The Scripps Translational Science Institute, The Scripps Research Institute, La Jolla, CA, USA.
Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA.
Nat Rev Genet. 2018 Sep;19(9):581-590. doi: 10.1038/s41576-018-0018-x.
Initial expectations for genome-wide association studies were high, as such studies promised to rapidly transform personalized medicine with individualized disease risk predictions, prevention strategies and treatments. Early findings, however, revealed a more complex genetic architecture than was anticipated for most common diseases - complexity that seemed to limit the immediate utility of these findings. As a result, the practice of utilizing the DNA of an individual to predict disease has been judged to provide little to no useful information. Nevertheless, recent efforts have begun to demonstrate the utility of polygenic risk profiling to identify groups of individuals who could benefit from the knowledge of their probabilistic susceptibility to disease. In this context, we review the evidence supporting the personal and clinical utility of polygenic risk profiling.
人们最初对全基因组关联研究寄予厚望,因为这些研究有望通过个体化疾病风险预测、预防策略和治疗方法,快速推动个性化医疗的发展。然而,早期的研究结果显示,大多数常见疾病的遗传结构比预期的更为复杂——这种复杂性似乎限制了这些发现的直接应用。因此,利用个体的 DNA 预测疾病的做法被认为几乎没有提供有用的信息。尽管如此,最近的研究已经开始证明多基因风险分析在确定可能受益于了解其疾病易感性概率的个体群体方面的实用性。在这种情况下,我们回顾了支持多基因风险分析的个人和临床实用性的证据。