Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score.

<h4>Background</h4>Identifying individuals at risk for developing Alzheimer disease (AD) is of utmost importance. Although genetic studies have identified AD-associated SNPs in APOE and other genes, genetic information has not been integrated into an epidemiological framework for risk pr...

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Main Authors: Rahul S Desikan, Chun Chieh Fan, Yunpeng Wang, Andrew J Schork, Howard J Cabral, L Adrienne Cupples, Wesley K Thompson, Lilah Besser, Walter A Kukull, Dominic Holland, Chi-Hua Chen, James B Brewer, David S Karow, Karolina Kauppi, Aree Witoelar, Celeste M Karch, Luke W Bonham, Jennifer S Yokoyama, Howard J Rosen, Bruce L Miller, William P Dillon, David M Wilson, Christopher P Hess, Margaret Pericak-Vance, Jonathan L Haines, Lindsay A Farrer, Richard Mayeux, John Hardy, Alison M Goate, Bradley T Hyman, Gerard D Schellenberg, Linda K McEvoy, Ole A Andreassen, Anders M Dale
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2017-03-01
Series:PLoS Medicine
Online Access:https://doi.org/10.1371/journal.pmed.1002258
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author Rahul S Desikan
Chun Chieh Fan
Yunpeng Wang
Andrew J Schork
Howard J Cabral
L Adrienne Cupples
Wesley K Thompson
Lilah Besser
Walter A Kukull
Dominic Holland
Chi-Hua Chen
James B Brewer
David S Karow
Karolina Kauppi
Aree Witoelar
Celeste M Karch
Luke W Bonham
Jennifer S Yokoyama
Howard J Rosen
Bruce L Miller
William P Dillon
David M Wilson
Christopher P Hess
Margaret Pericak-Vance
Jonathan L Haines
Lindsay A Farrer
Richard Mayeux
John Hardy
Alison M Goate
Bradley T Hyman
Gerard D Schellenberg
Linda K McEvoy
Ole A Andreassen
Anders M Dale
author_facet Rahul S Desikan
Chun Chieh Fan
Yunpeng Wang
Andrew J Schork
Howard J Cabral
L Adrienne Cupples
Wesley K Thompson
Lilah Besser
Walter A Kukull
Dominic Holland
Chi-Hua Chen
James B Brewer
David S Karow
Karolina Kauppi
Aree Witoelar
Celeste M Karch
Luke W Bonham
Jennifer S Yokoyama
Howard J Rosen
Bruce L Miller
William P Dillon
David M Wilson
Christopher P Hess
Margaret Pericak-Vance
Jonathan L Haines
Lindsay A Farrer
Richard Mayeux
John Hardy
Alison M Goate
Bradley T Hyman
Gerard D Schellenberg
Linda K McEvoy
Ole A Andreassen
Anders M Dale
author_sort Rahul S Desikan
collection DOAJ
description <h4>Background</h4>Identifying individuals at risk for developing Alzheimer disease (AD) is of utmost importance. Although genetic studies have identified AD-associated SNPs in APOE and other genes, genetic information has not been integrated into an epidemiological framework for risk prediction.<h4>Methods and findings</h4>Using genotype data from 17,008 AD cases and 37,154 controls from the International Genomics of Alzheimer's Project (IGAP Stage 1), we identified AD-associated SNPs (at p < 10-5). We then integrated these AD-associated SNPs into a Cox proportional hazard model using genotype data from a subset of 6,409 AD patients and 9,386 older controls from Phase 1 of the Alzheimer's Disease Genetics Consortium (ADGC), providing a polygenic hazard score (PHS) for each participant. By combining population-based incidence rates and the genotype-derived PHS for each individual, we derived estimates of instantaneous risk for developing AD, based on genotype and age, and tested replication in multiple independent cohorts (ADGC Phase 2, National Institute on Aging Alzheimer's Disease Center [NIA ADC], and Alzheimer's Disease Neuroimaging Initiative [ADNI], total n = 20,680). Within the ADGC Phase 1 cohort, individuals in the highest PHS quartile developed AD at a considerably lower age and had the highest yearly AD incidence rate. Among APOE ε3/3 individuals, the PHS modified expected age of AD onset by more than 10 y between the lowest and highest deciles (hazard ratio 3.34, 95% CI 2.62-4.24, p = 1.0 × 10-22). In independent cohorts, the PHS strongly predicted empirical age of AD onset (ADGC Phase 2, r = 0.90, p = 1.1 × 10-26) and longitudinal progression from normal aging to AD (NIA ADC, Cochran-Armitage trend test, p = 1.5 × 10-10), and was associated with neuropathology (NIA ADC, Braak stage of neurofibrillary tangles, p = 3.9 × 10-6, and Consortium to Establish a Registry for Alzheimer's Disease score for neuritic plaques, p = 6.8 × 10-6) and in vivo markers of AD neurodegeneration (ADNI, volume loss within the entorhinal cortex, p = 6.3 × 10-6, and hippocampus, p = 7.9 × 10-5). Additional prospective validation of these results in non-US, non-white, and prospective community-based cohorts is necessary before clinical use.<h4>Conclusions</h4>We have developed a PHS for quantifying individual differences in age-specific genetic risk for AD. Within the cohorts studied here, polygenic architecture plays an important role in modifying AD risk beyond APOE. With thorough validation, quantification of inherited genetic variation may prove useful for stratifying AD risk and as an enrichment strategy in therapeutic trials.
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spelling doaj-art-14159604a7684d2ca1b93c7c8aca5c2f2025-08-20T02:33:44ZengPublic Library of Science (PLoS)PLoS Medicine1549-12771549-16762017-03-01143e100225810.1371/journal.pmed.1002258Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score.Rahul S DesikanChun Chieh FanYunpeng WangAndrew J SchorkHoward J CabralL Adrienne CupplesWesley K ThompsonLilah BesserWalter A KukullDominic HollandChi-Hua ChenJames B BrewerDavid S KarowKarolina KauppiAree WitoelarCeleste M KarchLuke W BonhamJennifer S YokoyamaHoward J RosenBruce L MillerWilliam P DillonDavid M WilsonChristopher P HessMargaret Pericak-VanceJonathan L HainesLindsay A FarrerRichard MayeuxJohn HardyAlison M GoateBradley T HymanGerard D SchellenbergLinda K McEvoyOle A AndreassenAnders M Dale<h4>Background</h4>Identifying individuals at risk for developing Alzheimer disease (AD) is of utmost importance. Although genetic studies have identified AD-associated SNPs in APOE and other genes, genetic information has not been integrated into an epidemiological framework for risk prediction.<h4>Methods and findings</h4>Using genotype data from 17,008 AD cases and 37,154 controls from the International Genomics of Alzheimer's Project (IGAP Stage 1), we identified AD-associated SNPs (at p < 10-5). We then integrated these AD-associated SNPs into a Cox proportional hazard model using genotype data from a subset of 6,409 AD patients and 9,386 older controls from Phase 1 of the Alzheimer's Disease Genetics Consortium (ADGC), providing a polygenic hazard score (PHS) for each participant. By combining population-based incidence rates and the genotype-derived PHS for each individual, we derived estimates of instantaneous risk for developing AD, based on genotype and age, and tested replication in multiple independent cohorts (ADGC Phase 2, National Institute on Aging Alzheimer's Disease Center [NIA ADC], and Alzheimer's Disease Neuroimaging Initiative [ADNI], total n = 20,680). Within the ADGC Phase 1 cohort, individuals in the highest PHS quartile developed AD at a considerably lower age and had the highest yearly AD incidence rate. Among APOE ε3/3 individuals, the PHS modified expected age of AD onset by more than 10 y between the lowest and highest deciles (hazard ratio 3.34, 95% CI 2.62-4.24, p = 1.0 × 10-22). In independent cohorts, the PHS strongly predicted empirical age of AD onset (ADGC Phase 2, r = 0.90, p = 1.1 × 10-26) and longitudinal progression from normal aging to AD (NIA ADC, Cochran-Armitage trend test, p = 1.5 × 10-10), and was associated with neuropathology (NIA ADC, Braak stage of neurofibrillary tangles, p = 3.9 × 10-6, and Consortium to Establish a Registry for Alzheimer's Disease score for neuritic plaques, p = 6.8 × 10-6) and in vivo markers of AD neurodegeneration (ADNI, volume loss within the entorhinal cortex, p = 6.3 × 10-6, and hippocampus, p = 7.9 × 10-5). Additional prospective validation of these results in non-US, non-white, and prospective community-based cohorts is necessary before clinical use.<h4>Conclusions</h4>We have developed a PHS for quantifying individual differences in age-specific genetic risk for AD. Within the cohorts studied here, polygenic architecture plays an important role in modifying AD risk beyond APOE. With thorough validation, quantification of inherited genetic variation may prove useful for stratifying AD risk and as an enrichment strategy in therapeutic trials.https://doi.org/10.1371/journal.pmed.1002258
spellingShingle Rahul S Desikan
Chun Chieh Fan
Yunpeng Wang
Andrew J Schork
Howard J Cabral
L Adrienne Cupples
Wesley K Thompson
Lilah Besser
Walter A Kukull
Dominic Holland
Chi-Hua Chen
James B Brewer
David S Karow
Karolina Kauppi
Aree Witoelar
Celeste M Karch
Luke W Bonham
Jennifer S Yokoyama
Howard J Rosen
Bruce L Miller
William P Dillon
David M Wilson
Christopher P Hess
Margaret Pericak-Vance
Jonathan L Haines
Lindsay A Farrer
Richard Mayeux
John Hardy
Alison M Goate
Bradley T Hyman
Gerard D Schellenberg
Linda K McEvoy
Ole A Andreassen
Anders M Dale
Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score.
PLoS Medicine
title Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score.
title_full Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score.
title_fullStr Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score.
title_full_unstemmed Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score.
title_short Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score.
title_sort genetic assessment of age associated alzheimer disease risk development and validation of a polygenic hazard score
url https://doi.org/10.1371/journal.pmed.1002258
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