BrainXcan identifies brain features associated with behavioral and psychiatric traits using large scale genetic and imaging data

Abstract

Advances in brain MRI have enabled many discoveries in neuroscience. Comparison of brain MRI features between cases and controls have highlighted potential causes of psychiatric and behavioral disorders (complex traits). However, due to the cost of collecting MRI data and the difficulty in recruiting particular patient groups, most studies have small sample sizes, limiting their reliability. Furthermore, reverse causality complicates interpretation because many observed brain differences are the result rather than the cause of the disease. Here we propose a method (BrainXcan) that leverages the power of large-scale genome-wide association studies (GWAS) and reference brain MRI data to discover new mechanisms of disease etiology and validate existing ones. BrainXcan tests the association with genetic predictors of brain MRI-derived features and complex traits to pinpoint relevant region-specific and cross-brain features. As this approach requires only genetic data, BrainXcan allows us to test a host of hypotheses on mental illness, across many disorders and MRI modalities, using existing public data resources. For example, our method shows that reduced axonal density across the brain is associated with the risk of schizophrenia, consistent with the disconnectivity hypothesis. We also find structural features in the hippocampus, amygdala, and anterior cingulate cortex, among others associated with schizophrenia risk highlighting the potential of our approach, which uses orthogonal lines of evidence to inform the biology of complex traits.