Poster No:
369
Submission Type:
Abstract Submission
Authors:
Youngwoo Bryan Yoon1, Wi Hoon Jung2
Institutions:
1New York University, NEW YORK, NY, 2Gachon University, Seongnam-si, Gyeonggi-do
First Author:
Co-Author:
Introduction:
Investigations have demonstrated that patients' use of antipsychotic medications is associated with loss of gray matter volume (GMV) . In patients with treatment-resistant schizophrenia taking clozapine, reductions in GMV have been observed,
especially in cortico-striatal regions such as the caudate and putamen . However, to date, the e ects of clozapine on brain alteration, particularly GMV, and its association with clinical symptoms have been primarily investigated using univariate
approaches [i.e., voxel or cluster level of inference on GMV maps generated from voxel-based morphometry (VBM)]. Adoption of a multivariate approach – source-based morphometry (SBM), a multivariate extension of VBM utilizing spatially
independent component analysis (ICA) to obtain patterns of common GMV variation among participants (hereinafter referred to as "gray matter covariance network") – may be more powerful in ascertaining the e ects of clozapine on brain structures
and their association with clinical symptoms . Therefore, we apply SBM to investigate di erences between pre- and post-switching to clozapine in gray matter covariance networks and the association between clinical symptom severity (i.e., total
PANSS scores) and the networks.
Methods:
We recruited patients with schizophrenia (n = 38) planning to start clozapine and prospectively investigated changes in symptom severity (total Positive and Negative Syndrome Scale [PANSS] scores) and structural brain, particularly GMV. Of these, data
from 29 patients (18 females; age [mean±S.D.], 35.66±10.75 years old; duration of illness, 102.97±100.72 months) were used in the nal analysis due to several reasons (e.g., poor image quality or dropout). T1-weighted brain magnetic images were
obtained before and 18 weeks after the initiation of clozapine treatment. The VBM method with the Computational Anatomy Toolbox (CAT) was performed to extract GMV images. Next, the SBM method with the GIFT toolbox was applied to the GMV
images of all participants to extract 41 gray matter covariance networks. The number of independent components (ICs; i.e., gray matter covariance networks) was determined by the minimum description length (MDL) algorithm. Based on the stability
index (> 0.95) for ICA estimate-clusters, 15 ICs were selected and used for the subsequent statistical analyses. For the fteen ICs, paired t-tests were performed to investigate which networks' loading coe cients changed signi cantly after switching to
clozapine. We then performed correlation analyses between each network's loading coe cient and total PANSS score over time to determine which networks' loading coe cient was associated with clinical symptom severity (i.e., total PANSS score). A
signi cant threshold was set at p < 0.05 and corrected for multiple comparisons using Bonferroni correction (i.e., p < 0.0033 = 0.05/15).
Results:
We observed a signi cant improvement in patients' symptoms after treatment with clozapine (total PANSS score before and after treatment [mean±S.D.], 71.45±13.35 and 60.41±7.56; total PANSS score reduction after treatment, 14.18±10.49%, t-value
= 3.87; p<0.001). We then observed a signi cant decrease in the loading coe cients of IC 10, composed of striatum, after switching to clozapine (t = 11.61, p < 0.001). We also found that the total PANSS score was positively associated with the loading
coe cients of IC 9, composed of the thalamus and cerebellum, over time (r = 0.45, p < 0.001).
Conclusions:
These results provide evidence that the use of clozapine can lead to improvement in clinical symptoms and changes in brain structure in patients with treatment-resistant schizophrenia. These results also suggest that the severity of clinical symptoms may be related to speci c brain structures.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Anatomy and Functional Systems
Novel Imaging Acquisition Methods:
Anatomical MRI 2
Keywords:
MRI
Schizophrenia
STRUCTURAL MRI
Structures
1|2Indicates the priority used for review
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Structural MRI
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