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Article: Combined Utility of 25 Disease and Risk Factor Polygenic Risk Scores for Stratifying Risk of All-Cause Mortality

TitleCombined Utility of 25 Disease and Risk Factor Polygenic Risk Scores for Stratifying Risk of All-Cause Mortality
Authors
KeywordsAll-cause mortality
Cause-specific mortality
Genome-wide association studies
Genetic risk stratification
Lifestyle modification
Polygenic risk scores
Issue Date2020
PublisherCell Press. The Journal's web site is located at http://www.cell.com/ajhg/home
Citation
The American Journal of Human Genetics, 2020, v. 107 n. 3, p. 418-431 How to Cite?
AbstractWhile genome-wide association studies have identified susceptibility variants for numerous traits, their combined utility for predicting broad measures of health, such as mortality, remains poorly understood. We used data from the UK Biobank to combine polygenic risk scores (PRS) for 13 diseases and 12 mortality risk factors into sex-specific composite PRS (cPRS). These cPRS were moderately associated with all-cause mortality in independent data within the UK Biobank: the estimated hazard ratios per standard deviation were 1.10 (95% confidence interval: 1.05, 1.16) and 1.15 (1.10, 1.19) for women and men, respectively. Differences in life expectancy between the top and bottom 5% of the cPRS were estimated to be 4.79 (1.76, 7.81) years and 6.75 (4.16, 9.35) years for women and men, respectively. These associations were substantially attenuated after adjusting for non-genetic mortality risk factors measured at study entry (i.e., middle age for most participants). The cPRS may be useful in counseling younger individuals at higher genetic risk of mortality on modification of non-genetic factors.
Persistent Identifierhttp://hdl.handle.net/10722/305446
ISSN
2021 Impact Factor: 11.043
2020 SCImago Journal Rankings: 6.661
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorMeisner, A-
dc.contributor.authorKundu, P-
dc.contributor.authorZhang, YD-
dc.contributor.authorLan, LV-
dc.contributor.authorKim, S-
dc.contributor.authorGhandwani, D-
dc.contributor.authorPal Choudhury, P-
dc.contributor.authorBerndt, SI-
dc.contributor.authorFreedman, ND-
dc.contributor.authorGarcia-Closas, M-
dc.contributor.authorChatterjee, N-
dc.date.accessioned2021-10-20T10:09:30Z-
dc.date.available2021-10-20T10:09:30Z-
dc.date.issued2020-
dc.identifier.citationThe American Journal of Human Genetics, 2020, v. 107 n. 3, p. 418-431-
dc.identifier.issn0002-9297-
dc.identifier.urihttp://hdl.handle.net/10722/305446-
dc.description.abstractWhile genome-wide association studies have identified susceptibility variants for numerous traits, their combined utility for predicting broad measures of health, such as mortality, remains poorly understood. We used data from the UK Biobank to combine polygenic risk scores (PRS) for 13 diseases and 12 mortality risk factors into sex-specific composite PRS (cPRS). These cPRS were moderately associated with all-cause mortality in independent data within the UK Biobank: the estimated hazard ratios per standard deviation were 1.10 (95% confidence interval: 1.05, 1.16) and 1.15 (1.10, 1.19) for women and men, respectively. Differences in life expectancy between the top and bottom 5% of the cPRS were estimated to be 4.79 (1.76, 7.81) years and 6.75 (4.16, 9.35) years for women and men, respectively. These associations were substantially attenuated after adjusting for non-genetic mortality risk factors measured at study entry (i.e., middle age for most participants). The cPRS may be useful in counseling younger individuals at higher genetic risk of mortality on modification of non-genetic factors.-
dc.languageeng-
dc.publisherCell Press. The Journal's web site is located at http://www.cell.com/ajhg/home-
dc.relation.ispartofThe American Journal of Human Genetics-
dc.subjectAll-cause mortality-
dc.subjectCause-specific mortality-
dc.subjectGenome-wide association studies-
dc.subjectGenetic risk stratification-
dc.subjectLifestyle modification-
dc.subjectPolygenic risk scores-
dc.titleCombined Utility of 25 Disease and Risk Factor Polygenic Risk Scores for Stratifying Risk of All-Cause Mortality-
dc.typeArticle-
dc.identifier.emailZhang, YD: doraz@hku.hk-
dc.identifier.authorityZhang, YD=rp02590-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1016/j.ajhg.2020.07.002-
dc.identifier.pmid32758451-
dc.identifier.pmcidPMC7477009-
dc.identifier.scopuseid_2-s2.0-85089960637-
dc.identifier.hkuros327562-
dc.identifier.volume107-
dc.identifier.issue3-
dc.identifier.spage418-
dc.identifier.epage431-
dc.identifier.isiWOS:000565899700004-
dc.publisher.placeUnited States-

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