Machine learning models for diagnosis and risk prediction in eating disorders, depression, and alcohol use disorder
Autor(in); Institution
Zhang, Zuo; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK ; School of Psychology, Institute for Mental Health, University of Birmingham, Birmingham, UK
Robinson, Lauren; Department of Psychological Medicine, Centre for Research in Eating and Weight Disorders, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK ; South London and Maudsley NHS Foundation Trust, London, UK ; Oxford Institute of Clinical Psychology Training and Research, Oxford University, Oxford, UK
Whelan, Robert; School of Psychology and Global Brain Health Institute, Trinity College Dublin, IRELAND
Jollans, Lee; School of Psychology and Global Brain Health Institute, Trinity College Dublin, IRELAND
Wang, Zijian; School of Computer Science and Technology, Donghua University, Shanghai, CHINA
Nees, Frauke; Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany ; Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany ; Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein, Kiel University, Kiel, GERMANY
Chu, Congying; University of Chinese Academy of Sciences, Beijing, China ; Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 100190 Beijing, China; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, CHINA
Bobou, Marina; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK ; Research Department of Clinical, Educational and Health Psychology, University College London, London, UK
Du, Dongping; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK ; Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA, USA
Cristea, Ilinca; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
Banaschewski, Tobias; Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, GERMANY
Barker, Gareth J; Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
Bokde, Arun L W; Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, IRELAND
Grigis, Antoine; NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, FRANCE
Garavan, Hugh; Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT, USA
Heinz, Andreas; Charité - Universitätsmedizin Berlin, 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
Brühl, Rüdiger; 8.1, Biomedizinische Magnetresonanz, PTB-Berlin; Université Paris Cité, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli UMR9010, Gif-sur-Yvette, FRANCE
Martinot, Jean-Luc; Institut National de la Santé et de la Recherche Médicale, INSERM U1299 "Developmental trajectories & psychiatry", Université Paris-Saclay, Université Paris Cité, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli UMR9010, Gif-sur-Yvette, FRANCE
Paillère Martinot, Marie-Laure; Institut National de la Santé et de la Recherche Médicale, INSERM U1299 "Developmental trajectories & psychiatry", Université Paris-Saclay, Université Paris Cité, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli UMR9010, Gif-sur-Yvette, France ; AP-HP, Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, FRANCE
Artiges, Eric; Institut National de la Santé et de la Recherche Médicale, INSERM U1299 "Developmental trajectories & psychiatry", Université Paris-Saclay, Université Paris Cité, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli UMR9010, Gif-sur-Yvette, France ; AP-HP, Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, FRANCE
Papadopoulos Orfanos, Dimitri; NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, FRANCE
Poustka, Luise; Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen, GERMANY
Hohmann, Sarah; Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, GERMANY
Millenet, Sabina; Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, GERMANY
Fröhner, Juliane H; Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, GERMANY
Smolka, Michael N; Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, GERMANY
Vaidya, Nilakshi; Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, GERMANY
Walter, Henrik; Charité - Universitätsmedizin Berlin, 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
Winterer, Jeanne; Charité - Universitätsmedizin Berlin, 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 ; Department of Education and Psychology, Freie Universität Berlin, Berlin, GERMANY
Broulidakis, M John; Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK ; Department of Psychology, College of Science, Northeastern University, Boston, MA, USA
van Noort, Betteke Maria; Department of Psychology, MSB Medical School Berlin, Berlin, GERMANY
Stringaris, Argyris; Division of Psychiatry and Department of Clinical, Educational & Health Psychology, University College London, UK
Penttilä, Jani; Department of Social and Health Care, Psychosocial Services Adolescent Outpatient Clinic Kauppakatu, Lahti, FINLAND
Grimmer, Yvonne; Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, GERMANY
Insensee, Corinna; Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen, GERMANY
Becker, Andreas; Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen, GERMANY
Zhang, Yuning; Psychology Department, B44 University Rd, University of Southampton, Southampton, UK
King, Sinead; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK ; School of Medicine, Centre for Neuroimaging, Cognition and Genomics, National University of Ireland (NUI), Galway, IRELAND ; Beaumont Hospital, Royal College of Surgeons, IRELAND
Sinclair, Julia; Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
Schumann, Gunter; Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, GERMANY ; Centre for Population Neuroscience and Precision Medicine (PONS), Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, CHINA
Schmidt, Ulrike; Department of Psychological Medicine, Centre for Research in Eating and Weight Disorders, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK ; South London and Maudsley NHS Foundation Trust, London, UK
Desrivières, Sylvane; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
Quelle/Jahr
Journal of Affective Disorders: 379
(2025), 889
- 899
alcohol use disorder ; eating disorders ; major depressive disorder ; predictive modeling ; risk factors
Zusammenfassung
Background
Early diagnosis and treatment of mental illnesses is hampered by the lack of reliable markers. This study used machine learning models to uncover diagnostic and risk prediction markers for eating disorders (EDs), major depressive disorder (MDD), and alcohol use disorder (AUD).
Methods
Case-control samples (aged 18–25 years), including participants with Anorexia Nervosa (AN), Bulimia Nervosa (BN), MDD, AUD, and matched controls, were used for diagnostic classification. For risk prediction, we used a longitudinal population-based sample (IMAGEN study), assessing adolescents at ages 14, 16 and 19. Regularized logistic regression models incorporated broad data domains spanning psychopathology, personality, cognition, substance use, and environment.
Results
The classification of EDs was highly accurate, even when excluding body mass index from the analysis. The area under the receiver operating characteristic curves (AUC-ROC [95 % CI]) reached 0.92 [0.86–0.97] for AN and 0.91 [0.85–0.96] for BN. The classification accuracies for MDD (0.91 [0.88–0.94]) and AUD (0.80 [0.74–0.85]) were also high. The models demonstrated high transdiagnostic potential, as those trained for EDs were also accurate in classifying AUD and MDD from healthy controls, and vice versa (AUC-ROCs, 0.75–0.93). Shared predictors, such as neuroticism, hopelessness, and symptoms of attention-deficit/hyperactivity disorder, were identified as reliable classifiers. In the longitudinal population sample, the models exhibited moderate performance in predicting the development of future ED symptoms (0.71 [0.67–0.75]), depressive symptoms (0.64 [0.60–0.68]), and harmful drinking (0.67 [0.64–0.70]).
Conclusions
Our findings demonstrate the potential of combining multi-domain data for precise diagnostic and risk prediction applications in psychiatry..
Zitierung
Zhang, Z., Robinson, L., Whelan, R., Jollans, L., Wang, Z., Nees, F., Chu, C., Bobou, M., Du, D., Cristea, I., Banaschewski, T., Barker, G. J., Bokde, A. L. W., Grigis, A., Garavan, H., Heinz, A., Brühl, R., Martinot, J.-L., Paillère Martinot, M.-L., Artiges, E., Papadopoulos Orfanos, D., Poustka, L., Hohmann, S., Millenet, S., Fröhner, J. H., Smolka, M. N., Vaidya, N., Walter, H., Winterer, J., Broulidakis, M. J., van Noort, B. M., Stringaris, A., Penttilä, J., Grimmer, Y., Insensee, C., Becker, A., Zhang, Y., King, S., Sinclair, J., Schumann, G., Schmidt, U., & Desrivières, S. (2025). Machine learning models for diagnosis and risk prediction in eating disorders, depression, and alcohol use disorder. Journal of Affective Disorders, 379, 889–899. https://doi.org/10.1016/j.jad.2024.12.053
