Understanding the genetic determinants of the brain with MOSTest

Regional brain morphology has a complex genetic architecture, consisting of many common polymorphisms with small individual effects. This has proven challenging for genome-wide association studies (GWAS). Due to the distributed nature of genetic signal across brain regions, multivariate analysis of regional measures may enhance discovery of genetic variants. Current multivariate approaches to GWAS are ill-suited for complex, large-scale data of this kind. Here, we introduce the Multivariate Omnibus Statistical Test (MOSTest), with an efficient computational design enabling rapid and reliable inference, and apply it to 171 regional brain morphology measures from 26,502 UK Biobank participants. At the conventional genome-wide significance threshold of α = 5 × 10-8, MOSTest identifies 347 genomic loci associated with regional brain morphology, more than any previous study, improving upon the discovery of established GWAS approaches more than threefold. Our findings implicate more than 5% of all protein-coding genes and provide evidence for gene sets involved in neuron development and differentiation.U24 DA041147 - NIDA NIH HHS; U01 DA051039 - NIDA NIH HHS; U24 DA041123 - NIDA NIH HHS; U01 DA041022 - NIDA NIH HHS; U01 DA041106 - NIDA NIH HHS; U01 DA041148 - NIDA NIH HHS; MC_PC_17228 - Medical Research Council; U01 DA041174 - NIDA NIH HHS; MC_QA137853 - Medical Research Council; U01 DA041093 - NIDA NIH HHS; U01 DA041025 - NIDA NIH HHS; U01 DA050989 - NIDA NIH HHSPublished versio