Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 950 West Walnut Street R2 E124, Indianapolis, IN 46202, USA.
Neuroimage. 2010 Nov 15;53(3):1051-63. doi: 10.1016/j.neuroimage.2010.01.042. Epub 2010 Jan 25.
A genome-wide, whole brain approach to investigate genetic effects on neuroimaging phenotypes for identifying quantitative trait loci is described. The Alzheimer's Disease Neuroimaging Initiative 1.5 T MRI and genetic dataset was investigated using voxel-based morphometry (VBM) and FreeSurfer parcellation followed by genome-wide association studies (GWAS). One hundred forty-two measures of grey matter (GM) density, volume, and cortical thickness were extracted from baseline scans. GWAS, using PLINK, were performed on each phenotype using quality-controlled genotype and scan data including 530,992 of 620,903 single nucleotide polymorphisms (SNPs) and 733 of 818 participants (175 AD, 354 amnestic mild cognitive impairment, MCI, and 204 healthy controls, HC). Hierarchical clustering and heat maps were used to analyze the GWAS results and associations are reported at two significance thresholds (p<10(-7) and p<10(-6)). As expected, SNPs in the APOE and TOMM40 genes were confirmed as markers strongly associated with multiple brain regions. Other top SNPs were proximal to the EPHA4, TP63 and NXPH1 genes. Detailed image analyses of rs6463843 (flanking NXPH1) revealed reduced global and regional GM density across diagnostic groups in TT relative to GG homozygotes. Interaction analysis indicated that AD patients homozygous for the T allele showed differential vulnerability to right hippocampal GM density loss. NXPH1 codes for a protein implicated in promotion of adhesion between dendrites and axons, a key factor in synaptic integrity, the loss of which is a hallmark of AD. A genome-wide, whole brain search strategy has the potential to reveal novel candidate genes and loci warranting further investigation and replication.
本文描述了一种全基因组、全脑方法，用于研究遗传效应对神经影像学表型的影响，以确定数量性状基因座。使用基于体素的形态测量学 (VBM) 和 FreeSurfer 分割，对阿尔茨海默病神经影像学倡议 1.5T MRI 和遗传数据集进行了研究，随后进行了全基因组关联研究 (GWAS)。从基线扫描中提取了 142 种灰质 (GM) 密度、体积和皮质厚度测量值。使用 PLINK 在每个表型上进行 GWAS，使用经过质量控制的基因型和扫描数据，包括 620,903 个单核苷酸多态性 (SNP) 中的 530,992 个和 818 名参与者中的 733 个 (175 名 AD、354 名遗忘型轻度认知障碍，MCI 和 204 名健康对照，HC)。使用层次聚类和热图分析 GWAS 结果，并在两个显著阈值 (p<10(-7) 和 p<10(-6)) 下报告关联。正如预期的那样，APOE 和 TOMM40 基因中的 SNP 被确认为与多个大脑区域强烈相关的标记。其他顶级 SNP 靠近 EPHA4、TP63 和 NXPH1 基因。rs6463843（侧翼 NXPH1）的详细图像分析显示，与 GG 纯合子相比，TT 相对的所有诊断组的全球和区域 GM 密度均降低。交互分析表明，携带 T 等位基因的 AD 患者对右侧海马 GM 密度丧失的易感性存在差异。NXPH1 编码一种蛋白，该蛋白参与促进树突和轴突之间的粘附，这是突触完整性的关键因素，其丢失是 AD 的标志。全基因组、全脑搜索策略有可能揭示新的候选基因和基因座，值得进一步研究和复制。
