Variations in predicted risks in personal genome testing for common complex diseases.
Variations in predicted risks in personal genome testing for common complex diseases.
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DOI：
10.1038/gim.2013.80
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发表时间：
2014-01
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影响因子：
--
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中科院分区：
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--
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针对常见复杂疾病的个性化基因组学的前景，部分取决于基于单核苷酸多态性预测遗传风险的能力。我们研究并比较了三家公司（23andMe、deCODEme和Navigenics）提供的直接面向消费者的个人基因组检测方法。我们在公布的基因型频率的基础上模拟了10万人的基因型数据，并使用这些公司的方法预测了疾病风险。通过AUC评估对6种疾病的预测能力。不同疾病和不同公司的AUC值存在差异。年龄相关性黄斑变性、乳糜泻和克罗恩病的AUC值最高。两家公司在乳糜泻方面的差异最大：23andMe的AUC为0.73，deCODEme的AUC为0.82。由于所选择的单核苷酸多态性集和公司选择的平均人口风险以及用于计算风险的公式的差异，公司之间的预测风险存在很大差异。了解这些早期公司设计的预测算法的优势和局限性，可能有助于未来为常见复杂疾病的基因组学设计预测模型。
The promise of personalized genomics for common complex diseases depends, in part, on the ability to predict genetic risks on the basis of single nucleotide polymorphisms. We examined and compared the methods of three companies (23andMe, deCODEme, and Navigenics) that have offered direct-to-consumer personal genome testing. We simulated genotype data for 100,000 individuals on the basis of published genotype frequencies and predicted disease risks using the methods of the companies. Predictive ability for six diseases was assessed by the AUC. AUC values differed among the diseases and among the companies. The highest values of the AUC were observed for age related macular degeneration, celiac disease, and Crohn disease. The largest difference among the companies was found for celiac disease: the AUC was 0.73 for 23andMe and 0.82 for deCODEme. Predicted risks differed substantially among the companies as a result of differences in the sets of single nucleotide polymorphisms selected and the average population risks selected by the companies, and in the formulas used for the calculation of risks. Future efforts to design predictive models for the genomics of common complex diseases may benefit from understanding the strengths and limitations of the predictive algorithms designed by these early companies.
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