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author Kraja, Aldi T.
Vaidya, Dhananjay
Pankow, James S.
Goodarzi, Mark O.
Assimes, Themistocles L.
Kullo, Iftikhar J.
Sovio, Ulla
Mathias, Rasika A.
Sun, Yan V.
Franceschini, Nora
Absher, Devin
Li, Guo
Zhang, Qunyuan
Feitosa, Mary F.
Glazer, Nicole L.
Haritunians, Talin
Hartikainen, Anna-Liisa
Knowles, Joshua W.
North, Kari E.
Iribarren, Carlos
Kral, Brian
Yanek, Lisa
O’Reilly, Paul F.
McCarthy, Mark I.
Jaquish, Cashell
Couper, David J.
Chakravarti, Aravinda
Psaty, Bruce M.
Becker, Lewis C.
Province, Michael A.
Boerwinkle, Eric
Quertermous, Thomas
Palotie, Leena
Jarvelin, Marjo-Riitta
Becker, Diane M.
Kardia, Sharon L.R.
Rotter, Jerome I.
Chen, Yii-Der Ida
Borecki, Ingrid B.
author_facet Kraja, Aldi T.
Vaidya, Dhananjay
Pankow, James S.
Goodarzi, Mark O.
Assimes, Themistocles L.
Kullo, Iftikhar J.
Sovio, Ulla
Mathias, Rasika A.
Sun, Yan V.
Franceschini, Nora
Absher, Devin
Li, Guo
Zhang, Qunyuan
Feitosa, Mary F.
Glazer, Nicole L.
Haritunians, Talin
Hartikainen, Anna-Liisa
Knowles, Joshua W.
North, Kari E.
Iribarren, Carlos
Kral, Brian
Yanek, Lisa
O’Reilly, Paul F.
McCarthy, Mark I.
Jaquish, Cashell
Couper, David J.
Chakravarti, Aravinda
Psaty, Bruce M.
Becker, Lewis C.
Province, Michael A.
Boerwinkle, Eric
Quertermous, Thomas
Palotie, Leena
Jarvelin, Marjo-Riitta
Becker, Diane M.
Kardia, Sharon L.R.
Rotter, Jerome I.
Chen, Yii-Der Ida
Borecki, Ingrid B.
author_sort Kraja, Aldi T.
collection PubMed
description OBJECTIVE: The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS. RESEARCH DESIGN AND METHODS: Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of ∼2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected. RESULTS: Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from ∼9% of the variance in triglycerides, 5.8% of high-density lipoprotein cholesterol, 3.6% of fasting glucose, and 1.4% of systolic blood pressure. CONCLUSIONS: Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants.
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spelling pubmed-30641072012-04-01 A Bivariate Genome-Wide Approach to Metabolic Syndrome: STAMPEED Consortium Kraja, Aldi T. Vaidya, Dhananjay Pankow, James S. Goodarzi, Mark O. Assimes, Themistocles L. Kullo, Iftikhar J. Sovio, Ulla Mathias, Rasika A. Sun, Yan V. Franceschini, Nora Absher, Devin Li, Guo Zhang, Qunyuan Feitosa, Mary F. Glazer, Nicole L. Haritunians, Talin Hartikainen, Anna-Liisa Knowles, Joshua W. North, Kari E. Iribarren, Carlos Kral, Brian Yanek, Lisa O’Reilly, Paul F. McCarthy, Mark I. Jaquish, Cashell Couper, David J. Chakravarti, Aravinda Psaty, Bruce M. Becker, Lewis C. Province, Michael A. Boerwinkle, Eric Quertermous, Thomas Palotie, Leena Jarvelin, Marjo-Riitta Becker, Diane M. Kardia, Sharon L.R. Rotter, Jerome I. Chen, Yii-Der Ida Borecki, Ingrid B. Diabetes Genetics OBJECTIVE: The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS. RESEARCH DESIGN AND METHODS: Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of ∼2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected. RESULTS: Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from ∼9% of the variance in triglycerides, 5.8% of high-density lipoprotein cholesterol, 3.6% of fasting glucose, and 1.4% of systolic blood pressure. CONCLUSIONS: Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants. American Diabetes Association 2011-04 2011-03-22 /pmc/articles/PMC3064107/ /pubmed/21386085 http://dx.doi.org/10.2337/db10-1011 Text en © 2011 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details.
spellingShingle Genetics
Kraja, Aldi T.
Vaidya, Dhananjay
Pankow, James S.
Goodarzi, Mark O.
Assimes, Themistocles L.
Kullo, Iftikhar J.
Sovio, Ulla
Mathias, Rasika A.
Sun, Yan V.
Franceschini, Nora
Absher, Devin
Li, Guo
Zhang, Qunyuan
Feitosa, Mary F.
Glazer, Nicole L.
Haritunians, Talin
Hartikainen, Anna-Liisa
Knowles, Joshua W.
North, Kari E.
Iribarren, Carlos
Kral, Brian
Yanek, Lisa
O’Reilly, Paul F.
McCarthy, Mark I.
Jaquish, Cashell
Couper, David J.
Chakravarti, Aravinda
Psaty, Bruce M.
Becker, Lewis C.
Province, Michael A.
Boerwinkle, Eric
Quertermous, Thomas
Palotie, Leena
Jarvelin, Marjo-Riitta
Becker, Diane M.
Kardia, Sharon L.R.
Rotter, Jerome I.
Chen, Yii-Der Ida
Borecki, Ingrid B.
A Bivariate Genome-Wide Approach to Metabolic Syndrome: STAMPEED Consortium
title A Bivariate Genome-Wide Approach to Metabolic Syndrome: STAMPEED Consortium
title_full A Bivariate Genome-Wide Approach to Metabolic Syndrome: STAMPEED Consortium
title_fullStr A Bivariate Genome-Wide Approach to Metabolic Syndrome: STAMPEED Consortium
title_full_unstemmed A Bivariate Genome-Wide Approach to Metabolic Syndrome: STAMPEED Consortium
title_short A Bivariate Genome-Wide Approach to Metabolic Syndrome: STAMPEED Consortium
title_sort bivariate genome-wide approach to metabolic syndrome: stampeed consortium
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3064107/
https://www.ncbi.nlm.nih.gov/pubmed/21386085
http://dx.doi.org/10.2337/db10-1011
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