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Exploring Associations between Grey Matter Volume and Clinical High-Risk for Psychosis: A Transdiagnostic Study Utilizing the NAPLS-2 Risk Calculator in the PRONIA Cohort

Published online by Cambridge University Press:  27 August 2024

L.-M. Neuner*
Affiliation:
1Department of Psychiatry and Psychotherapy, LMU University Hospital, Ludwig-Maximilians-Universität, Munich
L. Hahn
Affiliation:
1Department of Psychiatry and Psychotherapy, LMU University Hospital, Ludwig-Maximilians-Universität, Munich
J. Kambeitz
Affiliation:
2Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany
R. K. Salokangas
Affiliation:
3Department of Psychiatry, University of Turku, Turku, Finland
J. Hietala
Affiliation:
3Department of Psychiatry, University of Turku, Turku, Finland
A. Bertolino
Affiliation:
4Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
S. Borgwardt
Affiliation:
5Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany 6Department of Psychiatry (Psychiatric University Hospital, UPK), University of Basel, Basel, Switzerland
P. Brambilla
Affiliation:
7Department of Neurosciences and Mental Health, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico 8Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
R. Upthegrove
Affiliation:
9Institute of Mental Health, University of Birmingham 10Early Intervention Service, Birmingham Women’s and Children’s NHS Foundation Trust
S. J. Wood
Affiliation:
11School of Psychology, University of Birmingham, Birmingham, United Kingdom 12Centre for Youth Mental Health, University of Melbourne 13Orygen, Melbourne, Australia
R. Lencer
Affiliation:
5Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany 14Institute for Translational Psychiatry, University Münster, Münster
E. Meisenzahl
Affiliation:
15Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich Heine University, Düsseldorf
P. Falkai
Affiliation:
1Department of Psychiatry and Psychotherapy, LMU University Hospital, Ludwig-Maximilians-Universität, Munich 16Max-Planck Institute of Psychiatry, Munich, Germany
T. D. Cannon
Affiliation:
17Department of Psychiatry 18Department of Psychology, Yale University, New Haven, Connecticut, United States
N. Koutsouleris
Affiliation:
1Department of Psychiatry and Psychotherapy, LMU University Hospital, Ludwig-Maximilians-Universität, Munich 16Max-Planck Institute of Psychiatry, Munich, Germany 19Institute of Psychiatry, Psychology And Neurosciences, King’s College London, London, United Kingdom
*
*Corresponding author.

Abstract

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Introduction

The clinical high-risk state for psychosis (CHR) is associated with alterations in grey matter volume (GMV) in various regions such as the hippocampus (Vissink et al. BP:GOS 2022; 2(2) 147-152). Within the scope of the North American Prodrome Longitudinal Study (NAPLS-2; Cannon et al. AM J Psychiatry 2016; 173(10), 980-988), a publicly available risk calculator based on clinical variables was developed to assess the likelihood of individuals to transition to psychosis within a 2-year period.

Objectives

In the current study, we aim to examine the association between GMV and NAPLS-2 risk scores calculated for individuals with CHR and recent-onset depression (ROD), taking a transdiagnostic approach on the transition to psychosis.

Methods

The sample consisted of 315 CHR (M = 23.85, SD = ± 5.64; female: 164) and 295 ROD (M = 25.11, SD = ± 6.21; female: 144) patients from the multi-site Personalised Prognostic Tools for Early Psychosis Management (PRONIA) Study (Koutsouleris et al. JAMA Psychiatry 2018; 57(11), 1156-1172). Risk scores were calculated using the six clinical and neurocognitive variables included in the NAPLS-2 risk calculator that were significant for predicting psychosis. Further, we derived smoothed GMV maps from T1-weighted structural magnetic resonance imaging using a full width at half maximum kernel size of 8 mm. We employed a multiple regression design in SPM12 to examine associations between risk scores and GMV. On the whole-brain level, we calculated permutation-based threshold-free cluster enhancement (TFCE) contrasts using the TFCE toolbox. Additionally, we calculated t-contrasts within a region-of-interest (ROI) analysis encompassing the hippocampus. All results were thresholded at p < 0.05 with family wise error correction to address multiple comparisons.

Results

Our analysis revealed that linear GMV increases in the right middle and superior frontal gyrus (kE= 2726 voxels) were significantly associated with higher risk for psychosis transition within two years (see figure 1, highlighted in blue). In the ROI analysis, we found a significant negative linear association between GMV decreases in the left hippocampus (kE = 353 voxels) and higher risk for psychosis transition (see figure 1, highlighted in red).

Image:

Conclusions

GMV reductions in the hippocampus have frequently been observed in CHR and psychosis patients (Vissink et al. BP:GOS 2022; 2(2) 147-152), therefore our results further highlight the crucial role of this region in the progression of the disease. There is limited evidence on GMV increases in CHR patients. However, the GMV increase we found in the frontal pole may reflect compensatory mechanisms of the brain in the development of psychosis. In addition, we were able to provide biological validation of the NAPLS-2 risk calculator and its assessment of risk for transition to psychosis.

Disclosure of Interest

None Declared

Type
Abstract
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of European Psychiatric Association
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