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Adiposity-Related Heterogeneity in Patterns of Type 2 Diabetes Susceptibility Observed in Genome-Wide Association Data

OBJECTIVE—This study examined how differences in the BMI distribution of type 2 diabetic case subjects affected genome-wide patterns of type 2 diabetes association and considered the implications for the etiological heterogeneity of type 2 diabetes. RESEARCH DESIGN AND METHODS—We reanalyzed data fro...

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Autores principales: Timpson, Nicholas J., Lindgren, Cecilia M., Weedon, Michael N., Randall, Joshua, Ouwehand, Willem H., Strachan, David P., Rayner, N. William, Walker, Mark, Hitman, Graham A., Doney, Alex S.F., Palmer, Colin N.A., Morris, Andrew D., Hattersley, Andrew T., Zeggini, Eleftheria, Frayling, Timothy M., McCarthy, Mark I.
Formato: Texto
Lenguaje:English
Publicado: American Diabetes Association 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2628627/
https://www.ncbi.nlm.nih.gov/pubmed/19056611
http://dx.doi.org/10.2337/db08-0906
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author Timpson, Nicholas J.
Lindgren, Cecilia M.
Weedon, Michael N.
Randall, Joshua
Ouwehand, Willem H.
Strachan, David P.
Rayner, N. William
Walker, Mark
Hitman, Graham A.
Doney, Alex S.F.
Palmer, Colin N.A.
Morris, Andrew D.
Hattersley, Andrew T.
Zeggini, Eleftheria
Frayling, Timothy M.
McCarthy, Mark I.
author_facet Timpson, Nicholas J.
Lindgren, Cecilia M.
Weedon, Michael N.
Randall, Joshua
Ouwehand, Willem H.
Strachan, David P.
Rayner, N. William
Walker, Mark
Hitman, Graham A.
Doney, Alex S.F.
Palmer, Colin N.A.
Morris, Andrew D.
Hattersley, Andrew T.
Zeggini, Eleftheria
Frayling, Timothy M.
McCarthy, Mark I.
author_sort Timpson, Nicholas J.
collection PubMed
description OBJECTIVE—This study examined how differences in the BMI distribution of type 2 diabetic case subjects affected genome-wide patterns of type 2 diabetes association and considered the implications for the etiological heterogeneity of type 2 diabetes. RESEARCH DESIGN AND METHODS—We reanalyzed data from the Wellcome Trust Case Control Consortium genome-wide association scan (1,924 case subjects, 2,938 control subjects: 393,453 single-nucleotide polymorphisms [SNPs]) after stratifying case subjects (into “obese” and “nonobese”) according to median BMI (30.2 kg/m(2)). Replication of signals in which alternative case-ascertainment strategies generated marked effect size heterogeneity in type 2 diabetes association signal was sought in additional samples. RESULTS—In the “obese-type 2 diabetes” scan, FTO variants had the strongest type 2 diabetes effect (rs8050136: relative risk [RR] 1.49 [95% CI 1.34–1.66], P = 1.3 × 10(−13)), with only weak evidence for TCF7L2 (rs7901695 RR 1.21 [1.09–1.35], P = 0.001). This situation was reversed in the “nonobese” scan, with FTO association undetectable (RR 1.07 [0.97–1.19], P = 0.19) and TCF7L2 predominant (RR 1.53 [1.37–1.71], P = 1.3 × 10(−14)). These patterns, confirmed by replication, generated strong combined evidence for between-stratum effect size heterogeneity (FTO: P(DIFF) = 1.4 × 10(−7); TCF7L2: P(DIFF) = 4.0 × 10(−6)). Other signals displaying evidence of effect size heterogeneity in the genome-wide analyses (on chromosomes 3, 12, 15, and 18) did not replicate. Analysis of the current list of type 2 diabetes susceptibility variants revealed nominal evidence for effect size heterogeneity for the SLC30A8 locus alone (RR(obese) 1.08 [1.01–1.15]; RR(nonobese) 1.18 [1.10–1.27]: P(DIFF) = 0.04). CONCLUSIONS—This study demonstrates the impact of differences in case ascertainment on the power to detect and replicate genetic associations in genome-wide association studies. These data reinforce the notion that there is substantial etiological heterogeneity within type 2 diabetes.
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spelling pubmed-26286272010-02-01 Adiposity-Related Heterogeneity in Patterns of Type 2 Diabetes Susceptibility Observed in Genome-Wide Association Data Timpson, Nicholas J. Lindgren, Cecilia M. Weedon, Michael N. Randall, Joshua Ouwehand, Willem H. Strachan, David P. Rayner, N. William Walker, Mark Hitman, Graham A. Doney, Alex S.F. Palmer, Colin N.A. Morris, Andrew D. Hattersley, Andrew T. Zeggini, Eleftheria Frayling, Timothy M. McCarthy, Mark I. Diabetes Genetics OBJECTIVE—This study examined how differences in the BMI distribution of type 2 diabetic case subjects affected genome-wide patterns of type 2 diabetes association and considered the implications for the etiological heterogeneity of type 2 diabetes. RESEARCH DESIGN AND METHODS—We reanalyzed data from the Wellcome Trust Case Control Consortium genome-wide association scan (1,924 case subjects, 2,938 control subjects: 393,453 single-nucleotide polymorphisms [SNPs]) after stratifying case subjects (into “obese” and “nonobese”) according to median BMI (30.2 kg/m(2)). Replication of signals in which alternative case-ascertainment strategies generated marked effect size heterogeneity in type 2 diabetes association signal was sought in additional samples. RESULTS—In the “obese-type 2 diabetes” scan, FTO variants had the strongest type 2 diabetes effect (rs8050136: relative risk [RR] 1.49 [95% CI 1.34–1.66], P = 1.3 × 10(−13)), with only weak evidence for TCF7L2 (rs7901695 RR 1.21 [1.09–1.35], P = 0.001). This situation was reversed in the “nonobese” scan, with FTO association undetectable (RR 1.07 [0.97–1.19], P = 0.19) and TCF7L2 predominant (RR 1.53 [1.37–1.71], P = 1.3 × 10(−14)). These patterns, confirmed by replication, generated strong combined evidence for between-stratum effect size heterogeneity (FTO: P(DIFF) = 1.4 × 10(−7); TCF7L2: P(DIFF) = 4.0 × 10(−6)). Other signals displaying evidence of effect size heterogeneity in the genome-wide analyses (on chromosomes 3, 12, 15, and 18) did not replicate. Analysis of the current list of type 2 diabetes susceptibility variants revealed nominal evidence for effect size heterogeneity for the SLC30A8 locus alone (RR(obese) 1.08 [1.01–1.15]; RR(nonobese) 1.18 [1.10–1.27]: P(DIFF) = 0.04). CONCLUSIONS—This study demonstrates the impact of differences in case ascertainment on the power to detect and replicate genetic associations in genome-wide association studies. These data reinforce the notion that there is substantial etiological heterogeneity within type 2 diabetes. American Diabetes Association 2009-02 /pmc/articles/PMC2628627/ /pubmed/19056611 http://dx.doi.org/10.2337/db08-0906 Text en Copyright © 2009, 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
Timpson, Nicholas J.
Lindgren, Cecilia M.
Weedon, Michael N.
Randall, Joshua
Ouwehand, Willem H.
Strachan, David P.
Rayner, N. William
Walker, Mark
Hitman, Graham A.
Doney, Alex S.F.
Palmer, Colin N.A.
Morris, Andrew D.
Hattersley, Andrew T.
Zeggini, Eleftheria
Frayling, Timothy M.
McCarthy, Mark I.
Adiposity-Related Heterogeneity in Patterns of Type 2 Diabetes Susceptibility Observed in Genome-Wide Association Data
title Adiposity-Related Heterogeneity in Patterns of Type 2 Diabetes Susceptibility Observed in Genome-Wide Association Data
title_full Adiposity-Related Heterogeneity in Patterns of Type 2 Diabetes Susceptibility Observed in Genome-Wide Association Data
title_fullStr Adiposity-Related Heterogeneity in Patterns of Type 2 Diabetes Susceptibility Observed in Genome-Wide Association Data
title_full_unstemmed Adiposity-Related Heterogeneity in Patterns of Type 2 Diabetes Susceptibility Observed in Genome-Wide Association Data
title_short Adiposity-Related Heterogeneity in Patterns of Type 2 Diabetes Susceptibility Observed in Genome-Wide Association Data
title_sort adiposity-related heterogeneity in patterns of type 2 diabetes susceptibility observed in genome-wide association data
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2628627/
https://www.ncbi.nlm.nih.gov/pubmed/19056611
http://dx.doi.org/10.2337/db08-0906
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