Significant advances in the identification of risk loci for AD in the past decade can be largely attributed to the advent of genome-wide association studies (GWAS). However, the individual loci that have been identified explain just a fraction of the variance in AD risk. This has led to efforts to exploit GWAS data using different analytic approaches, including studies of the heritability, risk prediction, and pathways involved in AD.
