Anderson Kevin M, Ge Tian, Kong Ru, Patrick Lauren M, Spreng R Nathan, Sabuncu Mert R, Yeo B T Thomas, Holmes Avram J
Department of Psychology, Yale University, New Haven, CT 06520;
Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114.
Proc Natl Acad Sci U S A. 2021 Mar 2;118(9). doi: 10.1073/pnas.2016271118.
Human cortex is patterned by a complex and interdigitated web of large-scale functional networks. Recent methodological breakthroughs reveal variation in the size, shape, and spatial topography of cortical networks across individuals. While spatial network organization emerges across development, is stable over time, and is predictive of behavior, it is not yet clear to what extent genetic factors underlie interindividual differences in network topography. Here, leveraging a nonlinear multidimensional estimation of heritability, we provide evidence that individual variability in the size and topographic organization of cortical networks are under genetic control. Using twin and family data from the Human Connectome Project ( = 1,023), we find increased variability and reduced heritability in the size of heteromodal association networks ( : M = 0.34, SD = 0.070), relative to unimodal sensory/motor cortex ( : M = 0.40, SD = 0.097). We then demonstrate that the spatial layout of cortical networks is influenced by genetics, using our multidimensional estimation of heritability (multi; M = 0.14, SD = 0.015). However, topographic heritability did not differ between heteromodal and unimodal networks. Genetic factors had a regionally variable influence on brain organization, such that the heritability of network topography was greatest in prefrontal, precuneus, and posterior parietal cortex. Taken together, these data are consistent with relaxed genetic control of association cortices relative to primary sensory/motor regions and have implications for understanding population-level variability in brain functioning, guiding both individualized prediction and the interpretation of analyses that integrate genetics and neuroimaging.
人类大脑皮层由复杂且相互交错的大规模功能网络构成。最近的方法学突破揭示了个体间皮层网络在大小、形状和空间拓扑结构上的差异。虽然空间网络组织在发育过程中形成，随时间稳定，且可预测行为，但尚不清楚基因因素在多大程度上构成了网络拓扑结构个体差异的基础。在此，我们利用遗传力的非线性多维估计，提供证据表明皮层网络大小和拓扑组织的个体变异性受基因控制。利用来自人类连接组计划（ = 1,023）的双胞胎和家庭数据，我们发现相对于单峰感觉/运动皮层（ : M = 0.40, SD = 0.097），异模态联合网络大小的变异性增加且遗传力降低（ : M = 0.34, SD = 0.070）。然后，我们利用遗传力的多维估计（multi; M = 0.14, SD = 0.015）证明皮层网络的空间布局受遗传影响。然而，异模态和单峰网络之间的拓扑遗传力并无差异。基因因素对大脑组织的影响存在区域差异，使得网络拓扑结构的遗传力在额叶、楔前叶和顶叶后部皮层中最大。综上所述，这些数据与联合皮层相对于初级感觉/运动区域的遗传控制放松相一致，对理解大脑功能的群体水平变异性具有启示意义，可为个体预测以及整合遗传学和神经影像学的分析解释提供指导。
