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Risk prediction of late-onset Alzheimer's disease implies an oligogenic architecture.

TitleRisk prediction of late-onset Alzheimer's disease implies an oligogenic architecture.
Publication TypeJournal Article
Year of Publication2020
AuthorsZhang Q, Sidorenko J, Couvy-Duchesne B, Marioni RE, Wright MJ, Goate AM, Marcora E, Huang K-L, Porter T, Laws SM, Sachdev PS, Mather KA, Armstrong NJ, Thalamuthu A, Brodaty H, Yengo L, Yang J, Wray NR, McRae AF, Visscher PM
Corporate AuthorsAustralian Imaging Biomarkers and Lifestyle(AIBL) Study
JournalNat Commun
Date Published2020 09 23
KeywordsAdult, Age of Onset, Aged, Alzheimer Disease, Female, Genetic Association Studies, Genetic Predisposition to Disease, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Risk Factors

Genetic association studies have identified 44 common genome-wide significant risk loci for late-onset Alzheimer's disease (LOAD). However, LOAD genetic architecture and prediction are unclear. Here we estimate the optimal P-threshold (P) of a genetic risk score (GRS) for prediction of LOAD in three independent datasets comprising 676 cases and 35,675 family history proxy cases. We show that the discriminative ability of GRS in LOAD prediction is maximised when selecting a small number of SNPs. Both simulation results and direct estimation indicate that the number of causal common SNPs for LOAD may be less than 100, suggesting LOAD is more oligogenic than polygenic. The best GRS explains approximately 75% of SNP-heritability, and individuals in the top decile of GRS have ten-fold increased odds when compared to those in the bottom decile. In addition, 14 variants are identified that contribute to both LOAD risk and age at onset of LOAD.

Pubmed Link
Alternate JournalNat Commun
PubMed ID32968074
PubMed Central IDPMC7511365
Grant ListS10 OD018522 / OD / NIH HHS / United States
S10 OD026880 / OD / NIH HHS / United States

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