Common genetic variation influencing human white matter microstructure

INTRODUCTION

White matter in the human brain serves a critical role in organizing distributed neural networks. Diffusion magnetic resonance imaging (dMRI) has enabled the study of white matter in vivo, showing that interindividual variations in white matter microstructure are associated with a wide variety of clinical outcomes. Although white matter differences in general population cohorts are known to be heritable, few common genetic variants influencing white matter microstructure have been identified.

RATIONALE

To identify genetic variants influencing white matter microstructure, we conducted a genome-wide association study (GWAS) of dMRI data from 43,802 individuals across five data resources. We analyzed five major diffusion tensor imaging (DTI) model–derived parameters along 21 cerebral white matter tracts.

RESULTS

In the discovery GWAS with 34,024 individuals of British ancestry, we replicated 42 of the 44 genomic regions discovered in the largest previous GWAS and identified 109 additional regions associated with white matter microstructure (P < 2.3 × 10⁻¹⁰, adjusted for the number of phenotypes studied). These results indicate strong polygenic influences on white matter microstructure. Of the 151 regions, 52 passed the Bonferroni significance level (P < 5 × 10⁻⁵) in our analysis of nine independent validation datasets, including four with subjects of non-European ancestry.

On average, common genetic variants explained 41% (standard error = 2%) of the variation in white matter microstructure. The 151 identified genomic regions can explain 32.3% of heritability for white matter microstructure, whereas the 44 previously identified genomic regions can only explain 11.7% of heritability. As a biological validation of our GWAS findings, we observed heritability enrichment within regulatory elements active in oligodendrocytes and other glia, whereas no enrichment was observed in neurons. These results are expected and suggest that genetic variation leads to changes in white matter microstructure by affecting gene regulation in glia.

We observed genetic correlations and colocalizations of white matter microstructure with a wide range of brain-related complex traits and diseases, such as cognitive functions, cardiovascular risk factors, as well as various neurological and psychiatric diseases. For example, of the 25 reported genetic risk regions of glioma, 11 were also associated with white matter microstructure, which illustrates the close genetic relationship between glioma and white matter integrity. Additionally, we found that 14 white matter microstructure–associated genes (P < 1.2 × 10⁻⁸) were targets for 79 commonly used nervous system drugs, such as antipsychotics, antidepressants, anticonvulsants, and drugs for Parkinson’s disease and dementia.

CONCLUSION

This large-scale study of dMRI scans from 43,802 subjects improved our understanding of the highly polygenic genetic architecture of human brain white matter tracts. We identified 151 genomic regions associated with white matter microstructure. The GWAS findings were supported by enrichments within cell types that make up white matter microstructure. Moreover, we uncovered genetic relationships between white matter and various clinical endpoints, such as stroke, major depressive disorder, schizophrenia, and attention deficit hyperactivity disorder. The targets of many drugs commonly used for disabling cognitive disorders have genetic associations with white matter, which suggests that the neuropharmacology of many disorders can potentially be improved by studying how these medications work in the brain white matter.