Multivariate genome-wide association study identifies 780 unique genetic loci associated with cortical morphology.
Alexey A. ShadriniD, Tobias KaufmanniD, Dennis van der MeeriD, Clare E. PalmeriD, Carolina MakowskiiD, Robert J. LoughnaniD, Terry L. JerniganiD, Tyler M. SeibertiD, Donald J. HagleriD, Olav Bjerkehagen SmelandiD, Ehsan MotazediiD, Yunhan Chu, Aihua Lin, Weiqiu ChengiD, Guy HindleyiD, Wesley Kurt ThompsoniD, Chun Chieh FaniD, Dominic HollandiD, Lars Tjelta WestlyeiD, Oleksandr FreiiD, Ole A. AndreasseniD, Anders Martin DaleiD
Abstract
Brain morphology has been shown to be highly heritable, yet only a small portion of the heritability is explained by the genetic variants discovered so far. Here we exploit the distributed nature of genetic effects across the brain and apply the Multivariate Omnibus Statistical Test (MOSTest) to genome-wide association studies (GWAS) of vertex-wise structural magnetic resonance imaging (MRI) cortical measures from N=35,657 participants in the UK Biobank. We identified 695 loci for cortical surface area and 539 for cortical thickness, in total 780 unique genetic loci associated with cortical morphology. This reflects an approximate 10-fold increase compared to the commonly applied univariate GWAS methods. Power analysis indicates that applying MOSTest to vertex-wise structural MRI data triples the effective sample size compared to conventional univariate GWAS approaches. Functional follow up including gene-based analyses implicate 10% of all protein-coding genes and point towards pathways involved in neurogenesis and cell differentiation.
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