Developing and evaluating polygenic risk prediction models for stratified disease prevention

被引：521

作者：

Chatterjee, Nilanjan ^{[1
,2
,3
]}

Shi, Jianxin ^{[3
]}

Garcia-Closas, Montserrat ^{[3
]}

机构：

[1] Johns Hopkins Univ, Dept Biostat, Bloomberg Sch Publ Hlth, Baltimore, MD 21205 USA

[2] Johns Hopkins Univ, Sch Med, Dept Oncol, Baltimore, MD 21205 USA

[3] NCI, Div Canc Epidemiol & Genet, NIH, Dept Hlth & Human Serv, Bethesda, MD 20892 USA

来源：

NATURE REVIEWS GENETICS | 2016年 / 17卷 / 07期

基金：

美国国家卫生研究院;

关键词：

GENOME-WIDE ASSOCIATION; SINGLE-NUCLEOTIDE POLYMORPHISMS; GENE-ENVIRONMENT INTERACTIONS; CANCER-RISK; BREAST-CANCER; FAMILY-HISTORY; COMMON SNPS; SUSCEPTIBILITY LOCI; MULTIPLE-SCLEROSIS; INCREASES ACCURACY;

D O I：

10.1038/nrg.2016.27

中图分类号：

Q3 [遗传学];

学科分类号：

071007 [遗传学];

摘要：

Knowledge of genetics and its implications for human health is rapidly evolving in accordance with recent events, such as discoveries of large numbers of disease susceptibility loci from genome-wide association studies, the US Supreme Court ruling of the non-patentability of human genes, and the development of a regulatory framework for commercial genetic tests. In anticipation of the increasing relevance of genetic testing for the assessment of disease risks, this Review provides a summary of the methodologies used for building, evaluating and applying risk prediction models that include information from genetic testing and environmental risk factors. Potential applications of models for primary and secondary disease prevention are illustrated through several case studies, and future challenges and opportunities are discussed.

引用

页码：392 / 406

页数：15

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