December 2022
Volume 22, Issue 14
Open Access
Vision Sciences Society Annual Meeting Abstract  |   December 2022
Visual disturbances in recent-onset psychosis and clinical high-risk state for psychosis
Author Affiliations & Notes
  • Rebekka Lencer
    University of Luebeck
    University of Muenster
  • Johanna Schwarzer
    University of Muenster
  • Inga Meyhoefer
    University of Muenster
  • Linda A. Antonucci
    University of Bari Aldo Moro
  • Lana Kambeitz-Ilankovic
    University of Cologne
  • Marian Surmann
    University of Muenster
  • Olga Bienek
    University of Muenster
  • Georg Romer
    University of Muenster
  • Udo Dannlowski
    University of Muenster
  • Tim Hahn
    University of Muenster
  • Alexandra Korda
    University of Luebeck
  • Dominic B. Dwyer
    Ludwig Maximilian University Munich
  • Anne Ruef
    Ludwig Maximilian University Munich
  • Shalaila S. Haas
    Icahn School of Medicine at Mount Sinai
  • Joseph Kambeitz
    University of Cologne
  • Raimo K.R. Salokangas
    University of Turku
  • Christos Pantelis
    University of Melbourne
  • Frauke Schultze-Lutter
    University of Duesseldorf
    University of Bern
    Airlangga University, Surabaya, Indonesia
  • Eva Meisenzahl
    University of Duesseldorf
  • Paolo Brambilla
    University of Milan
  • Alessandro Bertolino
    University of Bari Aldo Moro
  • Stefan Borgwardt
    University of Luebeck
  • Rachel Upthegrove
    University of Birmingham
  • Nikolaos Koutsouleris
    Ludwig Maximilian University Munich
    Max-Planck-Institute of Psychiatry Munich
    King's College London
  • Footnotes
    Acknowledgements  The presented work was supported by the grant for the Personalized Prognostic Indicators for early Psychosis management (PRONIA- Study): EU-FP7-HEALTH; agreement number: 602152. Primary contact to the PRONIA consortium is Prof. Nikolaos Koutsouleris (nikolaos.koutsouleris@med.uni-muenchen.de)
Journal of Vision December 2022, Vol.22, 3529. doi:https://doi.org/10.1167/jov.22.14.3529
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      Rebekka Lencer, Johanna Schwarzer, Inga Meyhoefer, Linda A. Antonucci, Lana Kambeitz-Ilankovic, Marian Surmann, Olga Bienek, Georg Romer, Udo Dannlowski, Tim Hahn, Alexandra Korda, Dominic B. Dwyer, Anne Ruef, Shalaila S. Haas, Joseph Kambeitz, Raimo K.R. Salokangas, Christos Pantelis, Frauke Schultze-Lutter, Eva Meisenzahl, Paolo Brambilla, Alessandro Bertolino, Stefan Borgwardt, Rachel Upthegrove, Nikolaos Koutsouleris; Visual disturbances in recent-onset psychosis and clinical high-risk state for psychosis. Journal of Vision 2022;22(14):3529. https://doi.org/10.1167/jov.22.14.3529.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Discrete visual perceptual disturbances (VisDis) are often neglected in clinical examination of schizophrenia patients though being reported by 50% of patients. Moreover, the relevance of VisDis in patients presenting with recent-onset psychosis (ROP) or a clinical high-risk state for psychosis (CHR) is unclear. Deeper insights into visual dysfunction in early psychosis states could not only hold beneficial information for clinical practice but foster understanding of basic perceptual disease mechanisms mediating susceptibility to psychosis. Here, we systematically investigated the relationship between VisDis and (a) core clinical measures across early phase psychiatric conditions, and (b) intrinsic brain systems using a novel machine learning approach. VisDis, clinical measures, and resting-state fMRI were assessed in ROP (N=147), CHR (N=143) and, for comparison reasons, in recent onset depression (ROD, N=151) and healthy controls (HC, N=280). Our machine-learning approach used pairwise functional connectivity within occipital (ON) and frontoparietal (FPN) networks implicated in visual information processing to predict VisDis. VisDis were reported more frequently in ROP (50.3%) and CHR (55.9%) than in ROD (16.6%) and HC (4.3%), (p<0.0001). Higher VisDis burden was associated with worse psycho-functional remission in both CHR and ROP, and lower quality of life (Qol) and higher depressiveness in CHR specifically (all p<0.05). Functional connectivity within ON predicted VisDis in ROP (balanced accuracy (BAC) 60.2%, p=0.0001) and CHR (BAC 67.4 %, p=0.029). Additionally, VisDis were predicted by functional connectivity within FPN in the combined ROP-CHR sample (BAC 61.1%, p=0.006). These large-sample study findings imply that VisDis are highly relevant in ROP and, especially, CHR being related to measures of psycho-functional outcome and emotional states. Results from the multivariate machine learning approach suggest that functional intrinsic activity within ON and FPN is associated with the VisDis phenomenon. This strongly supports a model of the visual system being implicated in core disease mechanisms of psychosis.

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