Linked patterns of biological and environmental covariation with brain structure in adolescence: a population-based longitudinal study
-
Published:2020-05-22
Issue:9
Volume:26
Page:4905-4918
-
ISSN:1359-4184
-
Container-title:Molecular Psychiatry
-
language:en
-
Short-container-title:Mol Psychiatry
Author:
Modabbernia Amirhossein, Reichenberg Abraham, Ing Alex, Moser Dominik A., Doucet Gaelle E.ORCID, Artiges EricORCID, Banaschewski TobiasORCID, Barker Gareth J.ORCID, Becker Andreas, Bokde Arun L. W., Quinlan Erin BurkeORCID, Desrivières SylvaneORCID, Flor Herta, Fröhner Juliane H.ORCID, Garavan Hugh, Gowland Penny, Grigis Antoine, Grimmer Yvonne, Heinz Andreas, Insensee Corinna, Ittermann Bernd, Martinot Jean-LucORCID, Martinot Marie-Laure Paillère, Millenet Sabina, Nees Frauke, Orfanos Dimitri PapadopoulosORCID, Paus Tomáš, Penttilä JaniORCID, Poustka Luise, Smolka Michael N.ORCID, Stringaris Argyris, van Noort Betteke M.ORCID, Walter HenrikORCID, Whelan RobertORCID, Schumann GunterORCID, Frangou Sophia,
Abstract
AbstractAdolescence 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.
Publisher
Springer Science and Business Media LLC
Subject
Cellular and Molecular Neuroscience,Psychiatry and Mental health,Molecular Biology
Reference63 articles.
1. Demetriou A, Christou C, Spanoudis G, Platsidou M. The development of mental processing: efficiency, working memory, and thinking. Monogr Soc Res Child Dev. 2002;67:i–viii. 1−155; discussion 156. 2. Blakemore SJ, Burnett S, Dahl RE. The role of puberty in the developing adolescent brain. Hum Brain Mapp. 2010;31:926–33. 3. Blakemore SJ, Choudhury S. Development of the adolescent brain: implications for executive function and social cognition. J Child Psychol Psychiatry. 2006;47:296–312. 4. Paus T, Keshavan M, Giedd JN. Why do many psychiatric disorders emerge during adolescence? Nat Rev Neurosci. 2008;9:947–57. 5. Andersen SL. Trajectories of brain development: point of vulnerability or window of opportunity? Neurosci Biobehav Rev. 2003;27:3–18.
Cited by
34 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|