Orbitofrontal-Striatal Structural Alterations Linked to Negative Symptoms at Different Stages of the Schizophrenia Spectrum

Comparison of Negative Symptom Network Structures Between Patients With Early and Chronic Schizophrenia: A Network and Exploratory Graph Analysis

BACKGROUND AND HYPOTHESIS

Despite the clinical relevance of negative symptoms in schizophrenia, our understanding of negative symptoms remains limited. Although various courses and stages of schizophrenia have been identified, variations in the negative symptom networks between distinct stages of schizophrenia remain unexplored.

STUDY DESIGN

We examined 405 patients with early schizophrenia (ES) and 330 patients with chronic schizophrenia (CS) using the Scale for the Assessment of Negative Symptoms. Network analysis and exploratory graph analysis were used to identify and compare the network structures and community memberships of negative symptoms between the two groups. Further, associations between communities and social functioning were evaluated. The potential influences of other symptom domains and confounding factors were also examined.

STUDY RESULTS

Multidimensional differences were found in the networks of negative symptoms between ES and CS. The global connectivity strength was higher in the network of ES than in the network of CS. In ES, central symptoms were mainly related to expressive deficits, whereas in CS they were distributed across negative symptom domains. A three-community structure was suggested across stages but with different memberships and associations with social functioning. Potential confounding factors and symptom domains, including mood, positive, disorganization, and excitement symptoms, did not affect the network structures.

CONCLUSION

Our findings revealed the presence of stage-specific network structures of negative symptoms in schizophrenia, with negative symptom communities having differential significance for social functioning. These findings provide implications for the future development of tailored interventions to alleviate negative symptoms and improve functionality across stages.

A Hidden Mark of a Troubled Past: Neuroimaging and Transcriptomic Analyses Reveal Interactive Effects of Maternal Immune Activation and Adolescent THC Exposure Suggestive of Increased Neuropsychiatric Risk

Background

Maternal exposure to infections during gestation has been shown to predispose individuals to neuropsychiatric disorders. Additionally, clinical data suggest that cannabis use may trigger the onset of schizophrenia in vulnerable individuals. However, the direction of causality remains unclear.

Methods

To elucidate this issue, we utilized a rat model of maternal immune activation combined with exposure to increasing doses of Δ9-tetrahydrocannabinol during adolescence in both male and female rats. We investigated several behaviors in adulthood relevant for neuropsychiatric disorders, including impairments in working memory, deficits in sensorimotor gating, alterations in social behavior, anhedonia, and potential changes in implicit learning (conditioned taste aversion). Furthermore, we conducted a longitudinal positron emission tomography study to target affected brain regions and, subsequently, collected brain samples of one such region (the orbitofrontal cortex) for RNA sequencing analyses, which were also performed on peripheral blood mononuclear cells to identify peripheral biomarkers.

Results

While adolescent Δ9-tetrahydrocannabinol did not unmask latent behavioral disruptions, positron emission tomography scans revealed several brain alterations dependent on the combination of both hits. Additionally, the transcriptomic studies demonstrated that maternal immune activation affected dopaminergic, glutamatergic, and serotoninergic genes, with the combination of both exposures in most cases shifting the expression from downregulation to upregulation. In peripheral cells, interactive effects were observed on inflammatory pathways, and some genes were proposed as biomarkers.

Conclusions

These results suggest that the combination of these 2 vulnerability factors leaves a lasting mark on the body, potentially predisposing individuals to neuropsychiatric disorders even before behavioral alterations manifest.

Thinning of the temporal and insular cortex is associated with negative symptoms and impaired attention in Chinese chronic schizophrenia patients with deficit syndrome

BACKGROUND

The considerable clinical heterogeneity of schizophrenia poses significant challenges for elucidating its neurobiology. The concept of deficit schizophrenia (DS) is a valuable framework for addressing the heterogeneity of schizophrenia. Growing evidence suggests notable differences between deficit (DS) and nondeficit (NDS) schizophrenia, indicating that DS could represent a separate disease entity.

METHODS

We aimed to use FreeSurfer to identify specific changes in cortical thickness among NDS patients and healthy controls (HCs) in a Chinese sample. Furthermore, we examined the potential relationships between changes in cerebral cortical thickness and negative symptoms and attention deficits in DS patients. A total of 142 subjects (48 HCs, 50 NDSs, and 44 DSs) underwent MRI scans and completed the assessment of psychopathological severity and cognitive performance.

RESULTS

Compared with HCs, DS and NDS patients presented common cortical thinning in the right insula, whereas cortical thinning in the left supramarginal cortex was more prominent in DS patients. We also found that thinning of the temporal and insular cortex was correlated with negative symptoms and impaired attention in DS patients.

CONCLUSIONS

Cortical thinning in specific brain regions in DS patients was found to be correlated with specific clinical and cognitive symptoms.

The study on agitation and structure of orbitofrontal cortex subregion in first-episode drug-naïve patients with schizophrenia

Agitation is one of the core symptoms of schizophrenia. The occurrence of agitation may be related to orbitofrontal cortex dysfunction. However, due to methodological heterogeneity, the relationship between agitation and orbitofrontal cortex subregions remains unclear. Based on the multi-dimensional structure of the orbitofrontal cortex subregion, this study aims to explore the relationship between orbitofrontal cortex structure and agitation in first-episode drug-naïve patients with schizophrenia. The study subjects included 50 first-episode drug-naïve patients with schizophrenia and 29 healthy controls. All participants underwent structure magnetic resonance imaging scanning. The patients' clinical symptoms were assessed using the Positive and Negative Syndrome Scale, and the agitation were evaluated using the Brief Agitation Rating Scale. SPSS 26.0 was used to compare the differences in the orbitofrontal cortex subregion between the two groups in different structure dimensions and then conduct a Pearson's partial correlations analysis to observe the relationship between orbitofrontal cortex subregion structure and agitation. There were no significant differences in demographic factors between the two groups. Our results show the folding index of the orbitofrontal cortex subregion in patients with schizophrenia were significantly smaller compared to the healthy controls. The surface area in the orbitofrontal cortex subregion is significantly negatively correlated with agitation in first-episode drug-naïve schizophrenia patients. These results suggest that structure alterations in the orbitofrontal cortex subregion may be involved in schizophrenia agitation.

Orbitofrontal cortex hypergyrification in hallucinating schizophrenia patients: Surface ratio as a promising brain biomarker

The study of brain gyrification may provide useful information on the cytoarchitecture and connectivity of the brain. One of the methods that have been developed to estimate brain gyrification, known as surface ratio (SR), has not yet been studied in schizophrenia. Here we aimed to assess whether SR could provide new insights on the brain structure of schizophrenia patients and the severity of symptoms. We also computed a more established brain gyrification measure, namely absolute mean curvature (AMC). We analyzed 63 magnetic resonance images, 25 from schizophrenia patients with treatment-resistant auditory verbal hallucinations (SCH-H), 18 from schizophrenia patients without hallucinations (SCH-NH), and 20 from healthy controls (HC). The SR measure revealed that SCH-H patients had a more folded orbitofrontal cortex than SCH-NH patients and HC. Gyrification in this region was also negatively associated with positive symptoms, specifically with the delusions and conceptual disorganization items, only in the SCH-H group. Regarding the AMC measure, we identified two areas where HC showed more gyrification than SCH-H patients, but no relationships arose with symptoms. The hypergyrification of the orbitofrontal cortex displayed by SCH-H patients, as captured by the SR measure, suggests aberrant and/or excessive wiring in these patients, which in turn could give rise to auditory verbal hallucinations. Alternatively, we comment on potential compensatory mechanisms that may better explain the negative association between orbitofrontal gyrification and positive symptomatology. The SR measure captured the most relevant differences and associations, making it a promising biomarker in schizophrenia.

Prediction of anhedonia in patients with first-episode schizophrenia using a Wavelet-ALFF-based Support vector regression model

Anhedonia is one of the core features of the negative symptoms of schizophrenia and can be extremely burdensome. Our study applied resting-state functional magnetic resonance imaging (fMRI)-based support vector regression (SVR) to predict anhedonia in patients with first-episode schizophrenia (FES) and analysed the correlation between the wavelet-based amplitude low-frequency fluctuation (wavelet-ALFF) of the main brain region and anhedonia. We recruited 31 patients with FES and 33 healthy controls (HCs) from the Affiliated Brain Hospital of Guangzhou Medical University. All subjects completed the Temporal Experience of Pleasure Scale (TEPS) and received resting-state fMRI (rs-fMRI). We used the wavelet-ALFF method and SVR to analyse the data. Patients with FES had lower consummatory pleasure scores than healthy subjects (t = -2.71, P<0.01). FES displays variable wavelet-ALFF in a wide range of cerebral cortices (P<0.05, GFR corrected). The SVR analysis showed that wavelet-ALFF, based primarily on the right putamen (r = 0.40, P<0.05) and right superior occipital gyrus (r = -0.39, P<0.05), was effective in predicting consummatory pleasure scores with an accuracy of 56.43 %. Our study shows that abnormal spontaneous neural activity in FES may be related to the state of consummatory anhedonia in FES. Wavelet-ALFF changes in the right putamen and superior occipital gyrus may be a biological feature of FES with anhedonia and could serve as a potential biological marker of FES with anhedonia.

Abnormal Global Cortical Responses in Drug-Naïve Patients With Schizophrenia Following Orbitofrontal Cortex Stimulation: A Concurrent Transcranial Magnetic Stimulation-Electroencephalography Study

BACKGROUND

Abnormalities in cortical excitability and plasticity have been considered to underlie the pathophysiology of schizophrenia. Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) can provide a direct evaluation of cortical responses to TMS. Here, we employed TMS-EEG to investigate cortical responses to orbitofrontal cortex (OFC) stimulation in schizophrenia.

METHODS

In total, we recruited 92 drug-naïve patients with first-episode schizophrenia and 51 age- and sex-matched healthy individuals. For each participant, one session of 1-Hz repetitive TMS (rTMS) was delivered to the right OFC, and TMS-EEG data were obtained to explore the change in cortical-evoked activities before and immediately after rTMS during the eyes-closed state. The MATRICS Consensus Cognitive Battery was used to assess neurocognitive performance.

RESULTS

The cortical responses indexed by global mean field amplitudes (i.e., P30, N45, and P60) were larger in patients with schizophrenia than in healthy control participants at baseline. Furthermore, after one session of 1-Hz rTMS over the right OFC, the N100 amplitude was significantly reduced in the healthy control group but not in the schizophrenia group. In the healthy control participants, there was a significant correlation between modulation of P60 amplitude by rTMS and working memory; however, this correlation was absent in patients with schizophrenia.

CONCLUSIONS

Aberrant global cortical responses following right OFC stimulation were found in patients with drug-naïve first-episode schizophrenia, supporting its significance in the primary pathophysiology of schizophrenia.

Distinct Volume Alterations of Thalamic Nuclei Across the Schizophrenia Spectrum

BACKGROUND AND HYPOTHESIS

Abnormal thalamic nuclei volumes and their link to cognitive impairments have been observed in schizophrenia. However, whether and how this finding extends to the schizophrenia spectrum is unknown. We hypothesized a distinct pattern of aberrant thalamic nuclei volume across the spectrum and examined its potential associations with cognitive symptoms.

STUDY DESIGN

We performed a FreeSurfer-based volumetry of T1-weighted brain MRIs from 137 healthy controls, 66 at-risk mental state (ARMS) subjects, 89 first-episode psychosis (FEP) individuals, and 126 patients with schizophrenia to estimate thalamic nuclei volumes of six nuclei groups (anterior, lateral, ventral, intralaminar, medial, and pulvinar). We used linear regression models, controlling for sex, age, and estimated total intracranial volume, both to compare thalamic nuclei volumes across groups and to investigate their associations with positive, negative, and cognitive symptoms.

STUDY RESULTS

We observed significant volume alterations in medial and lateral thalamic nuclei. Medial nuclei displayed consistently reduced volumes across the spectrum compared to controls, while lower lateral nuclei volumes were only observed in schizophrenia. Whereas positive and negative symptoms were not associated with reduced nuclei volumes across all groups, higher cognitive scores were linked to lower volumes of medial nuclei in ARMS. In FEP, cognition was not linked to nuclei volumes. In schizophrenia, lower cognitive performance was associated with lower medial volumes.

CONCLUSIONS

Results demonstrate distinct thalamic nuclei volume reductions across the schizophrenia spectrum, with lower medial nuclei volumes linked to cognitive deficits in ARMS and schizophrenia. Data suggest a distinctive trajectory of thalamic nuclei abnormalities along the course of schizophrenia.

Neurostructural subgroup in 4291 individuals with schizophrenia identified using the subtype and stage inference algorithm

Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal 'trajectory' of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

Mindfulness-based interventions for patients with schizophrenia spectrum disorders: A systematic review of the literature

BACKGROUND

Mindfulness-based interventions (MBIs) have emerged as secular practices, including elements of mindfulness-based stress reduction (MBSR) and mindfulness-based cognitive therapy (MBCT). While MBIs have been widely adopted for physical and mental illness, only a few available programs are explicitly adapted for psychosis. However, previous reviews have reported the vital heterogeneity regarding treatment program structure. Therefore, this review aims to compare the structure of different mindfulness protocols applied to patients with schizophrenia spectrum disorder (SSD).

METHODS

A systematic search was conducted up to March 2023 in PubMed, Embase and PsycInfo. Following our protocol (CRD 42023253356), we followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) checklist.

RESULTS

We included 22 randomized controlled trials (RCTs) involving 1500 patients SSD. All programs varied in structure, session components, duration, and instructor experience. While MBSR-like programs focused on stress reactivity, MBCT-like programs addressed primary symptoms of psychosis and relapse prevention. Despite the heterogeneity of programs, some common mechanisms emerged, including attention training, emotion and stress regulation, decentering, self-compassion, and cognitive restructuring.

CONCLUSIONS

The critical heterogeneity found limits the interpretation of results. However, most recent trials present fewer risks of bias and more homogenous programs. Findings suggested potential benefits, such as reduced negative symptoms, increased well-being, and decreased hospitalization rates. For future studies, authors should align on more congruent MBIs programs for patients with SSD. Further research is needed to identify optimal mindfulness teaching approaches for patients with psychosis and investigate specific mechanisms of action, relevant processes, and optimal doses in varying settings.

A neuromarker for deficit syndrome in schizophrenia from a combination of structural and functional magnetic resonance imaging

AIM

Deficit schizophrenia (DS), defined by primary and enduring negative symptoms, has been proposed as a promising homogeneous subtype of schizophrenia. It has been demonstrated that unimodal neuroimaging characteristics of DS were different from non-deficit schizophrenia (NDS), however, whether multimodal-based neuroimaging features could identify deficit syndrome remains to be determined.

METHODS

Functional and structural multimodal magnetic resonance imaging of DS, NDS and healthy controls were scanned. Voxel-based features of gray matter volume, fractional amplitude of low-frequency fluctuations, and regional homogeneity were extracted. The support vector machine classification models were constructed using these features separately and jointly. The most discriminative features were defined as the first 10% of features with the greatest weights. Moreover, relevance vector regression was applied to explore the predictive values of these top-weighted features in predicting negative symptoms.

RESULTS

The multimodal classifier achieved a higher accuracy (75.48%) compared with the single modal model in distinguishing DS from NDS. The most predictive brain regions were mainly located in the default mode and visual networks, exhibiting differences between functional and structural features. Further, the identified discriminative features significantly predicted scores of diminished expressivity factor in DS but not NDS.

CONCLUSIONS

The present study demonstrated that local properties of brain regions extracted from multimodal imaging data could distinguish DS from NDS with a machine learning-based approach and confirmed the relationship between distinctive features and the negative symptoms subdomain. These findings may improve the identification of potential neuroimaging signatures and improve the clinical assessment of the deficit syndrome.

Basal-Forebrain Cholinergic Nuclei Alterations are Associated With Medication and Cognitive Deficits Across the Schizophrenia Spectrum

BACKGROUND AND HYPOTHESIS

The cholinergic system is altered in schizophrenia. Particularly, patients' volumes of basal-forebrain cholinergic nuclei (BFCN) are lower and correlated with attentional deficits. It is unclear, however, if and how BFCN changes and their link to cognitive symptoms extend across the schizophrenia spectrum, including individuals with at-risk mental state for psychosis (ARMS) or during first psychotic episode (FEP).

STUDY DESIGN

To address this question, we assessed voxel-based morphometry (VBM) of structural magnetic resonance imaging data of anterior and posterior BFCN subclusters as well as symptom ratings, including cognitive, positive, and negative symptoms, in a large multi-site dataset (n = 4) comprising 68 ARMS subjects, 98 FEP patients (27 unmedicated and 71 medicated), 140 patients with established schizophrenia (SCZ; medicated), and 169 healthy controls.

RESULTS

In SCZ, we found lower VBM measures for the anterior BFCN, which were associated with the anticholinergic burden of medication and correlated with patients' cognitive deficits. In contrast, we found larger VBM measures for the posterior BFCN in FEP, which were driven by unmedicated patients and correlated at-trend with cognitive deficits. We found no BFCN changes in ARMS. Altered VBM measures were not correlated with positive or negative symptoms.

CONCLUSIONS

Results demonstrate complex (posterior vs. anterior BFCN) and non-linear (larger vs. lower VBM) differences in BFCN across the schizophrenia spectrum, which are specifically associated both with medication, including its anticholinergic burden, and cognitive symptoms. Data suggest an altered trajectory of BFCN integrity in schizophrenia, influenced by medication and relevant for cognitive symptoms.

Psychometric properties of the Clinical Assessment Interview for Negative Symptoms (CAINS) in patients with depression and its relationship to affective symptoms

BACKGROUND

There is a conceptual overlap between negative and depressive symptoms, requiring further exploration to advance the understanding of negative symptoms. The aim of this study was to examine psychometric properties of the Clinical Assessment Interview for Negative Symptoms (CAINS) in patients with depression, and to explore the relationship between the negative and affective symptoms domains.

METHODS

Fifty-one patients with a depressive episode were included and interviewed with the CAINS and the Brief Psychiatric Rating Scale-Expanded (BPRS-E). Self-reported depressive symptoms were collected with the Montgomery-Asberg Depression Rating Scale (MADRS-S). Inter-rater agreement, internal consistency and validity measures were examined, as were correlations between negative and affective symptoms.

RESULTS

The intraclass correlation for the CAINS motivation and pleasure subscale (CAINS-MAP) was 0.98 (95% CI 0.96-0.99) and that for the expressional subscale (CAINS-EXP) was 0.81 (95% CI 0.67-0.89). Cronbach's alpha was 0.71 (95% CI 0.57-0.82) for the CAINS-MAP and 0.86 (95% CI 0.79-0.92) for the CAINS-EXP. The correlation with the negative symptoms subscale of the BPRS-E was 0.35 (p = 0.011, blinded/different raters) or 0.55 (p < 0.001, not blinded/same rater). The CAINS-MAP correlated with the affective symptoms subscale of the BPRS-E (r = 0.39, p = 0.005) and the MADRS-S total score (r = 0.50, p < 0.001), but not with anxiety symptoms.

CONCLUSIONS

Negative symptoms in depression can be assessed with the CAINS with good inter-rater agreement and acceptable internal consistency and validity. There are associations between negative and depressive symptoms that call for further exploration.

Two neurostructural subtypes: results of machine learning on brain images from 4,291 individuals with schizophrenia

Machine learning can be used to define subtypes of psychiatric conditions based on shared clinical and biological foundations, presenting a crucial step toward establishing biologically based subtypes of mental disorders. With the goal of identifying subtypes of disease progression in schizophrenia, here we analyzed cross-sectional brain structural magnetic resonance imaging (MRI) data from 4,291 individuals with schizophrenia (1,709 females, age=32.5 years±11.9) and 7,078 healthy controls (3,461 females, age=33.0 years±12.7) pooled across 41 international cohorts from the ENIGMA Schizophrenia Working Group, non-ENIGMA cohorts and public datasets. Using a machine learning approach known as Subtype and Stage Inference (SuStaIn), we implemented a brain imaging-driven classification that identifies two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter (GM) loss in schizophrenia. Subgroup 1 (n=2,622) was characterized by an early cortical-predominant loss (ECL) with enlarged striatum, whereas subgroup 2 (n=1,600) displayed an early subcortical-predominant loss (ESL) in the hippocampus, amygdala, thalamus, brain stem and striatum. These reconstructed trajectories suggest that the GM volume reduction originates in the Broca's area/adjacent fronto-insular cortex for ECL and in the hippocampus/adjacent medial temporal structures for ESL. With longer disease duration, the ECL subtype exhibited a gradual worsening of negative symptoms and depression/anxiety, and less of a decline in positive symptoms. We confirmed the reproducibility of these imaging-based subtypes across various sample sites, independent of macroeconomic and ethnic factors that differed across these geographic locations, which include Europe, North America and East Asia. These findings underscore the presence of distinct pathobiological foundations underlying schizophrenia. This new imaging-based taxonomy holds the potential to identify a more homogeneous sub-population of individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

Deficits in Key Brain Network for Social Interaction in Individuals with Schizophrenia

Individuals with schizophrenia (SZ) show impairment in social functioning. The reward network and the emotional salience network are considered to play important roles in social interaction. The current study investigated alterations in the resting-state (rs-) amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo) and functional connectivity (fc) in the reward network and the emotional salience network in SZ patients. MRI scans were collected from 60 subjects, including 30 SZ patients and 30 matched healthy controls. SZ symptoms were measured using the Positive and Negative Syndrome Scale (PANSS). We analyzed the ALFF, fALFF and ReHo in key brain regions in the reward network and emotional salience network as well as rs-fc among the bilateral amygdala, lateral orbitofrontal cortex (OFC), medial OFC and insula between groups. The SZ patients demonstrated increased ALFF in the right caudate and right putamen, increased fALFF and ReHo in the bilateral caudate, putamen and pallidum, along with decreased fALFF in the bilateral insula. Additionally, reduced rs-fc was found between the right lateral OFC and the left amygdala, which simultaneously belong to the reward network and the emotional salience network. These findings highlight the association between impaired social functioning in SZ patients and aberrant resting-state ALFF, fALFF, ReHo and fc. Future studies are needed to conduct network-based statistical analysis and task-state fMRI, reflecting live social interaction to advance our understanding of the mechanism of social interaction deficits in SZ.

Negative symptoms in First-Episode Schizophrenia related to morphometric alterations in orbitofrontal and superior temporal cortex: the OPTiMiSE study

BACKGROUND

Negative symptoms are one of the most incapacitating features of Schizophrenia but their pathophysiology remains unclear. They have been linked to alterations in grey matter in several brain regions, but findings have been inconsistent. This may reflect the investigation of relatively small patient samples, and the confounding effects of chronic illness and exposure to antipsychotic medication. We sought to address these issues by investigating concurrently grey matter volumes (GMV) and cortical thickness (CTh) in a large sample of antipsychotic-naïve or minimally treated patients with First-Episode Schizophrenia (FES).

METHODS

T1-weighted structural MRI brain scans were acquired from 180 antipsychotic-naïve or minimally treated patients recruited as part of the OPTiMiSE study. The sample was stratified into subgroups with (N = 88) or without (N = 92) Prominent Negative Symptoms (PMN), based on PANSS ratings at presentation. Regional GMV and CTh in the two groups were compared using Voxel-Based Morphometry (VBM) and FreeSurfer (FS). Between-group differences were corrected for multiple comparisons via Family-Wise Error (FWE) and Monte Carlo z-field simulation respectively at p < 0.05 (2-tailed).

RESULTS

The presence of PMN symptoms was associated with larger left inferior orbitofrontal volume (p = 0.03) and greater CTh in the left lateral orbitofrontal gyrus (p = 0.007), but reduced CTh in the left superior temporal gyrus (p = 0.009).

CONCLUSIONS

The findings highlight the role of orbitofrontal and temporal cortices in the pathogenesis of negative symptoms of Schizophrenia. As they were evident in generally untreated FEP patients, the results are unlikely to be related to effects of previous treatment or illness chronicity.

Neuroanatomical subtypes of schizophrenia and relationship with illness duration and deficit status

BACKGROUND

The heterogeneity of schizophrenia (SCZ) regarding psychopathology, illness trajectory and their inter-relationships with underlying neural substrates remain incompletely understood. In a bid to reduce illness heterogeneity using neural substrates, our study aimed to replicate the findings of an earlier study by Chand et al. (2020). We employed brain structural measures for subtyping SCZ patients, and evaluate each subtype's relationship with clinical features such as illness duration, psychotic psychopathology, and additionally deficit status.

METHODS

Overall, 240 subjects (160 SCZ patients, 80 healthy controls) were recruited for this study. The participants underwent brain structural magnetic resonance imaging scans and clinical rating using the Positive and Negative Syndrome Scale. Neuroanatomical subtypes of SCZ were identified using "Heterogeneity through discriminative analysis" (HYDRA), a clustering technique which accounted for relevant covariates and the inter-group normalized percentage changes in brain volume were also calculated.

RESULTS

As replicated, two neuroanatomical subtypes (SG-1 and SG-2) were found amongst our patients with SCZ. The subtype SG-1 was associated with enlargements in the third and lateral ventricles, volume increase in the basal ganglia (putamen, caudate, pallidum), longer illness duration, and deficit status. The subtype SG-2 was associated with reductions of cortical and subcortical structures (hippocampus, thalamus, basal ganglia).

CONCLUSIONS

These replicated findings have clinical implications in the early intervention, response monitoring, and prognostication of SCZ. Future studies may adopt a multi-modal neuroimaging approach to enhance insights into the neurobiological composition of relevant subtypes.

Cortical and subcortical neuroanatomical signatures of schizotypy in 3004 individuals assessed in a worldwide ENIGMA study

Neuroanatomical abnormalities have been reported along a continuum from at-risk stages, including high schizotypy, to early and chronic psychosis. However, a comprehensive neuroanatomical mapping of schizotypy remains to be established. The authors conducted the first large-scale meta-analyses of cortical and subcortical morphometric patterns of schizotypy in healthy individuals, and compared these patterns with neuroanatomical abnormalities observed in major psychiatric disorders. The sample comprised 3004 unmedicated healthy individuals (12-68 years, 46.5% male) from 29 cohorts of the worldwide ENIGMA Schizotypy working group. Cortical and subcortical effect size maps with schizotypy scores were generated using standardized methods. Pattern similarities were assessed between the schizotypy-related cortical and subcortical maps and effect size maps from comparisons of schizophrenia (SZ), bipolar disorder (BD) and major depression (MDD) patients with controls. Thicker right medial orbitofrontal/ventromedial prefrontal cortex (mOFC/vmPFC) was associated with higher schizotypy scores (r = 0.067, p_FDR = 0.02). The cortical thickness profile in schizotypy was positively correlated with cortical abnormalities in SZ (r = 0.285, p_spin = 0.024), but not BD (r = 0.166, p_spin = 0.205) or MDD (r = -0.274, p_spin = 0.073). The schizotypy-related subcortical volume pattern was negatively correlated with subcortical abnormalities in SZ (rho = -0.690, p_spin = 0.006), BD (rho = -0.672, p_spin = 0.009), and MDD (rho = -0.692, p_spin = 0.004). Comprehensive mapping of schizotypy-related brain morphometry in the general population revealed a significant relationship between higher schizotypy and thicker mOFC/vmPFC, in the absence of confounding effects due to antipsychotic medication or disease chronicity. The cortical pattern similarity between schizotypy and schizophrenia yields new insights into a dimensional neurobiological continuity across the extended psychosis phenotype.

White Matter Network Disruption Is Associated With Melancholic Features in Major Depressive Disorder

BACKGROUND

The efficacy and prognosis of major depressive disorder (MDD) are limited by its heterogeneity. MDD with melancholic features is an important subtype of MDD. The present study aimed to reveal the white matter (WM) network changes in melancholic depression.

MATERIALS AND METHODS

Twenty-three first-onset, untreated melancholic MDD, 59 non-melancholic MDD patients and 63 health controls underwent diffusion tensor imaging (DTI) scans. WM network analysis based on graph theory and support vector machine (SVM) were used for image data analysis.

RESULTS

Compared with HC, small-worldness was reduced and abnormal node attributes were in the right orbital inferior frontal gyrus, left orbital superior frontal gyrus, right caudate nucleus, right orbital superior frontal gyrus, right orbital middle frontal gyrus, left rectus gyrus, and left median cingulate and paracingulate gyrus of MDD patients. Compared with non-melancholic MDD, small-worldness was reduced and abnormal node attributes were in right orbital inferior frontal gyrus, left orbital superior frontal gyrus and right caudate nucleus of melancholic MDD. For correlation analysis, the 7th item score of the HRSD-17 (work and interest) was positively associated with increased node betweenness centrality (aBC) values in right orbital inferior frontal gyrus, while negatively associated with the decreased aBC in left orbital superior frontal gyrus. SVM analysis results showed that abnormal aBC in right orbital inferior frontal gyrus and left orbital superior frontal gyrus showed the highest accuracy of 81.0% (69/83), the sensitivity of 66.3%, and specificity of 85.2% for discriminating MDD patients with or without melancholic features.

CONCLUSION

There is a significant difference in WM network changes between MDD patients with and without melancholic features.