Heritability of individualized cortical network topography.

Autor:	Anderson KM; Department of Psychology, Yale University, New Haven, CT 06520; kevin.anderson@yale.edu., Ge T; Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114.; Stanley Center for Psychiatric Research, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142.; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114., Kong R; Department of Electrical and Computer Engineering, Centre for Sleep and Cognition, National University of Singapore, Singapore 119077.; Department of Electrical and Computer Engineering, Centre for Translational Magnetic Resonance Research, National University of Singapore, Singapore 119077.; N.1 Institute for Health, National University of Singapore, Singapore 119077.; Institute for Digital Medicine, National University of Singapore, Singapore 119077., Patrick LM; Department of Psychology, Yale University, New Haven, CT 06520., Spreng RN; Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC H3A 0G4, Canada.; McConnell Brain Imaging Centre, McGill University, Montreal, QC H3A 0G4, Canada., Sabuncu MR; School of Electrical and Computer Engineering, Cornell University, Ithaca, NY 14850.; Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY 14850.; Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129., Yeo BTT; Department of Electrical and Computer Engineering, Centre for Sleep and Cognition, National University of Singapore, Singapore 119077.; Department of Electrical and Computer Engineering, Centre for Translational Magnetic Resonance Research, National University of Singapore, Singapore 119077.; N.1 Institute for Health, National University of Singapore, Singapore 119077.; Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129.; National University of Singapore Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore 119077., Holmes AJ; Department of Psychology, Yale University, New Haven, CT 06520.; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114.; Department of Psychiatry, Yale University, New Haven, CT 06520.
Jazyk:	angličtina
Zdroj:	Proceedings of the National Academy of Sciences of the United States of America [Proc Natl Acad Sci U S A] 2021 Mar 02; Vol. 118 (9).
DOI:	10.1073/pnas.2016271118
Abstrakt:	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 ( n = 1,023), we find increased variability and reduced heritability in the size of heteromodal association networks ( h 2 : M = 0.34, SD = 0.070), relative to unimodal sensory/motor cortex ( h 2 : 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 ( h 2 - 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. Competing Interests: The authors declare no competing interest. (Copyright © 2021 the Author(s). Published by PNAS.)
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu