Evaluation of a Genetic Risk Score to Improve Risk Prediction for Alzheimer's Disease

Effective prevention of Alzheimer's disease (AD) requires the development of risk prediction tools permitting preclinical intervention. We constructed a genetic risk score (GRS) comprising common genetic variants associated with AD, evaluated its association with incident AD and assessed its capacity to improve risk prediction over traditional models based on age, sex, education, and APOE epsilon 4. In eight prospective cohorts included in the International Genomics of Alzheimer's Project (IGAP), we derived weighted sum of risk alleles from the 19 top SNPs reported by the IGAPGWAS in participants aged 65 and older without prevalent dementia. Hazard ratios (HR) of incident AD were estimated in Cox models. Improvement in risk prediction was measured by the difference in C-index (Delta-C), the integrated discrimination improvement (IDI) and continuous net reclassification improvement (NRI>0). Overall, 19,687 participants at risk were included, of whom 2,782 developed AD. The GRS was associated with a 17% increase in AD risk (pooled HR=1.17; 95% CI = [1.13-1.21] per standard deviation increase in GRS; p-value = 2.86x10(-16)). This association was stronger among persons with at least one APOE epsilon 4 allele (HRGRS = 1.24; 95% CI = [1.15-1.34]) than in others (HRGRS = 1.13; 95% CI = [1.08-1.18]; p(interaction) = 3.45x10(-2)). Risk prediction after seven years of follow-up showed a small improvement when adding the GRS to age, sex, APOE epsilon 4, and education (Delta-Cindex = 0.0043 [0.0019-0.0067]). Similar patterns were observed for IDI and NRI>0. In conclusion, a risk score incorporating common genetic variation outside the APOE epsilon 4 locus improved AD risk prediction and may facilitate risk stratification for prevention trials.