Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.
Transl Psychiatry. 2020 Feb 4;10(1):55. doi: 10.1038/s41398-020-0724-y.
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 (N = 14,518) and mean diffusivity (N = 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 (β FA = 0.0339-0.0453; MD = 0.0308-0.0381) and individual tracts (β 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.
表达数量性状基因座 (eQTL) 是与基因表达相关的遗传变异。利用全基因组基因型数据,现在可以通过 eQTL 图谱绘制来推断基因表达。这种方法可用于分析基因表达与遗传性活体人脑结构连接性之间以前未探索的关系。我们使用大规模 eQTL 图谱研究,使用 UK Biobank 中的全基因组基因型数据计算了 6457 个基因表达分数(eQTL 分数),每个分数代表基因表达的遗传代理测量值。然后,我们测试了这些分数与两种扩散张量成像测量值(各向异性分数 (FA) 和平均弥散度 (MD))之间的关联,这些测量值代表了白质结构完整性。我们发现,8 个 eQTL 分数与结构连接性表型之间存在 FDR 校正显著关联,包括全局和区域测量值(FA:0.0339-0.0453;MD:0.0308-0.0381)和个体束(FA:0.0320-0.0561;MD:0.0295-0.0480)。这些 eQTL 分数中的基因座已被报道可调节与各种与大脑相关的过程和疾病相关的基因的表达,如轴突生长和帕金森病(DCAKD、SLC35A4、SEC14L4、SRA1、NMT1、CPNE1、PLEKHM1、UBE3C)。我们的研究结果表明,eQTL 分数与活体脑连接性测量值相关,并提供了以前通过传统全基因组关联研究未发现的新信息。虽然这些基因表达对白质微观结构完整性的作用尚不清楚,但这些结果表明,未来可能可以将潜在的与特征和疾病相关的 eQTL 映射到活体脑连接性上,并更好地理解精神疾病和脑特征及其相关成像发现的机制。