Developing and evaluating polygenic risk prediction models for stratified disease prevention

Nilanjan Chatterjee, Jianxin Shi, Montserrat García-Closas

Research output: Contribution to journalReview article

Abstract

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.

Original languageEnglish (US)
Pages (from-to)392-406
Number of pages15
JournalNature Reviews Genetics
Volume17
Issue number7
DOIs
Publication statusPublished - Jul 1 2016

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ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)
  • Molecular Biology

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