Janssens A Cecile J W, Moonesinghe Ramal, Yang Quahne, Steyerberg Ewout W, van Duijn Cornelia M, Khoury Muin J
Department of Public Health, Erasmus University Medical Center, Rotterdam, The Netherlands.
Genet Med. 2007 Aug;9(8):528-35. doi: 10.1097/gim.0b013e31812eece0.
Single genetic variants in multifactorial disorders typically have small effects, so major increases in disease risk are expected only from the simultaneous exposure to multiple risk genotypes. We investigated the impact of genotype frequencies on the clinical discriminative accuracy for the simultaneous testing of 40 independent susceptibility genetic variants.
In separate simulation scenarios, we varied the genotype frequency from 1% to 50% and the odds ratio for each genetic variant from 1.1 to 2.0. Population size was 1 million and the population disease risk was 10%. Discriminative accuracy was quantified as the area under the receiver-operating characteristic curve. Using an example of genomic profiling for type 2 diabetes, we evaluated the area under the receiver-operating characteristic curve when the odds ratios and genotype frequencies varied between five postulated genetic variants.
When the genotype frequency was 1%, none of the subjects carried more than six of 40 risk genotypes, and when risk genotypes were frequent (> or =30%), all carried at least six. The area under the receiver-operating characteristic curve did not increase above 0.70 when the odds ratios were modest (1.1 or 1.25), but higher genotype frequency increased the area under the receiver-operating characteristic curve from 0.57 to 0.82 and from 0.63 to 0.93 when odds ratios were 1.5 or 2.0. The example of type 2 diabetes showed that the area under the receiver-operating characteristic curve did not change when differences in the odds ratios were ignored.
Given that the effects of susceptibility genes in complex diseases are small, the feasibility of future genomic profiling for predicting common diseases will depend substantially on the frequencies of the risk genotypes.
多因素疾病中的单个基因变异通常影响较小,因此预计只有同时暴露于多种风险基因型时疾病风险才会大幅增加。我们研究了基因型频率对同时检测40个独立易感性基因变异的临床判别准确性的影响。
在不同的模拟场景中,我们将基因型频率从1%变化到50%,每个基因变异的比值比从1.1变化到2.0。群体大小为100万,群体疾病风险为10%。判别准确性通过受试者操作特征曲线下面积进行量化。以2型糖尿病的基因组分析为例,我们评估了在五个假定的基因变异之间比值比和基因型频率变化时受试者操作特征曲线下面积。
当基因型频率为1%时,没有受试者携带超过40个风险基因型中的6个,而当风险基因型频率较高(≥30%)时,所有人至少携带6个。当比值比适中(1.1或1.25)时,受试者操作特征曲线下面积未增加到0.70以上,但当比值比为1.5或2.0时,较高的基因型频率使受试者操作特征曲线下面积从0.57增加到0.82,从0.63增加到0.93。2型糖尿病的例子表明,当忽略比值比的差异时,受试者操作特征曲线下面积没有变化。
鉴于复杂疾病中易感基因的影响较小,未来基因组分析预测常见疾病的可行性将在很大程度上取决于风险基因型的频率。