The impact of genotype frequencies on the clinical validity of genomic profiling for predicting common chronic diseases
The impact of genotype frequencies on the clinical validity of genomic profiling for predicting common chronic diseases
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DOI：
10.1097/gim.0b013e31812eece0
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发表时间：
2007-08-01
影响因子：
8.8
通讯作者：
Khoury, Muin J.
中科院分区：
文献类型：
--
作者：
Janssens, A. Cecile J. W.;Moonesinghe, Ramal;Khoury, Muin J.
目的：多因素疾病中的单个遗传变异通常会产生较小的影响，因此仅通过同时暴露于多种风险基因型的同时暴露于疾病风险的重大增加。我们研究了基因型频率对40个独立易感性遗传变异的同时测试临床判别准确性的影响。方法：在单独的模拟方案中，我们将基因型频率从1％变为50％，每个遗传变异的几率从1.1变为1.1到2.0。人口规模为100万，人口疾病风险为10％。判别精度被量化为接收器操作特征曲线下的面积。以2型糖尿病的基因组分析的示例，当五个假定的遗传变异型之间的几率比和基因型频率变化时，我们评估了接收器操作特征曲线下的面积。结果：当基因型频率为1％时，没有一个受试者携带40种风险基因型中的六个以上，而当风险基因型经常使用（> = 30％）时，所有受试者至少携带至少6个。当优势比适度（1.1或1.25）时，接收器操作特征曲线下的面积不会增加0.70，但是较高的基因型频率将接收器操作特征曲线下的面积从0.57增加到0.82，从0.63增加到0.63赔率比为1.5或2.0。 2型糖尿病的例子表明，当忽略优势比的差异时，接收器操作特征曲线下的面积不会改变。结论：鉴于易感基因在复杂疾病中的影响很小，因此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。
Purpose: 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. Methods: 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. Results: When the genotype frequency was 1%, none of the subjects carried more than six of 40 risk genotypes, and when risk genotypes were frequent (>= 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. Conclusions: 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.