Impaired insight into illness affects up to 95% of individuals with schizophrenia, depending on the stage of illness, and is a predictor of antipsychotic nonadherence and poor clinical outcomes. Despite its importance, no effective treatment exists. Interhemispheric imbalance in frontoparietal regions may serve as a biomarker of impaired insight into illness and target for transcranial direct current stimulation (tDCS). Meta-analyses suggest that sham-controlled multisession tDCS applied to frontotemporoparietal areas improves insight in schizophrenia. However, no randomized controlled tDCS trial has targeted the posterior parietal areas to improve insight into illness. We hypothesized that multisession biparietal tDCS would lead to both immediate (ie, following 2-weeks of tDCS) and sustained (ie, up to 4-weeks) improvement in insight in schizophrenia. Thirty-four participants with schizophrenia/schizoaffective disorder and impaired insight into illness were randomized to receive either active (n = 18) or sham (n = 16) biparietal tDCS (anodal/cathodal:P4/P3), administered twice daily over 10 days. Insight was assessed using the VAGUS Insight into Psychosis scale at baseline pre-treatment, post-treatment, and weekly for 4 weeks. Linear mixed-effects models compared estimated marginal mean VAGUS scores between conditions, with and without adjusting for Intelligence Quotient (IQ), illness severity, and clozapine use. Active tDCS significantly improved average VAGUS scores immediately following and up to 4 weeks post-treatment. Biparietal tDCS appears to be a promising intervention for improving insight in schizophrenia. Future research should explore its adjunctive use with medication to enhance treatment adherence.
Pre-attentive information processing deficits are associated with poor outcomes in schizophrenia. The auditory mismatch negativity (MMN), observed when an auditory signal changes, is reduced in schizophrenia, related to glutamatergic dysfunction and is considered a response biomarker. We hypothesized that glycine, an N-methyl-d-aspartate receptor (NMDAR) coagonist, could reverse the NMDAR-antagonistic effects of ketamine, which produces schizophrenia-like clinical symptoms and neurophysiological changes. Using a placebo-controlled crossover design, this 64-channel electroencephalography (EEG) study assessed psychopathological changes using the Positive and Negative Syndrome Scale (PANSS) and the 5-Dimensional Altered States of Consciousness (5D-ASC) scale in 25 participants. MMN responses to duration (dMMN) and frequency deviant tones, their underlying theta-band activity and sources, P3a, and associations were examined. Ketamine induced schizophrenia-like symptoms, and reduced MMN amplitudes, theta power, and P3a. While glycine did not modulate ketamine's effect on the (time-domain) MMN or P3a amplitude, it did prevent the effect of ketamine on dMMN-associated theta power and phase consistency. The underlying theta power was associated with auditory alterations, and elevated theta activity due to glycine pretreatment predicted a clinically relevant improvement in negative symptoms. This is the first study in humans to investigate the effects of glycine on the MMN in the ketamine model of schizophrenia. The results confirm a key role of the glutamate system for pre-attentive auditory processing deficits underlying the symptoms of schizophrenia. From a translational perspective, the MMN and its theta-band signature may serve as biomarkers to identify patients who may benefit from glutamatergic treatment options.
Accurate prediction of treatment response is essential for optimizing therapeutic strategies in patients with schizophrenia. Compared to neuroimaging or genetic biomarkers, clinical symptom patterns have received relatively little attention as predictors of treatment outcome. This study aimed to address this gap by comprehensively analyzing early symptom trajectories to predict long-term treatment outcomes. A cohort of 387 inpatients with schizophrenia during acute episodes was followed for 8 weeks of standardized antipsychotic treatment. Clinical symptom severity was assessed by Positive and Negative Syndrome Scale (PANSS) at baseline, week 2, and week 8. Using network analysis and machine learning model, we evaluated symptom patterns associated with treatment outcome and the predictive value of early clinical symptom trajectories. (1) Effective treatment responders (ETR) and poor treatment responders (PTR) exhibited distinct clinical symptom profiles at baseline and early treatment response. (2) At week 2, ETR patients showed a denser PANSS change network compared to PTR, indicating more coordinated symptom changes. (3) Early symptom change was significantly correlated with 8-week treatment outcome. (4) Although the absence of early treatment response had limited predictive value, a machine learning model based on early %PANSS change achieved 76% balanced accuracy, with changes in the negative domain emerging as key predictors. These findings highlight the distinctive symptom profiles associated with different treatment outcomes and underscore the importance of early symptom patterns in predicting 8-week responses in patients with acute schizophrenia.
Individuals with schizophrenia experience severe impairments in everyday functioning. Cognitive behavioral social skills training (CBSST) has demonstrated moderate effects on functional outcomes in controlled trials. This study examined whether CBSST, when integrated into assertive community treatment (ACT), improves daily-life functioning as assessed by ecological momentary assessment (EMA). This was a secondary analysis of a pragmatic randomized controlled trial involving 155 participants diagnosed with schizophrenia or schizoaffective disorder. Participants were randomized to receive either ACT + CBSST (n = 75) or ACT alone (n = 80). Assessments occurred at baseline, 9 months (n = 100), and 18 months (n = 67) to capture real-time reports of "productive" and "non-productive" activities. The primary outcome was productive activity. Secondary outcomes included non-productive activity, the productive/non-productive activity ratio, anhedonia, and defeatist beliefs. Linear mixed models were used to test for differential changes over time between groups. Although the groups differed at baseline, the ACT + CBSST group showed significantly greater improvements over time relative to the ACT group in productive activities, the productive/non-productive activity ratio, and in reductions in anhedonia and defeatist beliefs. However, between-group differences at follow-up were not statistically significant. Adding CBSST to ACT may yield greater improvements in daily-life functioning than ACT alone. While these results support the potential added value of integrating CBSST into routine care, further research is needed to confirm its superiority. Together with the companion report from this study, these findings suggest that EMA may offer a sensitive approach for detecting changes in real-world functioning in clinical trials.Trial Registration: ClinicalTrials.gov (NCT02254733; https://clinicaltrials.gov/).
Schizophrenia (SZ) is a debilitating mental disorder characterized by heterogeneous clinical manifestations and widespread brain structural abnormalities. However, the relationship between individual neuroanatomical abnormalities and clinical symptoms remains inconsistent. We hypothesize that isolating SZ-specific neuroanatomical variations could deepen our understanding of its pathophysiology and yield more reliable biomarkers for its clinical heterogeneity. To investigate this, we developed DECODE-SZ (Dual Encoder Contrastive Decoding for Schizophrenia), a novel model combining contrastive learning, 3D convolutional neural networks, and variational autoencoders (VAE) to isolate SZ-specific neuroanatomical features. We applied this model to structural MRI data from 641 patients diagnosed with SZ and 609 healthy controls across 8 independent sites in China, employing a leave-one-site-out cross-validation approach to ensure robust and unbiased results. Our analysis focused on examining the relationship between SZ-specific gray matter alterations and clinical symptoms (measured by PANSS scores), while also considering non-clinical variables such as age, sex, and education. The DECODE-SZ model successfully extracted SZ-specific gray matter features, revealing that these features, rather than common variations with controls, were more strongly associated with PANSS scores. Consistent brain regions exhibiting these alterations were identified across multiple sites, supporting the reliability of the findings. A control experiment using a traditional VAE model demonstrated the superior performance of DECODE-SZ in isolating meaningful SZ-specific neuroanatomical variations. Our findings highlight the potential of SZ-specific neuroanatomical alterations as key biomarkers for clinical outcomes in SZ. DECODE-SZ offers a promising tool for advancing the understanding of SZ and may inform future diagnostic and therapeutic strategies.
Metabolic syndrome (MetS) is a major risk factor for cardiovascular disease in schizophrenia (SCZ), yet its metabolic underpinnings, particularly in chronic SCZ, remain unclear. This study investigated plasma metabolic profiles and their associations with clinical features in chronic SCZ. We recruited 374 chronic SCZ patients (222 with MetS, 152 without MetS). Plasma metabolomic profiling was conducted using ultra-high-performance liquid chromatography-high resolution mass spectrometry. Data were analyzed with orthogonal partial least squares discriminant analysis and receiver operating characteristic curves. Psychopathology and cognition were evaluated via the Positive and Negative Symptom Scale and the Repeatable Battery for the Assessment of Neuropsychological Status, respectively. Metabolomic profiling revealed 37 metabolites significantly altered in MetS among chronic SCZ (variable importance projection > 1.5 and P-false discovery rate < .05). Pathway enrichment highlighted glycerophospholipid metabolism (impact = 0.1404, P<.001) and ascorbate/aldarate metabolism (impact = 0.5238, P = .044) as key contributors. A diagnostic panel comprising 12-Hydroxystearic acid (FFA (18:0-OH)) and 2-Aminoheptanoic acid, both fatty acid derivatives, showed moderate predictive accuracy for MetS (area under the curve = 0.713, 95% confidence interval = 0.660-0.765). Importantly, these fatty acids were also linked to the severity of negative symptoms and memory deficits in SCZ patients without MetS (all P<.05). Specific fatty acid metabolites may serve as early biomarkers for MetS in chronic SCZ and provide mechanistic links to negative symptoms and cognitive deficits, particularly in individuals without the syndrome. Glycerophospholipid and ascorbate/aldarate metabolism are identified as the primary affected pathways in schizophrenia (SCZ) with metabolic syndrome (MetS). 12-Hydroxystearic acid (FFA (18:0-OH)) and 2-Aminoheptanoic acid demonstrated diagnostic potential for MetS. Fatty acids were linked to the severity of negative symptoms and memory impairment in SCZ without MetS.
Xanomeline and trospium chloride (formerly KarXT) is a muscarinic M1 and M4 receptor agonist recently approved for the treatment of schizophrenia in adults. Unlike all previously approved antipsychotics, it does not directly block dopamine D2 receptors. Given its novel mechanism of action, understanding patients' subjective treatment experiences, including perceived symptom changes, is clinically important. This is a qualitative study embedded within a larger 52-week open-label long-term safety study that investigated patient perspectives on xanomeline/trospium monotherapy in clinically stable outpatients transitioned from previous antipsychotic treatments. A subsample completed up to 2 semi-structured interviews to explore their experience-favorable or unfavorable-approximately 6 weeks (n = 70) and 6 months (n = 47) post-initiation. Thematic analysis was applied to interview transcripts. At study entry, most participants reported symptoms despite ongoing antipsychotic treatment, including positive (auditory hallucinations, >80%), negative (low motivation, >70%), and cognitive (trouble concentrating, >70%) symptoms. Over 60% reported meaningful improvement in one or more symptoms within 6 weeks of starting xanomeline/trospium, increasing to about 80% by 6 months. Less than 10% reported symptom worsening at either time point. Participants described these improvements as personally meaningful, with notable benefits in daily functioning. Participants entered this study with various persistent, burdensome schizophrenia symptoms despite ongoing treatment. Most experienced substantial and sustained symptom relief for up to 6 months after initiating xanomeline/trospium treatment. These qualitative findings highlight xanomeline/trospium's potential to provide meaningful relief across multiple symptom domains and support functional recovery. A companion report explores quality of life and medication satisfaction.
Perception integrates sensory input with prior knowledge. Alterations in how both information sources are combined may lead to the departures from consensus reality that characterize schizophrenia (SZ). One source of prior knowledge is recent experience. Visual aftereffects-perceptions of the "opposite" of previously viewed stimulus-are driven by neuronal adaptation and demonstrate how recent experience influences perception. Our recent work revealed stronger tilt (orientation) aftereffects, but not negative afterimages (luminance aftereffects) in people with SZ relating to negative symptom severity, suggesting altered adaptation is more prominent in cortical than subcortical visual systems and may be an important illness mechanism. Because different aftereffects depend differentially on adaptation at different levels of the visual hierarchy, we sought to extend findings and probe where in the cortical hierarchy neuronal adaptation is most pronounced in SZ. Two types of motion aftereffects were measured in SZ (n = 55) and healthy controls (HC; n = 43): "first-order" aftereffects caused by luminance-defined motion that elicits strong adaptation in early visual cortex, and "higher-order" aftereffects caused by non-luminance-feature-defined motion (eg, texture) that is primarily represented in extrastriate motion-sensitive areas. Relative to HC, SZ showed stronger first-order but not higher-order motion aftereffects. Differences were not explained by task sensitivity, response bias, visual acuity, blinks, or fixation deviations. Altered neuronal adaptation in SZ is likely more pronounced at earlier (eg, V1) versus later (eg, V5/MT) stages of the visual hierarchy. Consequently, findings potentially implicate early visual cortical processing alterations in illness pathophysiology and/or clinical presentation.
Auditory hallucinations (AHs) are debilitating symptoms of schizophrenia spectrum disorders (SSDs) associated with several negative outcomes. AHs are often resistant to existing pharmacological and psychological interventions. Virtual reality (VR) has emerged as a promising intervention for AHs. This systematic review and meta-analysis aimed to assess the effectiveness of VR interventions in treating AHs in SSDs. A comprehensive literature search was conducted on Embase, APA PsycINFO, and MEDLINE via the Ovid Database. Studies with a randomized controlled trial (RCT) or randomized cross-over trial design that had treatment and active or treatment-as-usual control conditions were included. Random-effects meta-analyses compared the change in the primary outcome of AH severity from baseline to post-treatment and at follow-up between the groups. Eight studies (n = 1004) met the criteria for the meta-analyses. Eight studies used avatar therapy (AT), and 1 study used a VR-based mindfulness intervention. Random-effects meta-analyses found that VR interventions were more effective than the control conditions in reducing AH severity immediately post-intervention (Hedges' g = -0.41, 95% CI [-0.62, -0.20], P < .01) and at follow-up (Hedges' g = -0.28, 95% CI [-0.40, -0.17], P < .001). This review was limited by a small sample size, study heterogeneity, and intervention homogeneity. Future research should prioritize larger RCTs of VR-based interventions for psychosis before VR can be reliably used in clinical settings. Overall, the results of this meta-analysis suggest that VR-based AT may be a promising avenue to improve AHs in SSDs.
Auditory verbal hallucinations (AVH) are hypothesized to result from failures in corollary discharge mechanisms to correctly predict self-initiated inner speech. However, the role of motor preparation in inner speech, during which sensorimotor predictions are formed, remains unclear. This study aimed to test the hypothesis by examining the relationship between AVH and an electrophysiological marker of action preparation: the contingent negative variation (CNV). Participants completed an electroencephalographic paradigm. In the Active condition, they imagined an inner syllable at a cued moment coinciding with the presentation of an audible syllable. In the Passive condition, participants passively listened to audible syllables. The amplitude of the late CNV preceding inner speech production was compared with that associated with passive listening across 3 groups: (1) schizophrenia spectrum patients with current AVH (SZAVH+, n = 58), (2) schizophrenia spectrum patients without current AVH (SZAVH-, n = 50), and (3) healthy controls (HC, n = 49). The HC group showed a more negative late CNV in the Active condition compared with the Passive condition. In contrast, the SZAVH+ and SZAVH- groups showed positive-going slow cortical potentials in both conditions, with less positivity in the Active condition in the former. This pattern significantly predicted AVH status. These findings provide evidence of motor preparation dysfunction during inner speech in schizophrenia spectrum disorders. The distinct pattern of deficits observed in hallucinators may reflect imprecise corollary discharges theorized to underlie some AVH. Premovement neural indices may provide a novel window into abnormalities in prediction formation.
People with schizophrenia (SCZ) show characteristic impairments in semantic cognition, yet the cognitive mechanisms underlying these patterns remain unclear. Here, we propose a unified mechanistic account in which semantic retrieval is constrained by limitations in internal attention. Specifically, we approximate semantic space as a network of interconnected concepts and posit two attentional control parameters: representational precision (resolution; the ability to distinguish nearby concepts) and the size of the attended field (the subset of semantic space prioritized). We hypothesize that attentional constraints in SCZ reduce precision and/or narrow the attended field, yielding complementary, theoretically predicted patterns of semantic search. We first constructed a directed semantic graph using a large sample of individuals performing the animal Category Fluency Test (CFT). We then used this network as a normative reference to analyze fluency-derived paths from SCZ and control participants. Relative to controls, CFT paths in the SCZ group showed increased reliance on abstract, category-level structure, and reduced exploration radius. These patterns align with compensatory strategies predicted by the proposed mechanism: reliance on coarse-grained structure when resolution is limited, and restriction of traversal when the effective attended field is narrow. The findings support an attention-constrained retrieval account rather than a stochastic retrieval deficit, indicating that group-level semantic retrieval differences in SCZ may arise from reduced representational resolution and/or a narrowed attended field. These results highlight the value of considering internal attention mechanisms when interpreting semantic impairments in SCZ, with potential connections to attentional phenotypes of ADHD/ADD.
Schizophrenia (SZ) is characterized by excitation-inhibition (E-I) imbalance as a core pathophysiological feature, but its molecular underpinnings remain elusive. Susceptibility gene Roundabout2 (Robo2), which regulates E-I balance in the central nervous system, may play a critical role in the pathogenesis of SZ by contributing to this dysregulation. We conducted a transcriptomic analysis of Robo2 in postmortem brain tissues from patients with SZ and controls using the GEO/GSE datasets. The plasma levels of Robo2 were quantified in clinical cohorts via ELISA. We assessed the correlation between plasma Robo2 levels and clinical assessments (Positive and Negative Syndrome Scale [PANSS] and MATRICS Consensus Cognitive Battery [MCCB]) or neurophysiological measures (functional near-infrared spectroscopy [fNIRS] and event-related potentials). Rats with hippocampal Robo2 knockdown underwent comprehensive behavioral, electrophysiological, and ultrastructural (Golgi staining) assessments. Proteomic sequencing with pathway enrichment analysis was conducted to identify downstream molecular mediators. Hippocampal and plasma Robo2 expression were significantly downregulated in patients with SZ. The plasma levels of Robo2 were inversely correlated with PANSS scores and positively associated with MCCB performance. Neurophysiological correlations revealed positive associations between Robo2 and dorsolateral prefrontal cortex activation (fNIRS and P300 peak amplitude). Robo2-deficient rats exhibited anxiety-like behaviors, cognitive impairments, social withdrawal, and sensory gating abnormalities, accompanied by decreased dendritic spine density and increased hippocampal field potential power. Proteomics identified disrupted GABAergic/glutamatergic synaptic pathways, with neurexin-3 (Nrxn3) downregulation emerging as a potential downstream candidate. Our findings established Robo2-Nrxn3 deficiency as a potential molecular hub linking E-I imbalance to SZ-associated behavioral and neurophysiological deficits, highlighting novel therapeutic targets for E-I modulation.
Identifying reliable diagnostic biomarkers in catatonia remains a key challenge to improve early intervention and reduce morbidity and mortality. Since its pathophysiology may involve cortical dysconnectivity, electroencephalography (EEG) could provide accessible disease-associated measures, such as power spectral density (PSD), peak alpha frequency (PAF), and C and D microstates. However, EEG is yet to be used for this purpose. This study is a case-control retrospective transdiagnostic hospital-based cohort. We analyzed resting-state EEG data from patients diagnosed with schizophrenia or mood disorders, both with (n = 102) and without (n = 519) catatonia. Linear regression models assessed associations between catatonia status and PSD, PAF, and microstates, adjusting for age, sex, medication (computed as olanzapine, fluoxetine, and diazepam equivalents), and comorbid neurodevelopmental or neurological conditions. Patients with catatonia showed increased delta power (T = 2.37, PFDR = .03), decreased alpha power (T = -3.55, PFDR = .002) and increased gamma power (T = 3.14, PFDR = .008), reduced PAF (T = -2.60, P = .03), and longer mean duration of microstate C (T = 2.17, P = .03). Routine clinical EEG revealed quantitative neurophysiological differences between patients with and without catatonia in a transdiagnostic population with psychotic and mood disorders. PSD, alpha peak frequency, and microstate anomalies in catatonia shed light on its underlying pathophysiology, suggesting a probable neurodevelopmentally-related excitation/inhibition dysregulation. Importantly, this indicates that routine clinical EEG could be used for diagnostic biomarker development, which would ultimately improve early detection and treatment.
Working memory (WM) deficits are a core cognitive impairment in schizophrenia (SCZ). High-definition transcranial direct current stimulation (HD-tDCS) targeting the dorsolateral prefrontal cortex (DLPFC) has shown promise for improving WM, yet biomarkers indicating its efficacy remain limited. We hypothesized that HD-tDCS would enhance WM in SCZ and that changes in transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) metrics can serve as potential biomarkers of treatment response. Sixty-three SCZ patients were randomized to receive either active (n = 32) or sham (n = 31) HD-tDCS. WM was assessed using the accuracy (ACC) and reaction time (RT) of the 2-back task before and after the 20-day intervention. TMS-EEG was conducted before and after the first HD-tDCS session to measure cortical responses. Changes in global mean field amplitude (GMFA) components were analyzed for their association with WM improvement. Active HD-tDCS significantly improved ACC (P<.001) and reduced RT (P<.001), whereas performance remained unchanged in the sham (all P>.05). A single session of active HD-tDCS reduced the N45 amplitude (P=.038), with no significant differences observed in the sham (all P>.05). The N45 reduction correlated with the ACC improvement (r = -0.452, P=.009). Stepwise regression confirmed the N45 reduction as a significant contributor of ACC improvement (β = -0.03, t = -2.15, P=.040). HD-tDCS effectively improved WM in SCZ patients. Reduction in N45 amplitude may serve as a neurophysiological marker of HD-tDCS treatment response.
Executive function (EF) impairments are often seen in mental disorders, particularly schizophrenia (SZ), where they relate to adverse outcomes. As a heterogeneous construct, how specifically each dimension of EF to characterize the diagnostic and prognostic aspects of SZ remains opaque. We used classification models with a stacking approach on systematically measured EFs using 6 tasks to discriminate 195 patients with SZ from healthy individuals. Baseline EF measurements were moreover employed to predict symptomatically remitted or non-remitted prognostic subgroups. EF feature importance was determined at the group-level and the ensuing individual importance scores were associated with 4 symptom dimensions. The models highlighted the importance of inhibitory control (interference and response inhibitions) or working memory (WM) in accurately identifying individuals with SZ (area under the curve [AUC] = 0.87) or those in remission (AUC = 0.81). Patients who are correctly classified, in the association with the contribution of interference inhibition function to our diagnostic classifier, present more severe baseline negative symptoms compared to those who are more likely to be misclassified. Also, linked to the function of WM updating, patients who are successfully classified as remitted display milder cognitive symptoms at follow-up. Remitted patients do not differ significantly from non-remitted cases in baseline EF assessments or overall symptom severity. Our work indicates that impairments in specific EF dimensions in SZ are differentially linked to individual symptom-load and prognostic outcomes. Thus, assessments and models based on EF may be promising in the clinical evaluation of this disorder.
Shared clinical features and genetic factors in schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD) have led to the hypothesis of common pathophysiological mechanisms. This study aims to elucidate aberrant transdiagnostic structural covariance patterns across these disorders employing a multivariate analytical approach. Structural magnetic resonance imaging data were acquired from a sample of 704 subjects, comprising 244 healthy controls, 119 first-episode treatment-naïve SCZ individuals, 159 BD individuals, and 182 treatment-naïve MDD individuals. Seed-based partial least squares correlation analysis was applied to construct structural covariance networks (SCNs) across 6 predefined functional networks: the default mode network (DMN), dorsal attention network (DAN), frontoparietal control network (FPCN), somatomotor network (SMN), ventral attention network (VAN), and visual network. Network seeds were selected based on functional network definitions. Spatial distributions of SCNs were calculated, and individual network integrity indices were derived as measures of SCN strength. Group comparisons of network integrity were performed using multiple t-tests to identify network-specific alterations across the diagnostic groups. Structural covariance patterns exhibited spatial distributions akin to those of functional networks. Network integrity showed common reductions across all 3 disorders in DMN, DAN, and FPCN, while BD showed specific reductions in the SMN, and both BD and MDD showed reductions in the VAN. Furthermore, there was a significant correlation between individualized network integrity and clinical and cognitive manifestations. Our results highlight the potential of the integrity of SCNs as transdiagnostic biomarkers.
Altered cortical folding is a well-established finding in schizophrenia spectrum disorders (SSD). Patients with SSD have been hypothesized to exhibit an accelerated decline in age-related cortical folding, quantified with the local gyrification index (LGI). Here, we assessed longitudinal and cross-sectional LGI differences in patients with chronic SSD relative to healthy controls across 13 years. The sample comprised patients with SSD (mean baseline age = 41.28 years) and healthy controls (mean baseline age = 41.56 years), with magnetic resonance imaging acquisitions at baseline (103 SSD patients and 99 controls) and follow-up after 5 (50 SSD patients and 57 controls) and 13 years (42 SSD patients and 60 controls). T1-weighted images were processed with the longitudinal pipeline in FreeSurfer. Spatiotemporal linear mixed-effects models were used to test for longitudinal and cross-sectional case-control differences in LGI, as well as the impact of symptom severity and antipsychotic medication dose among patients. Although cross-sectional LGI was lower in patients in extensive frontal, parietal, and occipital regions, we observed no significant differences in longitudinal trajectories between patients and controls after FDR correction. Medication dose was linked cross-sectionally to lower LGI of the anterior cingulate, orbitofrontal cortex, and postcentral gyrus. In the longest longitudinal study on cortical folding in SSD patients to date, we found no evidence for accelerated progressive decline in cortical folding. Rather, chronic SSD appears to be characterized by a state of stable hypogyria relative to healthy controls, consistent with the interpretation of LGI as a marker of early gyrification disturbances in SSD.
Obesity is prevalent among schizophrenia (SZ) patients receiving long-term antipsychotic treatment, yet a subset of patients remains lean or maintains a normal weight. While prior studies have linked the gut microbiome to antipsychotic-induced weight gain, its role in maintaining weight stability among non-obese SZ patients remains largely unexplored. We recruited 177 participants for the discovery cohort, including chronically antipsychotic-treated SZ patients with or without obesity, as well as healthy controls (HCs) matched by weight status. Additionally, we enrolled 20 first-episode, drug-naïve SZ (FSZ) patients with normal weight to assess their weight changes during one year of antipsychotic treatment. Fecal 16S rRNA sequencing, combined with untargeted metabolomics, was conducted to characterize gut microbiota and metabolite profiles in non-obese SZ patients, and to investigate their association with antipsychotic-induced weight changes. In total, 15 bacterial genera were identified. Among them, the genera Bacteroides, Dialister, and Pseudomonas exhibited the lowest abundance in non-obese SZ patients, whereas the genus Oscillospira showed the highest abundance. Notably, Desulfovibrio was more abundant in non-obese SZ patients and HCs than in their obese counterparts. This microbial profile was accompanied by enhanced tryptophan metabolism. In FSZ patients, higher baseline levels of Desulfovibrio were linked to less weight gain after 1 year of antipsychotic treatment. Moreover, Desulfovibrio abundance correlated positively with fecal indoleacetic acid levels and inversely with serum tryptophan concentrations. These findings suggest a potential protective role of genus Desulfovibrio against antipsychotic-induced weight gain, possibly through modulation of tryptophan metabolism.
People who hear voices may have strong prior expectations of speech, so that noisy auditory signals are resolved as speech. Data in non-clinical voice hearers suggest that voice hearing may involve sensitivity to speech in degraded stimuli. This has yet to be examined in people with schizophrenia (SZ). In this case-control study, we presented sine-wave-speech (SWS; made by replacing the formants in speech with pure tone whistles) to people with SZ (n = 63) and healthy controls (HC; n = 27). SWS is typically unintelligible on first exposure. However, once the listener knows that it is potentially intelligible as speech (by exposure to the unaltered speech template, which thus serves as a prior expectation), relatively high levels of comprehension are achieved. Our participants first listened to intelligible and unintelligible SWS and reported whether they heard speech. They were then exposed to the speech templates, and then the first phase was repeated. Compared to HC, people with SZ reported hearing more speech before template exposure. The Reveal increased both groups' false alarms and reporting of speech, but there was no interaction with group. Change in hit rates after the Reveal correlated with hallucinations, which is consistent with a greater influence of the priors enhancement in SZ patients who hear voices. These findings suggest that people with SZ have stronger expectations of speech. This task has validity for hallucinatory voice hearing. It is also simple and convenient to administer, and may prove useful in detecting prodromal risk, as well as acute exacerbation in voice hearing.
Schizo-obsessive comorbidity (SOC), defined as obsessive-compulsive symptoms (OCS) in schizophrenia (SCZ), is linked to severe psychopathology and poor prognosis. Schizophrenia and obsessive-compulsive disorder (OCD) share cognitive impairments, particularly in inhibition and cognitive flexibility, which may underlie SOC. However, little is known regarding the underlying neural mechanisms of SOC. We aimed to directly compare the inhibition- and cognitive flexibility-related neural activations between patients with SOC, SCZ, OCD, and healthy controls (HCs). Twenty-eight patients with SOC, 33 SCZ patients, 30 OCD patients, and 33 HCs undertook fMRI while performing the combined shifting go/no-go task. We analyzed the shifting-related (shift vs go) and stopping-related (no-go vs go) activations among the different diagnostic groups. Compared to HCs, the 3 clinical groups showed significant shifting-related hypoactivation in the left postcentral gyrus, left paracentral lobule, left supplementary motor area, and right superior frontal gyrus, with SOC exhibiting significantly lower activation than SCZ and OCD patients. Regarding stopping, OCD patients showed significant hyperactivation in the left precuneus compared with SCZ patients and HCs. Like OCD patients, SOC patients also exhibited greater hyperactivation than SCZ patients. Behaviorally, SOC and SCZ patients made significantly more commission errors than OCD patients, with SCZ also having more commission errors than HCs. Furthermore, SOC and SCZ made more shifting errors than HCs; and SOC made more shifting errors than SCZ and OCD patients. All 3 clinical groups shared cognitive inflexibility. Moreover, the presence of the 2 features appears to amplify the neural alterations, implicating "additive effects."