Jussi Surakka, Ida Pietiläinen, Kirsi H. Rissanen, Aila Salomaa, Veikko Ripatti, Samuli Yki-Järvinen, Hannele van Duijn, Cornelia M. Wichmann, H.-Erich Kaprio, Jaakko Taskinen, Marja-Riitta ENGAGE Consortium |
| author_sort | Peltonen, Leena |
| collection | MIT |
| description | To get beyond the “low-hanging fruits” so far identified by genome-wide association (GWA) studies, new methods must be developed in order to discover the numerous remaining genes that estimates of heritability indicate should be contributing to complex human phenotypes, such as obesity. Here we describe a novel integrative method for complex disease gene identification utilizing both genome-wide transcript profiling of adipose tissue samples and consequent analysis of genome-wide association data generated in large SNP scans. We infer causality of genes with obesity by employing a unique set of monozygotic twin pairs discordant for BMI (n = 13 pairs, age 24–28 years, 15.4 kg mean weight difference) and contrast the transcript profiles with those from a larger sample of non-related adult individuals (N = 77). Using this approach, we were able to identify 27 genes with possibly causal roles in determining the degree of human adiposity. Testing for association of SNP variants in these 27 genes in the population samples of the large ENGAGE consortium (N = 21,000) revealed a significant deviation of P-values from the expected (P = 4×10−4). A total of 13 genes contained SNPs nominally associated with BMI. The top finding was blood coagulation factor F13A1 identified as a novel obesity gene also replicated in a second GWA set of ~2,000 individuals. This study presents a new approach to utilizing gene expression studies for informing choice of candidate genes for complex human phenotypes, such as obesity. |
| first_indexed | 2024-09-23T08:34:08Z |
| format | Article |
| id | mit-1721.1/60388 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T08:34:08Z |
| publishDate | 2011 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | mit-1721.1/603882022-09-30T09:39:18Z Use of Genome-Wide Expression Data to Mine the "Gray Zone" of GWA Studies Leads to Novel Candidate Obesity Genes Peltonen, Leena Naukkarinen, Jussi Surakka, Ida Pietiläinen, Kirsi H. Rissanen, Aila Salomaa, Veikko Ripatti, Samuli Yki-Järvinen, Hannele van Duijn, Cornelia M. Wichmann, H.-Erich Kaprio, Jaakko Taskinen, Marja-Riitta ENGAGE Consortium Broad Institute of MIT and Harvard Peltonen, Leena Peltonen, Leena To get beyond the “low-hanging fruits” so far identified by genome-wide association (GWA) studies, new methods must be developed in order to discover the numerous remaining genes that estimates of heritability indicate should be contributing to complex human phenotypes, such as obesity. Here we describe a novel integrative method for complex disease gene identification utilizing both genome-wide transcript profiling of adipose tissue samples and consequent analysis of genome-wide association data generated in large SNP scans. We infer causality of genes with obesity by employing a unique set of monozygotic twin pairs discordant for BMI (n = 13 pairs, age 24–28 years, 15.4 kg mean weight difference) and contrast the transcript profiles with those from a larger sample of non-related adult individuals (N = 77). Using this approach, we were able to identify 27 genes with possibly causal roles in determining the degree of human adiposity. Testing for association of SNP variants in these 27 genes in the population samples of the large ENGAGE consortium (N = 21,000) revealed a significant deviation of P-values from the expected (P = 4×10−4). A total of 13 genes contained SNPs nominally associated with BMI. The top finding was blood coagulation factor F13A1 identified as a novel obesity gene also replicated in a second GWA set of ~2,000 individuals. This study presents a new approach to utilizing gene expression studies for informing choice of candidate genes for complex human phenotypes, such as obesity. Seventh Framework Programme (European Commission) (FP7/2007-2013) ENGAGE Consortium (grant agreement HEALTH-F4-2007-201413) 2011-01-06T22:17:58Z 2011-01-06T22:17:58Z 2010-06 2009-11 Article http://purl.org/eprint/type/JournalArticle 1553-7404 1553-7390 http://hdl.handle.net/1721.1/60388 Naukkarinen, Jussi et al. “Use of Genome-Wide Expression Data to Mine the “Gray Zone” of GWA Studies Leads to Novel Candidate Obesity Genes.” PLoS Genet 6.6 (2010): e1000976. en_US http://dx.doi.org/10.1371/journal.pgen.1000976 PLoS Genetics Creative Commons Attribution http://creativecommons.org/licenses/by/2.5/ application/pdf Public Library of Science PLoS |
| spellingShingle | Peltonen, Leena Naukkarinen, Jussi Surakka, Ida Pietiläinen, Kirsi H. Rissanen, Aila Salomaa, Veikko Ripatti, Samuli Yki-Järvinen, Hannele van Duijn, Cornelia M. Wichmann, H.-Erich Kaprio, Jaakko Taskinen, Marja-Riitta ENGAGE Consortium Use of Genome-Wide Expression Data to Mine the "Gray Zone" of GWA Studies Leads to Novel Candidate Obesity Genes |
| title | Use of Genome-Wide Expression Data to Mine the "Gray Zone" of GWA Studies Leads to Novel Candidate Obesity Genes |
| title_full | Use of Genome-Wide Expression Data to Mine the "Gray Zone" of GWA Studies Leads to Novel Candidate Obesity Genes |
| title_fullStr | Use of Genome-Wide Expression Data to Mine the "Gray Zone" of GWA Studies Leads to Novel Candidate Obesity Genes |
| title_full_unstemmed | Use of Genome-Wide Expression Data to Mine the "Gray Zone" of GWA Studies Leads to Novel Candidate Obesity Genes |
| title_short | Use of Genome-Wide Expression Data to Mine the "Gray Zone" of GWA Studies Leads to Novel Candidate Obesity Genes |
| title_sort | use of genome wide expression data to mine the gray zone of gwa studies leads to novel candidate obesity genes |
| url | http://hdl.handle.net/1721.1/60388 |
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