Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3–90 years

S Frangou; A Modabbernia; SCR Williams; E Papachristou; GE Doucet; I Agartz; M Aghajani; TN Akudjedu; A Albajes-Eizagirre; D Alnæs; KI Alpert; M Andersson; NC Andreasen; OA Andreassen; P Asherson; T Banaschewski; N Bargallo; S Baumeister; R Baur-Streubel; A Bertolino; A Bonvino; DI Boomsma; S Borgwardt; J Bourque; D Brandeis; A Breier; H Brodaty; RM Brouwer; JK Buitelaar; GF Busatto; RL Buckner; V Calhoun; EJ Canales-Rodríguez; DM Cannon; X Caseras; FX Castellanos; S Cervenka; TM Chaim-Avancini; CRK Ching; V Chubar; VP Clark; P Conrod; A Conzelmann; B Crespo-Facorro; F Crivello; EA Crone; AM Dale; U Dannlowski; C Davey; EJC de Geus; L de Haan; GI de Zubicaray; A den Braber; EW Dickie; A Di Giorgio; NT Doan; ES Dørum; S Ehrlich; S Erk; T Espeseth; H Fatouros-Bergman; SE Fisher; JP Fouche; B Franke; T Frodl; P Fuentes-Claramonte; DC Glahn; IH Gotlib; HJ Grabe; O Grimm; NA Groenewold; D Grotegerd; O Gruber; P Gruner; RE Gur; RC Gur; T Hahn; BJ Harrison; CA Hartman; SN Hatton; A Heinz; DJ Heslenfeld; DP Hibar; IB Hickie; BC Ho; PJ Hoekstra; S Hohmann; AJ Holmes; M Hoogman; N Hosten; FM Howells; HE Hulshoff Pol; C Huyser; N Jahanshad; A James; TL Jernigan; J Jiang; EG Jönsson; JA Joska; R Kahn

Journal article

Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3–90 years

S Frangou, A Modabbernia, SCR Williams, E Papachristou, GE Doucet, I Agartz, M Aghajani, TN Akudjedu, A Albajes-Eizagirre, D Alnæs, KI Alpert, M Andersson, NC Andreasen, OA Andreassen, P Asherson, T Banaschewski, N Bargallo, S Baumeister, R Baur-Streubel, A Bertolino Show all

Human Brain Mapping | WILEY | Published : 2022

DOI: 10.1002/hbm.25364

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Abstract

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3–90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu,..

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University of Melbourne Researchers

Chris Davey Author

Ben Harrison Author

Lianne Schmaal Author

Related Projects (1)

ENIGMA Bipolar Initiative: A Global Study of Imaging Genomics & Clinical Outcomes

Grants

Awarded by Fresenius Medical Care North America

Funding Acknowledgements

European Community's Seventh Framework Programme, Grant/Award Numbers: 278948, 602450, 603016, 602805; US National Institute of Child Health and Human Development, Grant/Award Numbers: RO1HD050735, 1009064, 496682; QIMR Berghofer Medical Research Institute and the Centre for Advanced Imaging, University of Queensland; ICTSI NIH/NCRR, Grant/Award Number: RR025761; European Community's Horizon 2020 Programme, Grant/Award Numbers: 667302, 643051; Vici Innovation Program, Grant/Award Numbers: #91619115, 016-130-669; NWO Brain & Cognition Excellence Program, Grant/Award Number: 433-09-229; Biobanking and Biomolecular Resources Research Infrastructure (Netherlands) (BBMRI-NL); Spinozapremie, Grant/Award Number: NWO-56-464-14192; Biobanking and Biomolecular Resources Research Infrastructure, Grant/Award Numbers: 184.033.111, 184.021.007; Netherlands Organization for Health Research and Development (ZonMW), Grant/Award Numbers: 480-15-001/674, 024.001.003, 911-09-032, 056-32-010, 481-08-011, 016-115-035, 31160008, 400-07-080, 400-05-717, 451-04-034, 463-06-001, 480-04-004, 904-61-193, 912-10-020, 985-10-002, 904-61-090; NIMH, Grant/ Award Number: R01 MH090553; Geestkracht programme of the Dutch Health Research Council, Grant/Award Number: 10-000-1001; FP7 Ideas: European Research Council; Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Grant/Award Numbers: NWO/SPI 56-464-14192, NWOMagW 480-04-004, 433-09-220, NWO 51.02.062, NWO 51.02.061; National Center for Advancing Translational Sciences, National Institutes of Health, Grant/Award Number: UL1 TR000153; National Center for Research Resources; National Center for Research Resources at the National Institutes of Health, Grant/Award Numbers: NIH 1U24 RR025736-01, NIH 1U24 RR021992; NIH Institutes contributing to the Big Data to Knowledge; U.S. National Institutes of Health, Grant/Award Numbers: R01 CA101318, P30 AG10133, R01 AG19771; Medical Research Council, Grant/Award Numbers: U54EB020403, G0500092; National Institute of Mental Health, Grant/Award Numbers: R01MH117014, R01MH042191; Fundacion Instituto de Investigacion Marques de Valdecilla, Grant/Award Numbers: API07/011, NCT02534363, NCT0235832; Instituto de Salud Carlos III, Grant/Award Numbers: PI14/00918, PI14/00639, PI060507, PI050427, PI020499; Swedish Research Council, Grant/Award Numbers: 523-2014-3467, 2017-00949, 521-2014-3487; South-Eastern Norway Health Authority; the Research Council of Norway, Grant/Award Number: 223273; South Eastern Norway Regional Health Authority, Grant/Award Numbers: 2017-112, 2019107; Icahn School of Medicine at Mount Sinai; Seventh Framework Programme (FP7/2007-2013), Grant/Award Number: 602450; National Institutes of Health, Grant/ Award Numbers: R01 MH116147, R01 MH113619, R01 MH104284; South London and Maudsley NHS Foundation Trust; the National Institute for Health Research (NIHR)