To determine if AD symptom count was associated with any single, common variant, we performed single locus tests on all common variants passing QC filters using a linear regression model of additive effects in PLINK (Purcell et al., 2007) for the VTASBD and MTFS separately. Sex, age and 10 ancestry principal components (PCs; see Supplemental Material) were included as covariates to control for sex differences and ancestry. The results from each dataset were then meta-analyzed using a fixed effects model in PLINK (Purcell et al., 2007). We used a false discovery rate (FDR) based approach to declare significance (Supplemental Material). Briefly, we set an FDR threshold of 0.10 (van den Oord and Sullivan, 2003) for declaring genome-wide significance that was implemented using q-values (Black, 2004), which are FDRs calculated using the p-value of the markers as thresholds for declaring significance.
