Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation

Ge, Ruiyang, Yu, Yuetong, Qi, Yi Xuan, Fan, Yu nan, Chen, Shiyu, Gao, Chuntong, Haas, Shalaila S., New, Faye, Boomsma, Dorret I., Brodaty, Henry, Brouwer, Rachel M., Buckner, Randy, Caseras, Xavier, Crivello, Fabrice, Crone, Eveline A., Erk, Susanne, Fisher, Simon E., Franke, Barbara, Glahn, David C., Dannlowski, Udo, Grotegerd, Dominik, Gruber, Oliver, Hulshoff Pol, Hilleke E., Schumann, Gunter, Tamnes, Christian K., Walter, Henrik, Wierenga, Lara M., Jahanshad, Neda, Thompson, Paul M., Frangou, Sophia, Agartz, Ingrid, Asherson, Philip, Ayesa-Arriola, Rosa, Banaj, Nerisa, Banaschewski, Tobias, Baumeister, Sarah, Bertolino, Alessandro, Borgwardt, Stefan, Bourque, Josiane, Brandeis, Daniel, Breier, Alan, Buitelaar, Jan K., Cannon, Dara M., Cervenka, Simon, Conrod, Patricia J., Crespo-Facorro, Benedicto, Davey, Christopher G., de Haan, Lieuwe, , Di Giorgio, Annabella, Frodl, Thomas, Gruner, Patricia, Gur, Raquel E., Gur, Ruben C., Harrison, Ben J., Hatton, Sean N., Hickie, Ian, Howells, Fleur M., Huyser, Chaim, Jernigan, Terry L., Jiang, Jiyang, Joska, John A., Kahn, René S., Kalnin, Andrew J., Kochan, Nicole A., Koops, Sanne, Kuntsi, Jonna, Lagopoulos, Jim, Lazaro, Luisa, Lebedeva, Irina S., Lochner, Christine, Martin, Nicholas G., Mazoyer, Bernard, McDonald, Brenna C., McDonald, Colm, , , Modabbernia, Amirhossein, Mwangi, Benson, Nakao, Tomohiro, Nyberg, Lars, Piras, Fabrizio, Portella, Maria J., Qiu, Jiang, Roffman, Joshua L., Sachdev, Perminder S., Sanford, Nicole, Satterthwaite, Theodore D., Saykin, Andrew J., Sellgren, Carl M., Sim, Kang, Smoller, Jordan W., Soares, Jair C., Sommer, Iris E., Spalletta, Gianfranco, Stein, Dan J., Thomopoulos, Sophia I., Tomyshev, Alexander S., Tordesillas-Gutiérrez, Diana, Trollor, Julian N., van 't Ent, Dennis, van den Heuvel, Odile A., van Erp, Theo GM, van Haren, Neeltje EM, Vecchio, Daniela, Veltman, Dick J., Wang, Yang, Weber, Bernd, Wei, Dongtao, Wen, Wei, Westlye, Lars T., Williams, Steven CR, Wright, Margaret J., Wu, Mon Ju, Yu, Kevin, & other, and (2024) Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation. The Lancet Digital Health, 6(3), e211-e221.

Open access copy at publisher website

Description

The value of normative models in research and clinical practice relies on their robustness and a systematic comparison of different modelling algorithms and parameters; however, this has not been done to date. We aimed to identify the optimal approach for normative modelling of brain morphometric data through systematic empirical benchmarking, by quantifying the accuracy of different algorithms and identifying parameters that optimised model performance. We developed this framework with regional morphometric data from 37 407 healthy individuals (53% female and 47% male; aged 3–90 years) from 87 datasets from Europe, Australia, the USA, South Africa, and east Asia following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The multivariate fractional polynomial regression (MFPR) emerged as the preferred algorithm, optimised with non-linear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3000 study participants. This model can inform about the biological and behavioural implications of deviations from typical age-related neuroanatomical changes and support future study designs. The model and scripts described here are freely available through CentileBrain.

Impact and interest:

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ID Code: 248589
Item Type: Contribution to Journal (Review article)
Refereed: Yes
ORCID iD:
de Zubicaray, Greig I.orcid.org/0000-0003-4506-0579
McMahon, Katie L.orcid.org/0000-0002-6357-615X
Measurements or Duration: 11 pages
DOI: 10.1016/S2589-7500(23)00250-9
ISSN: 2589-7500
Pure ID: 168975659
Divisions: Current > QUT Faculties and Divisions > Faculty of Health
Current > Schools > School of Clinical Sciences
Current > Schools > School of Psychology & Counselling
Funding Information: We thank the following organisations for funding: EU Seventh Framework Programme (278948, 602450, 603016, 602805, and 602450); EU Horizon 2020 Programme (667302 and 643051); European Research Council (ERC–230374); EU Joint Programme-Neurodegenerative Disease Research (FKZ:01ED1615); Australian National Health and Medical Research Council (496682 and 1009064); German Federal Ministry of Education and Research (01ZZ9603, 01ZZ0103, and 01ZZ0403); Vici Innovation Program (91619115 and 016–130–669); Nederlandse Organisatie voor Wetenschappelijk Onderzoek: Cognition Excellence Program (433–09–229, NW0-SP 56–464–14192, NWO–MagW 480–04–004, NWO 433–09–220, NWO 51–02–062, and NWO 51–02–061); Organization for Health Research and Development (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, 912–10–020, 451–04–034, 481–08–011, 056–32–010, and 911–09–032); Dutch Health Research Council (10–000–1001); Biobanking and Biomolecular Resources Research Infrastructure (184–033–111 and 84.021.00); Research Council of Norway (223273); South and Eastern Norway Regional Health Authority (2017–112, 2019–107, 2014–097, and 2013–054); Russian Foundation for Basic Research (20–013–00748); Fundación Instituto de Investigación Marqués de Valdecilla (API07/011, NCT02534363 , and NCT0235832 ); Instituto de Salud Carlos III (PI14/00918, PI14/00639, PI060507, PI050427, and PI020499); Swedish Research Council (523–2014–3467, 2017–00949, 521–2014–3487, K2007–62X–15077–04–1, K2008–62P–20597–01–3, K2010–62X–15078–07–2, and K2012–61X–15078–09–3); Knut and Alice Wallenberg Foundation; UK Medical Research Council (G0500092); and US National Institutes of Health—Mental Health, Aging, Child Health and Human Development, Drug Abuse, and National Center for Advancing Translational Sciences (UL1 TR000153, U24RR025736–01, U24RR021992, U54EB020403, U24RR025736, U24RR025761, P30AG10133, R01AG19771, R01MH117014, R01MH042191, R01HD050735, 1009064, 496682, R01MH104284, R01MH113619, R01MH116147, R01MH116147, R01MH113619, R01MH104284, R01MH090553, R01MH090553, R01CA101318, RC2DA029475, and T32MH122394). We thank Dr Andre F Marquand and Dr Seyed Mostafa Kia (Radboud University, Netherlands) for their guidance with the HBR models. This work was supported by the computational resources and staff expertise provided by the Advanced Research Computing at the University of British Columbia and by the Scientific Computing at the Icahn School of Medicine at Mount Sinai (supported by the Clinical and Translational Science Awards grant UL1TR004419 from the National Center for Advancing Translational Sciences).
Copyright Owner: 2024 The Author(s)
Copyright Statement: This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au
Deposited On: 17 May 2024 06:01
Last Modified: 01 Aug 2024 12:03

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