Becker Martin, Guadalupe Tulio, Franke Barbara, Hibar Derrek P, Renteria Miguel E, Stein Jason L, Thompson Paul M, Francks Clyde, Vernes Sonja C, Fisher Simon E
Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands.
Donders Institute for Brain, Cognition and Behaviour, Nijmegen, the Netherlands.
Hum Brain Mapp. 2016 May;37(5):1788-800. doi: 10.1002/hbm.23136. Epub 2016 Feb 18.
Genome-wide association screens aim to identify common genetic variants contributing to the phenotypic variability of complex traits, such as human height or brain morphology. The identified genetic variants are mostly within noncoding genomic regions and the biology of the genotype-phenotype association typically remains unclear. In this article, we propose a complementary targeted strategy to reveal the genetic underpinnings of variability in subcortical brain volumes, by specifically selecting genomic loci that are experimentally validated forebrain enhancers, active in early embryonic development. We hypothesized that genetic variation within these enhancers may affect the development and ultimately the structure of subcortical brain regions in adults. We tested whether variants in forebrain enhancer regions showed an overall enrichment of association with volumetric variation in subcortical structures of >13,000 healthy adults. We observed significant enrichment of genomic loci that affect the volume of the hippocampus within forebrain enhancers (empirical P = 0.0015), a finding which robustly passed the adjusted threshold for testing of multiple brain phenotypes (cutoff of P < 0.0083 at an alpha of 0.05). In analyses of individual single nucleotide polymorphisms (SNPs), we identified an association upstream of the ID2 gene with rs7588305 and variation in hippocampal volume. This SNP-based association survived multiple-testing correction for the number of SNPs analyzed but not for the number of subcortical structures. Targeting known regulatory regions offers a way to understand the underlying biology that connects genotypes to phenotypes, particularly in the context of neuroimaging genetics. This biology-driven approach generates testable hypotheses regarding the functional biology of identified associations. Hum Brain Mapp 37:1788-1800, 2016. © 2016 Wiley Periodicals, Inc.
全基因组关联筛查旨在识别导致复杂性状（如人类身高或脑形态）表型变异的常见遗传变异。所识别的遗传变异大多位于非编码基因组区域，基因型与表型关联的生物学机制通常仍不清楚。在本文中，我们提出了一种互补的靶向策略，通过专门选择在早期胚胎发育中活跃且经过实验验证的前脑增强子的基因组位点，来揭示皮质下脑容量变异的遗传基础。我们假设这些增强子内的遗传变异可能影响成年人皮质下脑区的发育并最终影响其结构。我们测试了前脑增强子区域的变异是否在超过13000名健康成年人的皮质下结构体积变异中总体上呈现关联富集。我们观察到在前脑增强子中影响海马体体积的基因组位点有显著富集（经验P值 = 0.0015），这一发现稳健地通过了对多种脑表型测试的校正阈值（在α = 0.05时，截断值为P < 0.0083）。在对单个单核苷酸多态性（SNP）的分析中，我们确定ID2基因上游的一个位点与rs7588305以及海马体体积变异存在关联。这种基于SNP的关联在对所分析SNP数量进行多重检验校正后仍然存在，但对皮质下结构数量的校正后不存在。靶向已知调控区域提供了一种理解将基因型与表型联系起来的潜在生物学机制的方法，特别是在神经影像遗传学的背景下。这种由生物学驱动的方法产生了关于已识别关联的功能生物学的可测试假设。《人类大脑图谱》37:1788 - 1800, 2016。© 2016威利期刊公司。
