Neural network correlates of high-altitude adaptive genetic variants in Tibetans: A pilot, exploratory study
Neural network correlates of high-altitude adaptive genetic variants in Tibetans: A pilot, exploratory study
复制标题
藏族高海拔适应性遗传变异的神经网络关联：一项试点探索性研究
DOI：
10.1002/hbm.24954
复制
发表时间：
2020-06-15
影响因子：
4.8
通讯作者：
Wang, Jinhui
中科院分区：
文献类型：
--
作者：
Guo, Zhiyue;Fan, Cunxiu;Wang, Jinhui
尽管在生理学、神经心理学和大脑组织的遗传基础的识别方面已经取得了实质性进展，但在高海拔（HA）适应的背景下，基因型-表型关联仍然很大程度上未知。在这里，我们将三个基因位点（EGLN1、EPAS1 和 PPARA）中的 HA 适应性遗传变异与 135 名西藏高地土著的一组生理特征、神经心理学测试以及大规模结构和功能大脑网络的拓扑属性的个体间差异联系起来。对个体 HA 适应性单核苷酸多态性 (SNP) 的分析表明，特定的 SNP 选择性调节生理特征（红细胞水平、第一秒用力呼气量与用力肺活量之间的比率、动脉血氧饱和度和心率）和结构网络中心性（左眼眶前回），而不影响神经心理学或功能性大脑网络。对遗传适应性评分的进一步分析总结了HA遗传适应的总体程度，揭示了仅与结构性大脑网络在整个网络的局部互连性、右额叶和顶叶模块与左枕叶模块之间的模块间通信、几个额叶区域的节点中心性以及主要涉及右颞叶和枕叶模块的模块内边缘的子网络的连接强度方面存在显着相关性。此外，这种关联取决于基因位点、体重类型或拓扑尺度。总之，这些发现为 HA 缺氧下基因型-表型相互作用提供了新的线索，并对开发新策略以优化生物体和组织对极端环境或疾病引起的慢性缺氧的反应具有重要意义。
Although substantial progress has been made in the identification of genetic substrates underlying physiology, neuropsychology, and brain organization, the genotype-phenotype associations remain largely unknown in the context of high-altitude (HA) adaptation. Here, we related HA adaptive genetic variants in three gene loci (EGLN1, EPAS1, and PPARA) to interindividual variance in a set of physiological characteristics, neuropsychological tests, and topological attributes of large-scale structural and functional brain networks in 135 indigenous Tibetan highlanders. Analyses of individual HA adaptive single-nucleotide polymorphisms (SNPs) revealed that specific SNPs selectively modulated physiological characteristics (erythrocyte level, ratio between forced expiratory volume in the first second to forced vital capacity, arterial oxygen saturation, and heart rate) and structural network centrality (the left anterior orbital gyrus) with no effects on neuropsychology or functional brain networks. Further analyses of genetic adaptive scores, which summarized the overall degree of genetic adaptation to HA, revealed significant correlations only with structural brain networks with respect to local interconnectivity of the whole networks, intermodule communication between the right frontal and parietal module and the left occipital module, nodal centrality in several frontal regions, and connectivity strength of a subnetwork predominantly involving in intramodule edges in the right temporal and occipital module. Moreover, the associations were dependent on gene loci, weight types, or topological scales. Together, these findings shed new light on genotype-phenotype interactions under HA hypoxia and have important implications for developing new strategies to optimize organism and tissue responses to chronic hypoxia induced by extreme environments or diseases.