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Original Investigation |

Early Cannabis Use, Polygenic Risk Score for Schizophrenia and Brain Maturation in Adolescence

Leon French, PhD1; Courtney Gray, MSc1; Gabriel Leonard, PhD2; Michel Perron, PhD3,4; G. Bruce Pike, PhD5,6; Louis Richer, PhD7; Jean R. Séguin, PhD8; Suzanne Veillette, PhD3,4; C. John Evans, PhD9; Eric Artiges, MD, PhD10,11,12,13,14; Tobias Banaschewski, MD, PhD15; Arun W. L. Bokde, PhD16; Uli Bromberg, PhD17; Ruediger Bruehl, PhD18; Christian Buchel, MD17; Anna Cattrell, PhD19,20; Patricia J. Conrod, PhD8,19; Herta Flor, PhD21; Vincent Frouin, PhD22; Jurgen Gallinat, MD17; Hugh Garavan, PhD23,24; Penny Gowland, PhD25; Andreas Heinz, MD26; Herve Lemaitre, PhD10,11,12,13,14; Jean-Luc Martinot, MD10,11,12,13,14; Frauke Nees, PhD21; Dimitri Papadopoulos Orfanos, PhD22; Melissa Marie Pangelinan, PhD1; Luise Poustka, MD15; Marcella Rietschel, MD21; Michael N. Smolka, PhD27; Henrik Walter, MD26; Robert Whelan, PhD28; Nic J. Timpson, PhD29; Gunter Schumann, MD19,20; George Davey Smith, MD, DSc29; Zdenka Pausova, MD30,31,32; Tomáš Paus, MD, PhD1,33,34,35
[+] Author Affiliations
1Rotman Research Institute, Baycrest, Toronto, Ontario, Canada
2Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
3Groupe d’Étude des Conditions de vie et des Besoins de la Population, Cégep de Jonquiere, Jonquiere, Saguenay, Quebec, Canada
4Department of Human Sciences, University of Quebec in Chicoutimi, Chicoutimi, Quebec, Canada
5Department of Radiology, University of Calgary, Calgary, Alberta, Canada
6Department of Clinical Neuroscience, University of Calgary, Calgary, Alberta, Canada
7Department of Health Sciences, University of Quebec in Chicoutimi, Chicoutimi, Quebec, Canada
8Department of Psychiatry and Centre de Recherche du Centre Hospitalier Universitaire Ste-Justine, University de Montréal, Montreal, Quebec, Canada
9School of Psychology, Cardiff University, Cardiff, Wales
10Institut National de la Santé et de la Recherche Medicale (INSERM), Unité Mixte de Recherche (UMR) 1000, Research Unit Imaging and Psychiatry, Commissariat à l’Énergie Atomique (CEA), Direction des Sciences du Vivant, Institut d’Imagerie Biomédicale, Service Hospitalier Frédéric Joliot, Orsay, France
11INSERM, UMR 1000, University Paris-Sud 11, Orsay
12INSERM, UMR 1000, Research Unit Imaging and Psychiatry, University Paris Descartes, Sorbonne Paris Cité, Paris, France
13INSERM, UMR 1000, Faculté de Médecine, Psychiatry Department 91G16, Orsay Hospital, Orsay, France
14INSERM, UMR 1000, Faculté de Médecine, Department of Adolescent Psychopathology and Medicine, Maison de Solenn, Cochin Hospital, Assistance Publique–Hôpitaux de Paris, Paris, France
15Department of Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
16Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neurosciences, Trinity College, Dublin, Ireland
17Institut für Systemische Neurowissenschaften, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
18Physikalisch-Technische Bundesanstalt, Berlin, Germany
19Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, England
20Medical Research Council–Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, England
21Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
22Neurospin, CEA-Saclay Center, Paris, France
23Department of Psychiatry, University of Vermont, Burlington
24Department of Psychology, University of Vermont, Burlington
25School of Physics and Astronomy, University of Nottingham, Nottingham, England
26Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité, Universitätsmedizin Berlin, Berlin, Germany
27Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
28Department of Psychology, University College Dublin, Dublin, Ireland
29Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, England
30Department of Physiology and Experimental Medicine, Hospital for Sick Children, University of Toronto, Ontario, Canada
31Department of Physiology, University of Toronto, Ontario, Canada
32Department of Nutritional Sciences, University of Toronto, Ontario, Canada
33Department of Psychology, University of Toronto, Ontario, Canada
34Department of Psychiatry, University of Toronto, Ontario, Canada
35Child Mind Institute, New York, New York
JAMA Psychiatry. 2015;72(10):1002-1011. doi:10.1001/jamapsychiatry.2015.1131.
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Importance  Cannabis use during adolescence is known to increase the risk for schizophrenia in men. Sex differences in the dynamics of brain maturation during adolescence may be of particular importance with regard to vulnerability of the male brain to cannabis exposure.

Objective  To evaluate whether the association between cannabis use and cortical maturation in adolescents is moderated by a polygenic risk score for schizophrenia.

Design, Setting, and Participants  Observation of 3 population-based samples included initial analysis in 1024 adolescents of both sexes from the Canadian Saguenay Youth Study (SYS) and follow-up in 426 adolescents of both sexes from the IMAGEN Study from 8 European cities and 504 male youth from the Avon Longitudinal Study of Parents and Children (ALSPAC) based in England. A total of 1577 participants (aged 12-21 years; 899 [57.0%] male) had (1) information about cannabis use; (2) imaging studies of the brain; and (3) a polygenic risk score for schizophrenia across 108 genetic loci identified by the Psychiatric Genomics Consortium. Data analysis was performed from March 1 through December 31, 2014.

Main Outcomes and Measures  Cortical thickness derived from T1-weighted magnetic resonance images. Linear regression tests were used to assess the relationships between cannabis use, cortical thickness, and risk score.

Results  Across the 3 samples of 1574 participants, a negative association was observed between cannabis use in early adolescence and cortical thickness in male participants with a high polygenic risk score. This observation was not the case for low-risk male participants or for the low- or high-risk female participants. Thus, in SYS male participants, cannabis use interacted with risk score vis-à-vis cortical thickness (P = .009); higher scores were associated with lower thickness only in males who used cannabis. Similarly, in the IMAGEN male participants, cannabis use interacted with increased risk score vis-à-vis a change in decreasing cortical thickness from 14.5 to 18.5 years of age (t137 = −2.36; P = .02). Finally, in the ALSPAC high-risk group of male participants, those who used cannabis most frequently (≥61 occasions) had lower cortical thickness than those who never used cannabis (difference in cortical thickness, 0.07 [95% CI, 0.01-0.12]; P = .02) and those with light use (<5 occasions) (difference in cortical thickness, 0.11 [95% CI, 0.03-0.18]; P = .004).

Conclusions and Relevance  Cannabis use in early adolescence moderates the association between the genetic risk for schizophrenia and cortical maturation among male individuals. This finding implicates processes underlying cortical maturation in mediating the link between cannabis use and liability to schizophrenia.

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Figure 1.
Age-Adjusted Cortical Thickness and Polygenic Risk Score for Schizophrenia in the Saguenay Youth Study (SYS) Participants

The SYS participants are stratified by cannabis use as never and ever having used. A, Among SYS male participants, 317 had never and 142 had ever used cannabis. Regression lines for those who never and ever used are plotted with shaded 95% CIs. Median risk score is marked with the dotted vertical line. Risk scores range from −1.86 to 1.53, with greater scores indicating higher risk. B, Dot plots show age-adjusted cortical thickness across risk score deciles of male adolescents who never and ever used cannabis. Mean thickness values are marked with solid bars. The Schizophrenia Working Group of the Psychiatric Genomics Consortium17 found that the top decile (based on the top 108 loci) contained about 3 times more cases of schizophrenia than the bottom decile (mean odds ratio across 39 samples, 3.21). C, Among SYS female participants, 319 had never and 171 had ever used cannabis. A weak albeit significant relationship between cortical thickness and risk score is seen with cannabis exposure. Lines and risk scores are described in part A. Cortical thickness is presented in arbitrary units (residuals).

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Figure 2.
Dot Plots of Mean Cortical Thickness for Different Groups of Male Cannabis Users at High and Low Risk

Thickness values are binned and stacked horizontally within each grouping. Mean thickness values are marked with thick black lines. Significant group differences are marked with lines and Cohen d statistics. A, Age-adjusted cortical thickness is presented in male participants who ever and never used cannabis. B, Change in cortical thickness (time 2 − time 1) by number of occasions of use. C, Age-adjusted cortical thickness is presented by number of occasions of use. ALSPAC indicates Avon Longitudinal Study of Parents and Children; SYS, Saguenay Youth Study. Cortical thickness is presented in arbitrary units (residuals).

aP < .005, t test.

bP < .05, t test.

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Figure 3.
Regional Variations in Group Differences in Cortical Thickness and CNR1 Expression

A. Median values of CNR1 expression (across 6 donors) are plotted as bars for the 34 cortical regions (left hemisphere); regions are ordered according to the expression values (lowest [left] to highest [right]). Median values obtained in each donor (median of all samples available for a given cortical region) are indicated by individual points. Lines connect expression values belonging to the same donor; solid line connects values contributed by a donor with relatively low (flat) expression values. (donor ID:H0351.2002; 39-year old male). B. Group differences in age-adjusted cortical thickness between male adolescent participants who never and ever used cannabis as a function of CNR1 expression in groups at low (left) and high (right) risk from the Saguenay Youth Study (SYS). Regression lines are plotted with shaded 95% CIs; correlation statistics are provided. All corresponding (mean) values are provided in eTable 3 in the Supplement. The 5 regions with highest CNR1 expression are identified by their rank; corresponding names are provided in the x-axis of part A. Bankssts indicates banks of superior temporal sulcus.

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