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Genetic architecture of hippocampal subfields on standard resolution MRI: How the parts relate to the whole

机译:基于标准分辨率MRI的海马亚域的遗传结构:各部分与整体的关系

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摘要

The human hippocampus can be subdivided into subfields with unique functional properties and differential vulnerability to disease or neuropsychiatric conditions. Identifying genes that confer susceptibility to such processes is an important goal in developing treatments. Recent advances in automatic subfield segmentation from magnetic resonance images make it possible to use these measures as phenotypes in large‐scale genome‐wide association studies. Such analyses are likely to rely largely on standard resolution (~1 mm isotropic) T ‐weighted images acquired on 3.0T scanners. Determining whether the genetic architecture of subfields can be detected from such images is therefore an important step. We used Freesurfer v6.0 to segment hippocampal subfields in two large twin studies, the Vietnam Era Twin Study of Aging and the Human Connectome Project. We estimated heritability of subfields and the genetic overlap with total hippocampal volume. Heritability was similar across samples, but little genetic variance remained after accounting for genetic influences on total hippocampal volume. Importantly, we examined genetic relationships between subfields to determine whether subfields can be grouped based on a smaller number of underlying, genetically independent factors. We identified three genetic factors in both samples, but the high degree of cross loadings precluded formation of genetically distinct groupings of subfields. These results confirm the reliability of Freesurfer v6.0 generated subfields across samples for phenotypic analyses. However, the current results suggest that it will be difficult for large‐scale genetic analyses to identify subfield‐specific genes that are distinct from both total hippocampal volume and other subfields using segmentations generated from standard resolution T ‐weighted images.
机译:人海马可细分为具有独特功能特性和易受疾病或神经精神疾病困扰的亚域。鉴定赋予此类过程易感性的基因是开发治疗方法的重要目标。磁共振图像自动子场分割的最新进展使得在大规模的全基因组关联研究中将这些手段用作表型成为可能。此类分析可能很大程度上取决于在3.0T扫描仪上获取的标准分辨率(各向同性约1 mm)的T加权图像。因此,确定是否可以从此类图像中检测子域的遗传结构是重要的一步。我们在两个大型的双胞胎研究中使用Freesurfer v6.0对海马亚域进行了细分,这两个研究是越南时代的衰老双胞胎研究和人类Connectome项目。我们估计了子域的遗传力和与海马总体积的遗传重叠。样品间的遗传力相似,但考虑遗传因素对海马总体积的影响后,遗传变异仍然很小。重要的是,我们检查了子域之间的遗传关系,以确定是否可以根据较少的潜在遗传独立因素对子域进行分组。我们在两个样本中都确定了三个遗传因素,但是高度的交叉装载阻止了子领域遗传上不同的分组的形成。这些结果证实了Freesurfer v6.0生成的跨样本用于表型分析的子字段的可靠性。然而,目前的结果表明,使用标准分辨率T加权图像生成的分割方法,大规模遗传分析难以识别与总海马体积和其他子区域均不同的子区域特定基因。

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