Convergent Molecular, Cellular, and Cortical Neuroimaging Signatures of Major Depressive Disorder
Convergent molecular, cellular, and cortical neuroimaging signatures of major depressive disorder Kevin M. Andersona,1, Meghan A. Collinsa, Ru Kongb,c,d,e,f, Kacey Fanga, Jingwei Lib,c,d,e,f, Tong Heb,c,d,e,f, Adam M. Chekroudg,h, B. T. Thomas Yeob,c,d,e,f,i, and Avram J. Holmesa,g,j aDepartment of Psychology, Yale University, New Haven, CT 06520; bDepartment of Electrical and Computer Engineering, National University of Singapore, Singapore; cCentre for Sleep and Cognition, National University of Singapore, Singapore; dClinical Imaging Research Centre, National University of Singapore, Singapore; eN.1 Institute for Health, National University of Singapore, Singapore; fInstitute for Digital Medicine, National University of Singapore, Singapore; gDepartment of Psychiatry, Yale University, New Haven, CT 06520; hSpring Health, New York, NY 10001; iGraduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore; and jDepartment of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 Edited by Huda Akil, University of Michigan, Ann Arbor, MI, and approved August 12, 2020 (received for review May 5, 2020) Major depressive disorder emerges from the complex interactions detail. To date, there have been few opportunities to directly of biological systems that span genes and molecules through cells, explore the depressive phenotype across levels of analysis—from networks, and behavior. Establishing how neurobiological pro- genes and molecules through cells, circuits, networks, and cesses coalesce to contribute to depression requires a multiscale behavior—simultaneously (14). approach, encompassing measures of brain structure and function In vivo neuroimaging has identified depression-related corre- as well as genetic and cell-specific transcriptional data.
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