Juliane H Fröhner1, Stephan Ripke1, Sarah Jurk1, Shu-Chen Li2, Tobias Banaschewski3, Arun L W Bokde4, Erin Burke Quinlan5, Sylvane Desrivières5, Herta Flor6,7, Antoine Grigis8, Hugh Garavan9, Andreas Heinz10, Rüdiger Brühl11, Jean-Luc Martinot12, Marie-Laure Paillère Martinot12,13, Eric Artiges12,14,15, Frauke Nees3,6,16, Dimitri Papadopoulos Orfanos8, Luise Poustka17, Sarah Hohmann3, Henrik Walter10, Robert Whelan18, Gunter Schumann5,19,20,21, Michael N Smolka1. 1. Department of Psychiatry, Technische Universität Dresden, Dresden, Germany. 2. Faculty of Psychology, Chair of Lifespan Developmental Neuroscience, Technische Universität Dresden, Dresden, Germany. 3. Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany. 4. Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland. 5. Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, London, UK. 6. Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany. 7. Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany. 8. NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France. 9. Departments of Psychiatry and Psychology, University of Vermont, Burlington, Vermont, USA. 10. Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany. 11. Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany. 12. Institut National de la Santé et de la Recherche Médicale, INSERM U A10 "Trajectoires développementales & psychiatrie", École normale supérieure Paris-Saclay, CNRS, Centre Borelli, Université Paris-Saclay, Gif-sur-Yvette, France. 13. Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Sorbonne Université, Paris, France. 14. Psychiatry Department, EPS Barthélémy Durand, Etampes, France. 15. Institut des Maladies Neurodégénératives, UMR 5293, CNRS, CEA, Université de Bordeaux, Bordeaux, France. 16. Leibniz Institute for Neurobiology, Magdeburg, Germany. 17. Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen, Germany. 18. School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland. 19. PONS Research Group, Department of Psychiatry and Psychotherapy, Humboldt University, Berlin, Germany. 20. Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China. 21. Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig Holstein, Kiel University, Kiel, Germany.
Abstract
BACKGROUND: While drinking alcohol, one must choose between the immediate rewarding effects and the delayed reward of a healthier lifestyle. Individuals differ in their devaluation of a delayed reward based on the time required to receive it, i.e., delay discounting (DD). Previous studies have shown that adolescents discount more steeply than adults and that steeper DD is associated with heavier alcohol use in both groups. METHODS: In a large-scale longitudinal study, we investigated whether higher rates of DD are an antecedent or a consequence of alcohol use during adolescent development. As part of the IMAGEN project, 2220 adolescents completed the Monetary Choice Questionnaire as a DD measure, the Alcohol Use Disorders Identification Test, and the Timeline Follow Back interview at ages 14, 16, 18, and 22. Bivariate latent growth curve models were applied to investigate the relationship between DD and drinking. To explore the consequences of drinking, we computed the cumulative alcohol consumption and correlated it with the development of discounting. A subsample of 221 participants completed an intertemporal choice task (iTeCh) during functional magnetic resonance imaging at ages 14, 16, and 18. Repeated-measures ANOVA was used to differentiate between high-risk and low-risk drinkers on the development of neural processing during intertemporal choices. RESULTS: Overall, high rates of DD at age 14 predicted a greater increase in drinking over 8 years. In contrast, on average, moderate alcohol use did not affect DD from ages 14 to 22. Of note, we found indicators for less brain activity in top-down control areas during intertemporal choices in the participants who drank more. CONCLUSIONS: Steep DD was shown to be a predictor rather than a consequence of alcohol use in low-level drinking adolescents. Important considerations for future longitudinal studies are the sampling strategies to be used and the reliability of the assessments.
BACKGROUND: While drinking alcohol, one must choose between the immediate rewarding effects and the delayed reward of a healthier lifestyle. Individuals differ in their devaluation of a delayed reward based on the time required to receive it, i.e., delay discounting (DD). Previous studies have shown that adolescents discount more steeply than adults and that steeper DD is associated with heavier alcohol use in both groups. METHODS: In a large-scale longitudinal study, we investigated whether higher rates of DD are an antecedent or a consequence of alcohol use during adolescent development. As part of the IMAGEN project, 2220 adolescents completed the Monetary Choice Questionnaire as a DD measure, the Alcohol Use Disorders Identification Test, and the Timeline Follow Back interview at ages 14, 16, 18, and 22. Bivariate latent growth curve models were applied to investigate the relationship between DD and drinking. To explore the consequences of drinking, we computed the cumulative alcohol consumption and correlated it with the development of discounting. A subsample of 221 participants completed an intertemporal choice task (iTeCh) during functional magnetic resonance imaging at ages 14, 16, and 18. Repeated-measures ANOVA was used to differentiate between high-risk and low-risk drinkers on the development of neural processing during intertemporal choices. RESULTS: Overall, high rates of DD at age 14 predicted a greater increase in drinking over 8 years. In contrast, on average, moderate alcohol use did not affect DD from ages 14 to 22. Of note, we found indicators for less brain activity in top-down control areas during intertemporal choices in the participants who drank more. CONCLUSIONS: Steep DD was shown to be a predictor rather than a consequence of alcohol use in low-level drinking adolescents. Important considerations for future longitudinal studies are the sampling strategies to be used and the reliability of the assessments.
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