An expanded set of genome-wide association studies of brain imaging phenotypes in UK Biobank

Abstract

UK Biobank is a major prospective epidemiological study, including multimodal brain imaging, genetics and ongoing health outcomes. Previously, we published genome-wide associations of 3,144 brain imaging-derived phenotypes, with a discovery sample of 8,428 subjects. Here we present a new open resource of GWAS summary statistics, using the 2020 data release, almost tripling the discovery sample size. We now include the X chromosome, and new classes of image derived phenotypes (subcortical volumes and tissue contrast). Previously we had found 148 replicated clusters of associations between genetic variants and imaging phenotypes; here we find 692, including 12 on the X chromosome. We describe some of the newly found associations, focussing on the X chromosome and autosomal associations involving the new classes of imaging-derived phenotypes. Our novel associations implicate e.g. pathways involved in the rare X-linked syndrome STAR (syndactyly, telecanthus and anogenital and renal malformations), Alzheimer’s disease and mitochondrial disorders.

Outcome after acute ischemic stroke is linked to sex-specific lesion patterns

“…Therefore, future studies could attempt to gather data on hormonal status, and also to recruit more balanced numbers of men and women of premenopausal and postmenopausal status. In addition, it might be promising to test links between implicated brain regions and sex-specific genetic underpinnings, as was recently introduced for healthy population samples 47 , 48 .…”

From genetics to systems biology of stress-related mental disorders

“…However, these results did not replicate in an independent study ( Dinga et al, 2019 ). The lack of replication, apart from highlighting the general issue of reproducibility in human neuroscience research ( Poldrack, 2019 ), could be attributed to different factors: 1) the poor reproducibility of resting-state fMRI measures due to sample size, duration of scan and hardware configuration ( Noble et al, 2017 , 2019 ); 2) the lack of the genetic component in resting-state fMRI [i.e., low h 2 demonstrated in the large UKBB dataset ( Elliott et al, 2018 ; Smith et al, 2021 )], indicating sensitivity to environment; and 3) the difficulty of obtaining consistent MDD results in the resting-state fMRI ( Xia et al, 2019 ).…”

Genetic overlap between multivariate measures of human functional brain connectivity and psychiatric disorders

“…The copyright holder for this preprint this version posted June22, 2021. ; https://doi.org/10.1101/2021.06.15.21258954 doi: medRxiv preprint Roelfs et al | Genetics of the brain functional connectome 22…”