TY - JOUR
T1 - Linked patterns of biological and environmental covariation with brain structure in adolescence
T2 - a population-based longitudinal study
AU - IMAGEN Consortium
AU - Modabbernia, Amirhossein
AU - Reichenberg, Abraham
AU - Ing, Alex
AU - Moser, Dominik A.
AU - Doucet, Gaelle E.
AU - Artiges, Eric
AU - Banaschewski, Tobias
AU - Barker, Gareth J.
AU - Becker, Andreas
AU - Bokde, Arun L.W.
AU - Quinlan, Erin Burke
AU - Desrivières, Sylvane
AU - Flor, Herta
AU - Fröhner, Juliane H.
AU - Garavan, Hugh
AU - Gowland, Penny
AU - Grigis, Antoine
AU - Grimmer, Yvonne
AU - Heinz, Andreas
AU - Insensee, Corinna
AU - Ittermann, Bernd
AU - Martinot, Jean Luc
AU - Martinot, Marie Laure Paillère
AU - Millenet, Sabina
AU - Nees, Frauke
AU - Orfanos, Dimitri Papadopoulos
AU - Paus, Tomáš
AU - Penttilä, Jani
AU - Poustka, Luise
AU - Smolka, Michael N.
AU - Stringaris, Argyris
AU - van Noort, Betteke M.
AU - Walter, Henrik
AU - Whelan, Robert
AU - Schumann, Gunter
AU - Frangou, Sophia
N1 - Funding Information:
Acknowledgements Professor Gunter Schumann is the Principal Investigator for the IMAGEN Consortium. Furthermore, this work received support from the following sources: the European Union-funded FP6 Integrated Project IMAGEN (Reinforcement-related behaviour in normal brain function and psychopathology) (LSHM-CT-2007-037286), the Horizon 2020-funded ERC Advanced Grant ‘STRATIFY’ (Brain network-based stratification of reinforcement-related disorders) (695313), ERANID (Understanding the interplay between cultural, biological and subjective factors in drug use pathways) (PR-ST-0416-10004), BRIDGET (JPND: BRain Imaging, cognition Dementia and next generation GEnomics) (MR/N027558/1), Human Brain Project (HBP SGA 2, 785907), the FP7 project MATRICS (603016), the Medical Research Council Grant ‘c-VEDA’ (Consortium on vulnerability to externalizing disorders and addictions) (MR/N000390/1), the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, the Bundesminister-iumfür Bildung und Forschung (BMBF grants 01GS08152; 01EV0711; Forschungsnetz AERIAL 01EE1406A, 01EE1406B), the Deutsche Forschungsgemeinschaft (DFG grants SM 80/7-2, SFB 940, TRR 265, NE 1383/14-1), the Medical Research Foundation and Medical Research Council (grants MR/R00465X/1 and MR/S020306/ 1), the National Institutes of Health (NIH)-funded ENIGMA (grants 5U54EB020403-05 and 1R56AG058854-01). Further support was provided by grants from: ANR (project AF12-NEUR0008-01-WM2NA, ANR-12-SAMA-0004), the Eranet Neuron (ANR-18-NEUR00002-01), the Fondation de France (00081242), the Fondation pour la Recherche Médicale (DPA20140629802), the Mission Inter-ministérielle de Lutte-contre-les-Drogues-et-les-Conduites-Addictives (MILDECA), the Assistance-Publique-Hôpitaux-de-Paris and INSERM (interface grant), Paris Sud University IDEX 2012, the fondation de l’Avenir (grant AP-RM-17-013); the National Institutes of Health, Science Foundation Ireland (16/ERCD/3797), U.S.A. (Axon, Testosterone and Mental Health during Adolescence; RO1 MH085772-01A1), and by NIH Consortium grant U54 EB020403, supported by a cross-NIH alliance that funds Big Data to Knowledge Centres of Excellence. SF (corresponding author) was supported by grants from the US National Institutes of Mental Health (R01MH113619 and R01 MH116147). This work was supported in part through the computational resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai.
Publisher Copyright:
© 2020, The Author(s).
PY - 2021/9
Y1 - 2021/9
N2 - Adolescence is a period of major brain reorganization shaped by biologically timed and by environmental factors. We sought to discover linked patterns of covariation between brain structural development and a wide array of these factors by leveraging data from the IMAGEN study, a longitudinal population-based cohort of adolescents. Brain structural measures and a comprehensive array of non-imaging features (relating to demographic, anthropometric, and psychosocial characteristics) were available on 1476 IMAGEN participants aged 14 years and from a subsample reassessed at age 19 years (n = 714). We applied sparse canonical correlation analyses (sCCA) to the cross-sectional and longitudinal data to extract modes with maximum covariation between neuroimaging and non-imaging measures. Separate sCCAs for cortical thickness, cortical surface area and subcortical volumes confirmed that each imaging phenotype was correlated with non-imaging features (sCCA r range: 0.30–0.65, all PFDR < 0.001). Total intracranial volume and global measures of cortical thickness and surface area had the highest canonical cross-loadings (|ρ| = 0.31−0.61). Age, physical growth and sex had the highest association with adolescent brain structure (|ρ| = 0.24−0.62); at baseline, further significant positive associations were noted for cognitive measures while negative associations were observed at both time points for prenatal parental smoking, life events, and negative affect and substance use in youth (|ρ| = 0.10−0.23). Sex, physical growth and age are the dominant influences on adolescent brain development. We highlight the persistent negative influences of prenatal parental smoking and youth substance use as they are modifiable and of relevance for public health initiatives.
AB - Adolescence is a period of major brain reorganization shaped by biologically timed and by environmental factors. We sought to discover linked patterns of covariation between brain structural development and a wide array of these factors by leveraging data from the IMAGEN study, a longitudinal population-based cohort of adolescents. Brain structural measures and a comprehensive array of non-imaging features (relating to demographic, anthropometric, and psychosocial characteristics) were available on 1476 IMAGEN participants aged 14 years and from a subsample reassessed at age 19 years (n = 714). We applied sparse canonical correlation analyses (sCCA) to the cross-sectional and longitudinal data to extract modes with maximum covariation between neuroimaging and non-imaging measures. Separate sCCAs for cortical thickness, cortical surface area and subcortical volumes confirmed that each imaging phenotype was correlated with non-imaging features (sCCA r range: 0.30–0.65, all PFDR < 0.001). Total intracranial volume and global measures of cortical thickness and surface area had the highest canonical cross-loadings (|ρ| = 0.31−0.61). Age, physical growth and sex had the highest association with adolescent brain structure (|ρ| = 0.24−0.62); at baseline, further significant positive associations were noted for cognitive measures while negative associations were observed at both time points for prenatal parental smoking, life events, and negative affect and substance use in youth (|ρ| = 0.10−0.23). Sex, physical growth and age are the dominant influences on adolescent brain development. We highlight the persistent negative influences of prenatal parental smoking and youth substance use as they are modifiable and of relevance for public health initiatives.
UR - http://www.scopus.com/inward/record.url?scp=85085341287&partnerID=8YFLogxK
U2 - 10.1038/s41380-020-0757-x
DO - 10.1038/s41380-020-0757-x
M3 - Article
C2 - 32444868
AN - SCOPUS:85085341287
SN - 1359-4184
VL - 26
SP - 4905
EP - 4918
JO - Molecular Psychiatry
JF - Molecular Psychiatry
IS - 9
ER -