Gene and gene-set analyses

A gene-based analysis was applied to the results from our meta-analysis using Multi-marker Analysis of GenoMic Annotation (MAGMA) ¹⁴ to assess the simultaneous effect of multiple genetic variants on 17,842 genes. To account for LD the European panel of the 1,000 Genomes data (phase 3) ⁸⁰ was used as a reference panel. Genetic variants were assigned to genes based on their position according to the NCBI 37.3 build. To identify those genes that were genome-wide significant a P-value threshold was calculated by applying a Bonferroni correction (α = 0.05 / 17,842; P < 2.80 × 10^-6). Regional visualisation plots were produced using the online LocusZoom platform⁸¹.

A gene-set analysis was then performed on our gene-based results using gene annotation files from the Gene Ontology Consortium (http://geneontology.org/) ⁸² and the Molecular Signatures Database v5.2 ⁸³. The annotation file includes gene-sets covering three ontologies; molecular function, cellular components, and biological function and consisted of 5,917 gene-sets. To correct for multiple testing, we used the MAGMA default setting of 10,000 permutations, and applied a Bonferroni correction (α = 0.05 / 5,917; P < 8.45 × 10^-6). Additional gene-sets were obtained from Skene, et al. ¹⁵ providing expression-weighted enrichment for seven brain cell-types (astrocytes ependymal, endothelial mural, interneurons, microglia, oligodendrocytes, somatosensory pyramidal neurons, and hippocampus CA1 pyramidal neurons). These brain cell-types were assessed in MAGMA using the default setting of 10,000 permutations with a Bonferroni correction (α = 0.05 / 7; P < 7.14 × 10^-3) used to assess significance.