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Genetic, individual, and familial risk correlates of brain network controllability in major depressive disorder

Many therapeutic interventions in psychiatry can be viewed as attempts to influence the brain’s large-scale, dynamic network state transitions. Building on connectome-based graph analysis and control theory, Network Control Theory is emerging as a powerful tool to quantify network controllability—i....

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Main Authors: Hahn, Tim (Author) , Winter, Nils Ralf (Author) , Ernsting, Jan (Author) , Gruber, Marius (Author) , Mauritz, Marco J. (Author) , Fisch, Lukas (Author) , Leenings, Ramona (Author) , Sarink, Kelvin (Author) , Blanke, Julian (Author) , Holstein, Vincent (Author) , Emden, Daniel (Author) , Beisemann, Marie (Author) , Opel, Nils (Author) , Grotegerd, Dominik (Author) , Meinert, Susanne (Author) , Heindel, Walter (Author) , Witt, Stephanie (Author) , Rietschel, Marcella (Author) , Nöthen, Markus Maria (Author) , Forstner, Andreas Josef (Author) , Kircher, Tilo (Author) , Nenadic, Igor (Author) , Jansen, Andreas (Author) , Müller-Myhsok, Bertram (Author) , Andlauer, Till (Author) , Walter, Martin (Author) , van den Heuvel, Martijn P. (Author) , Jamalabadi, Hamidreza (Author) , Dannlowski, Udo (Author) , Repple, Jonathan (Author)
Format: Article (Journal)
Language:English
Published: March 2023
In: Molecular psychiatry
Year: 2023, Volume: 28, Issue: 3, Pages: 1057-1063
ISSN:1476-5578
DOI:10.1038/s41380-022-01936-6
Online Access:Verlag, kostenfrei, Volltext: https://doi.org/10.1038/s41380-022-01936-6
Verlag, kostenfrei, Volltext: https://www.nature.com/articles/s41380-022-01936-6
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Author Notes:Tim Hahn, Nils R. Winter, Jan Ernsting, Marius Gruber, Marco J. Mauritz, Lukas Fisch, Ramona Leenings, Kelvin Sarink, Julian Blanke, Vincent Holstein, Daniel Emden, Marie Beisemann, Nils Opel, Dominik Grotegerd, Susanne Meinert, Walter Heindel, Stephanie Witt, Marcella Rietschel, Markus M. Nöthen, Andreas J. Forstner, Tilo Kircher, Igor Nenadic, Andreas Jansen, Bertram Müller-Myhsok, Till F.M. Andlauer, Martin Walter, Martijn P. van den Heuvel, Hamidreza Jamalabadi, Udo Dannlowski and Jonathan Repple
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Summary:Many therapeutic interventions in psychiatry can be viewed as attempts to influence the brain’s large-scale, dynamic network state transitions. Building on connectome-based graph analysis and control theory, Network Control Theory is emerging as a powerful tool to quantify network controllability—i.e., the influence of one brain region over others regarding dynamic network state transitions. If and how network controllability is related to mental health remains elusive. Here, from Diffusion Tensor Imaging data, we inferred structural connectivity and inferred calculated network controllability parameters to investigate their association with genetic and familial risk in patients diagnosed with major depressive disorder (MDD, n = 692) and healthy controls (n = 820). First, we establish that controllability measures differ between healthy controls and MDD patients while not varying with current symptom severity or remission status. Second, we show that controllability in MDD patients is associated with polygenic scores for MDD and psychiatric cross-disorder risk. Finally, we provide evidence that controllability varies with familial risk of MDD and bipolar disorder as well as with body mass index. In summary, we show that network controllability is related to genetic, individual, and familial risk in MDD patients. We discuss how these insights into individual variation of network controllability may inform mechanistic models of treatment response prediction and personalized intervention-design in mental health.
Item Description:Online veröffentlicht: 13. Januar 2023
Gesehen am 16.07.2024
Physical Description:Online Resource
ISSN:1476-5578
DOI:10.1038/s41380-022-01936-6

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