A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains.
Despite evidence of the clustering of metabolic syndrome components, current approaches for identifying unifying genetic mechanisms typically evaluate clinical categories that do not provide adequate etiological information. Here, we used data from 19,486 European American and 6,287 African American...
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| Language: | English |
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Public Library of Science (PLoS)
2011-10-01
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| Series: | PLoS Genetics |
| Online Access: | https://journals.plos.org/plosgenetics/article/file?id=10.1371/journal.pgen.1002322&type=printable |
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| author | Christy L Avery Qianchuan He Kari E North Jose L Ambite Eric Boerwinkle Myriam Fornage Lucia A Hindorff Charles Kooperberg James B Meigs James S Pankow Sarah A Pendergrass Bruce M Psaty Marylyn D Ritchie Jerome I Rotter Kent D Taylor Lynne R Wilkens Gerardo Heiss Dan Yu Lin |
| author_facet | Christy L Avery Qianchuan He Kari E North Jose L Ambite Eric Boerwinkle Myriam Fornage Lucia A Hindorff Charles Kooperberg James B Meigs James S Pankow Sarah A Pendergrass Bruce M Psaty Marylyn D Ritchie Jerome I Rotter Kent D Taylor Lynne R Wilkens Gerardo Heiss Dan Yu Lin |
| author_sort | Christy L Avery |
| collection | DOAJ |
| description | Despite evidence of the clustering of metabolic syndrome components, current approaches for identifying unifying genetic mechanisms typically evaluate clinical categories that do not provide adequate etiological information. Here, we used data from 19,486 European American and 6,287 African American Candidate Gene Association Resource Consortium participants to identify loci associated with the clustering of metabolic phenotypes. Six phenotype domains (atherogenic dyslipidemia, vascular dysfunction, vascular inflammation, pro-thrombotic state, central obesity, and elevated plasma glucose) encompassing 19 quantitative traits were examined. Principal components analysis was used to reduce the dimension of each domain such that >55% of the trait variance was represented within each domain. We then applied a statistically efficient and computational feasible multivariate approach that related eight principal components from the six domains to 250,000 imputed SNPs using an additive genetic model and including demographic covariates. In European Americans, we identified 606 genome-wide significant SNPs representing 19 loci. Many of these loci were associated with only one trait domain, were consistent with results in African Americans, and overlapped with published findings, for instance central obesity and FTO. However, our approach, which is applicable to any set of interval scale traits that is heritable and exhibits evidence of phenotypic clustering, identified three new loci in or near APOC1, BRAP, and PLCG1, which were associated with multiple phenotype domains. These pleiotropic loci may help characterize metabolic dysregulation and identify targets for intervention. |
| format | Article |
| id | doaj-art-dcb9a64f4ecd47e4a6fe661e5f5ddea0 |
| institution | OA Journals |
| issn | 1553-7390 1553-7404 |
| language | English |
| publishDate | 2011-10-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Genetics |
| spelling | doaj-art-dcb9a64f4ecd47e4a6fe661e5f5ddea02025-08-20T02:05:36ZengPublic Library of Science (PLoS)PLoS Genetics1553-73901553-74042011-10-01710e100232210.1371/journal.pgen.1002322A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains.Christy L AveryQianchuan HeKari E NorthJose L AmbiteEric BoerwinkleMyriam FornageLucia A HindorffCharles KooperbergJames B MeigsJames S PankowSarah A PendergrassBruce M PsatyMarylyn D RitchieJerome I RotterKent D TaylorLynne R WilkensGerardo HeissDan Yu LinDespite evidence of the clustering of metabolic syndrome components, current approaches for identifying unifying genetic mechanisms typically evaluate clinical categories that do not provide adequate etiological information. Here, we used data from 19,486 European American and 6,287 African American Candidate Gene Association Resource Consortium participants to identify loci associated with the clustering of metabolic phenotypes. Six phenotype domains (atherogenic dyslipidemia, vascular dysfunction, vascular inflammation, pro-thrombotic state, central obesity, and elevated plasma glucose) encompassing 19 quantitative traits were examined. Principal components analysis was used to reduce the dimension of each domain such that >55% of the trait variance was represented within each domain. We then applied a statistically efficient and computational feasible multivariate approach that related eight principal components from the six domains to 250,000 imputed SNPs using an additive genetic model and including demographic covariates. In European Americans, we identified 606 genome-wide significant SNPs representing 19 loci. Many of these loci were associated with only one trait domain, were consistent with results in African Americans, and overlapped with published findings, for instance central obesity and FTO. However, our approach, which is applicable to any set of interval scale traits that is heritable and exhibits evidence of phenotypic clustering, identified three new loci in or near APOC1, BRAP, and PLCG1, which were associated with multiple phenotype domains. These pleiotropic loci may help characterize metabolic dysregulation and identify targets for intervention.https://journals.plos.org/plosgenetics/article/file?id=10.1371/journal.pgen.1002322&type=printable |
| spellingShingle | Christy L Avery Qianchuan He Kari E North Jose L Ambite Eric Boerwinkle Myriam Fornage Lucia A Hindorff Charles Kooperberg James B Meigs James S Pankow Sarah A Pendergrass Bruce M Psaty Marylyn D Ritchie Jerome I Rotter Kent D Taylor Lynne R Wilkens Gerardo Heiss Dan Yu Lin A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains. PLoS Genetics |
| title | A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains. |
| title_full | A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains. |
| title_fullStr | A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains. |
| title_full_unstemmed | A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains. |
| title_short | A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains. |
| title_sort | phenomics based strategy identifies loci on apoc1 brap and plcg1 associated with metabolic syndrome phenotype domains |
| url | https://journals.plos.org/plosgenetics/article/file?id=10.1371/journal.pgen.1002322&type=printable |
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