Data-driven multivariate identification of gyrification patterns in a transdiagnostic patient cohort: A cluster analysis approach
Julia-Katharina Pfarr,
Tina Meller,
Katharina Brosch,
Frederike Stein,
Florian Thomas-Odenthal,
Ulrika Evermann,
Adrian Wroblewski,
Kai G. Ringwald,
Tim Hahn,
Susanne Meinert,
Alexandra Winter,
Katharina Thiel,
Kira Flinkenflügel,
Andreas Jansen,
Axel Krug,
Udo Dannlowski,
Tilo Kircher,
Christian Gaser,
Igor Nenadić
Affiliations
Julia-Katharina Pfarr
Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Department of Psychology, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany; Corresponding author at: Department of Psychology, Philipps Universität Marburg, Gutenbergstr. 18, Marburg 35032, Germany
Tina Meller
Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany
Katharina Brosch
Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany
Frederike Stein
Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany
Florian Thomas-Odenthal
Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany
Ulrika Evermann
Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany
Adrian Wroblewski
Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany
Kai G. Ringwald
Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany
Tim Hahn
Institute for Translational Psychiatry, University of Münster, Germany
Susanne Meinert
Institute for Translational Psychiatry, University of Münster, Germany; Institute for Translational Neuroscience, University of Münster, Germany
Alexandra Winter
Institute for Translational Psychiatry, University of Münster, Germany
Katharina Thiel
Institute for Translational Psychiatry, University of Münster, Germany
Kira Flinkenflügel
Institute for Translational Psychiatry, University of Münster, Germany
Andreas Jansen
Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany; Core-Facility Brainimaging, Faculty of Medicine, University of Marburg, Germany
Axel Krug
Department of Psychiatry und Psychotherapy, University Hospital Bonn, Germany
Udo Dannlowski
Institute for Translational Psychiatry, University of Münster, Germany
Tilo Kircher
Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany
Christian Gaser
Department of Neurology, Jena University Hospital, Germany; Department of Psychiatry and Psychotherapy, Jena University Hospital, Germany; German Center for Mental Health (DZPG), Site Jena-Magdeburg-Halle, Germany; Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Jena-Magdeburg-Halle, Germany
Igor Nenadić
Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany
Background: Multivariate data-driven statistical approaches offer the opportunity to study multi-dimensional interdependences between a large set of biological parameters, such as high-dimensional brain imaging data. For gyrification, a putative marker of early neurodevelopment, direct comparisons of patterns among multiple psychiatric disorders and investigations of potential heterogeneity of gyrification within one disorder and a transdiagnostic characterization of neuroanatomical features are lacking. Methods: In this study we used a data-driven, multivariate statistical approach to analyze cortical gyrification in a large cohort of N = 1028 patients with major psychiatric disorders (Major depressive disorder: n = 783, bipolar disorder: n = 129, schizoaffective disorder: n = 44, schizophrenia: n = 72) to identify cluster patterns of gyrification beyond diagnostic categories. Results: Cluster analysis applied on gyrification data of 68 brain regions (DK-40 atlas) identified three clusters showing difference in overall (global) gyrification and minor regional variation (regions). Newly, data-driven subgroups are further discriminative in cognition and transdiagnostic disease risk factors. Conclusions: Results indicate that gyrification is associated with transdiagnostic risk factors rather than diagnostic categories and further imply a more global role of gyrification related to mental health than a disorder specific one. Our findings support previous studies highlighting the importance of association cortices involved in psychopathology. Explorative, data-driven approaches like ours can help to elucidate if the brain imaging data on hand and its a priori applied grouping actually has the potential to find meaningful effects or if previous hypotheses about the phenotype as well as its grouping have to be revisited.
