Gene and pathway analyses were completed using MAGMA (Multi-marker Analysis of GenoMic Annotation)26 and default parameters as in the manual (version 1.06). Gene and pathway analyses were conducted on the 16 data sets with individual-level genotype data (versus SNP-level P-values) so that we could control for ancestry using PCs. This was particularly important for the AA, LA and South African samples given poorer external sequence data resources that are needed for the option that uses summary statistics. Thus, we performed gene-based analyses on each of the 16 data sets with genotype data and PCs, followed by pathway analyses on the gene-level results (as per MAGMA procedures). For completeness we also then used the summary statistic method on the three remaining data sets for which raw data were not available, and meta-analyzed (at the gene level, per MAGMA procedures) with the other 16 data sets. Like de Leeuw et al.,26 we used the MSigDB Canonical Pathways because this list contains a wide variety of gene sets, drawn from different gene-set databases, thus providing results that are not overly dependent on the choice of a narrow set of gene sets.
