Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction

Predicting cancer risk requires large datasets and sophisticated models. Here the authors integrate polygenic risk scores and modifiable risk factors for multiple cancers in the UK Biobank, improving general risk prediction and distinguishing cases where genetic or lifestyle factors have stronger as...

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Autores principales:	Linda Kachuri, Rebecca E. Graff, Karl Smith-Byrne, Travis J. Meyers, Sara R. Rashkin, Elad Ziv, John S. Witte, Mattias Johansson
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/81dc1615a08241648effc080de295adb
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spelling	oai:doaj.org-article:81dc1615a08241648effc080de295adb2021-12-02T16:49:44ZPan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction10.1038/s41467-020-19600-42041-1723https://doaj.org/article/81dc1615a08241648effc080de295adb2020-11-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-19600-4https://doaj.org/toc/2041-1723Predicting cancer risk requires large datasets and sophisticated models. Here the authors integrate polygenic risk scores and modifiable risk factors for multiple cancers in the UK Biobank, improving general risk prediction and distinguishing cases where genetic or lifestyle factors have stronger associations.Linda KachuriRebecca E. GraffKarl Smith-ByrneTravis J. MeyersSara R. RashkinElad ZivJohn S. WitteMattias JohanssonNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-11 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Linda Kachuri Rebecca E. Graff Karl Smith-Byrne Travis J. Meyers Sara R. Rashkin Elad Ziv John S. Witte Mattias Johansson Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction
description	Predicting cancer risk requires large datasets and sophisticated models. Here the authors integrate polygenic risk scores and modifiable risk factors for multiple cancers in the UK Biobank, improving general risk prediction and distinguishing cases where genetic or lifestyle factors have stronger associations.
format	article
author	Linda Kachuri Rebecca E. Graff Karl Smith-Byrne Travis J. Meyers Sara R. Rashkin Elad Ziv John S. Witte Mattias Johansson
author_facet	Linda Kachuri Rebecca E. Graff Karl Smith-Byrne Travis J. Meyers Sara R. Rashkin Elad Ziv John S. Witte Mattias Johansson
author_sort	Linda Kachuri
title	Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction
title_short	Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction
title_full	Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction
title_fullStr	Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction
title_full_unstemmed	Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction
title_sort	pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/81dc1615a08241648effc080de295adb
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Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction

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