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Genetic Determinants of Cortical Structure (Thickness, Surface Area and Volumes) among Disease Free Adults in the CHARGE Consortium

By Edith Hofer, Gennady V Roshchupkin, Hieab H. H. Adams, Maria J Knol, Honghuang Lin, Shuo Li, Habil Zare, Shahzad Ahmad, Nicola J. Armstrong, Claudia L. Satizabal, Manon Bernard, Joshua Bis, Nathan A Gillespie, Michelle Luciano, Aniket Mishra, Markus Scholz, Alexander Teumer, Rui Xia, Xueqiu Jian, Thomas H Mosley, Yasaman Saba, Lukas Pirpamer, Stephan Seiler, James T Becker, Owen Carmichael, Jerome Rotter, Bruce M Psaty, Oscar L. Lopez, Najaf Amin, Sven J. van der Lee, Qiong Yang, Jayandra J. Himali, Pauline Maillard, Alexa S. Beiser, Charles DeCarli, Sherif Karama, Lindsay Lewis, Mat Harris, Mark Bastin, Ian J Deary, A.Veronica Witte, Frauke Beyer, Markus Loeffler, Karen A. Mather, Peter R. Schofield, Anbupalam Thalamuthu, J. B. Kwok, Margaret J Wright, David Ames, Julian Trollor, Jiyang Jiang, Henry Brodaty, Wei Wen, Meike W Vernooij, Albert Hofman, André G. Uitterlinden, Wiro J. Niessen, Katharina Wittfeld, Robin Bülow, Uwe Völker, Zdenka Pausova, G. Bruce Pike, Sophie Maingault, Fabrice Crivello, Christophe Tzourio, Philippe Amouye, Bernard Mazoyer, Michael C Neale, Carol Franz, Michael J Lyons, Matthew S Panizzon, Ole A. Andreassen, Anders M. Dale, Mark W Logue, Katrina L. Grasby, Neda Jahanshad, Jodie N Painter, Lucía Colodro-Conde, Janita Bralten, Derrek P. Hibar, Penelope A. Lind, F. Pizzagalli, Jason L. Stein, Paul M Thompson, Sarah E Medland

Posted 09 Sep 2018
bioRxiv DOI: 10.1101/409649

Cortical thickness, surface area and volumes (MRI cortical measures) vary with age and cognitive function, and in neurological and psychiatric diseases. We examined heritability, genetic correlations and genome-wide associations of cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprised 22,824 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the United Kingdom Biobank. Significant associations were replicated in the Enhancing Neuroimaging Genetics through Meta-analysis (ENIGMA) consortium, and their biological implications explored using bioinformatic annotation and pathway analyses. We identified genetic heterogeneity between cortical measures and brain regions, and 160 genome-wide significant associations pointing to wnt/β-catenin, TGF-β and sonic hedgehog pathways. There was enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.

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