The goal of this report was to test a new method for the detection of small effect risk variants for complex neuropsychiatric disorders. We proposed 7 gene sets based on a priori biological hypotheses and tested these sets for their impact on risk for AD. Using the standard Benjamini-Hochberg FDR procedure, we identified four gene sets significantly associated with AD with at an FDR of 10%, indicating a low likelihood of their being false discoveries. In contrast, no individual SNP in any of the selected gene sets would have been selected in a chip-wide study at an FDR less than 40%. If we had hypothesized a priori that our candidate genes would belong to one of the seven groups tested and restricted our single locus tests to those SNPs only, then we would have had only one SNP significant at an FDR of 0.2, (which would also be a Bonferroni-corrected p-value of 0.2), but none at an FDR of 0.15.
