Shared and Specific Patterns of Structural Brain Connectivity Across Affective and Psychotic Disorders

Jonathan Repple*, Marius Gruber, Marco Mauritz, Siemon C. de Lange, Nils Ralf Winter, Nils Opel, Janik Goltermann, Susanne Meinert, Dominik Grotegerd, Elisabeth J. Leehr, Verena Enneking, Tiana Borgers, Melissa Klug, Hannah Lemke, Lena Waltemate, Katharina Thiel, Alexandra Winter, Fabian Breuer, Pascal Grumbach, Hannes HofmannFrederike Stein, Katharina Brosch, Kai G. Ringwald, Julia Pfarr, Florian Thomas-Odenthal, Tina Meller, Andreas Jansen, Igor Nenadic, Ronny Redlich, Jochen Bauer, Tilo Kircher, Tim Hahn, Martijn van den Heuvel, Udo Dannlowski

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

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Abstract

BACKGROUND: Altered brain structural connectivity has been implicated in the pathophysiology of psychiatric disorders including schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). However, it is unknown which part of these connectivity abnormalities are disorder specific and which are shared across the spectrum of psychotic and affective disorders. We investigated common and distinct brain connectivity alterations in a large sample (N = 1743) of patients with SZ, BD, or MDD and healthy control (HC) subjects.

METHODS: This study examined diffusion-weighted imaging-based structural connectome topology in 720 patients with MDD, 112 patients with BD, 69 patients with SZ, and 842 HC subjects (mean age of all subjects: 35.7 years). Graph theory-based network analysis was used to investigate connectome organization. Machine learning algorithms were trained to classify groups based on their structural connectivity matrices.

RESULTS: Groups differed significantly in the network metrics global efficiency, clustering, present edges, and global connectivity strength with a converging pattern of alterations between diagnoses (e.g., efficiency: HC > MDD > BD > SZ, false discovery rate-corrected p = .028). Subnetwork analysis revealed a common core of edges that were affected across all 3 disorders, but also revealed differences between disorders. Machine learning algorithms could not discriminate between disorders but could discriminate each diagnosis from HC. Furthermore, dysconnectivity patterns were found most pronounced in patients with an early disease onset irrespective of diagnosis.

CONCLUSIONS: We found shared and specific signatures of structural white matter dysconnectivity in SZ, BD, and MDD, leading to commonly reduced network efficiency. These results showed a compromised brain communication across a spectrum of major psychiatric disorders.

Original languageEnglish
Pages (from-to)178-186
Number of pages9
JournalBiological psychiatry
Volume93
Issue number2
Early online date21 Jun 2022
DOIs
Publication statusPublished - 15 Jan 2023

Bibliographical note

Funding Information:
This work is part of the German multicenter consortium “Neurobiology of Affective Disorders. A translational perspective on brain structure and function,” funded by the DFG Forschungsgruppe/Research Unit FOR2107. Principal investigators with respective areas of responsibility in the FOR2107 consortium are as follows: Work Package WP1, FOR2107/MACS cohort and brainimaging: TK (speaker FOR2107; DFG Grant Nos. KI 588/14-1, KI 588/14-2), UD (cospeaker FOR2107; Grant Nos. DA 1151/5-1, DA 1151/5-2), Axel Krug (Grant Nos. KR 3822/5-1, KR 3822/7-2), IN (Grant No. NE 2254/1-2), Carsten Konrad (Grant No. KO 4291/3-1). CP1, biobank: Petra Pfefferle (Grant Nos. PF 784/1-1, PF 784/1-2), Harald Renz (Grant Nos. RE 737/20-1, 737/20-2). CP2, administration: TK (Grant Nos. KI 588/15-1, KI 588/17-1), UD (Grant No. DA 1151/6-1), Carsten Konrad (Grant No. KO 4291/4-1). MvdH was supported by an ALW open (Grant No. ALWOP.179) and Vidi (Grant No. 452-16-015) grant from the Netherlands Organization for Scientific Research (NWO) and a Fellowship of MQ.

Funding Information:
This work was funded by the German Research Foundation (Deutsche Forschungsgemeinschaft [DFG] Grant Nos. FOR2107, DA1151/5-1, and DA1151/5-2 [to UD], Grant Nos. HA7070/2-2, HA7070/3, and HA7070/4 [to TH], and Grant No. SFB-TRR58, Projects C09 and Z02 [to UD]); the Interdisciplinary Center for Clinical Research of the medical faculty of Münster (Grant No. Dan3/012/17 [to UD]); the Innovative Medical Research Funding Agency (IMF), University of Münster (Grant Nos. RE111604 and RE111722 [to RR]); IMF, University of Münster (Grant No. RE 22 17 07 [to JR]); and the Deanery of the Medical Faculty of the University of Münster; ERC Consolidator grant (Grant No. ERC-COG 101001062 [to MP]); and an NWO Vidi grant of the Dutch Research Council (Netherlands Organization for Scientific Research Grant No. VIDI-452-16-015 [to MP]). This work is part of the German multicenter consortium “Neurobiology of Affective Disorders. A translational perspective on brain structure and function,” funded by the DFG Forschungsgruppe/Research Unit FOR2107. Principal investigators with respective areas of responsibility in the FOR2107 consortium are as follows: Work Package WP1, FOR2107/MACS cohort and brainimaging: TK (speaker FOR2107; DFG Grant Nos. KI 588/14-1, KI 588/14-2), UD (cospeaker FOR2107; Grant Nos. DA 1151/5-1, DA 1151/5-2), Axel Krug (Grant Nos. KR 3822/5-1, KR 3822/7-2), IN (Grant No. NE 2254/1-2), Carsten Konrad (Grant No. KO 4291/3-1). CP1, biobank: Petra Pfefferle (Grant Nos. PF 784/1-1, PF 784/1-2), Harald Renz (Grant Nos. RE 737/20-1, 737/20-2). CP2, administration: TK (Grant Nos. KI 588/15-1, KI 588/17-1), UD (Grant No. DA 1151/6-1), Carsten Konrad (Grant No. KO 4291/4-1). MvdH was supported by an ALW open (Grant No. ALWOP.179) and Vidi (Grant No. 452-16-015) grant from the Netherlands Organization for Scientific Research (NWO) and a Fellowship of MQ. The FOR2107 cohort project (WP1) was approved by the Ethics Committees of the Medical Faculties, University of Marburg (AZ: 07/14) and University of Münster (AZ: 2014-422-b-S). Acknowledgments and members by Work Package (WP). WP1: Henrike Bröhl, Katharina Brosch, Bruno Dietsche, Rozbeh Elahi, Jennifer Engelen, Sabine Fischer, Jessica Heinen, Svenja Klingel, Felicitas Meier, Tina Meller, Torsten Sauder, Simon Schmitt, Frederike Stein, Annette Tittmar, Dilara Yüksel (Department of Psychiatry, Marburg University); Mechthild Wallnig, Rita Werner (Core-Facility Brainimaging, Marburg University); Carmen Schade-Brittinger, Maik Hahmann (Coordinating Centre for Clinical Trials, Marburg); Michael Putzke (Psychiatric Hospital, Friedberg); Rolf Speier, Lutz Lenhard (Psychiatric Hospital, Haina); Birgit Köhnlein (Psychiatric Practice, Marburg); Peter Wulf, Jürgen Kleebach, Achim Becker (Psychiatric Hospital Hephata, Schwalmstadt-Treysa); Ruth Bär (Care facility Bischoff, Neunkirchen); Matthias Müller, Michael Franz, Siegfried Scharmann, Anja Haag, Kristina Spenner, Ulrich Ohlenschläger (Psychiatric Hospital Vitos, Marburg); Matthias Müller, Michael Franz, Bernd Kundermann (Psychiatric Hospital Vitos, Gießen); Christian Bürger, Katharina Dohm, Fanni Dzvonyar, Verena Enneking, Stella Fingas, Katharina Förster, Janik Goltermann, Dominik Grotegerd, Hannah Lemke, Susanne Meinert, Nils Opel, Ronny Redlich, Jonathan Repple, Kordula Vorspohl, Bettina Walden, Dario Zaremba (Dept. of Psychiatry, University of Münster); Harald Kugel, Jochen Bauer, Walter Heindel, Birgit Vahrenkamp (Department of Clinical Radiology, University of Münster); Gereon Heuft, Gudrun Schneider (Department of Psychosomatics and Psychotherapy, University of Münster); Thomas Reker (LWL-Hospital Münster); Gisela Bartling (IPP Münster); and Ulrike Buhlmann (Department of Clinical Psychology, University of Münster); CP1: Julian Glandorf, Fabian Kormann, Arif Alkan, Fatana Wedi, Lea Henning, Alena Renker, Karina Schneider, Elisabeth Folwarczny, Dana Stenzel, Kai Wenk, Felix Picard, Alexandra Fischer, Sandra Blumenau, Beate Kleb, Doris Finholdt, Elisabeth Kinder, Tamara Wüst, Elvira Przypadlo, Corinna Brehm (Comprehensive Biomaterial Bank Marburg, Marburg University). All principal investigators take responsibility for the integrity of the respective study data and their components. All authors and coauthors had full access to all study data. All authors have approved the final article. TK received unrestricted educational grants from Servier, Janssen, Recordati, Aristo Pharma, Otsuka, and neuraxpharm. All other authors report no biomedical financial interests or potential conflicts of interest.

Funding Information:
This work was funded by the German Research Foundation (Deutsche Forschungsgemeinschaft [DFG] Grant Nos. FOR2107, DA1151/5-1, and DA1151/5-2 [to UD], Grant Nos. HA7070/2-2, HA7070/3, and HA7070/4 [to TH], and Grant No. SFB-TRR58, Projects C09 and Z02 [to UD]); the Interdisciplinary Center for Clinical Research of the medical faculty of Münster (Grant No. Dan3/012/17 [to UD]); the Innovative Medical Research Funding Agency (IMF), University of Münster (Grant Nos. RE111604 and RE111722 [to RR]); IMF , University of Münster (Grant No. RE 22 17 07 [to JR]); and the Deanery of the Medical Faculty of the University of Münster; ERC Consolidator grant (Grant No. ERC-COG 101001062 [to MP]); and an NWO Vidi grant of the Dutch Research Council (Netherlands Organization for Scientific Research Grant No. VIDI-452-16-015 [to MP]).

Funding Information:
TK received unrestricted educational grants from Servier , Janssen, Recordati, Aristo Pharma, Otsuka, and neuraxpharm. All other authors report no biomedical financial interests or potential conflicts of interest.

Publisher Copyright:
© 2022 Society of Biological Psychiatry

Keywords

  • Bipolar
  • Connectomics
  • Depression
  • Network
  • Schizophrenia
  • Transdiagnostic

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