Heritability of white matter in twins: A diffusion neuroimaging review

IF 13.7 1区 生物学 Q1 BIOLOGY
Giovanni Videtta , Chiara Colli , Letizia Squarcina , Corrado Fagnani , Emanuela Medda , Paolo Brambilla , Giuseppe Delvecchio
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引用次数: 0

Abstract

Diffusion neuroimaging has emerged as an essential non-invasive technique to explore in vivo microstructural characteristics of white matter (WM), whose integrity allows complex behaviors and cognitive abilities. Studying the factors contributing to inter-individual variability in WM microstructure can provide valuable insight into structural and functional differences of brain among individuals. Genetic influence on this variation has been largely investigated in twin studies employing different measures derived from diffusion neuroimaging. In this context, we performed a comprehensive literature search across PubMed, Scopus and Web of Science of original twin studies focused on the heritability of WM. Overall, our results highlighted a consistent heritability of diffusion indices (i.e., fractional anisotropy, mean, axial and radial diffusivity), and network topology among twins. The genetic influence resulted prominent in frontal and occipital regions, in the limbic system, and in commissural fibers. To enhance the understanding of genetic influence on WM microstructure further studies in less heterogeneous experimental settings, encompassing all diffusion indices, are warranted.

双胞胎白质的遗传性:扩散神经成像回顾
扩散神经成像已成为探索体内白质(WM)微观结构特征的重要非侵入性技术。研究导致白质微观结构个体间差异的因素,可为了解个体间大脑结构和功能差异提供宝贵的信息。遗传因素对这种变异的影响主要是在双生子研究中通过不同的弥散神经影像学测量方法进行研究的。在此背景下,我们在 PubMed、Scopus 和 Web of Science 上对有关 WM 遗传性的原始双生子研究进行了全面的文献检索。总体而言,我们的研究结果表明,扩散指数(即分数各向异性、平均值、轴向和径向扩散率)和网络拓扑结构在双胞胎中具有一致的遗传性。遗传影响在额叶和枕叶区域、边缘系统和神经纤维中表现突出。为了进一步了解遗传对 WM 微观结构的影响,有必要在异质性较低的实验环境中进行进一步的研究,并涵盖所有的扩散指数。
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来源期刊
Physics of Life Reviews
Physics of Life Reviews 生物-生物物理
CiteScore
20.30
自引率
14.50%
发文量
52
审稿时长
8 days
期刊介绍: Physics of Life Reviews, published quarterly, is an international journal dedicated to review articles on the physics of living systems, complex phenomena in biological systems, and related fields including artificial life, robotics, mathematical bio-semiotics, and artificial intelligent systems. Serving as a unifying force across disciplines, the journal explores living systems comprehensively—from molecules to populations, genetics to mind, and artificial systems modeling these phenomena. Inviting reviews from actively engaged researchers, the journal seeks broad, critical, and accessible contributions that address recent progress and sometimes controversial accounts in the field.
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