To obtain more detailed insight into height biology, we applied DEPICT, a novel data-driven integrative method that uses gene sets reconstituted based on large scale expression data to prioritize genes and gene sets, and also to identify tissues enriched in highly expressed genes from associated loci (Pers et al. in preparation; Online Methods and Supplementary Note). The DEPICT analysis highlighted 2,330 reconstituted gene sets (after pruning for high levels of redundancy). These gene sets both confirmed and extended the MAGENTA and GRAIL findings, and identified novel pathways not identified in our previous height GWAS (for example regulation of beta-catenin, biology related to glycosaminoglycans such as chondroitin sulfate and hyaluronic acid, and mTOR signaling) (Supplementary Table 14). Gene sets identified based on 327 strictly novel height variants (>1Mb from the 180 known variants loci) highly resembled gene sets highlighted by the already known 180 loci (Spearman’s rank correlation coefficient between gene set enrichment Z-scores r=0.91, P=2×10−16). Thus, the variants discovered through increased sample size continued to highlight specific and relevant growth-associated gene sets, while the combined analysis of both old and new loci provided the additional power needed to identify new gene sets (Table 3 and Supplementary Table 14).
