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
StatePublished - Jul 1 2016

Fingerprint

Genetic Testing
Genome-Wide Association Study
Disease Susceptibility
Human Development
Secondary Prevention
Health
Genes

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)
  • Molecular Biology

Cite this

Developing and evaluating polygenic risk prediction models for stratified disease prevention. / Chatterjee, Nilanjan; Shi, Jianxin; García-Closas, Montserrat.

In: Nature Reviews Genetics, Vol. 17, No. 7, 01.07.2016, p. 392-406.

Research output: Contribution to journalReview article

Chatterjee, Nilanjan ; Shi, Jianxin ; García-Closas, Montserrat. / Developing and evaluating polygenic risk prediction models for stratified disease prevention. In: Nature Reviews Genetics. 2016 ; Vol. 17, No. 7. pp. 392-406.
@article{26f9fb567156452ab05b5ff3a2543224,
title = "Developing and evaluating polygenic risk prediction models for stratified disease prevention",
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.",
author = "Nilanjan Chatterjee and Jianxin Shi and Montserrat Garc{\'i}a-Closas",
year = "2016",
month = "7",
day = "1",
doi = "10.1038/nrg.2016.27",
language = "English (US)",
volume = "17",
pages = "392--406",
journal = "Nature Reviews Genetics",
issn = "1471-0056",
publisher = "Nature Publishing Group",
number = "7",

}

TY - JOUR

T1 - Developing and evaluating polygenic risk prediction models for stratified disease prevention

AU - Chatterjee, Nilanjan

AU - Shi, Jianxin

AU - García-Closas, Montserrat

PY - 2016/7/1

Y1 - 2016/7/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84965076156&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84965076156&partnerID=8YFLogxK

U2 - 10.1038/nrg.2016.27

DO - 10.1038/nrg.2016.27

M3 - Review article

C2 - 27140283

AN - SCOPUS:84965076156

VL - 17

SP - 392

EP - 406

JO - Nature Reviews Genetics

JF - Nature Reviews Genetics

SN - 1471-0056

IS - 7

ER -