Shile Qi1, Gunter Schumann2, Juan Bustillo3, Jessica A Turner4, Rongtao Jiang5, Dongmei Zhi5, Zening Fu6, Andrew R Mayer3, Victor M Vergara6, Rogers F Silva6, Armin Iraji6, Jiayu Chen6, Eswar Damaraju6, Xiaohong Ma7, Xiao Yang7, Michael Stevens8, Daniel H Mathalon9, Judith M Ford9, James Voyvodic10, Bryon A Mueller11, Aysenil Belger12, Steven G Potkin13, Adrian Preda13, Chuanjun Zhuo14, Yong Xu15, Congying Chu2, Tobias Banaschewski16, Gareth J Barker17, Arun L W Bokde18, Erin Burke Quinlan2, Sylvane Desrivières2, Herta Flor19, Antoine Grigis20, Hugh Garavan21, Penny Gowland22, Andreas Heinz23, Jean-Luc Martinot24, Marie-Laure Paillère Martinot24, Eric Artiges24, Frauke Nees16, Dimitri Papadopoulos Orfanos20, Tomáš Paus25, Luise Poustka26, Sarah Hohmann16, Juliane H Fröhner27, Michael N Smolka27, Henrik Walter23, Robert Whelan28, Vince D Calhoun29, Jing Sui30. 1. Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute Technology, and Emory University, Atlanta, Georgia; Department of Computer Science and Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China. 2. Centre for Population Neuroscience and Stratified Medicine, Institute for Science and Technology of Brain-Inspired Intelligence, Fudan University, Shanghai, China. 3. Department of Psychiatry, University of New Mexico, Albuquerque, New Mexico. 4. Department of Psychology, Georgia State University, Atlanta, Georgia. 5. University of Chinese Academy of Sciences, Beijing, China; Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China. 6. Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute Technology, and Emory University, Atlanta, Georgia. 7. Psychiatric Laboratory and Mental Health Center, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China. 8. Olin Neuropsychiatry Research Center, Hartford, Connecticut. 9. Department of Psychiatry, University of California San Francisco, San Francisco, California. 10. Department of Radiology, Duke University, Durham, North Carolina. 11. Department of Psychiatry, University of Minnesota, Minneapolis, Minnesota. 12. Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina. 13. Department of Psychiatry, University of California Irvine, Irvine, California. 14. Department of Psychiatric-Neuroimaging-Genetics and Morbidity Laboratory, Nankai University Affiliated Anding Hospital, Tianjin, China. 15. Department of Humanities and Social Science, Shanxi Medical University, Taiyuan, China. 16. Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany. 17. Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom. 18. Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland. 19. Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany. 20. NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France. 21. Departments of Psychiatry and Psychology, University of Vermont, Burlington, Vermont. 22. Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, United Kingdom. 23. Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Campus Charité Mitte, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Berlin, Germany. 24. Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 "Neuroimaging & Psychiatry," University Paris-Saclay, Paris, France. 25. Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital and Departments of Psychology and Psychiatry, University of Toronto, Toronto, Ontario, Canada. 26. Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen, Germany. 27. Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany. 28. PONS Research Group, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Humboldt University, Berlin, Germany. 29. Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute Technology, and Emory University, Atlanta, Georgia; Department of Psychology, Georgia State University, Atlanta, Georgia. Electronic address: vcalhoun@ece.gatech.edu. 30. Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute Technology, and Emory University, Atlanta, Georgia; University of Chinese Academy of Sciences, Beijing, China; State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China. Electronic address: kittysj@gmail.com.
Abstract
BACKGROUND: Dysfunctional reward processing is implicated in multiple mental disorders. Novelty seeking (NS) assesses preference for seeking novel experiences, which is linked to sensitivity to reward environmental cues. METHODS: A subset of 14-year-old adolescents (IMAGEN) with the top 20% ranked high-NS scores was used to identify high-NS-associated multimodal components by supervised fusion. These features were then used to longitudinally predict five different risk scales for the same and unseen subjects (an independent dataset of subjects at 19 years of age that was not used in predictive modeling training at 14 years of age) (within IMAGEN, n ≈1100) and even for the corresponding symptom scores of five types of patient cohorts (non-IMAGEN), including drinking (n = 313), smoking (n = 104), attention-deficit/hyperactivity disorder (n = 320), major depressive disorder (n = 81), and schizophrenia (n = 147), as well as to classify different patient groups with diagnostic labels. RESULTS: Multimodal biomarkers, including the prefrontal cortex, striatum, amygdala, and hippocampus, associated with high NS in 14-year-old adolescents were identified. The prediction models built on these features are able to longitudinally predict five different risk scales, including alcohol drinking, smoking, hyperactivity, depression, and psychosis for the same and unseen 19-year-old adolescents and even predict the corresponding symptom scores of five types of patient cohorts. Furthermore, the identified reward-related multimodal features can classify among attention-deficit/hyperactivity disorder, major depressive disorder, and schizophrenia with an accuracy of 87.2%. CONCLUSIONS: Adolescents with higher NS scores can be used to reveal brain alterations in the reward-related system, implicating potential higher risk for subsequent development of multiple disorders. The identified high-NS-associated multimodal reward-related signatures may serve as a transdiagnostic neuroimaging biomarker to predict disease risks or severity.
BACKGROUND: Dysfunctional reward processing is implicated in multiple mental disorders. Novelty seeking (NS) assesses preference for seeking novel experiences, which is linked to sensitivity to reward environmental cues. METHODS: A subset of 14-year-old adolescents (IMAGEN) with the top 20% ranked high-NS scores was used to identify high-NS-associated multimodal components by supervised fusion. These features were then used to longitudinally predict five different risk scales for the same and unseen subjects (an independent dataset of subjects at 19 years of age that was not used in predictive modeling training at 14 years of age) (within IMAGEN, n ≈1100) and even for the corresponding symptom scores of five types of patient cohorts (non-IMAGEN), including drinking (n = 313), smoking (n = 104), attention-deficit/hyperactivity disorder (n = 320), major depressive disorder (n = 81), and schizophrenia (n = 147), as well as to classify different patient groups with diagnostic labels. RESULTS: Multimodal biomarkers, including the prefrontal cortex, striatum, amygdala, and hippocampus, associated with high NS in 14-year-old adolescents were identified. The prediction models built on these features are able to longitudinally predict five different risk scales, including alcohol drinking, smoking, hyperactivity, depression, and psychosis for the same and unseen 19-year-old adolescents and even predict the corresponding symptom scores of five types of patient cohorts. Furthermore, the identified reward-related multimodal features can classify among attention-deficit/hyperactivity disorder, major depressive disorder, and schizophrenia with an accuracy of 87.2%. CONCLUSIONS: Adolescents with higher NS scores can be used to reveal brain alterations in the reward-related system, implicating potential higher risk for subsequent development of multiple disorders. The identified high-NS-associated multimodal reward-related signatures may serve as a transdiagnostic neuroimaging biomarker to predict disease risks or severity.
Authors: Shile Qi; Zening Fu; Lei Wu; Vince D Calhoun; Daoqiang Zhang; Stacey B Daughters; Ping-Ching Hsu; Rongtao Jiang; Victor M Vergara; Jing Sui; Merideth A Addicott Journal: Front Neurosci Date: 2022-07-27 Impact factor: 5.152