UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

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

Desikan, RS; Fan, CC; Wang, Y; Schork, AJ; Cabra, HJ; Cupples, LA; Thompson, WK; ... Dale, AM; + view all (2017) Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score. PLOS Medicine , 14 (3) , Article e1002258. 10.1371/journal.pmed.1002258. Green open access

[thumbnail of Published article]
Preview
Text (Published article)
Hardy_journal.pmed.1002258.pdf - Published Version

Download (1MB) | Preview
[thumbnail of Supplemental methods and figures]
Preview
Text (Supplemental methods and figures)
Desikan_Genetic_assessment_age-associated_Suppl.pdf

Download (719kB) | Preview
[thumbnail of Supplemental acknowledgments and funding information]
Preview
Text (Supplemental acknowledgments and funding information)
Desikan_Genetic_assessment_age-associated_Acknowledgements.pdf

Download (291kB) | Preview
[thumbnail of TRIPOD checklist]
Preview
Text (TRIPOD checklist)
Desikan_Genetic_assessment_age-associated_Checklist.pdf

Download (97kB) | Preview
[thumbnail of Supplementary table] Text (Supplementary table)
Desikan_Genetic_assessment_age-associated_Table.csv

Download (31kB)

Abstract

BACKGROUND: 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. METHODS AND FINDINGS: 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. CONCLUSIONS: 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.

Type: Article
Title: Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score
Open access status: An open access version is available from UCL Discovery
DOI: 10.1371/journal.pmed.1002258
Publisher version: http://dx.doi.org/10.1371/journal.pmed.1002258
Language: English
Additional information: Copyright © 2017 Desikan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Neurodegenerative Diseases
URI: https://discovery.ucl.ac.uk/id/eprint/1549954
Downloads since deposit
533Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item