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. 2019 Oct 1;176(10):829-838.
doi: 10.1176/appi.ajp.2019.18101212. Epub 2019 Jul 29.

White Matter in Schizophrenia Treatment Resistance

Peter Kochunov  1 , Junchao Huang  1 , Song Chen  1 , Yanli Li  1 , Shuping Tan  1 , Fengmei Fan  1 , Wei Feng  1 , Yunhui Wang  1 , Laura M Rowland  1 , Anya Savransky  1 , Xiaoming Du  1 , Joshua Chiappelli  1 , Shuo Chen  1 , Neda Jahanshad  1 , Paul M Thompson  1 , Meghann C Ryan  1 , Bhim Adhikari  1 , Hemalatha Sampath  1 , Yimin Cui  1 , Zhiren Wang  1 , Fude Yang  1 , Yunlong Tan  1 , L Elliot Hong  1
Affiliations

White Matter in Schizophrenia Treatment Resistance

Peter Kochunov et al. Am J Psychiatry. .

Abstract

Objective: Failure of antipsychotic medications to resolve symptoms in patients with schizophrenia creates a clinical challenge that is known as treatment resistance. The causes of treatment resistance are unknown, but it is associated with earlier age at onset and more severe cognitive deficits. The authors tested the hypothesis that white matter deficits that are involved in both neurodevelopment and severity of cognitive deficits in schizophrenia are associated with a higher risk of treatment resistance.

Methods: The study sample (N=122; mean age, 38.2 years) included schizophrenia patients at treatment initiation (N=45), patients whose symptoms were treatment responsive (N=40), and patients whose symptoms were treatment resistant (N=37), as well as healthy control subjects (N=78; mean age, 39.2 years). White matter regional vulnerability index (RVI) was tested as a predictor of treatment resistance and cognitive deficits. Higher RVI is indicative of better agreement between diffusion tensor imaging fractional anisotropy across the brain in an individual and the pattern identified by the largest-to-date meta-analysis of white matter deficits in schizophrenia.

Results: Patients with treatment-resistant symptoms showed the highest white matter RVI (mean=0.38 [SD=0.2]), which was significantly higher than the RVI among patients with treatment-responsive symptoms (mean=0.30 [SD=0.02]). At the onset of treatment, schizophrenia patients showed significantly higher RVI than healthy control subjects (mean=0.18 [SD=0.03] and mean=0.13 [SD=0.02], respectively). RVIs were significantly correlated with performance on processing speed and negative symptoms.

Conclusions: Schizophrenia affects white matter microstructure in specific regional patterns. Susceptibility to white matter regional deficits is associated with an increased likelihood of treatment resistance. Developments to overcome schizophrenia treatment resistance should consider white matter as an important target.

Keywords: Magnetic Resonance Imaging; Schizophrenia.

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Conflict of interest statement

Conflict of Interest

LEH has received or plans to receive research funding or consulting fees on research projects from Mitsubishi, Your Energy Systems LLC, Neuralstem, Taisho, Heptares, Pfizer, Sound Pharma, Takeda, and Regeneron. None was involved in the design, analysis or outcomes of the study. PT and NJ have received research funding, unrelated to this work, from Biogen. All other authors declare no conflicts of interest.

Figures

Figure 1.
Figure 1.
The mean effect size of group (Cohen’s d) of the twenty-one white matter regions were plotted against the effects sizes of the ENIGMA region for all patients (A) and three subgroups (B-D). The significant correlations indicate that the pattern of FA deficits in the Chinese sample were consistent with the ENIGMA pattern. The data (mean and s.d.) of all the effect sizes are in Supplementary Table 1. Abbreviations: Anterior Corona Radiata (ACR), Anterior Limb of Internal Capsule (ALIC), Body of Corpus Callosum (BCC), Cingulum (CGC), Corona Radiata (CR), Cortico-Spinal Tract (CST), External Capsule (EC), Fornix (FX), Genu of Corpus Callosum (GCC), Internal Capsule (IC), Inferior Frontal Occipital fasciculus (IFO), Posterior Corona Radiata (PCR), Posterior Limb of Internal Capsule (PLIC), Posterior Thalamic Radiation (PTR), Retrolenticular Limb of the Internal Capsule (RLIC), Splenium of Corpus Callosum (SCC), Superior Corona Radiata (SCR), Superior Fronto-Occipital Fasciculus (SFO), Superior Longitudinal Fasciculus (SLF), Sagittal Striatum (SS), Uncinate Fasciculus (UNC).
Figure 2.
Figure 2.
A: Average coefficients of regional vulnerability index (RVI) plotted by group. B: There was a significance ordinal trend of elevation of RVI with respect to group assignment (p<0.001).
Figure 3.
Figure 3.
Replication of the relationship between cognition and white matter vulnerability to schizophrenia that were reported in Kochunov et al 2017 (for convenience to the readers, the figure of original findings in the U.S. sample is reproduced in Supplementary Figure 1). X-axis: Effect sizes of the 21 major white matter regions in ENIGMA, higher values indicate more severe impairment in schizophrenia compared with controls in the ENIGMA meta-analysis. Y-axis: The correlation coefficients between FA of each region and cognitive measures in processing speed (PS) or working memory (WM) in the current Chinese sample. Full sample: all participants combined. Patients: all patients combined. A: Relationship between correlation coefficients for regional FA - processing speed (PS) (y-axis) and regional FA effect sizes of schizophrenia from ENIGMA-Schizophrenia (x-axis, Cohen’s d). B: partial correlation coefficients of A after corrected for working memory (WM). C: Relationship between correlation coefficients for regional FA values and working memory (y-axis) and regional FA effect sizes of schizophrenia (x-axis). D: partial correlation coefficients of C after corrected for PS. This was tested in the full sample (A to D) and then patients (E to H) and controls (I to L) separately.
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