Cargando…

Combining Information from Common Type 2 Diabetes Risk Polymorphisms Improves Disease Prediction

BACKGROUND: 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 (~20%), and they are thought to be unhelpful in assessing individuals' risk...

Descripción completa

Detalles Bibliográficos
Autores principales: Weedon, Michael N, McCarthy, Mark I, Hitman, Graham, Walker, Mark, Groves, Christopher J, Zeggini, Eleftheria, Rayner, N. William, Shields, Beverley, Owen, Katharine R, Hattersley, Andrew T, Frayling, Timothy M
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1584415/
https://www.ncbi.nlm.nih.gov/pubmed/17020404
http://dx.doi.org/10.1371/journal.pmed.0030374
_version_ 1782130338508570624
author Weedon, Michael N
McCarthy, Mark I
Hitman, Graham
Walker, Mark
Groves, Christopher J
Zeggini, Eleftheria
Rayner, N. William
Shields, Beverley
Owen, Katharine R
Hattersley, Andrew T
Frayling, Timothy M
author_facet Weedon, Michael N
McCarthy, Mark I
Hitman, Graham
Walker, Mark
Groves, Christopher J
Zeggini, Eleftheria
Rayner, N. William
Shields, Beverley
Owen, Katharine R
Hattersley, Andrew T
Frayling, Timothy M
author_sort Weedon, Michael N
collection PubMed
description BACKGROUND: 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 (~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. METHODS AND FINDINGS: 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. CONCLUSIONS: 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.
format Text
id pubmed-1584415
institution National Center for Biotechnology Information
language English
publishDate 2006
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-15844152006-10-03 Combining Information from Common Type 2 Diabetes Risk Polymorphisms Improves Disease Prediction Weedon, Michael N McCarthy, Mark I Hitman, Graham Walker, Mark Groves, Christopher J Zeggini, Eleftheria Rayner, N. William Shields, Beverley Owen, Katharine R Hattersley, Andrew T Frayling, Timothy M PLoS Med Research Article BACKGROUND: 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 (~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. METHODS AND FINDINGS: 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. CONCLUSIONS: 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. Public Library of Science 2006-10 2006-10-03 /pmc/articles/PMC1584415/ /pubmed/17020404 http://dx.doi.org/10.1371/journal.pmed.0030374 Text en © 2006 Weedon et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Weedon, Michael N
McCarthy, Mark I
Hitman, Graham
Walker, Mark
Groves, Christopher J
Zeggini, Eleftheria
Rayner, N. William
Shields, Beverley
Owen, Katharine R
Hattersley, Andrew T
Frayling, Timothy M
Combining Information from Common Type 2 Diabetes Risk Polymorphisms Improves Disease Prediction
title 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_short 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
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1584415/
https://www.ncbi.nlm.nih.gov/pubmed/17020404
http://dx.doi.org/10.1371/journal.pmed.0030374
work_keys_str_mv AT weedonmichaeln combininginformationfromcommontype2diabetesriskpolymorphismsimprovesdiseaseprediction
AT mccarthymarki combininginformationfromcommontype2diabetesriskpolymorphismsimprovesdiseaseprediction
AT hitmangraham combininginformationfromcommontype2diabetesriskpolymorphismsimprovesdiseaseprediction
AT walkermark combininginformationfromcommontype2diabetesriskpolymorphismsimprovesdiseaseprediction
AT groveschristopherj combininginformationfromcommontype2diabetesriskpolymorphismsimprovesdiseaseprediction
AT zegginieleftheria combininginformationfromcommontype2diabetesriskpolymorphismsimprovesdiseaseprediction
AT raynernwilliam combininginformationfromcommontype2diabetesriskpolymorphismsimprovesdiseaseprediction
AT shieldsbeverley combininginformationfromcommontype2diabetesriskpolymorphismsimprovesdiseaseprediction
AT owenkathariner combininginformationfromcommontype2diabetesriskpolymorphismsimprovesdiseaseprediction
AT hattersleyandrewt combininginformationfromcommontype2diabetesriskpolymorphismsimprovesdiseaseprediction
AT fraylingtimothym combininginformationfromcommontype2diabetesriskpolymorphismsimprovesdiseaseprediction