1] Rikengenesis CO., LTD., Tokyo, Japan [2] JST, PRESTO, Tokyo, Japan.
J Hum Genet. 2013 Nov;58(11):734-41. doi: 10.1038/jhg.2013.96. Epub 2013 Sep 26.
Disease risk prediction (DRP) is one of the most important challenges in personal genome research. Although many direct-to-consumer genetic test (DTC) companies have begun to offer personal genome services for DRP, there is still no consensus on what constitutes a gold-standard service. Here, we systematically evaluated the distributions of DRPs from three DTC companies, that is, 23andMe, Navigenics and deCODEme, for 22 diseases using three Japanese samples. We systematically quantified and analyzed the differences between each DTC company's DRPs. Our independency test showed that the overall prediction results were correlated with each other, but not perfectly matched; less than onethird mismatching of the opposite direction occurred in eight diseases. Moreover, we found that the differences could mainly be attributed to four factors: (1) single nucleotide polymorphism (SNP) selection, (2) average risk estimation, (3) the disease risk calculation algorithm and (4) ethnicity adjustment. In particular, only 7.1% of SNPs over 22 diseases were reviewed by all three companies. Therefore, development of a universal core SNPs list for non-Caucasian samples will be important for achieving better prediction capacity for Japanese samples. This systematic methodology provides useful insights for improving the capacity of DRPs in future personal genome services.
疾病风险预测 (DRP) 是个人基因组研究中最重要的挑战之一。尽管许多直接面向消费者的基因检测 (DTC) 公司已经开始提供用于 DRP 的个人基因组服务,但对于什么构成黄金标准服务仍没有共识。在这里,我们使用三个日本样本,系统地评估了三家 DTC 公司(即 23andMe、Navigenics 和 deCODEme)的 22 种疾病的 DRP 分布情况。我们系统地量化和分析了每个 DTC 公司的 DRP 之间的差异。我们的独立性检验表明,整体预测结果相互关联,但并不完全匹配;在八种疾病中,不到三分之一的相反方向的预测结果不匹配。此外,我们发现这些差异主要归因于四个因素:(1)单核苷酸多态性 (SNP) 选择,(2)平均风险估计,(3)疾病风险计算算法,(4)种族调整。特别是,三家公司仅对 22 种疾病中的 7.1% 的 SNP 进行了审查。因此,为非高加索样本开发通用核心 SNP 列表对于提高对日本样本的预测能力将是重要的。这种系统的方法为提高未来个人基因组服务中的 DRP 能力提供了有用的见解。