Cited by 395Alzheimer's disease research and treatmentsDementia and Cognitive Impairment ResearchGenetic Associations and Epidemiology

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

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Desikan, Rahul S., Fan, Chun Chieh, Wang, Yunpeng, Schork, Andrew J., Cabral, Howard J., Cupples, L. Adrienne, Thompson, Wesley K., Besser, Lilah +26 more·2017·PLoS Medicine

Published version of a preprint

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.

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  • Expanding PRS to include variants below the genome-wide statistical cutoff allows for a more complete view of the genetic contribution to disease risk and seems to provide an improved method for risk prediction over more selective PRS or standard predictors such as APOEε4 alleles, age, and sex.

    “risk and seems to provide an improved method for risk prediction over more selective PRS or standard predictors such as APOEε4 alleles, age, and sex [118, 122, 123].”

    From Genetic architecture of Alzheimer's disease (2020) · cites this paper as [118]

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Authors
Desikan, R. S., Fan, C. C., Wang, Y., Schork, A. J., Cabral, H. J., Cupples, L. A., Thompson, W. K., Besser, L., Kukull, W. A., Holland, D., Chen, C.-H., Brewer, J. B., Karow, D. S., Kauppi, K., Witoelar, A., Karch, C. M., Bonham, L. W., Yokoyama, J. S., Rosen, H. J., Miller, B. L., Dillon, W. P., Wilson, D. M., Hess, C. P., Pericak-Vance, M., Haines, J. L., Farrer, L. A., Mayeux, R., Hardy, J., Goate, A. M., Hyman, B. T., Schellenberg, G. D., McEvoy, L. K., Andreassen, O. A., & Dale, A. M.
Affiliations
  • University of California, San Francisco (US)
  • University of California San Diego (US)
  • Oslo University Hospital (NO)
  • Boston University (US)
  • Sankt Hans Hospital (DK)
  • University of Washington (US)
  • Washington University in St. Louis (US)
  • Case Western Reserve University (US)
  • Columbia University (US)
  • UCL Queen Square Institute of Neurology (GB)
  • Icahn School of Medicine at Mount Sinai (US)
  • Massachusetts General Hospital (US)
  • University of Pennsylvania (US)
Corresponding author
  • Desikan, Rahul S.
  • Andreassen, Ole A.
  • Dale, Anders M.
Venue
PLoS Medicine
Published
2017-03-21
Volume
14
Issue
3
Pages
e1002258
ISSN
  • 1549-1277 (ISSN-L)
  • 1549-1676
OpenAlex
W2600084629
Cited by
395
References
36
Citations by year
2026: 18 · 2025: 21 · 2024: 39 · 2023: 35 · 2022: 44 · 2021: 64 · 2020: 43 · 2019: 66 · 2018: 44 · 2017: 19 · 2016: 1 · 2013: 1
FWCI
34.82
Type
journal article
Language
en
Open access
Locations
  • PLoS Medicine (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • UCL Discovery (University College London) (submittedVersion)
  • Figshare (submittedVersion, cc-by)
  • Columbia Academic Commons (Columbia University)
Funders
  • National Institutes of Health (NIH-AG046374, K01AG049152, R01MH100351)
  • National Alzheimer's Coordinating Center
  • Radiological Society of North America
  • Foundation of the American Society of Neuroradiology
  • Norges Forskningsråd ((#213837, #225989, #223273, #237250/EU JPND)
  • South East Norway Health Authority (2013-123)
  • Norske Kvinners Sanitetsforening
  • KG Jebsen Foundation
Topics
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Keywords
Alzheimer's disease, polygenic hazard score, genetic risk prediction, age of onset, Cox proportional hazards model, neurofibrillary tangles, neuritic plaques, entorhinal cortex atrophy, amygdala atrophy, hippocampal atrophy, APOE ε4, APOE ε2
MeSH terms
Aged, Aged, 80 and over, Alzheimer Disease, Apolipoproteins E, Female, Genotype, Humans, Longitudinal Studies, Male, Middle Aged, United States, Geriatric Assessment, Multifactorial Inheritance, Polymorphism, Single Nucleotide

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