Meta-analyzed GWAS results (separately by population) from the discovery and SAGE datasets were used to identify biological pathways related to OD. First, the number of independent SNP association tests for each gene in the genome was computed according to the method of Li and Ji (20). Next, the smallest p-value for an individual SNP within each gene was multiplied by the number of independent tests in that gene to create a list of genes significantly associated with OD after correcting for the number of tests within that gene (Padj<0.05). The significant genes were evaluated by pathway analysis, performed using the Ingenuity Pathway Analysis (IPA) software suite (http://www.ingenuity.com) to identify an overrepresentation of selected genes within canonical pathways that were defined using information culled from multiple sources (Kyoto Encyclopedia of Genes and Genomes, interactome studies, manual curation, etc). A Fisher’s exact p-value for each pathway indicated whether the pathway contained more significantly associated genes than expected by chance. To validate the findings, we uploaded the same gene list into the Database for Annotation, Visualization and Integrated Discovery (DAVID; http://www.david.niaid.nih.gov) and performed a gene enrichment analysis using its functional annotation tools.
