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
Department of Diabetes Research and Vascular Medicine, Peninsula Medical School, Exeter, United Kingdom.
PLoS Med. 2006 Oct;3(10):e374. doi: 10.1371/journal.pmed.0030374.
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.
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.
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.
仅有少数研究评估了整合多种易感基因多态性信息时常见疾病的风险。在大多数情况下,单个多态性仅适度增加风险(约20%),并且人们认为它们在临床评估个体风险方面并无帮助。同时分析多个等位基因的价值尚未得到充分研究。这通常是因为对于任何特定疾病,已确认的常见风险等位基因非常少。
在许多大型研究中,已证实三种常见变异(KCNJ11基因的赖氨酸23位点、PPARG基因的脯氨酸12位点以及TCF7L2基因rs7903146位点的T等位基因)易导致2型糖尿病。在对照组中,风险等位基因频率范围为0.30至0.88。为评估多个易感等位基因的联合效应,我们在一项大型病例对照研究(3668例对照与2409例病例)中对这些变异进行了基因分型。单个等位基因的优势比(OR)范围为1.14(95%置信区间[CI],1.05至1.23)至1.48(95%CI,1.36至1.60)。我们未发现基因-基因相互作用的证据,并且多个等位基因的风险与乘法模型一致。每增加一个风险等位基因,2型糖尿病的发病几率增加1.28倍(95%CI,1.21至1.35)。与没有风险等位基因的参与者相比,具有所有六个风险等位基因的参与者的OR为5.71(95%CI,1.15至28.3)。与没有TCF7L2风险等位基因且没有或仅有一个Glu23Lys或Pro12Ala风险等位基因的4.3%的参与者相比,在TCF7L2和Pro12Ala位点风险等位基因呈双纯合子的8.1%的参与者的OR为3.16(95%CI,2.22至4.50)。
整合来自几种已知常见风险多态性的信息,与使用单个多态性相比,能够识别出患2型糖尿病风险明显不同的人群亚组。这种方法可能在未来常见多基因疾病的预防措施中发挥作用。