While the majority of genome-wide association studies (GWAS) have focused on agnostic or “hypothesis-free” testing of associations with genomic variants, few studies have focused on variants with prior genome-wide associations to major complex diseases and traits to identify potential pleiotropic effects and common pathologic mechanisms between different diseases. As part of custom genotyping in the replication phase of a major LOAD GWAS meta-analysis, we genotyped and analyzed 1,099 autosomal SNPs from a catalog of GWAS associations in 8,042 cases and 9,387 controls in order to identify potentially pleiotropic effects of these variants on LOAD risk. We selected GWAS hits from the NHGRI GWAS Catalog (downloaded 07/01/11) for paneling on the Illumina iSelect custom microarray, excluding those in known CNVs or non-autosomal (n=97), associations of P>5.0×10 -8 (n=2,547), previous association with AD (n=21), or identification in a non-Caucasian sample (n=850), leaving 1,099 variants. After genotyping, 974 GWAS SNPs and 17,429 Caucasian subjects from the USA, Canada, and 9 countries in Europe passed QC. We performed logistic regression on LOAD risk modeling genetic effects additively with covariate adjustment for population substructure, sex, and age. Analyses were stratified by country of origin, and resulting country-specific associations were meta-analyzed. Nine GWAS SNPs demonstrated statistically significant associations after Bonferroni correction (P<5×10 -5) and limited evidence of heterogeneity (P>0.05). These variants were associated with chronic kidney disease (P =1.65×10 -7), cardiac QT interval (P =2.85×10 -6), HIV-1 non-progression (P =5.99×10 -6), rheumatoid arthritis (P =3.40×10 -5), glycated hemoglobin levels (P =3.53×10 -5), and plasma eosinophil count (P =4.20×10 -5). Three variants in the MHC region associated with LOAD also had previous associations with chronic lymphocytic leukemia (P =2.75×10 -5), HIV-1 non-progression (P =3.07×10 -5), and ankylosing spondylitis (P =3.21×10 -5). Testing association of 974 SNPs with LOAD identified potential pleiotropic effects of at least nine SNPs, including variants previously associated with heart disease and multiple autoimmune diseases. While some of these conditions share some common pathologic characteristics with LOAD, further analyses of these SNPs in other studies is necessary to replicate and confirm these potentially pleiotropic effects.