Combining information from common type 2 diabetes risk polymorphisms improves disease prediction.

<h4>Background</h4>A limited number of studies have assessed the risk of common diseases when combining information from several predisposing polymorphisms. In most cases, individual polymorphisms only moderately increase risk (approximately 20%), and they are thought to be unhelpful in...

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Main Authors: Michael N Weedon, Mark I McCarthy, Graham Hitman, Mark Walker, Christopher J Groves, Eleftheria Zeggini, N William Rayner, Beverley Shields, Katharine R Owen, Andrew T Hattersley, Timothy M Frayling
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2006-10-01
Series:PLoS Medicine
Online Access:https://doi.org/10.1371/journal.pmed.0030374
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spelling doaj-cf205b2f553342df807ac9ebb20f5eca2021-04-21T18:17:43ZengPublic Library of Science (PLoS)PLoS Medicine1549-12771549-16762006-10-01310e37410.1371/journal.pmed.0030374Combining information from common type 2 diabetes risk polymorphisms improves disease prediction.Michael N WeedonMark I McCarthyGraham HitmanMark WalkerChristopher J GrovesEleftheria ZegginiN William RaynerBeverley ShieldsKatharine R OwenAndrew T HattersleyTimothy M Frayling<h4>Background</h4>A limited number of studies have assessed the risk of common diseases when combining information from several predisposing polymorphisms. In most cases, individual polymorphisms only moderately increase risk (approximately 20%), and they are thought to be unhelpful in assessing individuals' risk clinically. The value of analyzing multiple alleles simultaneously is not well studied. This is often because, for any given disease, very few common risk alleles have been confirmed.<h4>Methods and findings</h4>Three common variants (Lys23 of KCNJ11, Pro12 of PPARG, and the T allele at rs7903146 of TCF7L2) have been shown to predispose to type 2 diabetes mellitus across many large studies. Risk allele frequencies ranged from 0.30 to 0.88 in controls. To assess the combined effect of multiple susceptibility alleles, we genotyped these variants in a large case-control study (3,668 controls versus 2,409 cases). Individual allele odds ratios (ORs) ranged from 1.14 (95% confidence interval [CI], 1.05 to 1.23) to 1.48 (95% CI, 1.36 to 1.60). We found no evidence of gene-gene interaction, and the risks of multiple alleles were consistent with a multiplicative model. Each additional risk allele increased the odds of type 2 diabetes by 1.28 (95% CI, 1.21 to 1.35) times. Participants with all six risk alleles had an OR of 5.71 (95% CI, 1.15 to 28.3) compared to those with no risk alleles. The 8.1% of participants that were double-homozygous for the risk alleles at TCF7L2 and Pro12Ala had an OR of 3.16 (95% CI, 2.22 to 4.50), compared to 4.3% with no TCF7L2 risk alleles and either no or one Glu23Lys or Pro12Ala risk alleles.<h4>Conclusions</h4>Combining information from several known common risk polymorphisms allows the identification of population subgroups with markedly differing risks of developing type 2 diabetes compared to those obtained using single polymorphisms. This approach may have a role in future preventative measures for common, polygenic diseases.https://doi.org/10.1371/journal.pmed.0030374
collection DOAJ
language English
format Article
sources DOAJ
author Michael N Weedon
Mark I McCarthy
Graham Hitman
Mark Walker
Christopher J Groves
Eleftheria Zeggini
N William Rayner
Beverley Shields
Katharine R Owen
Andrew T Hattersley
Timothy M Frayling
spellingShingle Michael N Weedon
Mark I McCarthy
Graham Hitman
Mark Walker
Christopher J Groves
Eleftheria Zeggini
N William Rayner
Beverley Shields
Katharine R Owen
Andrew T Hattersley
Timothy M Frayling
Combining information from common type 2 diabetes risk polymorphisms improves disease prediction.
PLoS Medicine
author_facet Michael N Weedon
Mark I McCarthy
Graham Hitman
Mark Walker
Christopher J Groves
Eleftheria Zeggini
N William Rayner
Beverley Shields
Katharine R Owen
Andrew T Hattersley
Timothy M Frayling
author_sort Michael N Weedon
title Combining information from common type 2 diabetes risk polymorphisms improves disease prediction.
title_short Combining information from common type 2 diabetes risk polymorphisms improves disease prediction.
title_full Combining information from common type 2 diabetes risk polymorphisms improves disease prediction.
title_fullStr Combining information from common type 2 diabetes risk polymorphisms improves disease prediction.
title_full_unstemmed Combining information from common type 2 diabetes risk polymorphisms improves disease prediction.
title_sort combining information from common type 2 diabetes risk polymorphisms improves disease prediction.
publisher Public Library of Science (PLoS)
series PLoS Medicine
issn 1549-1277
1549-1676
publishDate 2006-10-01
description <h4>Background</h4>A limited number of studies have assessed the risk of common diseases when combining information from several predisposing polymorphisms. In most cases, individual polymorphisms only moderately increase risk (approximately 20%), and they are thought to be unhelpful in assessing individuals' risk clinically. The value of analyzing multiple alleles simultaneously is not well studied. This is often because, for any given disease, very few common risk alleles have been confirmed.<h4>Methods and findings</h4>Three common variants (Lys23 of KCNJ11, Pro12 of PPARG, and the T allele at rs7903146 of TCF7L2) have been shown to predispose to type 2 diabetes mellitus across many large studies. Risk allele frequencies ranged from 0.30 to 0.88 in controls. To assess the combined effect of multiple susceptibility alleles, we genotyped these variants in a large case-control study (3,668 controls versus 2,409 cases). Individual allele odds ratios (ORs) ranged from 1.14 (95% confidence interval [CI], 1.05 to 1.23) to 1.48 (95% CI, 1.36 to 1.60). We found no evidence of gene-gene interaction, and the risks of multiple alleles were consistent with a multiplicative model. Each additional risk allele increased the odds of type 2 diabetes by 1.28 (95% CI, 1.21 to 1.35) times. Participants with all six risk alleles had an OR of 5.71 (95% CI, 1.15 to 28.3) compared to those with no risk alleles. The 8.1% of participants that were double-homozygous for the risk alleles at TCF7L2 and Pro12Ala had an OR of 3.16 (95% CI, 2.22 to 4.50), compared to 4.3% with no TCF7L2 risk alleles and either no or one Glu23Lys or Pro12Ala risk alleles.<h4>Conclusions</h4>Combining information from several known common risk polymorphisms allows the identification of population subgroups with markedly differing risks of developing type 2 diabetes compared to those obtained using single polymorphisms. This approach may have a role in future preventative measures for common, polygenic diseases.
url https://doi.org/10.1371/journal.pmed.0030374
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