Elsevier

Asian Journal of Psychiatry

Volume 30, December 2017, Pages 144-151
Asian Journal of Psychiatry

Regional update
Elucidation of shared and specific white matter findings underlying psychopathology clusters in schizophrenia

https://doi.org/10.1016/j.ajp.2017.08.016Get rights and content

Highlights

  • Schizophrenia is associated with diverse white matter (WM) brain abnormalities.

  • WM findings underlying clinical psychopathology clusters are unclear.

  • We found common and unique WM changes for specific symptom clusters.

  • Such findings potentially allow for monitoring of clinically relevant WM changes.

Abstract

Background

Schizophrenia is associated with diverse white matter (WM) brain abnormalities. In this study, we sought to examine the WM microstructural findings which underlie clinical psychopathology clusters in schizophrenia and hypothesized that these symptom clusters are associated with common and unique WM tracts.

Methods

Overall, 76 healthy controls (HC), and 148 patients with schizophrenia (SZ) were recruited and severity of symptomatology in schizophrenia was assessed using the Positive and Negative Syndrome Scale. WM fractional anisotropy (FA) values were extracted from their diffusion tensor images. Psychopathology clusters were first determined using factor analysis and the relationship between these symptom factors and FA values were then assessed with structural equation modelling, which included covariates such as age, sex, duration of illness and medications prescribed.

Results

Patients with schizophrenia had reduced FA in the genu of corpus callosum (gCC) compared to HC. A three-factor model, namely Positive, Negative, Disorganised factors, was determined as the best fit for the data. All three psychopathology factors were associated with decreased FA in the gCC and bilateral cingulate gyrus. Higher Negative factor scores were uniquely associated with decreased FA in the right sagittal striatum and right superior longitudinal fasciculus.

Conclusions

This study found shared and specific WM changes and their associations with specific symptom clusters, which potentially allows for monitoring of such white matter findings associated with clinical presentations in schizophrenia over treatment and illness course.

Introduction

The dysconnection hypothesis indicates that schizophrenia is a disorder of brain connectivity (Friston and Frith, 1995). Previous diffusion tensor imaging (DTI) studies have found reductions of fractional anisotropy (FA) in different brain regions involving the frontal, temporal, limbic, parietal and occipital regions in patients with schizophrenia (d’Albis and Houenou, 2015, Peters et al., 2010). Considering the diversity in clinical presentations related to schizophrenia, it would be clinically meaningful to determine white matter findings underlying different symptom clusters (Karlsgodt, 2016).

The Positive and Negative Syndrome Scale (PANSS; Kay et al., 1987), a common rating tool to assess the nature and level of psychopathology in schizophrenia, was originally designed with three subscales i.e. positive, negative and general psychopathology, and recent factor analyses have generally found five-factor models consisting of Positive, Negative, Disorganised, Depression/Emotional Distress and Excitement/Mania factors (Jiang et al., 2013, van der Gaag et al., 2006, Wallwork et al., 2012). However, the lack of a consistent, consensus five-factor model suggests that a locally and contextually derived model might be more appropriate.

Overall, studies examining the relationship between brain white matter integrity and PANSS factors were limited and most studies have focused mainly on positive and negative symptom subscales and not the full factors. Positive symptoms were associated with increased or decreased FA in different WM structures, particularly in genu of corpus callosum (gCC) and superior longitudinal fasciculus (SLF) (Caprihan et al., 2015, Mitelman et al., 2007). This might be due to different sample sizes as increased FA was usually found in studies with smaller number of subjects (Park et al., 2014, Rotarska-Jagiela et al., 2009). In addition, higher negative symptoms were associated with decreased FA in gCC, inferior fronto-occipital fasciculus (IFOF) and inferior longitudinal fasciculus (ILF) (Arnedo et al., 2015, Sun et al., 2015).

Thus in this study, we sought to examine the patterns of WM anomalies associated with symptom clusters as measured by PANSS amongst our patients with schizophrenia.

Section snippets

Participants

Out of 244 participants, 96 were healthy controls (HC) and 148 were participants with schizophrenia (SZ). HC were recruited from the community via advertisements and patients with SZ were recruited from the Institute of Mental Health, Singapore. For all participants, presence and absence of psychopathology was established by a board-certificated psychiatrist (K.S.) using information obtained from the clinical history, mental status examination, existing medical records, interviews with

Study sample

Differences between HC and SZ groups were examined (Table 1). Compared with HC, SZ were more likely to be single and had fewer years of education.

For FA, significant main and interaction effects were found (See Supplementary Figures). The SZ group had decreased FA for gCC, bilateral CG and bilateral SLF (Group effect). Those who were older also had decreased FA for left SS, right CG, and right CHIP (Age effect). Post-hoc analyses found that within the control group, as age increased, FA

Discussion

Given the heterogeneity of WM findings in schizophrenia, this study evaluated the use of psychotic psychopathology clusters to clarify WM findings underlying these clinical presentations. A three-factor EFA-derived model, consisting of Positive, Negative and Disorganised factors, was the best fit for the PANSS data. Decreased FA in both gCC and bilateral CG were associated with all three symptom clusters. Higher Negative factor scores were also uniquely associated with decreased FA in right SS

Conflict of interest

Nil.

Funding

This study was supported by the National Healthcare Group Research Grant (NHG-SIG/05004) and Singapore Bioimaging Consortium Research Grant (SBIC RP C-009/2006) awarded to KS.

Contributors

K Sim designed the study and wrote the protocol. J Lim managed the literature searches, undertook statistical analysis and wrote the first draft of the manuscript. All authors contributed to and have approved the final manuscript.

Acknowledgements

The authors thank all the subjects, their families and the staff for their support of this study.

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