Expression quantitative trait loci-derived scores and white matter microstructure in UK Biobank: a novel approach to integrating genetics and neuroimaging
Open Access
- 4 February 2020
- journal article
- research article
- Published by Springer Science and Business Media LLC in Translational Psychiatry
- Vol. 10 (1), 1-12
- https://doi.org/10.1038/s41398-020-0724-y
Abstract
Expression quantitative trait loci (eQTL) are genetic variants associated with gene expression. Using genome-wide genotype data, it is now possible to impute gene expression using eQTL mapping efforts. This approach can be used to analyse previously unexplored relationships between gene expression and heritable in vivo measures of human brain structural connectivity. Using large-scale eQTL mapping studies, we computed 6457 gene expression scores (eQTL scores) using genome-wide genotype data in UK Biobank, where each score represents a genetic proxy measure of gene expression. These scores were then tested for associations with two diffusion tensor imaging measures, fractional anisotropy (NFA = 14,518) and mean diffusivity (NMD = 14,485), representing white matter structural integrity. We found FDR-corrected significant associations between 8 eQTL scores and structural connectivity phenotypes, including global and regional measures (βabsolute FA = 0.0339–0.0453; MD = 0.0308–0.0381) and individual tracts (βabsolute FA = 0.0320–0.0561; MD = 0.0295–0.0480). The loci within these eQTL scores have been reported to regulate expression of genes involved in various brain-related processes and disorders, such as neurite outgrowth and Parkinson’s disease (DCAKD, SLC35A4, SEC14L4, SRA1, NMT1, CPNE1, PLEKHM1, UBE3C). Our findings indicate that eQTL scores are associated with measures of in vivo brain connectivity and provide novel information not previously found by conventional genome-wide association studies. Although the role of expression of these genes regarding white matter microstructural integrity is not yet clear, these results suggest it may be possible, in future, to map potential trait- and disease-associated eQTL to in vivo brain connectivity and better understand the mechanisms of psychiatric disorders and brain traits, and their associated imaging findings.Funding Information
- Wellcome Trust (104036/Z/14/Z)
This publication has 52 references indexed in Scilit:
- Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlapScience, 2018
- Systematic Integration of Brain eQTL and GWAS IdentifiesZNF323as a Novel Schizophrenia Risk Gene and Suggests Recent Positive Selection Based on Compensatory Advantage on Pulmonary FunctionSchizophrenia Bulletin, 2015
- Expression quantitative trait loci: present and futurePhilosophical Transactions B, 2013
- Integration of GWAS SNPs and tissue specific expression profiling reveal discrete eQTLs for human traits in blood and brainNeurobiology of Disease, 2012
- Expression QTL analysis of top loci from GWAS meta-analysis highlights additional schizophrenia candidate genesEuropean Journal of Human Genetics, 2012
- Revealing the architecture of gene regulation: the promise of eQTL studiesTrends in Genetics, 2008
- The evolutionary significance of cis-regulatory mutationsNature Reviews Genetics, 2007
- Genome-Wide Associations of Gene Expression Variation in HumansPLoS Genetics, 2005
- Subjects with major depression or bipolar disorder show reduction of prodynorphin mRNA expression in discrete nuclei of the amygdaloid complexMolecular Psychiatry, 2002
- Differential messenger RNA expression of prodynorphin and proenkephalin in the human brainNeuroscience, 1996