ABSTRACT Importance Identifying individuals at risk for developing Alzheimer’s disease (AD) is of utmost importance. Although genetic studies have identified APOE and other AD associated single nucleotide polymorphisms (SNPs), genetic information has not been integrated into an epidemiological framework for personalized risk prediction. Objective To develop, replicate and validate a novel polygenic hazard score for predicting age-specific risk for AD. Setting Multi-center, multi-cohort genetic and clinical data. Participants We assessed genetic data from 17,008 AD patients and 37,154 controls from the International Genetics of Alzheimer’s Project (IGAP), and 6,409 AD patients and 9,386 older controls from Phase 1 Alzheimer’s Disease Genetics Consortium (ADGC). As independent replication and validation cohorts, we also evaluated genetic, neuroimaging, neuropathologic, CSF and clinical data from ADGC Phase 2, National Institute of Aging Alzheimer’s Disease Center (NIA ADC) and Alzheimer’s Disease Neuroimaging Initiative (ADNI) (total n = 20,680) Main Outcome(s) and Measure(s) Use the IGAP cohort to first identify AD associated SNPs (at p &lt; 10 -5 ). Next, integrate these AD associated SNPs into a Cox proportional hazards model using ADGC phase 1 genetic data, providing a polygenic hazard score (PHS) for each participant. Combine population based incidence rates, and genotype-derived PHS for each individual to derive estimates of instantaneous risk for developing AD, based on genotype and age. Finally, assess replication and validation of PHS in independent cohorts. Results Individuals in the highest PHS quantiles developed AD at a considerably lower age and had the highest yearly AD incidence rate. Among APOE ε3/3 individuals, PHS modified expected age of AD onset by more than 10 years between the lowest and highest deciles. In independent cohorts, PHS strongly predicted empirical age of AD onset (p = 1.1 x 10 -26 ), longitudinal progression from normal aging to AD (p = 1.54 x 10 -10 ) and associated with markers of AD neurodegeneration. Conclusions We developed, replicated and validated a clinically usable PHS for quantifying individual differences in age-specific risk of AD. Beyond APOE , polygenic architecture plays an important role in modifying AD risk. Precise quantification of AD genetic risk will be useful for early diagnosis and therapeutic strategies.

Personalized genetic assessment of age associated Alzheimer’s disease risk