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Premorbid screening of healthy students may carry latent liability for schizophrenia or bipolar affective disorder with neurocognitive and neurophenomenological methods

Published online by Cambridge University Press:  01 September 2022

I. Szendi Md Habil*
Affiliation:
University of Szeged, Department Of Psychiatry, Szeged, Hungary Kiskunhalas Semmelweis Hospital, University Teaching Hospital, Psychiatry Unit, Kiskunhalas, Hungary
A. Bagi
Affiliation:
University of Szeged, Department Of Psychiatry, Szeged, Hungary
S. Szalóki
Affiliation:
University of Szeged, Department Of Psychiatry, Szeged, Hungary
E. Hallgató
Affiliation:
University of Szeged, Institute Of Psychology, Szeged, Hungary
N. Domján
Affiliation:
University of Szeged, Department Of Psychiatry, Szeged, Hungary
A. Kanka
Affiliation:
University of Szeged, Department Of Psychiatry, Szeged, Hungary
B. Gál
Affiliation:
University of Szeged, Department Of Psychiatry, Szeged, Hungary
É. Karcher
Affiliation:
University of Szeged, Department Of Psychiatry, Szeged, Hungary
H. Pásztor
Affiliation:
University of Szeged, Department Of Psychiatry, Szeged, Hungary
T. Jenei
Affiliation:
Kiskunhalas Semmelweis Hospital, University Teaching Hospital, Psychiatry Unit, Kiskunhalas, Hungary
O. Bóna
Affiliation:
Kiskunhalas Semmelweis Hospital, University Teaching Hospital, Psychiatry Unit, Kiskunhalas, Hungary
C. Kovács
Affiliation:
Kiskunhalas Semmelweis Hospital, University Teaching Hospital, Psychiatry Unit, Kiskunhalas, Hungary
A. Pejin
Affiliation:
University of Szeged, Department Of Psychiatry, Szeged, Hungary
J. Daróczy
Affiliation:
University of Szeged, Department Of Psychiatry, Szeged, Hungary
Á. Diósi
Affiliation:
University of Szeged, Department Of Psychiatry, Szeged, Hungary
P. Pajkossy
Affiliation:
Budapest University of Technology and Economics, Department Of Cognitive Science, Budapest, Hungary Research Centre for Natural Sciences, Institute Of Cognitive Neuroscience And Psychology, Budapest, Hungary
B. Polner
Affiliation:
Budapest University of Technology and Economics, Department Of Cognitive Science, Budapest, Hungary
G. Demeter
Affiliation:
Budapest University of Technology and Economics, Department Of Cognitive Science, Budapest, Hungary
M. Racsmány
Affiliation:
Budapest University of Technology and Economics, Department Of Cognitive Science, Budapest, Hungary Research Centre for Natural Sciences, Institute Of Cognitive Neuroscience And Psychology, Budapest, Hungary
M. Baradits
Affiliation:
Semmelweis University, Department Of Psychiatry And Psychotherapy, Budapest, Hungary
A. Búzás
Affiliation:
Biological Research Center, Institute Of Biophysics, Szeged, Hungary
A. Dér
Affiliation:
Biological Research Center, Institute Of Biophysics, Szeged, Hungary
Z. Gingl
Affiliation:
University of Szeged, Department Of Technical Informatics, Szeged, Hungary
T. Gyimóthi
Affiliation:
University of Szeged, Department Of Software Development, Szeged, Hungary
*
*Corresponding author.

Abstract

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Introduction

This study was carried out to map psychosis spectrum disorder risk factors.

Objectives

Our goal was to find what kind of instrumental methods may help to detect latent liabilities for schizophrenia and bipolar affective disorder

Methods

Using online questionnaires n=710 students were screened. Groups were formed based on the inclusion criteria: N = 25 people prone to mood swings, N = 30 people prone to odd experiences and delusive thinking, and a normal control group with N = 30 people. Personality, temperament, self-experiences, affectivity scales, and cognitive screening were conducted in addition to actigraphy coupled with a mobile application for detecting subjective experiences (EMA). Furthermore, instrumental examination of self-agency, testing time interval discrimination and (re)production, eye-tracking, EEG-microstates, and laboratory testing of inflammatory, immunologic and cardio-metabolic measures of allostatic load were applied.

Results

Self-experience disorders: both risk groups showed significantly higher scores than the control group (CG). Self-agency: based on incorrectly attributed responses, the positive schizotypy risk factor (PSF) group differed from the CG (p = 0.003). Antisaccade study: the PSF group showed a difference from the CG (p = 0.002). Actigraphy: based on the distributions of diurnal cumulative activities, it distinguished those with a cyclothymic risk factor (CTF) from the CG (67% probability in the k-means clustering procedure).

Conclusions

Healthy students with a latent liability for schizotypy or bipolarity could be distinguished by some targeted laboratory methods. Susceptibility for bipolarity was indicated by actigraphic analyzes, and the risk for schizotypal development was indicated by deficiencies in the self-agency experience and by anti-saccadic eye movement disorders.

Disclosure

No significant relationships.

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 (http://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), 2022. Published by Cambridge University Press on behalf of the European Psychiatric Association
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