Brain neurodevelopmental markers related to the deficit subtype of schizophrenia

Author’s Accepted Manuscript Brain neurodevelopmental markers related to the deficit subtype of schizophrenia Tsutomu Takahashi, Yoichiro Takayanagi, Yumiko Nishikawa, Mihoko Nakamura, Yuko Komori, Atsushi Furuichi, Mikio Kido, Daiki Sasabayashi, Kyo Noguchi, Michio Suzuki www.elsevier.com

PII: DOI: Reference:

S0925-4927(17)30063-X http://dx.doi.org/10.1016/j.pscychresns.2017.05.007 PSYN10691

To appear in: Psychiatry Research: Neuroimaging Received date: 17 February 2017 Revised date: 29 March 2017 Accepted date: 19 May 2017 Cite this article as: Tsutomu Takahashi, Yoichiro Takayanagi, Yumiko Nishikawa, Mihoko Nakamura, Yuko Komori, Atsushi Furuichi, Mikio Kido, Daiki Sasabayashi, Kyo Noguchi and Michio Suzuki, Brain neurodevelopmental markers related to the deficit subtype of schizophrenia, Psychiatry Research: Neuroimaging, http://dx.doi.org/10.1016/j.pscychresns.2017.05.007 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. 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.

Brain neurodevelopmental markers related to the deficit subtype of schizophrenia Tsutomu Takahashia,*, Yoichiro Takayanagia, Yumiko Nishikawaa, Mihoko Nakamuraa, Yuko Komoria, Atsushi Furuichia, Mikio Kidoa, Daiki Sasabayashia, Kyo Noguchib, Michio Suzukia a Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan b

Department of Radiology, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan

*Correspondence to: Department of Neuropsychiatry, University of Toyama, 2630 Sugitani, Toyama 930-0194, Japan. Tel.: +81 76 434 7323; fax: +81 76 434 5030. [email protected]

Abstract Deficit schizophrenia is a homogeneous subtype characterized by a trait-like feature of primary and prominent negative symptoms, but the etiologic factors related to this specific subtype remain largely unknown. This magnetic resonance imaging study aimed to examine gross brain morphology that probably reflects early neurodevelopment in 38 patients with deficit schizophrenia, 37 patients with non-deficit schizophrenia, and 59 healthy controls. Potential brain neurodevelopmental markers investigated in this study were the adhesio interthalamica (AI), cavum septi pellucidi (CSP), and surface morphology (i.e., olfactory sulcus depth, sulcogyral pattern, and number of orbital sulci) of the orbitofrontal cortex (OFC). The subtype classification of schizophrenia patients was based on the score of Proxy for the Deficit Syndrome. The deficit schizophrenia group had a significantly shorter AI compared with the non-deficit group and controls. The deficit group, but not the non-deficit group, was also characterized by an altered distribution of the OFC sulcogyral pattern, as well as fewer

posterior orbital sulcus compared with controls. Other neurodevelopmental markers did not differentiate the deficit and non-deficit subgroups. These results suggest that the deficit subtype of schizophrenia and its clinical manifestation may be at least partly related to prominent neurodevelopmental pathology.

Keywords: Deficit schizophrenia; Neurodevelopment; Adhesio interthalamica; Orbitofrontal cortex; Magnetic resonance imaging

Abbreviations AI, adhesio interthalamica; CSP, cavum septi pellucidi; IOS, intermediate orbital sulcus; LOS, lateral orbital sulcus; MOS, medial orbital sulcus; OFC, orbitofrontal cortex; PDS, Proxy for the Deficit Syndrome; POS, posterior orbital sulcus; TOS, transverse orbital sulcus

1. Introduction Detailed examination of specific schizophrenia subtypes is one possible approach to reduce heterogeneity, which could partly explain the discrepant neurobiological findings of the disorder (Keshavan et al., 2008; van Os and Kapur, 2009). Deficit schizophrenia is a clinical subtype characterized by primary and prominent negative symptoms that persist even during periods of relative remission (Carpenter et al., 1988). While etiologic factors related to this specific subtype remain elusive, the association of deficit schizophrenia with poor premorbid adjustment (Bucci et al., 2016; Kirkpatrick and Galderisi, 2008), neurological abnormalities (Peralta et al., 2014), and general cognitive impairments (reviewed by Mucci et al., in press) may support the hypothesis of its pervasive neurodevelopmental abnormalities (Galderisi et al., 2002; Peralta et al., 2014). Furthermore, a recent magnetic resonance imaging (MRI) study of network-level properties of cortical thickness demonstrated altered intracortical relationships, which 2

may reflect reduced network differentiation during early neurodevelopment, in deficit schizophrenia (Wheeler et al., 2015). To our knowledge, however, no MRI studies have examined gross brain morphology closely associated with early neurodevelopment specifically in deficit schizophrenia. Previous MRI studies of gross brain morphology in schizophrenia have implicated the role of aberrant neurodevelopmental processes in the pathophysiology of schizophrenia (Pantelis et al., 2005). A smaller adhesio interthalamica (AI), which is a narrow bridge connecting the medial surfaces of the thalami that develops during early gestation (O'Rahilly and Muller, 1990; Rosales et al., 1968), and increased prevalence of large (e.g., ≥ 6mm in anterior-posterior length) cavum septi pellucidi (CSP) due to incomplete fusion of the septum pellucidum around birth (Rakic and Yakovlev, 1968) are thought to reflect early developmental characteristics in midline brain regions in schizophrenia (Landin-Romero et al., 2016; Trzesniak et al., 2011ab). However, a large number of MRI studies including our own study (Takahashi et al., 2007, 2013b) reported normal size of the CSP in schizophrenia (reviewed by Trzesniak et al., 2011b). The surface morphology of the orbitofrontal cortex (OFC) is also a potential neurodevelopmental marker because it is largely established by birth (Armstrong et al., 1995; Chi et al., 1977); schizophrenia patients are generally characterized by a shallower olfactory sulcus (Nishikawa et al., 2016; Takahashi et al., 2013a, 2014), decreased Type I and increased Type III expression in the variation of the OFC ‘H-shaped’ sulcus [Type I, II, and III; defined by Chiavaras and Petrides, 2000] (Chakirova et al., 2010; Nakamura et al., 2007; Takayanagi et al., 2010), as well as a decreased number of intermediate and posterior orbital sulci (IOS/POS) (Bartholomeusz et al., 2014; Takahashi et al., 2016). We have previously demonstrated that AI length and number of POS are related to the severity of negative symptoms in schizophrenia (Takahashi et al., 2008a, 2016). Further, nucleus accumbens atrophy (De Rossi et al., 2016) as well as microstructural disruption of the forceps minor (Spalletta et al., 2015) 3

in deficit schizophrenia may imply significant role of the OFC abnormalities in this clinical subtype, because both of these structures are functionally and structurally connected with the OFC (Catani and Thiebaut de Schotten, 2008; Diekhof et al., 2012). However, it remains largely unknown whether the deficit and non-deficit subtypes of schizophrenia have differences in the morphology of potential neurodevelopmental markers located in the midline and OFC regions. This MRI study aimed to expand our previous studies of a range of neurodevelopmental markers [AI (Takahashi et al., 2008ab), CSP (Takahashi et al., 2007), olfactory sulcus (Nishikawa et al., 2016; Takahashi et al., 2013a), and OFC surface morphology (Nishikawa et al., 2016; Takahashi et al., 2016)] in schizophrenia by investigating the characteristics of these neurodevelopmental markers in well-defined deficit subtype schizophrenia in comparison with non-deficit subtype as well as healthy controls. On the basis of hypothesized pervasive neurodevelopmental abnormalities in deficit schizophrenia (Galderisi et al., 2002; Peralta et al., 2014), we predicted that the deficit patients would exhibit greater changes in brain neurodevelopmental markers compared with the non-deficit patients. We also investigated the association between brain neurodevelopmental markers and clinical variables in each schizophrenia subgroup. Given the role of gross brain morphology as a stable trait marker that mainly reflects early neurodevelopment, we predicted that it would not be related to the symptom severity (especially positive symptoms) at scanning and potential confounding factors after illness onset (e.g., medication, illness duration).

2. Methods 2.1. Subjects Seventy-five patients with schizophrenia (38 deficit and 37 non-deficit subtypes) fulfilling the ICD-10 research criteria (World health organization, 1993), who were 4

recruited from the inpatient and outpatient clinics of the Department of Neuropsychiatry of Toyama University Hospital, were included in this study. The patients were diagnosed following a structured clinical interview by psychiatrists using the Comprehensive Assessment of Symptoms and History (CASH; Andreasen et al., 1992). Clinical symptoms were rated by trained psychiatrists at the time of scanning using the Brief Psychiatric Rating Scale (BPRS; Rhoades and Overall, 1988), the Scale for the Assessment of Negative Symptoms (SANS; Andreasen, 1984a), and the Scale for the Assessment of Positive Symptoms (SAPS; Andreasen, 1984b). The subtype classification of schizophrenia patients was based on the score of Proxy for the Deficit Syndrome (PDS), which is a valid and stable case-identification tool to discriminate deficit and non-deficit subtypes of schizophrenia patients (Goetz et al., 2007; Kirkpatrick et al., 1993). The PDS score is defined as the sum of the scores of the anxiety, guilt feelings, depressive mood, and hostility items, subtracted from the score for blunted affect on the basis of the BPRS ratings (Kirkpatrick et al., 1993) in order to reflects ‘primary’ (i.e., not secondary to factors such as anxiety, suspiciousness and other psychotic symptoms, and depression) and enduring negative symptomatology in deficit syndrome (Carpenter et al., 1988). Because a cross-sectional assessment using the PDS may yield excessive false positives (Subotnik et al., 1998), we followed a categorization method of recent MRI study (Wheeler et al., 2015) in order to reduce the likelihood of false classification. Specifically, among the full schizophrenia sample whose MRI data and BPRS score are available in our dataset (n = 135), the patients with top (≥ -3) and bottom (≤ -8) quartiles of the PDS scores were defined as the deficit and non-deficit schizophrenia patients, respectively. Fifty-nine control subjects were selected from our previous studies (e.g., Nishikawa et al., 2016; Takahashi et al., 2016) based on matching to the schizophrenia patients for age and gender. They were recruited from members of the local community, hospital staff, and university students, and were asked to complete a questionnaire 5

consisting of 15 items concerning their personal (13 items; including a history of obstetric complications, substantial head injury, seizures, neurological or psychiatric disease, impaired thyroid function, hypertension, diabetes, and substance abuse) and family (2 items) histories of illness. Subjects with any personal or family history of psychiatric illness among their first-degree relatives were excluded. All subjects were physically healthy at the time of the study and none had a lifetime history of serious head trauma, neurological illness, serious medical or surgical illness, or substance abuse disorders. All participants were also screened for gross brain abnormalities (except a large CSP) by neuroradiologists. The control subjects and 51/75 schizophrenia patients in this study have been partly included in our previous studies of the CSP (Takahashi et al., 2007), AI (Takahashi et al., 2008ab), olfactory sulcus (Nishikawa et al., 2016; Takahashi et al., 2013a), and OFC surface morphology (Nishikawa et al., 2016; Takahashi et al., 2016). The Committee on Medical Ethics of Toyama University approved this study. Written informed consent was obtained from all subjects.

2.2. Magnetic resonance imaging procedures MR images were obtained using a 1.5T Magnetom Vision (Siemens Medical System, Inc., Erlangen, Germany) with a three-dimensional gradient-echo sequence FLASH (fast low-angle shots) yielding 160-180 contiguous T1-weighted slices of 1.0 mm thickness in the sagittal plane. The imaging parameters were as follows: repetition time = 24 ms; echo time = 5 ms; flip angle = 40º; field of view = 256 mm; and matrix size = 256×256 pixels. The voxel size was 1.0×1.0×1.0 mm. The intracranial volume (ICV) was measured to correct for differences in head size as described previously (Zhou et al., 2003); there were no significant group differences for ICV (Table 2).

6

2.3. Assessment of the neurodevelopmental markers The images were processed on a Linux PC (Fujitsu Limited, Tokyo, Japan) using Dr. View software (Infocom, Tokyo, Japan). The brain images were realigned in three dimensions and then reconstructed into entire contiguous coronal images with a 1-mm thickness, perpendicular to the anterior commissure-posterior commissure line. Assessment of the AI, CSP, and olfactory sulcus was performed by one rater (TT). A second rater (HH, KN, YN, or DS) measured these structures in randomly selected brains in order to confirm the measurement reliabilities. For the OFC surface morphology that has high inter-individual variabilities (Chiavaras and Petrides, 2000), two raters (TT and YN or MN) independently performed the sulcogyral pattern classification and sulcus count for all subjects. A consensus agreement was reached in all cases even when the initial classification/count differed between the raters. All of these raters were blind to the subjects' identity. High intra- and inter-rater reliabilities (> 0.8; Cronbach's α in nominal measures and intraclass correlation coefficient for continuous measures) have been established for all of these structures in the MR images (n ≥ 10) scanned using the same scanner/parameters as in this study (Nishikawa et al., 2016; Takahashi et al., 2007, 2008ab, 2016). When we separately calculated the measurement reliabilities on each hemisphere (where applicable), the reliability values were ≥ 0.76 for left and ≥ 0.71 for right hemispheres, respectively.

2.3.1. Midline brain structures As described in detail elsewhere (Takahashi et al., 2007, 2008a), the rater counted the number of 1-mm coronal slices where each midline structure (AI and CSP) was clearly seen (Fig. 1). The length of the AI and CSP (in mm) was equal to the number of these slices. We considered the AI as present when it could be identified on three or more slices on both coronal and axial views (Takahashi et al., 2008a). A CSP equal to or greater than 6 mm was defined as large on the basis of previous reports (e.g., Nopoulos 7

et al., 1997, Kasai et al., 2004). On these coronal slices, the rater also manually traced the CSP, which could be readily differentiated from the surrounding structures (corpus callosum and septum pellucidum).

2.3.2. Olfactory sulcus depth On each coronal slice, the olfactory sulcus (Fig. 1) was traced beginning with the deepest point of the sulcus and ending inferiorly with a tangent line connecting the top surfaces of the gyrus rectus and medial orbital gyrus (Nishikawa et al., 2016; Rombaux et al., 2009). The average depth of the sulcus was calculated as follows: sum of the depth in all slices containing the sulcus / slice number.

2.3.3. OFC sulcogyral pattern classification and sulcus count The medial orbital sulcus (MOS), lateral orbital sulcus (LOS), and transverse orbital sulcus (TOS) were highlighted on consecutive 1-mm coronal slices, and then viewed in the axial plane for OFC pattern classification based on the definition by Chiavaras and Petrides (2000). Briefly, the OFC sulcogyral patterns were classified according to the continuity of the ‘H-shaped’ sulcus consisting of the MOS, TOS, and LOS; for Type I, the MOS is disconnected while the LOS is intact, for Type II, both the MOS and LOS are continuous, and for Type III, both the MOS and LOS are disconnected (Fig. 2A). We then identified and counted the number of IOS (single, double, or triple) and POS (absent, single, or double); the IOS was identified anterior to the TOS in between the rostral MOS and rostral LOS, while the POS was posterior to the TOS in between the caudal MOS and caudal LOS (Fig. 2B). According to previous reports (Lavoie et al., 2014; Takahashi et al., 2016), a fissure clearly visible in at least 4 coronal and 4 axial slices was defined as a sulcus.

8

2.4. Statistical analysis Clinical and demographic differences between groups (controls, deficit schizophrenia, and non-deficit schizophrenia) were examined by one-way analysis of variance (ANOVA), χ2 test, or Fisher’s exact test (when more than 20% of cells had expected counts less than 5). Group differences in nominal measures such as the prevalence of CSP (CSP ≥ 1 slice), large CSP (CSP ≥ 6 slices), and AI, as well as the OFC pattern distribution and number of IOS/POS, were evaluated by χ2 test or Fisher’s exact test. The CSP length and volume were log-transformed for the following analyses because of their skewed distributions (Table 2). The CSP length/volume (log) and AI length were analyzed using an analysis of covariance (ANCOVA) with age, gender, and ICV as covariates, with diagnosis as a between-subject factor. The olfactory sulcus depth was analyzed by a similar ANCOVA model, but the hemisphere was used as a within-subject variable. Post-hoc Newman–Keuls tests were used to follow-up any significant main effects or interactions. The relation between these potential neurodevelopmental markers and demographic/clinical variables in each group was examined using Pearson's partial correlation for continuous measures [CSP length/volume (log), AI length, and olfactory sulcus depth] with Bonferroni correction or ANCOVA with each brain measure as a between-subject factor for nominal measures. Age and ICV were used as controlling factors for these analyses (except for correlation with age). The hemispheres with triple-IOS and/or double-POS in the schizophrenia patients were excluded from the ANCOVAs due to small sample size. Asymmetry of the OFC pattern and number of IOS/POS in each group was assessed using χ2 test or Fisher’s exact test. Statistical significance was defined as p < 0.05.

9

3. Results 3.1. Demographic characteristics Demographic and clinical characteristics of the study participants are summarized in Table 1. Age, gender, and parental education did not differ significantly between the groups, but the healthy controls had attained a higher level of education compared with the schizophrenia subgroups. The handedness distribution differed between the groups. The deficit and non-deficit schizophrenia subgroups did not differ in onset age, illness duration, and medication. There were significant subscore-by-subgroup interactions for both SANS and SAPS; the deficit schizophrenia subgroup was characterized by a more severe blunted affect but milder hallucinations, delusions, and attention deficit compared with the non-deficit subgroup.

3.2. Group differences in the neurodevelopmental markers There was a significant group difference in the AI length (Table 2, Fig. 3); the deficit schizophrenia group had a significantly shorter AI compared with the non-deficit schizophrenia group (post-hoc test, p = 0.020) and controls (post-hoc test, p < 0.001). However, there was no significant group difference in the CSP measures. For the OFC surface morphology (Table 2), the deficit schizophrenia group, but not the non-deficit group, had a significantly decreased Type I and increased Type III pattern compared with controls in the right hemisphere. Furthermore, only the deficit group had a left absent-POS pattern more often than controls. However, direct comparison between the schizophrenia subgroups showed no significant difference in the OFC pattern distribution or IOS/POS counts (all p > 0.164). The olfactory sulcus was significantly shallower in both the deficit and non-deficit groups compared with controls (post-hoc test, p < 0.001).

10

The study findings remained essentially the same even when we included height as a covariate or analyzed only right-handed subjects because of significant group differences in these factors (Table 1).

3.3. Neurodevelopmental markers and demographic/clinical variables Age was negatively correlated with AI length only in the deficit schizophrenia group (r = -0.455, p = 0.005), while personal/parental education did not relate to brain measures in controls or schizophrenia subgroups. There was no significant relation between the neurodevelopmental markers (CSP, AI, olfactory sulcus, OFC pattern, and IOS/POS counts) and clinical variables (onset age, illness duration, dose/duration of medication, PDS score, and total SANS/SAPS/BPRS scores) in either schizophrenia subgroup. When we combined the deficit and non-deficit schizophrenia patients, the PDS score had a weak trend of negative correlation with the AI length (r = -0.167, p = 0.089).

3.4. Possible relation between neurodevelopmental markers There was no significant relation between the neurodevelopmental markers in either diagnostic group, suggesting that different neurodevelopmental marker abnormalities may reflect, at least partly, different neurodevelopmental pathologies. The CSP length was significantly correlated with its volume (r > 0.960, p < 0.001 for all diagnostic groups).

3.5. Asymmetry of the OFC surface morphology ANCOVA of the olfactory sulcus depth revealed significant group-by-hemisphere interaction [F (2, 131) = 7.87, p < 0.001], with only the control subjects having a pattern of right-deeper-than-left asymmetry (p < 0.001). The controls were characterized by a higher prevalence of Type III (χ2 = 7.47, p = 0.023) and lower prevalence of Type II 11

(Fisher’s exact test, p = 0.016) on the right hemisphere, while the patient groups had no significant asymmetry (p > 0.168). The number of IOS/POS showed no significant asymmetry for all groups (p > 0.449).

4. Discussion To our knowledge, this is the first MRI study that demonstrated greater morphologic changes in several neurodevelopmental markers in deficit schizophrenia. The length of the AI was significantly shorter in patients with deficit schizophrenia compared to those with non-deficit schizophrenia and control subjects. Furthermore, alteration of the OFC sulcogyral pattern (H-shaped variation and sulcus count) was more evident in the deficit schizophrenia group than in the non-deficit group. However, the morphology of CSP and olfactory sulcus did not differ between the deficit and non-deficit subgroups. These findings could not be explained by medication and illness duration, suggesting that the present results may reflect a neurobiological trait related to primary and prominent negative symptoms observed in the deficit subtype of schizophrenia. The present findings demonstrated that shorter length of the AI, which exists even at the early illness stages of schizophrenia (Takahashi et al., 2008abc; Trzesniak et al., 2011a), is a prominent feature of deficit subtype schizophrenia. The deficit subtype may be characterized by more severe gray matter reduction predominantly in frontal and temporo-limbic regions compared to the non-deficit subtype (Cascella et al., 2010; Takayanagi et al., 2013), while conflicting results [greater changes in non-deficit subtype (e.g., Volpe et al., 2012) or no subtype effect (Voineskos et al., 2013)] have also been reported (reviewed by Mucci et al., in press) potentially due to confounding factors after illness onset such as medication and disease chronicity (Tomelleri et al., 2009). However, we found no effect from these potential confounding factors on the AI morphology, supporting its role as a stable trait marker. Our findings may be also 12

consistent with the relation between the AI malformation and negative symptomatology in schizophrenia (Meisenzahl et al., 2000, 2002; Takahashi et al., 2008a), which may reflect the efferent connections of the AI to cortico-limbic regions related to social and emotional regulation [e.g., amygdala, frontal and anterior cingulate cortices (Graff-Radford, 1997; Percheron, 2004)], as well as the notion that improper development in midline neural circuits may explain the diverse symptoms of schizophrenia (Andreasen et al., 1994). In this study, the deficit schizophrenia group was also characterized by decreased Type I and increased Type III patterns, as well as fewer POS, in the surface of the OFC, which is a key brain region for emotional processing and the regulation of social behavior (Kringelbach and Rolls, 2004). Specifically, the OFC has strong connections with the cingulate cortex and is related to monitoring the reward value of many different reinforces (Diekhof et al., 2012; Kringelbach and Rolls, 2004). Given that cortical folding in human brains likely reflects critical neurodevelopmental events such as local neuronal connection and synaptic development (Armstrong et al., 1995; Rakic, 1988), an altered OFC sulcogyral pattern and its relation to cognitive impairments, as well as both positive and negative symptomatology reported in schizophrenia (Nakamura et al., 2007; Nishikawa et al., 2016; Takahashi et al., 2016), may at least partly reflect underdevelopment in neural organization and dysconnectivity in this region. Thus, the present OFC findings may be consistent with previous diffusion tensor imaging (DTI) studies that demonstrated disrupted circuitry of frontal and related brain regions specifically in deficit schizophrenia (Kitis et al., 2012; Rowland et al., 2009; Voineskos et al., 2013). A selective involvement of forceps minor in deficit schizophrenia (Spalletta et al., 2015) also supports such a hypothesis, because this fibre bundle is directly involved in the frontal connectivity (Catani and Thiebaut de Schotten, 2008). A recent network-based analysis of cortical thickness found enhanced frontoparietal and frontotemporal coupling in deficit schizophrenia, which may reflect a decreased 13

differentiation of brain regions and impairment in efficient network formation (Wheeler et al., 2015). Taken together, the present and previous neuroimaging findings in deficit schizophrenia may support the notion that dysfunctional neural reward processing involving the OFC in schizophrenia could represent the neurobiological underpinnings of the amotivational/apathetic component of negative symptoms (Lee et al., 2015), which is peculiar to deficit schizophrenia (Galderisi et al., 2013; Kirkpatrick et al., 1989). Our results of a range of potential neurodevelopmental markers may provide a clue to the timing of neurodevelopmental abnormalities related to schizophrenia and its specific subtypes. Lack of normal asymmetry of the OFC surface morphology in both deficit and non-deficit schizophrenia patients may reflect a perturbation in the lateralization process during early developmental (Kawasaki et al., 2008). The deficit and non-deficit schizophrenia groups also shared a reduced depth of the olfactory sulcus, which develops at around 16 to 25 weeks’ gestation (Chi et al., 1977), whereas decreased POS and altered H-shaped sulcogyral pattern, which likely reflect neurodevelopmental disturbance during the mid (around 28 weeks)-to-late gestation period (Armstrong et al., 1995; Chi et al., 1977), were evident predominantly in the deficit subgroup. We found abnormally small AI, which develops around 13 to 14 weeks of gestation (Rosales et al., 1968), especially in deficit schizophrenia, but the patients of both deficit/non-deficit subtypes had a normal CSP size, which is related to fusion of the septum pellucidi within 3-6 months of birth (Shaw and Alvord, 1969). Partly consistent with the notion that the AI may also exhibit increasing atrophy especially after the third decade (Rosales et al., 1968; Takahashi et al., 2013b), we found a negative correlation between the age and AI length in the deficit schizophrenia group. Taken together, our findings may support the idea that schizophrenia is more closely related to aberrant neurodevelopment early in gestation, with the deficit subtype having especially severe and prolonged neurodevelopmental pathology, possibly 14

including accelerated AI atrophy during late neurodevelopmental processes after birth (Pantelis et al., 2005). A few possible confounding factors in this study should be taken into account. First, the deficit/non-deficit classification was based on a proxy case identification method (i.e., PDS; Kirkpatrick et al., 1993), while the gold standard for diagnosis is a semi-structured interview using the Schedule for the Deficit Syndrome (Kirkpatrick et al., 1989). A large number of clinical (Messias et al., 2004; Strauss et al., 2010), neurocognitive (Cohen and Docherty, 2004; Fervaha et al., 2016), and neuroimaging (Voineskos et al., 2013; Wheeler et al., 2015) studies have used the PDS to identify deficit schizophrenia patients because of its reliability (Goetz et al., 2007; Kirkpatrick et al., 1993) and stability (Kirkpatrick et al., 1996; Strauss et al., 2010). However, a cross-sectional assessment using the PDS cannot directly examine the duration of deficit-like features, which is one of the criterion for the deficit syndrome (Kirkpatrick et al., 1993). As expected, our deficit schizophrenia group defined by the PDS score was characterized by severe blunted affect and mild positive psychotic symptoms. However, we could not reliably test the stability of the classification in our own sample due to a lack of clinical follow-up data. Second, it is possible that the higher proportion of males in our deficit group has affected the findings. We selected the deficit/non-deficit patients based on the PDS scores irrespective of gender, but their gender representation (males > females) was consistent with previous reports (Carpenter et al., 1988; Roy et al., 2001). In order to avoid sampling bias by artificially matching gender ratios between the subtypes, we used gender as a covariate and statistically controlled for this potential confounding factor. However, the possibility still exists that gender dimorphism of the AI length (females > males; Takahashi et al., 2008ab) have affected our findings. Third, in contrast to previous CSP studies in schizophrenia (Landin-Romero et al., 2016; Trzesniak et al., 2011b), the control subjects in this study had an even higher prevalence of large CSP than in schizophrenia patients (although not statistically significant). This 15

finding may support the hypothesis that only the size (length, volume) of the CSP is not sensitive enough to detect existing changes of the CSP (Choi et al., 2008). Finally, although the gross brain morphology investigated in this study is thought to reflect early neurodevelopment, it is also reported that the size of the AI and CSP can change during the course of schizophrenia (Takahashi et al., 2013b; Trzesniak et al., 2012). Thus, further longitudinal analyses would be required to clarify the relation between the potential neurodevelopmental markers and deficit subtype of schizophrenia. Despite these limitations, the present study that included the schizophrenia patients stratified into different clinical phenotypes partly supported the concept that the deficit schizophrenia is an etiologically distinct disease within the syndrome of schizophrenia (Kirkpatrick and Galderisi, 2008). Our findings also suggested the possible role of brain neurodevelopmental markers as one of the endophenotypes that aid the dissection of schizophrenia syndrome for future genetic/biological studies (Jablensky, 2010). Because the gross brain abnormalities can be easily visualized on a structural clinical scan, the approach of brain assessment in this study may be also suitable for translational research such as the prediction of treatment response using biomarkers (Malhotra, 2015). On the other hand, given that our findings of neurodevelopmental markers could reflect white matter abnormalities as well as diverse cortical underdevelopment as described above, further multimodal neuroimaging studies using DTI and automatic techniques for topographical cortical measurements (e.g., cortical thickness, whole brain gyrification pattern) would be required to clarify the etiological significance of our findings.

5. Conclusion The present MRI study of gross brain morphology demonstrated that the deficit schizophrenia group was characterized by shorter AI and more evident changes in the OFC sulcogyral pattern compared with the non-deficit group. Given the potential role of 16

these brain structures as a marker of early neurodevelopment, our findings may support the hypothesis, based on the clinical characteristics of deficit schizophrenia, that this specific subtype is associated with pervasive neurodevelopmental abnormalities (Galderisi et al., 2002; Peralta et al., 2014).

Contributors In this study, Drs. Suzuki and Takayanagi conceived the idea and methodology of the study. Dr. Takahashi conducted the statistical analyses and wrote the manuscript. Drs. Takahashi, Takayanagi, Furuichi, Kido, Nishikawa, Sasabayashi, and Nakamura recruited subjects, and were involved in clinical and diagnostic assessments. Drs. Takahashi, Nishikawa, and Nakamura analyzed the MRI data. Ms. Komori assisted in the management of clinical data of the study participants. Dr. Noguchi provided technical support for the MRI scanning and data processing. Drs. Takahashi, Takayanagi, and Suzuki contributed to the writing and editing of the manuscript. All authors contributed to and have approved the final manuscript.

Conflict of interest None.

Acknowledgements This work was supported by JSPS KAKENHI Grant Number JP26461738 to Y.T., JP26461739 to T.T., and JP24390281 to M.S., and by the Health and Labour Sciences Research Grants for Comprehensive Research on Persons with Disabilities from the Japan Agency for Medical Research and Development (AMED) to M.S. The authors would like to thank the radiological technologists, especially Mr. Koichi Mori and Mr. Sadanori Ito, who assisted in the MRI data collection at Toyama University Hospital.

17

References Andreasen, N.C., 1984a. The Scale for the Assessment of Negative Symptoms (SANS). The University of Iowa, Iowa City, IA. Andreasen, N.C., 1984b. The Scale for the Assessment of Positive Symptoms (SAPS). The University of Iowa, Iowa City, IA. Andreasen, N.C., Flaum, M., Arndt, S., 1992. The Comprehensive Assessment of Symptoms and History (CASH): an instrument for assessing diagnosis and psychopathology. Arch. Gen. Psychiatry 49, 615–623. Andreasen, N.C., Arndt, S., Swayze, 2nd. V., Cizadlo, T., Flaum, M., O'Leary, D., Ehrhardt, J.C., Yuh, W.T., 1994. Thalamic abnormalities in schizophrenia visualized through magnetic resonance image averaging. Science 266 (5183), 294-298. Armstrong, E., Schleicher, A., Omran, H., Curtis, M., Zilles, K., 1995. The ontogeny of human gyrification. Cereb. Cortex 5 (1), 56-63. Bartholomeusz, C.F., Whittle, S.L., Montague, A., Ansell, B., McGorry, P.D., Velakoulis, D., Pantelis, C., Wood, S.J., 2013. Sulcogyral patterns and morphological abnormalities of the orbitofrontal cortex in psychosis. Prog. Neuropsychopharmacol. Biol. Psychiatry 44, 168-177. Bucci, P., Mucci, A., Piegari, G., Nobile, M., Pini, S., Rossi, A., Vita, A., Galderisi, S., Maj, M., 2016. Characterization of premorbid functioning during childhood in patients with deficit vs. non-deficit schizophrenia and in their healthy sibling. Schizophr. Res. 174(1-3), 172-176. Carpenter, W.T. Jr, Heinrichs, D.W., Wagman, A.M., 1988. Deficit and nondeficit forms of schizophrenia: the concept. Am. J. Psychiatry 145(5), 578-583. Catani, M., Thiebaut de Schotten, M., 2008. A diffusion tensor imaging tractography atlas for virtual in vivo dissections. Cortex 44(8),1105-1132. Cascella, N.G., Fieldstone, S.C., Rao, V.A., Pearlson, G.D., Sawa, A., Schretlen, D.J., 18

2010. Gray-matter abnormalities in deficit schizophrenia. Schizophr. Res. 120(1-3), 63-70. Chakirova, G., Welch, K.A., Moorhead, T.W., Stanfield, A.C., Hall, J., Skehel, P., Brown, V.J., Johnstone, E.C., Owens, D.G., Lawrie, S.M., McIntosh, A.M., 2010. Orbitofrontal morphology in people at high risk of developing schizophrenia. Eur. Psychiatry 25 (6), 366-372. Chi, J.G., Dooling, E.C., Gilles, F.H., 1977. Gyral development of the human brain. Ann. Neurol. 1(1), 86-93. Chiavaras, M.M., Petrides, M., 2000. Orbitofrontal sulci of the human and macaque monkey brain. J. Comp. Neurol. 422 (1), 35–54. Choi, J.K., Kang, D.H., Park, J.Y., Jung, W.H., Choi, C.H., Chon, M.W., Jung, M.H., Lee, J.M., Kwon, J.S., 2008. Cavum septum pellucidum in subjects at ultra-high risk for psychosis: Compared with first-degree relatives of patients with schizophrenia and healthy volunteers. Prog. Neuropsychopharmacol. Biol. Psychiatry 32 (5), 1326-1330. Cohen, A.S., Docherty, N.M., 2004. Deficit versus negative syndrome in schizophrenia: prediction of attentional impairment. Schizophr. Bull.30(4), 827-835. De Rossi, P., Dacquino, C., Piras, F., Caltagirone, C., Spalletta, G., 2016. Left nucleus accumbens atrophy in deficit schizophrenia: A preliminary study. Psychiatry Res. 254, 48-55. Diekhof, E.K., Kaps, L., Falkai, P., Gruber, O., 2012. The role of the human ventral striatum and the medial orbitofrontal cortex in the representation of reward magnitude - an activation likelihood estimation meta-analysis of neuroimaging studies of passive reward expectancy and outcome processing. Neuropsychologia 50(7), 1252-1266. Fervaha, G., Agid, O., Foussias, G., Siddiqui, I., Takeuchi, H., Remington, G., 2016. Neurocognitive impairment in the deficit subtype of schizophrenia. Eur. Arch. 19

Psychiatry Clin. Neurosci. 266(5), 397-407. Galderisi, S., Maj, M., Mucci, A., Cassano, G.B., Invernizzi, G., Rossi, A., Vita, A., Dell'Osso, L., Daneluzzo, E., Pini, S., 2002. Historical, psychopathological, neurological, and neuropsychological aspects of deficit schizophrenia: a multicenter study. Am. J. Psychiatry 159(6), 983-990. Galderisi, S., Bucci, P., Mucci, A., Kirkpatrick, B., Pini, S., Rossi, A., Vita, A., Maj, M., 2013. Categorical and dimensional approaches to negative symptoms of schizophrenia: focus on long-term stability and functional outcome. Schizophr. Res. 147(1), 157-162. Goetz, R.R., Corcoran, C., Yale, S., Stanford, A.D., Kimhy, D., Amador, X., Malaspina, D., 2007. Validity of a 'proxy' for the deficit syndrome derived from the Positive And Negative Syndrome Scale (PANSS). Schizophr. Res. 93(1-3), 169-177. Graff-Radford, N.R., 1997. Syndromes due to acquired thalamic damage. In: Feinberg, T.E., Farah, M.J. (Eds.), Behavioral and Neurology and Neuropsychology. McGraw-Hill, NY, pp. 433–443. Jablensky, A., 2010. The diagnostic concept of schizophrenia: its history, evolution, and future prospects. Dialogues Clin. Neurosci. 12(3), 271-287. Kasai, K., McCarley, R.W., Salisbury, D.F., Onitsuka, T., Demeo, S., Yurgelun-Todd, D., Kikinis, R., Jolesz, F.A., Shenton, M.E., 2004. Cavum septi pellucidi in first-episode schizophrenia and first-episode affective psychosis: an MRI study. Schizophr. Res. 71(1), 65-76. Kawasaki, Y., Suzuki, M., Takahashi, T., Nohara, S., McGuire, P.K., Seto, H., Kurachi, M., 2008. Anomalous cerebral asymmetry in patients with schizophrenia demonstrated by voxel-based morphometry. Biol. Psychiatry 63(8), 793-800. Keshavan, M.S., Tandon, R., Boutros, N.N., Nasrallah, H.A., 2008. Schizophrenia,“Just the facts”: what we know in 2008 Part 3. Neurobiology. Schizophr. Res. 106(2-3), 89-107. 20

Kirkpatrick, B., Buchanan, R.W., McKenney, P.D., Alphs, L.D., Carpenter, W.T. Jr., 1989. The Schedule for the Deficit syndrome: an instrument for research in schizophrenia. Psychiatry Res. 30(2), 119-123. Kirkpatrick, B., Buchanan, R.W., Breier, A., Carpenter, W.T. Jr., 1993. Case identification and stability of the deficit syndrome of schizophrenia. Psychiatry Res. 47(1), 47-56 Kirkpatrick, B., Ram, R., Bromet, E., 1996. The deficit syndrome in the Suffolk County Mental Health Project. Schizophr. Res. 22(2), 119-126. Kirkpatrick, B., Galderisi, S., 2008. Deficit schizophrenia: an update. World Psychiatry, 7 (3), 143-147. Kringelbach, M.L., Rolls, E.T., 2004. The functional neuroanatomy of the human orbitofrontal cortex: evidence from neuroimaging and neuropsychology. Prog. Neurobiol. 72 (5), 341-372. Kitis ,O., Ozalay, O., Zengin, E.B., Haznedaroglu, D., Eker, M.C., Yalvac, D., Oguz, K., Coburn, K., Gonul, A.S., 2012. Reduced left uncinate fasciculus fractional anisotropy in deficit schizophrenia but not in non-deficit schizophrenia. Psychiatry Clin. Neurosci. 66(1), 34-43. Landin-Romero, R., Amann, B.L., Sarró, S., Guerrero-Pedraza, A., Vicens, V., Rodriguez-Cano, E., Vieta, E., Salvador, R., Pomarol-Clotet, E., Radua, J., 2016. Midline brain abnormalities across psychotic and mood disorders. Schizophr. Bull. 42(1), 229-238. Lavoie, S., Bartholomeuz, C.F., Nelson, B., Lin, A., McGorry, P.D., Velakoulis, D., Whittle, S.L., Yung, A.R., Pantelis, C., Wood, S.J., 2014. Sulcogyral pattern and sulcal count of the orbitofrontal cortex in individuals at ultra high risk for psychosis. Schizophr. Res. 154 (1-3), 93-99. Malhotra, A.K., 2015. Dissecting the heterogeneity of treatment response in first-episode schizophrenia. Schizophr. Bull. 41(6), 1224-1226. 21

Meisenzahl, E.M., Frodl, T., Zetzsche, T., Leinsinger, G., Heiss, D., Maag, K., Hegerl, U., Hahn, K., Möller, H.J., 2000. Adhesio interthalamica in male patients with schizophrenia. Am. J. Psychiatry 157(5), 823-825. Meisenzahl, E.M., Frodl, T., Zetzsche, T., Leinsinger, G., Maag, K., Hegerl, U., Hahn, K., Möller, H.J., 2002. Investigation of a possible diencephalic pathology in schizophrenia. Psychiatry Res. 115(3), 127-135. Messias, E., Kirkpatrick, B., Bromet, E., Ross, D., Buchanan, R.W., Carpenter, W.T. Jr., Tek, C., Kendler, K.S., Walsh, D., Dollfus, S., 2004. Summer birth and deficit schizophrenia: a pooled analysis from 6 countries. Arch. Gen. Psychiatry 61(10), 985-989. Mucci, A., Merlotti, E., Üçok, A., Aleman, A., Galderisi, S. Primary and persistent negative symptoms: Concepts, assessments and neurobiological bases. Schizophr. Res., in press. doi: 10.1016/j.schres.2016.05.014. Nakamura, M., Nestor, P.G., McCarley, R.W., Levitt, J.J., Hsu, L., Kawashima, T., Niznikiewicz, M., Shenton, M.E., 2007. Altered orbitofrontal sulcogyral pattern in schizophrenia. Brain 130 (3), 693-707. Nishikawa, Y., Takahashi, T., Takayanagi, Y., Furuichi, A., Kido, M., Nakamura, M., Sasabayashi, D., Noguchi, K., Suzuki, M., 2016. Orbitofrontal sulcogyral pattern and olfactory sulcus depth in the schizophrenia spectrum. Eur. Arch. Psychiatry Clin. Neurosci. 266 (1), 15-23. Nopoulos, P., Swayze, V., Flaum, M., Ehrhardt, J.C., Yuh, W.T., Andreasen, N.C., 1997. Cavum septi pellucidi in normals and patients with schizophrenia as detected by magnetic resonance imaging. Biol. Psychiatry 41(11), 1102-1108. O'Rahilly, R., Muller, F., 1990. Ventricular system and choroid plexuses of the human brain during the embryonic period proper. Am. J. Anat. 189(4), 285–302. Pantelis, C., Yücel, M., Wood, S.J., Velakoulis, D., Sun, D., Berger, G., Stuart, G.W., Yung, A., Phillips, L., McGorry, P.D., 2005. Structural brain imaging evidence for 22

multiple pathological processes at different stages of brain development in schizophrenia. Schizophr. Bull. 31(3), 672-696. Peralta, V., Moreno-Izco, L., Sanchez-Torres, A., García de Jalón, E., Campos, M.S., Cuesta, M.J., 2014. Characterization of the deficit syndrome in drug-naive schizophrenia patients: the role of spontaneous movement disorders and neurological soft signs. Schizophr. Bull. 40(1), 214-224. Percheron, G., 2004. Thalamus, In: Paxinos, G., Mai, J.K. (Eds.), The Human Nervous System, 2nd ed. Elsevier Academic Press, California, pp. 592–675. Rakic, P., Yakovlev, P.I., 1968. Development of the corpus callosum and cavum septi in man. J. Comp. Neurol. 132(1), 45–72. Rakic, P., 1988. Specification of cerebral cortical areas. Science 241(4862), 170-176. Rhoades, H.M., Overall, J.E., 1988. The semistructured BPRS interview and rating guide. Psychopharmacol. Bull. 24(1), 101–104. Rombaux, P., Grandin, C., Duprez, T., 2009. How to measure olfactory bulb volume and olfactory sulcus depth? B-ENT 5 Suppl 13, 53-60. Rosales, R.K., Lemay, M.J., Yakovlev, P.I., 1968. The development and involution of massa intermedia with regard to age and sex. J. Neuropathol. Exp. Neurol. 27(1), 166. Rowland, L.M., Spieker, E.A., Francis, A., Barker, P.B., Carpenter, W.T., Buchanan, R.W., 2009. White matter alterations in deficit schizophrenia. Neuropsychopharmacology 34(6), 1514-1522. Roy, M.A., Maziade, M., Labbé, A., Mérette, C., 2001. Male gender is associated with deficit schizophrenia: a meta-analysis. Schizophr. Res. 47(2-3), 141-147. Shaw, C.M., Alvord Jr., E.C., 1969. Cava septi pellucidi et vergae: their normal and pathological states. Brain 92(1), 213–223. Spalletta, G., De Rossi, P., Piras, F., Iorio, M., Dacquino, C., Scanu, F., Girardi, P., Caltagirone, C., Kirkpatrick, B., Chiapponi, C., 2015. Brain white matter 23

microstructure in deficit and non-deficit subtypes of schizophrenia. Psychiatry Res. 231(3), 252-261. Strauss, G.P., Harrow, M., Grossman, L.S., Rosen, C., 2010. Periods of recovery in deficit syndrome schizophrenia: a 20-year multi-follow-up longitudinal study. Schizophr. Bull. 36(4), 788-799. Subotnik, K.L., Nuechterlein, K.H., Ventura, J., Green, M.F., Hwang, S.S., 1998. Prediction of the deficit syndrome from initial deficit symptoms in the early course of schizophrenia. Psychiatry Res. 80(1), 53-59. Takahashi, T., Suzuki, M., Hagino, H., Niu, L., Zhou, S.Y., Nakamura, K., Tanino, R., Kawasaki, Y., Seto, H., Kurachi, M., 2007. Prevalence of large cavum septi pellucidi and its relation to the medial temporal lobe structures in schizophrenia spectrum. Prog. Neuropsychopharmacol. Biol. Psychiatry 31(6), 1235-1241. Takahashi, T., Suzuki, M., Nakamura, K., Tanino, R., Zhou, S.Y., Hagino, H., Niu, L., Kawasaki, Y., Seto, H., Kurachi, M., 2008a. Association between absence of the adhesio interthalamica and amygdala volume in schizophrenia. Psychiatry Res. 162(2), 101-111. Takahashi, T., Suzuki, M., Zhou, S.Y., Nakamura, K., Tanino, R., Kawasaki, Y., Seal, M.L., Seto, H., Kurachi, M., 2008b. Prevalence and length of the adhesio interthalamica in schizophrenia spectrum disorders. Psychiatry Res. 164(1), 90-94. Takahashi, T., Yücel, M., Yung, A.R., Wood, S.J., Phillips, L.J., Berger, G.E., Ang, A., Soulsby, B., McGorry, P.D., Suzuki, M., Velakoulis, D., Pantelis, C., 2008c. Adhesio interthalamica in individuals at high-risk for developing psychosis and patients with psychotic disorders. Prog. Neuropsychopharmacol. Biol. Psychiatry 32(7), 1708-1714. Takahashi, T., Nakamura, Y., Nakamura, K., Ikeda, E., Furuichi, A., Kido, M., Kawasaki, Y., Noguchi, K., Seto, H., Suzuki, M., 2013a. Altered depth of the olfactory sulcus in first-episode schizophrenia. Prog. Neuropsychopharmacol. Biol. 24

Psychiatry 40, 167-172. Takahashi, T., Nakamura, K., Ikeda, E., Furuichi, A., Kido, M., Nakamura, Y., Kawasaki, Y., Noguchi, K., Seto, H., Suzuki, M., 2013b. Longitudinal MRI study of the midline brain regions in first-episode schizophrenia. Psychiatry Res. 212(2), 150-153. Takahashi, T., Wood, S.J., Yung, A.R., Nelson, B., Lin, A., Yücel, M., Phillips, L.J., Nakamura, Y., Suzuki, M., Brewer, W.J., Proffitt, T.M., McGorry, P.D., Velakoulis, D., Pantelis, C., 2014. Altered depth of the olfactory sulcus in ultra high-risk individuals and patients with psychotic disorders. Schizophr. Res. 153 (1-3), 18-24. Takahashi, T., Nakamura, M., Nishikawa, Y., Takayanagi, Y., Furuichi, A., Kido, M., Sasabayashi, D., Noguchi, K., Suzuki, M., 2016. Decreased number of orbital sulci in schizophrenia spectrum disorders. Psychiatry Res. 250, 29-32. Takayanagi, M., Wentz, J., Takayanagi, Y., Schretlen, D.J., Ceyhan, E., Wang, L., Suzuki, M., Sawa, A., Barta, P.E., Ratnanather, J.T., Cascella, N.G., 2013. Reduced anterior cingulate gray matter volume and thickness in subjects with deficit schizophrenia. Schizophr. Res. 150(2-3), 484-490. Takayanagi, Y., Takahashi, T., Orikabe, L., Masuda, N., Mozue, Y., Nakamura, K., Kawasaki, Y., Itokawa, M., Sato, Y., Yamasue, H., Kasai, K., Okazaki, Y., Suzuki, M., 2010. Volume reduction and altered sulco-gyral pattern of the orbitofrontal cortex in first-episode schizophrenia. Schizophr. Res. 121 (1-3), 55-65. Tomelleri, L., Jogia, J., Perlini, C., Bellani, M., Ferro, A., Rambaldelli, G., Tansella, M., Frangou, S., Brambilla, P.; Neuroimaging Network of the ECNP networks initiative, 2009. Brain structural changes associated with chronicity and antipsychotic treatment in schizophrenia. Eur. Neuropsychopharmacol. 19(12), 835-840. Trzesniak, C., Kempton, M.J., Busatto, G.F., de Oliveira, I.R., Galvão-de Almeida, A., 25

Kambeitz, J., Ferrari, M.C., Filho, A.S., Chagas, M.H., Zuardi, A.W., Hallak, J.E., McGuire, P.K., Crippa, J.A., 2011a. Adhesio interthalamica alterations in schizophrenia spectrum disorders: A systematic review and meta-analysis. Prog. Neuropsychopharmacol. Biol. Psychiatry 35(4), 877-886. Trzesniak, C., Oliveira, I.R., Kempton, M.J., Galvão-de Almeida, A., Chagas, M.H., Ferrari, M.C., Filho, A.S., Zuardi, A.W., Prado, D.A., Busatto, G.F., McGuire, P.K., Hallak, J.E., Crippa, J.A., 2011b. Are cavum septum pellucidum abnormalities more common in schizophrenia spectrum disorders? A systematic review and meta-analysis. Schizophr. Res. 125(1), 1-12. Trzesniak, C., Schaufelberger, M.S., Duran, F.L., Santos, L.C., Rosa, P.G., McGuire, P.K., Murray, R.M., Scazufca, M., Menezes, P.R., Hallak, J.E., Crippa, J.A., Busatto, G.F., 2012. Longitudinal follow-up of cavum septum pellucidum and adhesio interthalamica alterations in first-episode psychosis: a population-based MRI study. Psychol. Med. 42(12), 2523-2534. van Os, J., Kapur, S., 2009. Schizophrenia. Lancet 374(9690), 635-645. Voineskos, A.N., Foussias, G., Lerch, J., Felsky, D., Remington, G., Rajji, T.K., Lobaugh, N., Pollock, B.G., Mulsant, B.H., 2013. Neuroimaging evidence for the deficit subtype of schizophrenia. JAMA Psychiatry 70(5), 472-480. Volpe, U., Mucci, A., Quarantelli, M., Galderisi, S., Maj, M., 2012. Dorsolateral prefrontal cortex volume in patients with deficit or nondeficit schizophrenia. Prog. Neuropsychopharmacol. Biol. Psychiatry 37(2), 264-269. Wheeler, A.L., Wessa, M., Szeszko, P.R., Foussias, G., Chakravarty, M.M., Lerch, J.P., DeRosse, P., Remington, G., Mulsant, B.H., Linke, J., Malhotra, A.K., Voineskos, A.N., 2015. Further neuroimaging evidence for the deficit subtype of schizophrenia: a cortical connectomics analysis. JAMA Psychiatry 72(5), 446-455. World Health Organization, 1993. The ICD-10 Classification of Mental and Behavioural Disorders: Diagnostic Criteria for Research. World Health 26

Organization, Geneva. Zhou, S.Y., Suzuki, M., Hagino, H., Takahashi, T., Kawasaki, Y., Nohara, S., Yamashita, I., Seto, H., Kurachi, M., 2003. Decreased volume and increased asymmetry of the anterior limb of the internal capsule in patients with schizophrenia. Biol. Psychiatry 54(4), 427-436.

Figure Legends Fig. 1. Sample coronal slices showing the adhesio interthalamica (A, arrow), cavum septum pellucidum (B, arrow), and olfactory sulcus (C, colored in red). Fig. 2. Classification of the orbitofrontal sulcogyral pattern colored in red (A) and variations in the number of intermediate and posterior orbital sulci colored in yellow (B) on sample axial views of the orbitofrontal cortex. c, caudal portion; IOS, intermediate orbital sulcus; LOS, lateral orbital sulcus; MOS, medial orbital sulcus; POS, posterior orbital sulcus; r, rostral portion; TOS, transverse orbital sulcus. Fig. 3. Length of the adhesio interthalamica in the controls, non-deficit schizophrenia (Sz) and deficit Sz. Horizontal lines indicate means of each group. *p < 0.01, **p < 0.05.

Table 1. Demographic and clinical data of the controls (C), non-deficit schizophrenia (ND-Sz), and deficit schizophrenia (D-Sz) subjects. C

Age (years) Male/female Height (cm) Handedness (right/mix/left) Education (years)

(n = 59) 26.1 ± 5.1 28/31 166.1 ± 8.0 59/0/ 0 16.7 ± 2.4

ND-S z (n = 37) 27.1 ± 7.5 12/25 162.0 ± 7.3 33/4/ 0 13.3 ± 2.1

D-Sz (n = 38) 27.1 ± 6.2 22/16 165.6 ± 8.3 35/2/ 1 13.6 ± 2.1

27

Group comparisons F (2, 131) = 0.49, p = 0.611 χ2 = 4.95, p = 0.084 F (2, 131) = 3.29, p = 0.040; C, D-Sz > ND-Sz Fisher's exact test, p = 0.019 F (2, 131) = 35.19, p < 0.001; C > D-Sz, ND-Sz

Parental education (years)

13.0 ± 2.5

Age at onset (years)

-

Duration of illness (years) Duration of medication (years) Drug (mg/day, haloperidol equivalent) Drug type (atypical/mix/typical )a

12.5 ± 1.9 22.7 ± 6.6 4.2 ± 4.9 3.1 ± 4.5

12.5 ± 2.0 23.0 ± 5.3 4.1 ± 4.9 2.0 ± 2.9

-

10.5 ± 9.0

8.3 ± 7.8

F (1, 73) = 1.26, p = 0.265

-

25/2/ 10

24/1/ 11

Fisher's exact test, p = 0.923

-10.1 ± 1.8 49.5 ± 12.0

-1.8 ± F (1, 73) = 504.04, p < 0.01; D-Sz 1.4 > ND-Sz

-

PDS score

-

Total BPRS score

-

36.5 ± 9.5

SAPS Hallucinations

-

Delusions

-

Bizarre behaviour Positive formal thought disorder

-

13.5 ± 8.2 19.0 ± 9.6 5.5 ± 4.4 6.8 ± 8.9

5.3 ± 7.5 8.1 ± 8.0 4.5 ± 4.0 3.7 ± 5.6

Blunted affect

Avolition-apathy

F (1, 73) = 0.02, p = 0.876 F (1, 73) < 0.01, p = 0.954 F (1, 73) = 1.79, p = 0.185

F (1, 73) = 27.45, p < 0.01; ND-Sz > D-Sz Subscore-by-subgroup interaction; F (3, 219) = 12.58, p < 0.001 Post hoc test, p < 0.001; ND-Sz > D-Sz Post hoc test, p < 0.001; ND-Sz > D-Sz Subscore-by-subgroup interaction; F (4, 292) = 5.25, p < 0.001

SANS

Alogia

F (2, 131) = 1.18, p = 0.311

-

12.7 ± 10.3 6.9 ± 4.3 10.7 ± 4.8

16.0 ± 8.8 8.0 ± 5.6 10.8 ± 5.0

Post hoc test, p = 0.009; D-Sz > ND-Sz -

Anhedonia-asocialit y

-

12.8 ± 7.9

10.6 ± 5.8

-

Attention deficit

-

10.4 ± 4.1

7.5 ± 4.7

Post hoc test, p = 0.023; ND-Sz > D-Sz

Values represent means ± SDs unless otherwise stated. BPRS, Brief Psychiatric

28

Rating Scale; PDS, Proxy for the Deficit Syndrome; SANS, Scale for the Assessment of Negative Symptoms; SAPS, Scale for the Assessment of Positive Symptoms. a

Two patients with D-Sz were drug-näive.

Table 2. Brain measures of the controls (C), non-deficit schizophrenia (ND-Sz), and deficit schizophrenia (D-Sz) subjects.

Intracranial volume (ml) AI length (mm) AI absent; n (%) CSP length (mm) CSP volume (mm3) CSP (≥1 slice) present; n (%) Large CSP (≥6 slices) present; n (%) Left OFC Type; n (%) I II III

C 1487.2 ± 148.7

ND-Sz 1459.0 ± 150.2

D-Sz 1472.9 ± 153.2

9.2 ± 3.5

8.0 ± 3.6

6.5 ± 3.5

6 (10.7) 4.8 ± 10.5 190.5 ± 838.2 51 (88.4)

5 (13.5) 3.5 ± 8.0 132.3 ± 636.2 32 (86.5)

9 (23.7) 2.1 ± 1.4

χ2 = 3.41, p = 0.182

13.3 ± 18.2

F (2, 128) = 0.34, p = 0.714b

34 (89.5)

χ2 = 0.22, p = 0.894

8 (13.6)

2 (5.4)

1 (2.6)

Fisher's exact test, p = 0.156

II III

F (2, 129) = 1.90, p = 0.154a F (2, 128) = 8.19, p < 0.001; C > D-Sz, ND-Sz > D-Sz

F (2, 128) = 0.76, p = 0.469b

χ2 = 7.926, p = 0.094 37 (62.7) 11 (18.6) 11 (18.6)

22 (59.5) 4 (10.8) 11 (29.7)

15 (39.5) 7 (18.4) 16 (42.1) Fisher's exact test, p = 0.013c

Right OFC Type; n (%) I

Group comparisons

47 (79.7) 2 (3.4) 10 (16.9)

25 (67.6) 0 (0) 12 (32.4)

19 (50.0) 2 (5.3) 17 (44.7)

29

Fisher's exact test, p = 0.027d

Left IOS [n(%)] single double triple

19 (32.2) 30 (50.8) 10 (16.9)

16 (43.2) 20 (54.1)

17 (44.7) 21 (55.3)

1 (2.7)

0 (0) Fisher's exact test, p = 0.002d

Right IOS [n (%)] single double triple

15 (25.4) 36 (61.0) 8 (13.6)

17 (45.9) 20 (54.1) 0 (0)

21 (55.3) 17 (44.7) 0 (0) Fisher's exact test, p = 0.002d

Left POS [n (%)] absent single double

18 (30.5) 28 (47.5) 13 (22.0)

20 (54.1) 15 (40.5)

25 (65.8) 12 (31.6)

2 (5.4)

1 (2.6) Fisher's exact test, p = 0.012d

Right POS [n (%)] absent single double Olfactory sulcus depth (mm) left right

18 (30.5) 33 (55.9) 8 (13.6)

21 (56.8) 15 (40.5) 1 (2.7)

20 (52.6) 17 (44.7) 1 (2.6) F (2, 128) = 106.99, p < 0.001; C > ND-Sz, D-Sz

13.5 ± 1.1 14.4 ± 1.2

10.6 ± 1.2 10.9 ± 1.5

10.7 ± 1.6 10.8 ± 1.8

Values represent means ± SDs unless otherwise stated. AI, adhesio interthalamica; CSP, cavum septi pellucidi; IOS, intermediate orbital sulcus; OFC, orbitofrontal cortex; POS, posterior orbital sulcus. a

Age and gender were used as covariates.

b

Analyzed using log-CSP values because of their skewed distributions (p < 0.01,

Kolmogorov-Smirnov test). For the length, the skewness and kurtosis statistics 30

were 5.01 and 26.88 before transformation and 1.16 and 3.08 after transformation, respectively. For the volume, the skewness and kurtosis statistics were 7.12 and and 55.04 before transformation and 1.05 and 3.08 after transformation, respectively. increased Type III (χ2 = 8.88, p = 0.003) pattern compared with controls. c

The D-Sz group had a significantly decreased Type I (χ2= 9.35, p = 0.002) and

d

Fisher's exact tests showed that the triple-IOS and double-POS patterns were

more common in the controls than in the D-Sz (left IOS, p = 0.006; right IOS, p = 0.021; left POS, p = 0.008) and ND-Sz (left IOS, p = 0.046; right IOS, p = 0.022; left POS, p = 0.041) groups. The controls had ‘two or more IOS’ more often and absent-POS pattern less often than the D-SZ (right IOS, χ2 = 8.82, p = 0.003; left POS, χ2 = 7.23, p = 0.007; right POS, χ2 = 4.75, p = 0.029) and ND-Sz (right IOS, χ2 = 4.31, p = 0.038; right POS, χ2 = 6.50, p = 0.011) groups.

Highlights 

Deficit schizophrenia is a clinical subtype with prominent negative symptoms.



This MRI study examined gross brain morphology in deficit and non-deficit subgroups.



Deficit group had a shorter adhesio interthalamica and altered sulcogyral pattern.



Deficit subtype schizophrenia may have pervasive neurodevelopmental abnormalities.

31

A

B

R

L

C

R

L

R

L

A

R

B

32

L

Length of the adhesio interthalamica (mm)

*

20

** 15

10

5

0

Controls

Non-deficit Sz

33

Deficit Sz