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Biological subtyping of schizophrenia and relationship with clinical features: a neuroimaging study

Published online by Cambridge University Press:  19 July 2023

K. Sim*
Affiliation:
IMH/National Healthcare Group
Q. Chew
Affiliation:
IMH/National Healthcare Group
B. Prakash
Affiliation:
Institute of Bioengineering and Bioimaging, Agency for Science, Technology and Research, Singapore
*
*Corresponding author.

Abstract

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Introduction

The heterogeneity of schizophrenia (SCZ) regarding clinical features including symptomatology, disease course and their inter-relationships with underlying biological substrates remain incompletely understood.

Objectives

In a bid to reduce illness heterogeneity using biological substrates, our study aimed to employ brain neurostructural measures for subtyping SCZ patients, and evaluate each subtype’s relationship with clinical features such as illness duration, psychotic psychopathology, and deficit status.

Methods

We recruited 240 subjects (160 SCZ patients, 80 healthy controls) for this study. All participants underwent brain structural magnetic resonance imaging scans and clinical assessments using the Positive and Negative Syndrome Scale. Biological subtypes of SCZ were identified using “Heterogeneity through discriminative analysis” (HYDRA), a clustering technique which accounted for relevant covariates and the inter-group normalized percentage changes in brain volume were also calculated.

Results

We found two neuroanatomical subtypes (SG-1 and SG-2) which were found amongst our patients with SCZ. The subtype SG-1 was associated with enlargements in the third and lateral ventricles, volume increase in the basal ganglia (putamen, caudate, pallidum), longer illness duration, and deficit status. The subtype SG-2 was associated with reductions of cortical and subcortical structures (hippocampus, thalamus, basal ganglia).

Conclusions

These findings have clinical implications in the early intervention, response monitoring, and prognostication of SCZ. Future studies may adopt a multi-modal neuroimaging approach to enhance insights into the neurobiological composition of relevant subtypes.

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), 2023. Published by Cambridge University Press on behalf of the European Psychiatric Association
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