Alzheimer’s Disease Polygenic Risk in the LEADS Cohort

Background Currently, it is unclear to what extent late‐onset Alzheimer’s disease (AD) risk variants contribute to early‐onset AD (EOAD). One method to clarify the contribution of late‐onset AD genetic risk to EOAD is to investigate the association of AD polygenic risk scores (PRS) with EOAD. We hypothesize that in the Longitudinal Early‐Onset Alzheimer’s Disease Study (LEADS), EOAD participants will have greater PRS than early‐onset amyloid‐negative cognitively‐impaired participants (EOnonAD) and controls, and investigate the association of AD PRS with age of disease onset (AoO) and cognitive performance. Methods GWAS data was generated for LEADS participants, including those with EOAD, EOnonAD, and controls, with the Illumina Global Screening Array. A PRS was calculated using the 31 SNPs and weights published previously by Desikan et al. (2017) for LEADS participants with imputed GWAS data (N = 369). Logistic regression models including age, sex, PRS, and genetic ancestry principal components were tested to identify predictors of EOAD (N = 210) vs. EOnonAD (N = 69) and controls (N = 89). ANCOVA models were used to assess group differences in PRS scores. Kaplan‐Meier regression was used to assess differences in EOAD AoO for tertile‐binned PRS groups. Within EOAD, pre‐calculated cognitive domain scores for speed and attention, working memory, episodic memory, language, and visuospatial performance were assessed for correlation with PRS. Results The AD PRS was a predictor of EOAD (p = 0.014), with the model explaining 10.5% of variance (X2 = 40.971, p