White matter microstructural organizations in patients with severe treatment-resistant schizophrenia: A diffusion tensor imaging study

Journal Pre-proof White matter microstructural organizations in patients with severe treatment-resistant schizophrenia: A diffusion tensor imaging study

Ryo Ochi, Yoshihiro Noda, Shohei Tsuchimoto, Ryosuke Tarumi, Shiori Honda, Karin Matsushita, Sakiko Tsugawa, Eric Plitman, Fumi Masuda, Kamiyu Ogyu, Masataka Wada, Takahiro Miyazaki, Shinya Fujii, M. Mallar Chakravarty, Ariel GraffGuerrero, Hiroyuki Uchida, Masaru Mimura, Shinichiro Nakajima PII:

S0278-5846(19)30688-8

DOI:

https://doi.org/10.1016/j.pnpbp.2020.109871

Reference:

PNP 109871

To appear in:

Progress in Neuropsychopharmacology & Biological Psychiatry

Received date:

15 August 2019

Revised date:

19 November 2019

Accepted date:

15 January 2020

Please cite this article as: R. Ochi, Y. Noda, S. Tsuchimoto, et al., White matter microstructural organizations in patients with severe treatment-resistant schizophrenia: A diffusion tensor imaging study, Progress in Neuropsychopharmacology & Biological Psychiatry(2019), https://doi.org/10.1016/j.pnpbp.2020.109871

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

© 2019 Published by Elsevier.

Journal Pre-proof

White Matter Microstructural Organizations in Patients with Severe Treatment-Resistant Schizophrenia: A Diffusion Tensor Imaging Study Ryo Ochi 1 , Yoshihiro Noda MD, PhD 2 , Shohei Tsuchimoto 3 , Ryosuke Tarumi MD 2,4 , Shiori 5

1

2

Honda , Karin Matsushita , Sakiko Tsugawa , Eric Plitman PhD

6,7

2

, Fumi Masuda MD, PhD ,

Kamiyu Ogyu MD 2 , Masataka Wada MD 2 , Takahiro Miyazaki MD, PhD 2 , Shinya Fujii PhD 1 , M. Mallar Chakravarty PhD 6,7,8 , Ariel Graff-Guerrero MD, PhD 9 , Hiroyuki Uchida MD, PhD 2

Masaru Mimura MD, PhD , Shinichiro Nakajima MD, PhD

2,9

,

2,9*

oo

f

1. Faculty of Environment and Information Studies, Keio University, Fujisawa, Japan 2. Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan 3. Graduate School of Science and Technology, Keio University, Yokohama, Japan

pr

4. Department of Psychiatry, Komagino Hospital, Tokyo, Japan

5. Graduate School of Media and Governance, Keio University, Fujisawa, Japan

e-

6. Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada

Pr

7. Department of Psychiatry, McGill University, Montreal, QC, Canada 8. Department of Biomedical Engineering, McGill University, Montreal, QC, Canada

al

9. Campbell Institute Research Program, Centre for Addiction and Mental Health, Toronto, Ontario,

*Corresponding author:

rn

Canada

Jo u

Shinichiro Nakajima, M.D., Ph.D.

Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan 35 Shinanomachi, Shinjuku-ku, Tokyo, Japan, 160-8582 Phone: +81-3-3353-1211 (ext. 62454) Fax: +81-3-5379-0187 Email: [email protected]

Main text: words: 3423 Abstract: words: 260 Number of Figures: 2 Number of Tables: 1 Supplemental information: 1

1

Journal Pre-proof

Abstract Previous diffusion tensor imaging (DTI) studies have reported white matter alterations in patients with schizophrenia. Notably, one third of this population does not respond to first-line antipsychotics and is thus referred to as treatment-resistant schizophrenia (TRS). Despite

f

potentially distinct neural bases between TRS and non-TRS, few studies have compared white

oo

matter integrity between these groups. In order to reflect clinical picture of TRS, we enrolled

pr

TRS patients who had severe symptoms. According to the consensus criteria for TRS. TRS was

e-

defined by severe positive symptomatology despite optimal antipsychotic treatment. Fractional

Pr

anisotropy (FA), an index of white matter integrity, was examined by DTI and analyzed with

al

tract-based spatial statistics in 24 TRS patients (mean PANSS=108.9), 28 non-TRS patients

rn

(mean PANSS=50.0), and 27 healthy controls (HCs) for group comparison. Additionally,

Jo u

correlation analyses were conducted between FA values and symptomatology. The TRS group had lower FA values in multiple tracts (cerebral peduncle, corona radiata, corpus callosum, external and internal capsules, posterior thalamic radiation, sagittal stratum, superior longitudinal fasciculus, tapetum, and uncinate fasciculus) compared to the HC group as well as the non-TRS group (p<0.05; family-wise error-corrected), while no differences were found between the non-TRS and HC groups. In the TRS group, FA values in most of the tracts (other than the left anterior limb of internal capsule, left cerebral peduncle, and right uncinate fasciculus) were negatively correlated with the Positive and Negative Syndrome Scale total 2

Journal Pre-proof

scores, and negative and general symptom scores. No such relationships were found in the non-TRS group. The identified white matter integrity deficits may reflect the pathophysiology of TRS.

f

Keywords: antipsychotics response; diffusion tensor imaging; fractional anisotropy; tract-based

Jo u

rn

al

Pr

e-

pr

oo

spatial statistics; treatment-resistant schizophrenia; white matter integrity

3

Journal Pre-proof

Introduction Schizophrenia is a severe mental disorder characterized by positive, negative, and cognitive symptoms, and the illness has a prevalence of approximately 1% (Howes and Murray, 2014). While antipsychotics are the primary treatment for patients with schizophrenia,

oo

f

approximately 20-35% of patients with schizophrenia show poor response to non-clozapine

pr

(CLZ) antipsychotics and are thus defined as treatment-resistant schizophrenia (TRS) (Kane,

e-

2012). Also, previous studies have reported that 70-80% of patients with TRS show

Pr

antipsychotic treatment resistance from illness onset (Lally et al., 2016; Demjaha et al., 2017). Moreover, Jauhar et al. reported that, among patients with first-episode psychosis, dopamine

rn

al

synthesis capacity before the commencement of antipsychotics was higher in antipsychotic

Jo u

responders compared with non-responders (Jauhar et al., 2018). These findings suggest that the identified difference in dopaminergic function between groups may exist from the onset of psychosis. Thus, there may be distinct biological mechanisms, other than dopaminergic functioning, that differ between patients with TRS and those who respond to first-line antipsychotics (i.e., non-TRS), warranting further investigation of this patient population. Neuroimaging techniques such as diffusion tensor imaging (DTI) permit the investigation of microstructural white matter organization in-vivo (Scheck et al., 2012). Specifically, fractional anisotropy (FA) is thought to reflect white matter integrity (Alexander et 4

Journal Pre-proof

al., 2011). Additionally, DTI measures include mean diffusivity (MD) (i.e., overall diffusivity), axial diffusivity (AD) (i.e., λ1: diffusion along the principal axis), and radial diffusivity (RD) (i.e., (λ2+λ3)/2: diffusivity along the two minor axes). Notably, MD is sensitive to cellularity, edema, and necrosis (Alexander et al., 2011), whereas AD is thought to be modulated by axonal

oo

f

degeneration and RD is related to myelin sheath alterations (Song et al., 2002).

pr

Several lines of evidence have indicated that patients with schizophrenia have white

e-

matter abnormalities, suggesting that white matter disturbances serve as a neural underpinning

Pr

of the illness (Shahab et al., 2017; Vitolo et al., 2017). Indeed, previous DTI studies have showed reduced FA values in the white matter of frontal regions in patients with schizophrenia

al

in comparison with healthy controls (HCs) (Patterson-Yeo et al., 2011; Kelly et al., 2018).

Jo u

rn

However, recent systematic reviews have also suggested that there is little evidence for neuroimaging correlates of TRS (Nakajima et al., 2015; Mouchlianitis et al., 2016; Crocker & Tibbo, 2018). To date, only two studies examined white matter microstructure in patients with TRS (McNabb et al., 2018; Kochunov et al., 2019). Kochunov et al. found that the white matter deficit pattern, as identified by the largest meta-analytic study of white matter abnormalities in schizophrenia (Kelly et al., 2018), was associated with treatment resistance. Also, McNabb et al. noted that patients with TRS had reduced FA values in the body of the corpus callosum than those with non-TRS. However, the symptom severity of patients in these studies ranged from

5

Journal Pre-proof

mild to modulate, which may not reflect the clinical picture of TRS that is typically often observed in clinical practice. Thus, white matter disturbances in patients with severe TRS require further elucidation. Therefore, we aimed to examine voxel-based differences in white matter integrity, as

oo

f

indexed by FA values, among patients with severe TRS, patients with non-TRS, and HCs. We

pr

included TRS patients whose illness severity was severe in order to be more representative of

e-

clinical practice. Based on previous literature suggesting potentially distinct biological

Pr

mechanisms between patients with TRS and patients with non-TRS (Lally et al., 2016; Demjaha et al., 2017), we hypothesized that the former would exhibit altered white matter integrity

al

relative to the latter. We also explored the relationships among FA values and clinical measures

Jo u

rn

in these patients. To further investigate white matter microstructure, other DTI measures such as MD, AD, and RD values were also explored as part of secondary analyses.

6

Journal Pre-proof

Materials and Methods Study Design This single-center cross-sectional DTI study was conducted at Komagino Hospital between 2017 and 2018. This study was approved by the ethics committees at Keio University

oo

f

School of Medicine and Komagino Hospital. All participants were included following

pr

successful completion of an informed consent procedure.

e-

Participants

Pr

All participants were aged 20 years or older and treated within the regular clinical

al

practice at Komagino Hospital. Patients met inclusion criteria if they had a DSM-IV diagnosis

rn

of schizophrenia or schizoaffective disorder. Symptom severity was assessed with the Positive

Jo u

and Negative Syndrome Scale (PANSS) (Kay et al., 1987) and Clinical Global Impression Severity Scale (CGI-S) (Guy, 1976). Antipsychotic treatment resistance was defined by the modified Treatment Response and Resistance in Psychosis (TRRIP) Working Group Consensus criteria (Howes et al., 2016). Optimal antipsychotic treatment was defined as treatment with ≥ 400 mg of chlorpromazine (CPZ) equivalent daily dose for ≥ 6 consecutive weeks (Inagaki and Inada, 2006). Treatment response was defined by: (a) a CGI-S of ≤ 3, (b) scores of ≤ 3 on all positive symptom items of the PANSS, and (c) no symptomatic relapse in the previous 3

7

Journal Pre-proof

months. Antipsychotic treatment failure was defined by: (a) a CGI-S score of ≥ 4 (moderate) and (b) a score of ≥ 4 (moderate) on 2 PANSS positive symptom items after optimal antipsychotic treatment. To establish failure to previous antipsychotic treatments, CGI-S scores were retrospectively collected based on available information provided by patients, their

oo

f

psychiatrists, chart, or other sources. The CGI-S scores were independently determined by two

pr

investigators (R.T. and S.N.). If there were discrepancies between them, we further discussed

e-

them with another investigator (Y.N.) to reach a consensus on group classification. TRS criteria

Pr

included: (a) a history of treatment failure to optimal treatment with at least 2 previous non-CLZ antipsychotics and (b) current severity defined as a score of ≥5 (moderate-severe) on 2 PANSS

al

positive symptom items or 4 (moderate) on 3 positive symptom items. Non-TRS criteria

Jo u

rn

included: (a) current intake of a non-CLZ antipsychotic and (b) treatment response to this antipsychotic. HCs were assessed by the Mini-International Neuropsychiatric Interview to confirm if they met inclusion criteria that they had no psychiatric illness (Sheehan et al., 1998). Exclusion criteria for all groups consisted of: (a) substance abuse or dependence within the past 6 months, (b) history of head trauma resulting in loss of consciousness for > 30 minutes, and (c) an unstable physical illness or neurological disorder. The definition of these criteria and the assessment procedures have been detailed in our previous study (Iwata et al., 2019). The patient groups and HCs were age- and sex-matched as closely as possible. To assess the smoking status

8

Journal Pre-proof

of participants, the Brinkman index, defined as the number of cigarettes smoked per day multiplied by the smoking years, was utilized. The sample size was calculated based on a previous study comparing white matter integrity between patients with TRS versus HCs (Holleran et al., 2014). Using that study, it was

oo

f

determined that 23 participants in each group would provide at least 85% power to detect the

pr

expected difference in white matter integrity levels with an alpha = 0.05 and a dropout ratio =

e-

20%. Therefore, we continued to recruit participants until 23 age- and sex-matched trios were

Pr

included.

al

Imaging protocol

rn

DTI data were scanned at one site in a 3T GE Signa HDxt scanner (GE Healthcare)

Jo u

with an 8-channel head coil. Each image consisted of 30 diffusion-weighted volumes with different noncollinear diffusion directions, all with a b-factor = 1000 s/mm2 and five diffusion-unweighted volumes with a b-factor = 0 s/mm2 (TE = 71 ms, TR = 16000 ms, flip angle = 90, 128 × 128 matrix, 1.0 × 1.0 × 2.5 mm).

DTI preprocessing First, DTI data were corrected for eddy current-induced distortions and gross subject movement (Andersson and Sotiropoulos, 2016). Then, the quality of the DTI data was assessed

9

Journal Pre-proof

using the eddy quality control (QC) tools (Bastiani et al., 2019). Participants that were more than two standard deviations away from the mean with respect to a summary measure of ‘total motion’ between different volumes were excluded for analyses. FA, MD, AD, and RD images were calculated by fitting a tensor model to the raw diffusion data. Nonlinear registration was

oo

f

performed by aligning each participant’s FA image to standard space (Montreal Neurological

pr

Institute 152 standard) using FMRIB’s Nonlinear Image Registration Tool. The aligned FA

e-

images were used to create a mean FA image and a mean FA skeleton of all FA images for

Pr

performing Tract-based spatial statistics (TBSS). The skeleton was set thresholds as FA > 0.2 (TBSS default) in order to incorporate only major fiber bundles. Additionally, the original FA

al

nonlinear registration was conducted for MD, AD, and RD maps, which were then projected

Jo u

rn

onto the mean FA skeleton. All preprocessing procedures were performed using the FMRIB Software Library (FSL version 6.0.1; https://fsl.fmrib.ox.ac.uk/fsl/fslwiki).

Statistical analysis

Clinico-demographic characteristics were compared among the groups with Chi-Square tests and analyses of variance for categorical or continuous variables, respectively. TBSS was conducted to compare white matter integrity among the groups (Smith et al., 2006). Differences in FA values between the groups were computed using voxel-wise independent two-sample t-tests with 5000 permutations. For the group comparison, the models included age, 10

Journal Pre-proof

gender, education year, and Brinkman index as nuisance variables. Furthermore, CPZ equivalent daily dose was also included when comparing the patients’ group. We used threshold-free cluster enhancement (TFCE) with a cutoff of p < 0.05 for correction of multiple comparisons. In order to localize significant voxels, contrast maps were divided according to the

oo

f

JHU-ICBM-DTI-81 white matter atlas. Additional analyses were conducted to investigate the

pr

relationships between FA values and the severity of symptoms. In these, we included PANSS

e-

total and subscale scores into statistical models. We performed secondary analyses on other DTI

Pr

measures (i.e. MD, AD, and RD) using the same procedures. All statistical models in

Jo u

rn

al

patients included CPZ equivalent daily dose as a nuisance covariate.

11

Journal Pre-proof

Results Demographic and clinical characteristics of participants A total of 79 participants were included in this study, consisting of 24 patients with TRS, 28 patients with non-TRS, and 27 HCs. Clinico-demographic characteristics are

oo

f

summarized in Table 1. After QC assessment of subject motion between DTI slices, 5

pr

participants (1 TRS and 4 non-TRS) were excluded from the analyses. HCs had more education

e-

years and a lower Brinkman index than both patients with TRS and non-TRS. Also, the TRS

Pr

group had greater severity of symptoms, as assessed by the PANSS subtotal scores and CGI-S

al

score, and higher CPZ equivalent daily doses, compared with the non-TRS group.

rn

Comparisons of white matter integrity among the groups

Jo u

TBSS revealed a reduction of FA values in patients with TRS compared with patients with non-TRS (Figure 1). Specifically, FA values were reduced in several regions including the cerebral peduncle, cingulum bundle, corona radiata, corpus callosum, external capsule, internal capsule, posterior thalamic radiation, sagittal stratum, superior longitudinal fasciculus, tapetum, and uncinate fasciculus (Table S1: p<0.05, FWE-corrected). The most affected cluster was located in the left superior longitudinal fasciculus (cluster size=23736, p=0.003, FWE-corrected; Cohen’s d=0.26). Patients with TRS showed no voxels with increased FA

12

Journal Pre-proof

values compared with patients with non-TRS. Also, patients with TRS showed an FA reduction in similar areas compared with HCs (Figure S1, Table S2). On the other hand, there were no differences in white matter integrity between patients with non-TRS and HCs. There was an increase in MD and RD values in patients with TRS compared with

oo

f

patients with non-TRS (Figure 1). MD value differences were observed in the cerebellar

pr

peduncle, cerebral peduncle, cingulum bundle, corona radiata, corpus callosum, corticospinal

e-

tract, external capsule, internal capsule, medial lemniscus, posterior thalamic radiation, sagittal

Pr

stratum, superior longitudinal fasciculus, and tapetum (Table S3). Furthermore, RD value differences were observed in the cerebellar peduncle, cerebral peduncle, cingulum bundle,

al

corona radiata, corpus callosum, internal capsule, posterior thalamic radiation, sagittal stratum,

rn

and tapetum (Table S4). For MD value, a cluster was located in the frontotemporal lobe (cluster

Jo u

size=11973, p=0.001, FWE-corrected; Cohen’s d=0.28). Further, the difference of RD values was most prominent in the cluster located in the splenium of corpus callosum (cluster size=2818, p=0.009, FWE-corrected; Cohen’s d=0.47). However, we did not find any differences in MD, AD, and RD values between patients with TRS and HCs or between patients with non-TRS and HCs.

Relationship with symptomatology

13

Journal Pre-proof

In patients with TRS, there were negative associations between PANSS total scores and FA values in the cerebral peduncle, cingulum bundle, corona radiata, corpus callosum, external capsule, internal capsule, posterior thalamic radiation, sagittal stratum, superior longitudinal fasciculus, and tapetum (Figure 2 and Table S5). Also, negative correlations were identified

oo

f

between PANSS negative or general subscale scores and FA values in similar tracts (Figure 2,

pr

Tables S6 and S7). Moreover, increased MD and RD values were associated with PANSS

e-

negative subscale scores (Figure S2, Table S8). Furthermore, there were no significant

Pr

associations between PANSS positive subscale scores and FA values. On the other hand, there

Jo u

rn

patients with non-TRS.

al

were no relationships between these any white matter metrics and clinical assessments in

14

Journal Pre-proof

Discussion To our knowledge, this is the first study to assess voxel-wise white matter integrity in patients with severe TRS compared to patients with non-TRS. Notably, we included more severe patients with TRS compared with most of previous studies (McNabb et al., 2018;

oo

f

Kochunov et al., 2019). Furthermore, most of the non-TRS patients in this study achieved

pr

remission based on the criteria by Andreassen and colleagues (Andreassen et al., 2005). Thus,

e-

this study can reflect the actual picture of TRS in clinical practice and have a potential to

Pr

determine the pathophysiology of TRS by comparing the subjects with clinical distinct characteristics. Our findings were three-fold. First, patients with severe TRS had reduced FA

rn

al

values in the cerebral peduncle, corona radiata, corpus callosum, external capsule, internal

Jo u

capsule, posterior thalamic radiation, sagittal stratum, superior longitudinal fasciculus, tapetum, and uncinate fasciculus relative to patients with non-TRS and HCs, while no differences were found in FA values between the non-TRS and HC groups. Second, in patients with TRS, negative relationships were found between PANSS total scores, and negative and general subscale scores and FA values in multiple tracts, while there were no such associations in patients with non-TRS. Finally, patients with TRS exhibited increased MD and RD values in multiple tracts relative to patients with non-TRS, while we did not find any differences between patients with TRS and HCs or between patients with non-TRS and HCs. 15

Journal Pre-proof

Two studies so far have examined white matter microstructure in patients with TRS (McNabb et al., 2018; Kochunov et al., 2019). Kochunov et al. found more severe patterns of white matter deficits in patients with TRS (PANSS total score = 69.0 ± 19.5) than those with non-TRS. Likewise, McNabb et al. noted that patients with TRS (PANSS total score = 79.1 ±

oo

f

17.4) had reduced FA values in the body of the corpus callosum relative to patients with

pr

non-TRS. Despite the differences of the clinical severity between these studies and ours

e-

(PANSS total score = 108.9 ± 19.5), our findings are consistent. Taken together, these findings

Pr

suggest that reduced white matter integrity deficits may be associated with the pathophysiology of TRS.

al

On the other hand, our results indicated that there were no differences in FA, MD, and

Jo u

rn

RD values between the non-TRS and HC groups. Of note, Xiao et al. reported that never-treated patients with schizophrenia (PANSS total score = 92.6 ± 18.1) displayed significantly reduced FA values compared with antipsychotic-treated patients (PANSS total score = 52.4 ± 10.8) in the anterior thalamic radiation, cingulum-hippocampus pathway, splenium and genu of corpus callosum, and superior longitudinal fasciculus; taken together, the beneficial impact of antipsychotics on white matter integrity in those areas may be inferred (Xiao et al., 2018).Based on the present findings, these protective effects of antipsychotics on white matter integrity may not be the case for patients with severe TRS. Furthermore, Reis Marques and colleagues noted

16

Journal Pre-proof

that even at baseline, patients who had poor treatment outcome showed reduced FA values mainly in the uncinate fasciculus, cingulum, and corpus callosum than those who responded to antipsychotics (Reis Marques et al., 2014). Thus, these findings may corroborate the hypothesis that there are distinct biological mechanisms underlying patients with TRS relative to patients

oo

f

with non-TRS. However, a small sample size in this study may have been insufficient to detect

pr

the difference. The effect size of the difference of whole brain average FA values between the

e-

non-TRS and HC group is 0.22, and at least 370 participants in each group are needed in order

Pr

to achieve statistical power of 85%. Future studies with a larger sample are needed to determine white matter deficits associated with treatment resistance in schizophrenia.

al

Previous prospective studies have reported upon the importance of white matter

Jo u

rn

integrity for the prediction of response to antipsychotics in patients with schizophrenia (Kim et al., 2016; Cho et al., 2018). Kim et al. reported a relationship between treatment response to paliperidone and FA values in the corpus callosum, corona radiata, internal and external capsules, superior longitudinal fasciculus, and frontotemporal white matter regions before administration of paliperidone. In another study, a reduction of clinical severity in positive symptoms after 8 weeks of amisulpride treatment was predicted by baseline FA values in the corpus callosum, superior longitudinal fasciculus, external capsule, internal capsule, and posterior thalamic radiation. In summary, these two prospective studies noted that response to

17

Journal Pre-proof

antipsychotic treatment might be predicted by white matter integrity in several regions including the corpus callosum, corona radiata, internal capsule, and superior longitudinal fasciculus, which is in line with the results of the present study. On the other hand, a selective review summarized findings of white matter integrity in

oo

f

patients with schizophrenia at different stages of the disease (Canu et al., 2015). In patients with

pr

drug-naïve first-episode schizophrenia, the most consistent result was reduced FA values in the

e-

anterior white matter including the anterior limb of the internal capsule, genu of the corpus

Pr

callosum, and anterior part of the cingulum (Canu et al., 2015). In chronic patients with schizophrenia, reduced FA values were found in the thalamic radiations, internal capsule, and

al

corpus callosum (Canu et al., 2015). The largest DTI study reported the greatest effects within

Jo u

rn

anterior corona radiata, and genu and body of the corpus callosum on FA values reduction in patients with schizophrenia relative to HCs (Kelly et al., 2018). FA value reductions in the anterior white matter including the internal capsule and corpus callosum were consistently identified in both patients with first-episode and chronic schizophrenia within previous findings (Patterson-Yeo et al., 2011; Kelly et al., 2018; Canu et al., 2015). Given that approximately 70% of TRS demonstrate resistance to antipsychotics from illness onset, these findings suggest that certain FA value reductions in the anterior white matter may emerge in early stages of TRS (Lally et al., 2016; Demjaha et al., 2017).

18

Journal Pre-proof

In terms of the diffusivity, we found increased MD and RD values in multiple tracts in patients with TRS relative to patients with non-TRS. McNabb et al. noted increased RD values in the body of the corpus callosum in patients with TRS relative to patients with non-TRS, which is in line with this study. In addition, we did not find any differences between patients

oo

f

with TRS and HCs or between patients with non-TRS and HCs. No differences between these

pr

combinations of groups might be due to not only a small sample size, but also potential

e-

neurobiological heterogeneity in TRS. In fact, we did not classify patients with TRS into

Pr

early-onset TRS (i.e., no period of remission from illness onset) and late-onset TRS (i.e., at least 6 months duration of antipsychotics response experience and failure to respond at a later stage),

al

while previous studies noted these two distinct patterns of TRS (Lally et al., 2016; Demjaha et

Jo u

rn

al., 2017). Additionally, no patients with TRS in this study took CLZ, suggesting that the TRS group potentially included CLZ-resistant and CLZ-responsive patients. Thus, these findings warrant larger studies in order to prospectively examine whether diffusivity metrics are potential biomarkers for treatment response/resistance of schizophrenia from illness onset. Moreover, we found relationships between reduced white matter integrity and increased severity of negative and general symptoms only in patients with severe TRS. These results are consistent with previous findings indicating relationships between negative symptoms and white matter alterations in the frontal and temporal areas (Wolkin et al., 2003;

19

Journal Pre-proof

Huang et al., 2018). Several lines of studies have reported that severe negative symptoms at illness onset predict more treatment resistance in schizophrenia (Ezeme et al., 2017; Demjaha et al., 2017). Taken together, white matter integrity deficits might be associated with more severe negative symptoms, which result in poorer treatment response in this population. However, no

oo

f

currently existing treatments have the capacity of improving negative symptoms with clinical

pr

significance (Fusar-Poli et al., 2014). Brady et al. indicated that transcranial magnetic

e-

stimulation applied to the cerebellar midline could modulate functional connectivity between

Pr

the cerebellum and dorsolateral prefrontal cortex, resulting in the improvement of negative symptoms in patients with schizophrenia (Brady et al., 2019). Thus, future research is warranted

rn

Jo u

patients with TRS.

al

to investigate the effect of the neuromodulation targeting these tracts on negative symptoms in

Among the tracts where FA values were reduced in patients with severe TRS relative to patients with non-TRS, FA values were correlated with clinical symptom severity in some but not others. More specifically, FA values in the left anterior limb of internal capsule, left cerebral peduncle, and right uncinate fasciculus were reduced but not correlated with symptom severity scores in patients with TRS. Despite a possible Type II error, these findings may suggest that these tracts are potential trait markers of TRS. The anterior limb of the internal capsule projects the thalamus to the cingulate and frontal cortices (Rosenberger et al., 2012). Also, the

20

Journal Pre-proof

connections to and from the substantia nigra, which provides the largest dopaminergic input to the striatum (the primary target of antipsychotic medications), are located within cerebral peduncle (Fallon & Moore, 1978). Furthermore, previous studies have suggested that white matter integrity in the uncinate fasciculus may be associated with treatment response in patients

oo

f

with schizophrenia (Reis Marquez et al., 2014; Huang et al., 2018). Alongside our results, white

pr

matter integrity deficits in these tracts may be a potential endophenotype for TRS.

e-

There are several limitations in this study. First, the sample size was relatively small in

Pr

each group in our study. Second, we did not correct for the influence of symptom severity when comparing white matter integrity between the two groups because treatment response and

al

resistance were determined based on symptom severity at the point of assessment. Third, both

Jo u

rn

patient groups were on different antipsychotics, which may have differently affected white matter microstructural organizations. Notably, no patients in the present study took CLZ. Finally, we could not accurately identify the onset of treatment resistance due to the nature of the cross-sectional study design. Previous studies have found two distinct patterns of TRS: early-onset TRS and late-onset TRS, suggesting the necessity to consider illness onset for subsequent TRS research (Lally et al., 2016; Demjaha et al., 2017). Furthermore, due to the nature of the cross-sectional design and the greater severity of the TRS group relative to the

21

Journal Pre-proof

non-TRS group, we cannot conclude whether our findings may be a trait maker for the pathophysiology of TRS or state marker representing the clinical severity of the TRS group. In summary, the present study revealed in-vivo white matter integrity differences among patients with severe TRS, patients with non-TRS, and HCs using the TRRIP Working

oo

f

Group Consensus criteria for the definition of treatment resistance. In patients with TRS,

pr

reduced FA values were found in multiple tracts relative to patients with non-TRS and HCs,

e-

while no differences were found between patients with non-TRS and HC groups. Also, reduced

Pr

FA values were related to increased severity of clinical symptoms in the severe TRS group, while no such associations were found in the non-TRS group. These neuroanatomical findings

al

provide new insight towards treatment resistance/response to antipsychotics in patients with

Jo u

rn

schizophrenia. Further, our results warrant further studies in larger sample sizes to investigate the neuroanatomical microstructures that may represent potential endophenotypes of TRS.

22

Journal Pre-proof

Acknowledgment We would like to acknowledge the important comment provided by Dr. Aristotle Voineskos. This work was supported by the Japan Society for the Promotion of Science and AMED (S.N, Y.N, and MM). The funding agency did not contribute to the study design; in the data collection, analyses, and interpretation; in the writing of the manuscript; and in the decision to submit the manuscript for

Jo u

rn

al

Pr

e-

pr

oo

f

publication.

23

Journal Pre-proof

Declaration of interests YN has received a Grant-in-Aid for Young Scientists (KAKENHI), a research grant from Japan Agency for Medical Research and development (AMED), an investigator-initiated clinical study grant from TEIJIN PHARMA LIMITED. YN also receives research grants from Japan Health Foundation, Meiji Yasuda Mental Health Foundation, Mitsui Life Social Welfare Foundation, Takeda Science Foundation, SENSHIN Medical Research Foundation, Health Science Center Foundation, Mochida Memorial Foundation for Medical and Pharmaceutical Research, and Daiichi Sankyo Scholarship Donation Program. He has received research supports from Otsuka Pharmaceutical, Shionogi, and Meiji Seika Pharma. YN also rec eives equipment-in-kind supports for an

oo

f

investigator-initiated study from Magventure Inc, Inter Reha Co., Ltd., Rogue Resolutions Ltd., and Miyuki Giken Co., Ltd. EP has received research support from an Ontario Graduate Scholarship (OGS), a Canadian Institutes of Health Research (CIHR) Canada Graduate Scholarship-Master’s, a

pr

CIHR Vanier Canada Graduate Scholarship, and he currently receives research support from the Healthy Brains for Healthy Lives Postdoctoral Fellowship. MMC has received research funding

e-

from the Weston Brain Institute, Alzheimer’s Association, and Michael J. Fox Foundation. He is currently receiving support from the Canadian Institutes of Health Research, National Sciences and

Pr

Engineering Research Council of Canada, and McGill University’s Healthy Brains for Healthy Lives Initiative. AG-G has received research support from the following external funding agencies: CIHR,

al

U.S National Institutes of Health, Ontario Mental Health Foundation, National Alliance for Research on Schizophrenia and Depression, Mexico Instituto de Ciencia y Tecnología del Distrito Federal,

rn

Consejo Nacional de Ciencia y Tecnología, Ministry of Economic Development and Innovation of Ontario, Ontario Academic Health Science Center Alternate Funding Plan Innovation Fund, and W.

Jo u

Garfield Weston Foundation. HU has received grants from Eisai, Otsuka Pharmaceutical, Dainippon-Sumitomo Pharma, Mochida Pharmaceutical, Meiji-Seika Pharmaceutical, and Novartis; speaker’s honoraria from Otsuka Pharmaceutical, Eli Lilly, Shionogi, Pfizer, Yoshitomi Yakuhin, Dainippon-Sumitomo Pharma, Meiji-Seika Pharma, MSD, and Janssen Pharmaceutical; and advisory panel payments from Dainippon-Sumitomo Pharma within the past three years. MM has received research support from Japan Society for the Promotion of Science and grants or speaker's honoraria from Daiichi Sankyo, Dainippon-Sumitomo Pharma, Eisai, Eli Lilly, Fuji Film RI Pharma, Janssen Pharmaceutical, Mochida Pharmaceutical, MSD, Nippon Chemipher, Novartis Pharma, Ono Yakuhin, Otsuka Pharmaceutical, Pfizer, Takeda Yakuhin, Tsumura, and Yoshitomi Yakuhin within the past three years. SN has received fellowship grants from CIHR, Japan Research Foundation for Clinical Pharmacology, Naito Foundation, Takeda Science Foundation, Uehara Memorial Foundation, and Daiichi Sankyo Scholarship Donation Program within the past three years. SN has also received research supports, manuscript fees or speaker's honoraria from Dainippon Sumitomo Pharma, Meiji-Seika Pharma, Otsuka Pharmaceutical, Shionogi, and Yoshitomi Yakuhin within the 24

Journal Pre-proof

past three years. Other authors have no financial or other relationship relevant to the subject of this

Jo u

rn

al

Pr

e-

pr

oo

f

manuscript.

25

Journal Pre-proof

References Alexander, A. L., Hurley, S. A., Samsonov, A. A., Adluru, N., Hosseinbor, A. P., Mossahebi, P., ... & Field, A. S. (2011). Characterization of cerebral white matter properties using quantitative magnetic resonance imaging stains. Brain connectivity, 1(6), 423-446.

Andreasen, N. C., Carpenter Jr, W. T., Kane, J. M., Lasser, R. A., Marder, S. R., & Weinberger, D. R. (2005). Remission in schizophrenia: proposed criteria and rationale for consensus. American Journal of Psychiatry, 162(3), 441-449.

oo

f

Andersson, J. L., & Sotiropoulos, S. N. (2016). An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. Neuroimage, 125, 1063-1078.

pr

Bastiani, M., Cottaar, M., Fitzgibbon, S. P., Suri, S., Alfaro-Almagro, F., Sotiropoulos, S. N., ... & Andersson, J. L. (2019). Automated quality control for within and between studies diffusion MRI

e-

data using a non-parametric framework for movement and distortion correction. NeuroImage, 184,

Pr

801-812.

Brady Jr, R. O., Gonsalvez, I., Lee, I., Öngür, D., Seidman, L. J., Schmahmann, J. D., ... & Halko, M.

al

A. (2019). Cerebellar-Prefrontal Network Connectivity and Negative Symptoms in Schizophrenia.

rn

American Journal of Psychiatry. doi:10.1176/appi.ajp.2018.18040429

Canu, E., Agosta, F., & Filippi, M. (2015). A selective review of structural connectivity

161(1), 19-28.

Jo u

abnormalities of schizophrenic patients at different stages of the disease. Schizophrenia research,

Chen, M., Zhuo, C. J., Qian, L. J., Wang, B., Zhai, J. G., Ji, F., & Ke, X. Y. (2018). Specific white matter impairments in patients with treatment-refractory first-episode schizophrenia: a 1-year follow-up pilot study. Chinese medical journal, 131(7), 879.

Cho, S. J., Kim, M. K., Bang, S. Y., Bang, M., & Lee, S. H. (2018). White matter integrity associated with severity reductions in positive symptoms after amisulpride treatment in drug-free patients with schizophrenia. Neuroscience letters, 685, 131-136.

Crocker, C. E., & Tibbo, P. G. (2018). Confused Connections? Targeting White Matter to Address Treatment Resistant Schizophrenia. Frontiers in pharmacology, 9, 1172.

26

Journal Pre-proof

Demjaha, A., Lappin, J. M., Stahl, D., Patel, M. X., MacCabe, J. H., Howes, O. D., ... & Charalambides, M. (2017). Antipsychotic treatment resistance in first-episode psychosis: prevalence, subtypes and predictors. Psychological medicine, 47(11), 1981-1989.

Ezeme, M. S., Uwakwe, R., Ndukuba, A. C., Igwe, M. N., Odinka, P. C., Amadi, K., & Obayi, N. O. (2017). Clinical correlates of treatment response among patients with schizophrenia in a tertiary Nigerian hospital. Journal of health care for the poor and underserved, 28(2), 721-738.

Fallon, J. H., & Moore, R. Y. (1978). Catecholamine innervation of the basal forebrain IV.

oo

f

Topography of the dopamine projection to the basal forebrain and neostriatum. Journal of Comparative Neurology, 180(3), 545-579.

pr

Fusar-Poli, P., Papanastasiou, E., Stahl, D., Rocchetti, M., Carpenter, W., Shergill, S., & McGuire, P. (2014). Treatments of negative symptoms in schizophrenia: meta-analysis of 168 randomized

e-

placebo-controlled trials. Schizophrenia Bulletin, 41(4), 892-899.

Pr

Guy W. ECDEU Assessment Manual for Psychopharmacology. Rockville, MD: US: Department of Health, Education, and Welfare Public Health Service Alcohol, Drug Abuse, and Mental Health

al

Administration; 1976.

rn

Holleran, L., Ahmed, M., Anderson-Schmidt, H., McFarland, J., Emsell, L., Leemans, A., ... & McDonald, C. (2014). Altered interhemispheric and temporal lobe white matter microstructural

Jo u

organization in severe chronic schizophrenia. Neuropsychopharmacology, 39(4), 944.

Howes, O. D., & Murray, R. M. (2014). Schizophrenia: an integrated sociodevelopmental-cognitive model. The Lancet, 383(9929), 1677-1687.

Howes, O. D., McCutcheon, R., Agid, O., De Bartolomeis, A., Van Beveren, N. J., Birnbaum, M. L., ... & Castle, D. J. (2016). Treatment-resistant schizophrenia: treatment response and resistance in psychosis (TRRIP) working group consensus guidelines on diagnos is and terminology. American Journal of Psychiatry, 174(3), 216-229.

Huang, J. Y., Liu, C. M., Hwang, T. J., Chen, Y. J., Hsu, Y. C., Hwu, H. G., ... & Ts eng, W. Y. I. (2018). Shared and distinct alterations of white matter tracts in remitted and nonremitted patients with schizophrenia. Human brain mapping, 39(5), 2007-2019.

27

Journal Pre-proof

Inagaki A, Inada T. Dose equivalence of psychotropic drugs. [18] Dose equivalence of psychotropic drugs: 2006 version. Rinsyo Seishin Yakuri (Jpn. J. Clin. Psychopharmacol.) 2006; 9: 1443–1447 (in Japanese).

Iwata, Y., Nakajima, S., Plitman, E., Caravaggio, F., Kim, J., Shah, P., ... & Remington, G. (2019). Glutamatergic neurometabolite levels in patients with ultra-treatment-resistant schizophrenia: A cross-sectional 3T proton magnetic resonance spectroscopy study. Biological psychiatry, 85(7), 596-605.

oo

f

Jauhar, S., Veronese, M., Nour, M. M., Rogdaki, M., Hathway, P., Turkheimer, F. E., ... & Howes, O. D. (2018). Determinants of treatment response in first-episode psychosis: an 18 F-DOPA PET study.

pr

Molecular psychiatry, 1. doi.org/10.1038/s41380-018-0042-4.

Kane, J. M. (2012). Addressing nonresponse in schizophrenia. The Journal of clinical psychiatry,

e-

73(2), e07-e07.

Pr

Kay, S. R., Fiszbein, A., & Opler, L. A. (1987). The positive and negative syndrome scale (PANSS)

al

for schizophrenia. Schizophrenia bulletin, 13(2), 261-276.

Kelly, S., Jahanshad, N., Zalesky, A., Kochunov, P., Agartz, I., Alloza, C., ... & Bousman, C. A.

rn

(2018). Widespread white matter microstructural differences in schizophrenia across 4322

23(5), 1261.

Jo u

individuals: results from the ENIGMA Schizophrenia DTI Working Group. Molecular psychiatry,

Kim, M. K., Kim, B., Lee, K. S., Kim, C. M., Bang, S. Y., Choi, T. K., & Lee, S. H. (2016). White-matter connectivity related to paliperidone treatment response in patients with schizophrenia. Journal of Psychopharmacology, 30(3), 294-302.

Kochunov, P., Huang, J., Chen, S., Li, Y., Tan, S., Fan, F., ... & Du, X. (2019). White Matter in Schizophrenia

Treatment

Resistance.

American

Journal

of

Psychiatry,

In

press.

doi:

10.1176/appi.ajp.2019.18101212.

Lally, J., Ajnakina, O., Di Forti, M., Trotta, A., Demjaha, A., Kolliakou, A., ... & Shergil, S. S. (2016). Two distinct patterns of treatment resistance: clinical predictors of treatment resistance in first-episode schizophrenia spectrum psychoses. Psychological medicine, 46(15), 3231-3240.

28

Journal Pre-proof

Luck, D., Buchy, L., Czechowska, Y., Bodnar, M., Pike, G. B., Campbell, J. S., ... & Lepage, M. (2011). Fronto-temporal disconnectivity and clinical short-term outcome in first episode psychosis: a DTI-tractography study. Journal of psychiatric research, 45(3), 369-377.

Mitelman, S. A., Torosjan, Y., Newmark, R. E., Schneiderman, J. S., Chu, K. W., Brickman, A. M., ... & Buchsbaum, M. S. (2007). Internal capsule, corpus callosum and long associative fibers in good and poor outcome schizophrenia: a diffusion tensor imaging survey. Schizophrenia research, 92(1-3), 211-224.

oo

f

Mouchlianitis, E., McCutcheon, R., & Howes, O. D. (2016). Brain-imaging studies of treatment-resistant schizophrenia: a systematic review. The Lancet Psychiatry, 3(5), 451-463.

pr

Nakajima, S., Takeuchi, H., Plitman, E., Fervaha, G., Gerretsen, P., Caravaggio, F., ... & Graff-Guerrero, A. (2015). Neuroimaging findings in treatment-resistant schizophrenia: a systematic

e-

review: lack of neuroimaging correlates of treatment-resistant schizophrenia. Schizophrenia research,

Pr

164(1-3), 164-175.

Pettersson-Yeo, W., Allen, P., Benetti, S., McGuire, P., & Mechelli, A. (2011). Dysconnectivity in

al

schizophrenia: where are we now?. Neuroscience & Biobehavioral Reviews, 35(5), 1110-1124.

rn

Reis Marques, T., Taylor, H., Chaddock, C., Dell’Acqua, F., Handley, R., Reinders, A. S., ... & David, A. S. (2013). White matter integrity as a predictor of response to treatment in first episode psychosis.

Jo u

Brain, 137(1), 172-182.

Rosenberger, G., Nestor, P. G., Oh, J. S., Levitt, J. J., Kindleman, G., Bouix, S., ... & McCarley, R. W. (2012). Anterior limb of the internal capsule in schizophrenia: a diffusion tensor tractography study. Brain imaging and behavior, 6(3), 417-425.

Scheck, S. M., Boyd, R. N., & Rose, S. E. (2012). New insights into the pathology of white matter tracts in cerebral palsy from diffusion magnetic resonance imaging: a systematic review. Developmental Medicine & Child Neurology, 54(8), 684-696.

Shahab, S., Stefanik, L., Foussias, G., Lai, M. C., Anderson, K. K., & Voineskos, A. N. (2017). Sex and diffusion tensor imaging of white matter in schizophrenia: a systematic review plus meta-analysis of the corpus callosum. Schizophrenia bulletin, 44(1), 203-221.

29

Journal Pre-proof

Sheehan, D. V., Lecrubier, Y., Sheehan, K. H., Amorim, P., Janavs, J., Weiller, E., ... & Dunbar, G. C. (1998). The Mini-International Neuropsychiatric Interview (MINI): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. The Journal of clinical psychiatry.

Smith, S. M., Jenkinson, M., Johansen-Berg, H., Rueckert, D., Nichols, T. E., Mackay, C. E., ... & Behrens, T. E. (2006). Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage, 31(4), 1487-1505.

oo

f

Song, S. K., Sun, S. W., Ramsbottom, M. J., Chang, C., Russell, J., & Cross, A. H. (2002). Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water.

pr

Neuroimage, 17(3), 1429-1436.

Vitolo, E., Tatu, M. K., Pignolo, C., Cauda, F., Costa, T., & Zennaro, A. (2017). White matter and

e-

schizophrenia: A meta-analys is of voxel-based morphometry and diffusion tensor imaging studies.

Pr

Psychiatry Research: Neuroimaging, 270, 8-21.

Wolkin, A., Choi, S. J., Szilagyi, S., Sanfilipo, M., Rotrosen, J. P., & Lim, K. O. (2003). Inferior

al

frontal white matter anisotropy and negative symptoms of schizophrenia: a diffusion tensor imaging

rn

study. American Journal of Psychiatry, 160(3), 572-574.

Xiao, Y., Sun, H., Shi, S., Jiang, D., Tao, B., Zhao, Y., ... & Lui, S. (2018). White matter

Jo u

abnormalities in never-treated patients with long-term schizophrenia. American Journal of Psychiatry, 175(11), 1129-1136.

30

Journal Pre-proof

Legends of Figures and Tables Table 1. Participants Demographics.

TRS = treatment-resistant schizophrenia; HCs = healthy controls; PANSS = Positive and Negative Syndrome Scale; CGI-S = Clinical Global Impression Severity; CPZ =

f

chlorpromazine.

oo

Figure 1. Voxelwise significant differences of FA, MD, and RD between patients with TRS and

pr

non-TRS.

e-

Blue scale denotes voxels with significantly lower values in patients with TRS relative to non-TRS,

Pr

and red-yellow scale denotes voxels with significantly higher values in patients with TRS relative to

al

non-TRS. All results were controlled for the effect of chlorpromazine equivalent daily dose

rn

antipsychotic treatment and thresholded at a family-wise error corrected cluster of 0.05. Voxels,

Jo u

where these values were significantly altered, were overlaid on the MNI standard image.

Figure 2. Voxelwise significant relationships of FA and the higher severity of PANSS total, and

negative, and general subscale scores in patients with TRS.

Blue scale denotes voxels that negatively correlated with the severity of symptoms in patients with

TRS, whereas red-yellow scale denotes voxels that positively correlated with the severity of

symptoms in patients with TRS. All results were controlled for the effect of chlorpromazine

equivalent daily dose antipsychotic treatment and thresholded at a family-wise error corrected cluster

of 0.05. Voxels, where these values were significantly altered, were overlaid on the MNI standard 31

Journal Pre-proof

Jo u

rn

al

Pr

e-

pr

oo

f

image.

32

Journal Pre-proof

Author Statement RO and ST performed statistical analyses in this study. YN, AGG, and SN designed the study. TR, SH, and KM performed sample collection and clinical assessments. RO drafted the manuscript. All

Jo u

rn

al

Pr

e-

pr

oo

f

authors adjusted the writing structure. All authors approved the final manuscript.

33

Journal Pre-proof

Conflict of Interest YN has received a Grant-in-Aid for Young Scientists (KAKENHI), a research grant from Japan Agency for Medical Research and development (AMED), an investigator-initiated clinical study grant from TEIJIN PHARMA LIMITED. YN also receives research grants from Japan Health Foundation, Meiji Yasuda Mental Health Foundation, Mitsui Life Social Welfare Foundation, Takeda Science Foundation, SENSHIN Medical Research Foundation, Health Science Center Foundation, Mochida Memorial Foundation for Medical and Pharmaceutical Research, and Daiichi Sankyo Scholarship Donation Program. He has received research supports from Otsuka Pharmaceutical,

oo

f

Shionogi, and Meiji Seika Pharma. YN also receives equipment-in-kind supports for an investigator-initiated study from Magventure Inc, Inter Reha Co., Ltd., Rogue Resolutions Ltd., and Miyuki Giken Co., Ltd. EP has received research support from an Ontario Graduate Scholarship

pr

(OGS), a Canadian Institutes of Health Research (CIHR) Canada Graduate Scholarship-Master’s, a CIHR Vanier Canada Graduate Scholarship, and he currently receives research support from the

e-

Healthy Brains for Healthy Lives Postdoctoral Fellowship. MMC has received research funding from the Weston Brain Institute, Alzheimer ’s Association, and Michael J. Fox Foundation. He is

Pr

currently receiving support from the Canadian Institutes of Health Research, National Sciences and Engineering Research Council of Canada, and McGill University’s Healthy Brains for Healthy Lives

al

Initiative. AG-G has received research support from the following external funding agencies: CIHR, U.S National Institutes of Health, Ontario Mental Health Foundation, National Alliance for Research

rn

on Schizophrenia and Depression, Mexico Instituto de Ciencia y Tecnología del Distrito Federal, Consejo Nacional de Ciencia y Tecnología, Ministry of Economic Development and Innovation of

Jo u

Ontario, Ontario Academic Health Science Center Alternate Funding Plan Innovation Fund, and W. Garfield Weston Foundation. HU has received grants from Eisai, Otsuka Pharmaceutical, Dainippon-Sumitomo Pharma, Mochida Pharmaceutical, Meiji-Seika Pharmaceutical, and Novartis; speaker’s honoraria from Otsuka Pharmaceutical, Eli Lilly, Shionogi, Pfizer, Yoshitomi Yakuhin, Dainippon-Sumitomo Pharma, Meiji-Seika Pharma, MSD, and Janssen Pharmaceutical; and advisory panel payments from Dainippon-Sumitomo Pharma within the past three years. MM has received research support from Japan Society for the Promotion of Science and grants or speaker's honoraria from Daiichi Sankyo, Dainippon-Sumitomo Pharma, Eisai, Eli Lilly, Fuji Film RI Pharma, Janssen Pharmaceutical, Mochida Pharmaceutical, MSD, Nippon Chemipher, Novartis Pharma, Ono Yakuhin, Otsuka Pharmaceutical, Pfizer, Takeda Yakuhin, Tsumura, and Yoshitomi Yakuhin within the past three years. SN has received fellowship grants from CIHR, Japan Research Foundation for Clinical Pharmacology, Naito Foundation, Takeda Science Foundation, Uehara Memorial Foundation, and Daiichi Sankyo Scholarship Donation Program within the past three years. SN has also received research supports, manuscript fees or speaker's honoraria from Dainippon Sumitomo 34

Journal Pre-proof

Pharma, Meiji-Seika Pharma, Otsuka Pharmaceutical, Shionogi, and Yoshitomi Yakuhin within the past three years. Other authors have no financial or other relationship relevant to the subject of this

Jo u

rn

al

Pr

e-

pr

oo

f

manuscript.

35

Journal Pre-proof

Highlights We involved patients with treatment-resistant schizophrenia (TRS) and treatment responsive schizophrenia according to the consensus criteria for TRS and calculated fractional anisotropy (FA) to examine white matter integrity deficits in TRS.

In order to reflect clinical picture of TRS, we enrolled TRS patients who had severe symptoms.

We found the TRS group had lower FA values in widespread tracts than the non-TRS group, and the

Jo u

rn

al

Pr

e-

pr

oo

f

identified white matter integrity deficits may reflect the pathophysiology of TRS.

36