Structural differences in adolescent brains can predict alcohol misuse

  1. Roshan Prakash Rane  Is a corresponding author
  2. Evert Ferdinand de Man
  3. JiHoon Kim
  4. Kai Görgen
  5. Mira Tschorn
  6. Michael A Rapp
  7. Tobias Banaschewski
  8. Arun LW Bokde
  9. Sylvane Desrivieres
  10. Herta Flor
  11. Antoine Grigis
  12. Hugh Garavan
  13. Penny A Gowland
  14. Rüdiger Brühl
  15. Jean-Luc Martinot
  16. Marie-Laure Paillere Martinot
  17. Eric Artiges
  18. Frauke Nees
  19. Dimitri Papadopoulos Orfanos
  20. Herve Lemaitre
  21. Tomas Paus
  22. Luise Poustka
  23. Juliane Fröhner
  24. Lauren Robinson
  25. Michael N Smolka
  26. Jeanne Winterer
  27. Robert Whelan
  28. Gunter Schumann
  29. Henrik Walter
  30. Andreas Heinz
  31. Kerstin Ritter
  32. IMAGEN Consortium
  1. Charité - Universitätsmedizin Berlin, Germany
  2. Technical University of Berlin, Germany
  3. Freie Universität Berlin, Germany
  4. University of Potsdam, Germany
  5. Heidelberg University, Germany
  6. Trinity College Dublin, Ireland
  7. King's College London, United Kingdom
  8. Université Paris-Saclay, France
  9. University of Vermont, United States
  10. University of Nottingham, United Kingdom
  11. Physikalisch-Technische Bundesanstalt, Germany
  12. Université Paris-Saclay, CNRS, INSERM, France
  13. University of Bordeaux, France
  14. University of Montreal, Canada
  15. Universitätsmedizin Göttingen, Germany
  16. TU Dresden, Germany

Abstract

Alcohol misuse during adolescence (AAM) has been associated with disruptive development of adolescent brains. In this longitudinal machine learning (ML) study, we could predict AAM significantly from brain structure (T1-weighted imaging and DTI) with accuracies of 73 - 78% in the IMAGEN dataset (n ~1182). Our results not only show that structural differences in brain can predict AAM, but also suggests that such differences might precede AAM behavior in the data. We predicted ten phenotypes of AAM at age 22 using brain MRI features at ages 14, 19, and 22. Binge drinking was found to be the most predictable phenotype. The most informative brain features were located in the ventricular CSF, and in white matter tracts of the corpus callosum, internal capsule, and brain stem. In the cortex, they were spread across the occipital, frontal, and temporal lobes and in the cingulate cortex. We also experimented with four different ML models and several confound control techniques. Support Vector Machine (SVM) with rbf kernel and Gradient Boosting consistently performed better than the linear models, linear SVM and Logistic Regression. Our study also demonstrates how the choice of the predicted phenotype, ML model, and confound correction technique are all crucial decisions in an explorative ML study analyzing psychiatric disorders with small effect sizes such as AAM.

Data availability

This is a computational study. All data analyses code including the modelling pipeline are openly provided publicly at https://github.com/RoshanRane/ML_for_IMAGEN for reuse and reproduction.Approval to use the IMAGEN dataset for this study was provided under the approval username / project code 'edeman'.

The following previously published data sets were used

Article and author information

Author details

  1. Roshan Prakash Rane

    Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
    For correspondence
    roshan.rane@bccn-berlin.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3996-2034
  2. Evert Ferdinand de Man

    Faculty IV - Electrical Engineering and Computer Science, Technical University of Berlin, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
  3. JiHoon Kim

    Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3157-3472
  4. Kai Görgen

    Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4711-9629
  5. Mira Tschorn

    Department of Sports and Health Sciences, University of Potsdam, Potsdam, Germany
    Competing interests
    The authors declare that no competing interests exist.
  6. Michael A Rapp

    Department of Sports and Health Sciences, University of Potsdam, Potsdam, Germany
    Competing interests
    The authors declare that no competing interests exist.
  7. Tobias Banaschewski

    Department of Child and Adolescent Psychiatry and Psychotherapy, Heidelberg University, Mannheim, Germany
    Competing interests
    The authors declare that no competing interests exist.
  8. Arun LW Bokde

    Discipline of Psychiatry, Trinity College Dublin, Dublin, Ireland
    Competing interests
    The authors declare that no competing interests exist.
  9. Sylvane Desrivieres

    Institute of Psychiatry, Psychology Neuroscience, King's College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  10. Herta Flor

    Institute of Cognitive and Clinical Neuroscience, Heidelberg University, Mannheim, Germany
    Competing interests
    The authors declare that no competing interests exist.
  11. Antoine Grigis

    NeuroSpin, CEA, Université Paris-Saclay, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  12. Hugh Garavan

    Departments of Psychiatry and Psychology, University of Vermont, Burlington, United States
    Competing interests
    The authors declare that no competing interests exist.
  13. Penny A Gowland

    School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  14. Rüdiger Brühl

    Physikalisch-Technische Bundesanstalt, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0111-5996
  15. Jean-Luc Martinot

    Université Paris-Saclay, CNRS, INSERM, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  16. Marie-Laure Paillere Martinot

    Université Paris-Saclay, CNRS, INSERM, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  17. Eric Artiges

    Université Paris-Saclay, CNRS, INSERM, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  18. Frauke Nees

    Department of Cognitive and Clinical Neuroscience, Heidelberg University, Mannheim, Germany
    Competing interests
    The authors declare that no competing interests exist.
  19. Dimitri Papadopoulos Orfanos

    NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1242-8990
  20. Herve Lemaitre

    Institut des Maladies Neurodégénératives, University of Bordeaux, Bordeaux, France
    Competing interests
    The authors declare that no competing interests exist.
  21. Tomas Paus

    Department of Psychiatry, University of Montreal, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
  22. Luise Poustka

    Department of Child and Adolescent Psychiatry and Psychotherapy, Universitätsmedizin Göttingen, Göttingen, Germany
    Competing interests
    The authors declare that no competing interests exist.
  23. Juliane Fröhner

    Department of Psychiatry, TU Dresden, Dresden, Germany
    Competing interests
    The authors declare that no competing interests exist.
  24. Lauren Robinson

    Department of Psychological Medicine, King's College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  25. Michael N Smolka

    Department of Psychiatry, TU Dresden, Dresden, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5398-5569
  26. Jeanne Winterer

    Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
  27. Robert Whelan

    School of Psychology, Trinity College Dublin, Dublin, Ireland
    Competing interests
    The authors declare that no competing interests exist.
  28. Gunter Schumann

    Department of Psychiatry and Psychotherapy, King's College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  29. Henrik Walter

    Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
  30. Andreas Heinz

    Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
  31. Kerstin Ritter

    Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
  32. IMAGEN Consortium

Funding

German Research Foundation (402170461-TRR 265)

  • Roshan Prakash Rane
  • JiHoon Kim
  • Henrik Walter
  • Andreas Heinz
  • Kerstin Ritter

German Research Foundation (389563835)

  • Kerstin Ritter

German Research Foundation (414984028-CRC 1404)

  • Kerstin Ritter

German Research Foundation (XC 2002/1 Science of Intelligence" - project number 390523135")

  • Kai Görgen

NSFC Research Fund for International Scientists (82150710554)

  • Gunter Schumann

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: Written and informed consent was obtained from all participants by the IMAGEN consortium and the study was approved by the institutional ethics committee of King's College London,University of Nottingham, Trinity College Dublin, University of Heidelberg, Technische Universität Dresden, Commissariat à l'Energie Atomique et aux Energies Alternatives, and University Medical Center at the University of Hamburg in accordance with the Declaration of Helsinki (doi:10. 1001/jama.2013.281053).For this specific data analysis project, approval was provided by the IMAGEN group to us under the approval username / project ID 'edeman'.For this specific data analysis project, approval was provided by the IMAGEN group under the approval username 'edeman'.

Reviewing Editor

  1. Saad Jbabdi, University of Oxford, United Kingdom

Publication history

  1. Received: February 2, 2022
  2. Accepted: May 25, 2022
  3. Accepted Manuscript published: May 26, 2022 (version 1)

Copyright

© 2022, Rane et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Roshan Prakash Rane
  2. Evert Ferdinand de Man
  3. JiHoon Kim
  4. Kai Görgen
  5. Mira Tschorn
  6. Michael A Rapp
  7. Tobias Banaschewski
  8. Arun LW Bokde
  9. Sylvane Desrivieres
  10. Herta Flor
  11. Antoine Grigis
  12. Hugh Garavan
  13. Penny A Gowland
  14. Rüdiger Brühl
  15. Jean-Luc Martinot
  16. Marie-Laure Paillere Martinot
  17. Eric Artiges
  18. Frauke Nees
  19. Dimitri Papadopoulos Orfanos
  20. Herve Lemaitre
  21. Tomas Paus
  22. Luise Poustka
  23. Juliane Fröhner
  24. Lauren Robinson
  25. Michael N Smolka
  26. Jeanne Winterer
  27. Robert Whelan
  28. Gunter Schumann
  29. Henrik Walter
  30. Andreas Heinz
  31. Kerstin Ritter
  32. IMAGEN Consortium
(2022)
Structural differences in adolescent brains can predict alcohol misuse
eLife 11:e77545.
https://doi.org/10.7554/eLife.77545

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