To obtain a more accurate estimate of AD variance explained by genome-wide markers, we conducted variance component analysis using the method proposed by the Yang et al. (2010). Based on this approach, we estimate from our LD-pruned GWAS data that 37.8% (s.e. = 10.4%) and 35.1% (s.e. = 27.8%) of the variation in AD risk is captured by common SNPs in EAs and AAs, respectively (Table S2). Although the heritability of AD is not fully recovered in these results, at least for the larger heritability estimates when one considers the substantial standard errors, it is reasonable that any unaccounted, additive genetic variation could be “hidden” from our statistical purview due to causal variants not being in strong LD with the GWAS markers, with the most probable candidates being those with small MAFs (Purcell et al. 2009; Visscher et al. 2012).
