A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Alterations of Functional Connectivity Dynamics in Affective and Psychotic Disorders
Tekijät: Hoheisel, Linnea; Kambeitz-Ilankovic, Lana; Wenzel, Julian; Haas, Shalaila S.; Antonucci, Linda A.; Ruef, Anne; Penzel, Nora; Schultze-Lutter, Frauke; Lichtenstein, Theresa; Rosen, Marlene; Dwyer, Dominic B.; Salokangas, Raimo K.R.; Lencer, Rebekka; Brambilla, Paolo; Borgwardt, Stephan; Wood, Stephen J.; Upthegrove, Rachel; Bertolino, Alessandro; Ruhrmann, Stephan; Meisenzahl, Eva; Koutsouleris, Nikolaos; Fink, Gereon R.; Daun, Silvia; Kambeitz, Joseph; for the PRONIA Consortium
Kustantaja: Elsevier
Julkaisuvuosi: 2024
Journal: Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
Tietokannassa oleva lehden nimi: Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
Vuosikerta: 9
Numero: 8
Aloitussivu: 765
Lopetussivu: 776
ISSN: 2451-9022
eISSN: 2451-9030
DOI: https://doi.org/10.1016/j.bpsc.2024.02.013
Verkko-osoite: https://doi.org/10.1016/j.bpsc.2024.02.013
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/457286986
Background: Patients with psychosis and patients with depression exhibit widespread neurobiological abnormalities. The analysis of dynamic functional connectivity (dFC) allows for the detection of changes in complex brain activity patterns, providing insights into common and unique processes underlying these disorders. Methods: We report the analysis of dFC in a large sample including 127 patients at clinical high risk for psychosis, 142 patients with recent-onset psychosis, 134 patients with recent-onset depression, and 256 healthy control participants. A sliding window–based technique was used to calculate the time-dependent FC in resting-state magnetic resonance imaging data, followed by clustering to reveal recurrent FC states in each diagnostic group. Results: We identified 5 unique FC states, which could be identified in all groups with high consistency (mean r = 0.889 [SD = 0.116]). Analysis of dynamic parameters of these states showed a characteristic increase in the lifetime and frequency of a weakly connected FC state in patients with recent-onset depression (p < .0005) compared with the other groups and a common increase in the lifetime of an FC state characterized by high sensorimotor and cingulo-opercular connectivities in all patient groups compared with the healthy control group (p < .0002). Canonical correlation analysis revealed a mode that exhibited significant correlations between dFC parameters and clinical variables (r = 0.617, p < .0029), which was associated with positive psychosis symptom severity and several dFC parameters. Conclusions: Our findings indicate diagnosis-specific alterations of dFC and underline the potential of dynamic analysis to characterize disorders such as depression and psychosis and clinical risk states.
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This work was supported by the Deutsche Forschungsgemeinschaft (DFG; German Research Foundation) (Grant Nos. Project-ID 431549029, SFB 1451, and 491111487) and Koeln Fortune Program/Faculty of Medicine, University of Cologne (Grant No. 370/2020 [to TL]). The PRONIA study is a Collaboration Project funded by the European Union under the Seventh Framework Programme (Grant Agreement No. 602152 ).
