Task-based functional neural correlates of social cognition across autism and schizophrenia spectrum disorders.

BACKGROUND: Autism and schizophrenia spectrum disorders (SSDs) both feature atypical social cognition. Despite evidence for comparable group-level performance in lower-level emotion processing and higher-level mentalizing, limited research has examined the neural basis of social cognition across these conditions. Our goal was to compare the neural correlates of social cognition in autism, SSDs, and typically developing controls (TDCs). METHODS: Data came from two harmonized studies in individuals diagnosed with autism or SSDs and TDCs (aged 16-35 years), including behavioral social cognitive metrics and two functional magnetic resonance imaging (fMRI) tasks: a social mirroring Imitate/Observe (ImObs) task and the Empathic Accuracy (EA) task. Group-level comparisons, and transdiagnostic analyses incorporating social cognitive performance, were run using FSL's PALM for each task, covarying for age and sex (1000 permutations, thresholded at p < 0.05 FWE-corrected). Exploratory region of interest (ROI)-based analyses were also conducted. RESULTS: ImObs and EA analyses included 164 and 174 participants, respectively (autism N = 56/59, SSD N = 50/56, TDC N = 58/59). EA and both lower- and higher-level social cognition scores differed across groups. While canonical social cognitive networks were activated, no significant whole-brain or ROI-based group-level differences in neural correlates for either task were detected. Transdiagnostically, neural activity during the EA task, but not the ImObs task, was associated with lower- and higher-level social cognitive performance. LIMITATIONS: Despite attempting to match our groups on age, sex, and race, significant group differences remained. Power to detect regional brain differences is also influenced by sample size and multiple comparisons in whole-brain analyses. Our findings may not generalize to autism and SSD individuals with co-occurring intellectual disabilities. CONCLUSIONS: The lack of whole-brain and ROI-based group-level differences identified and the dimensional EA brain-behavior relationship observed across our sample suggest that the EA task may be well-suited to target engagement in novel intervention testing. Our results also emphasize the potential utility of cross-condition approaches to better understand social cognition across autism and SSDs.

Multivariate Association between Functional Connectivity Gradients and Cognition in Schizophrenia Spectrum Disorders.

BACKGROUND: Schizophrenia Spectrum Disorders (SSDs), which are characterized by social cognitive deficits, have been associated with dysconnectivity in "unimodal" (e.g., visual, auditory) and "multimodal" (e.g., default-mode and frontoparietal) cortical networks. However, little is known regarding how such dysconnectivity relates to social and non-social cognition, and how such brain-behavioral relationships associate with clinical outcomes of SSDs. METHODS: We analyzed cognitive (non-social and social) measures and resting-state functional magnetic resonance imaging data from the 'Social Processes Initiative in Neurobiology of the Schizophrenia(s) (SPINS)' study (247 stable participants with SSDs and 172 healthy controls, ages 18-55). We extracted gradients from parcellated connectomes and examined the association between the first 3 gradients and the cognitive measures using partial least squares correlation (PLSC). We then correlated the PLSC dimensions with functioning and symptoms in the SSDs group. RESULTS: The SSDs group showed significantly lower differentiation on all three gradients. The first PLSC dimension explained 68.53% (p<.001) of the covariance and showed a significant difference between SSDs and Controls (bootstrap p<.05). PLSC showed that all cognitive measures were associated with gradient scores of unimodal and multimodal networks (Gradient 1), auditory, sensorimotor, and visual networks (Gradient 2), and perceptual networks and striatum (Gradient 3), which were less differentiated in SSDs. Furthermore, the first dimension was positively correlated with negative symptoms and functioning in the SSDs group. CONCLUSIONS: These results suggest a potential role of lower differentiation of brain networks in cognitive and functional impairments in SSDs.

Prebiotic Treatment in People With Schizophrenia.

BACKGROUND: Preliminary evidence suggests that people with schizophrenia have decreased relative abundance of butyrate-producing bacteria in the gut microbiota. Butyrate plays a critical role in maintaining the integrity of the gut-blood barrier and has a number of anti-inflammatory effects. This proof-of-concept study was designed to assess whether the addition of the oligofructose-enriched inulin (OEI) prebiotic: Prebiotin could increase the production of butyrate. METHODS: Twenty-seven people who met the criteria for either Diagnostic and Statistical Manual of Mental Disorders, 5th Edition, schizophrenia or schizoaffective disorder were entered into a 10-day, double-blind, placebo-controlled, randomized clinical trial. The study was conducted on an inpatient unit to standardize the participant diet and environment. Participants were randomized to either OEI (4 g, 3 times a day) or a placebo (4 g of maltodextrin, 3 times a day). In order to assess the effect of OEI treatment on butyrate levels, participants underwent pretreatment and posttreatment OEI challenges. The primary outcome measure was relative change in postchallenge plasma butyrate levels after 10 days of OEI treatment. RESULTS: In both the intent-to-treat and completer analyses, OEI treatment was associated with a greater number of participants who met the OEI challenge responder criteria than those treated with placebo. OEI treatment was also associated with an increase in baseline butyrate levels (effect size for the group difference in the change of baseline butyrate levels was 0.58). CONCLUSIONS: We were able to demonstrate that treatment with the prebiotic OEI selectively increased the level of plasma butyrate in people with schizophrenia.Trial registration:ClinicalTrials.gov identifier NCT03617783.

Transdiagnostic Neurobiology of Social Cognition and Individual Variability as Measured by Fractional Amplitude of Low-Frequency Fluctuation in Schizophrenia and Autism Spectrum Disorders.

Fractional amplitude of low-frequency fluctuation (fALFF) is a validated measure of resting-state spontaneous brain activity. Previous fALFF findings in autism and schizophrenia spectrum disorders (ASDs and SSDs) have been highly heterogeneous. We aimed to use fALFF in a large sample of typically developing control (TDC), ASD and SSD participants to explore group differences and relationships with inter-individual variability of fALFF maps and social cognition. fALFF from 495 participants (185 TDC, 68 ASD, and 242 SSD) was computed using functional magnetic resonance imaging as signal power within two frequency bands (i.e., slow-4 and slow-5), normalized by the power in the remaining frequency spectrum. Permutation analysis of linear models was employed to investigate the relationship of fALFF with diagnostic groups, higher-level social cognition, and lower-level social cognition. Each participant's average distance of fALFF map to all others was defined as a variability score, with higher scores indicating less typical maps. Lower fALFF in the visual and higher fALFF in the frontal regions were found in both SSD and ASD participants compared with TDCs. Limited differences were observed between ASD and SSD participants in the cuneus regions only. Associations between slow-4 fALFF and higher-level social cognitive scores across the whole sample were observed in the lateral occipitotemporal and temporoparietal junction. Individual variability within the ASD and SSD groups was also significantly higher compared with TDC. Similar patterns of fALFF and individual variability in ASD and SSD suggest some common neurobiological deficits across these related heterogeneous conditions.

Functional phenotypes in schizophrenia spectrum disorders: defining the constructs and identifying biopsychosocial correlates using data-driven methods.

Functional impairments contribute to poor quality of life in schizophrenia spectrum disorders (SSD). We sought to (Objective I) define the main functional phenotypes in SSD, then (Objective II) identify key biopsychosocial correlates, emphasizing interpretable data-driven methods. Objective I was tested on independent samples: Dataset I (N = 282) and Dataset II (N = 317), with SSD participants who underwent assessment of multiple functioning areas. Participants were clustered based on functioning. Objective II was evaluated in Dataset I by identifying key features for classifying functional phenotype clusters from among 65 sociodemographic, psychological, clinical, cognitive, and brain volume measures. Findings were replicated across latent discriminant analyses (LDA) and one-vs.-rest binomial regularized regressions to identify key predictors. We identified three clusters of participants in each dataset, demonstrating replicable functional phenotypes: Cluster 1-poor functioning across domains; Cluster 2-impaired Role Functioning, but partially preserved Independent and Social Functioning; Cluster 3-good functioning across domains. Key correlates were Avolition, anhedonia, left hippocampal volume, and measures of emotional intelligence and subjective social experience. Avolition appeared more closely tied to role functioning, and anhedonia to independent and social functioning. Thus, we found three replicable functional phenotypes with evidence that recovery may not be uniform across domains. Avolition and anhedonia were both critical but played different roles for different functional domains. It may be important to identify critical functional areas for individual patients and target interventions accordingly.

Bayesian Optimization of Neurostimulation (BOONStim).

BACKGROUND: Transcranial magnetic stimulation (TMS) treatment response is influenced by individual variability in brain structure and function. Sophisticated, user-friendly approaches, incorporating both established functional magnetic resonance imaging (fMRI) and TMS simulation tools, to identify TMS targets are needed. OBJECTIVE: The current study presents the development and validation of the Bayesian Optimization of Neuro-Stimulation (BOONStim) pipeline. METHODS: BOONStim uses Bayesian optimization for individualized TMS targeting, automating interoperability between surface-based fMRI analytic tools and TMS electric field modeling. Bayesian optimization performance was evaluated in a sample dataset (N=10) using standard circular and functional connectivity-defined targets, and compared to grid optimization. RESULTS: Bayesian optimization converged to similar levels of total electric field stimulation across targets in under 30 iterations, converging within a 5% error of the maxima detected by grid optimization, and requiring less time. CONCLUSIONS: BOONStim is a scalable and configurable user-friendly pipeline for individualized TMS targeting with quick turnaround.

Heterogeneity in functional connectivity: Dimensional predictors of individual variability during rest and task fMRI in psychosis.

BACKGROUND: Individuals with schizophrenia spectrum disorders (SSD) often demonstrate cognitive impairments, associated with poor functional outcomes. While neurobiological heterogeneity has posed challenges when examining social cognition in SSD, it provides a unique opportunity to explore brain-behavior relationships. The aim of this study was to investigate the relationship between individual variability in functional connectivity during resting state and the performance of a social task and social and non-social cognition in a large sample of controls and individuals diagnosed with SSD. METHODS: Neuroimaging and behavioral data were analyzed for 193 individuals with SSD and 155 controls (total n = 348). Individual variability was quantified through mean correlational distance (MCD) of functional connectivity between participants; MCD was defined as a global 'variability score'. Pairwise correlational distance was calculated as 1 - the correlation coefficient between a given pair of participants, and averaging distance from one participant to all other participants provided the mean correlational distance metric. Hierarchical regressions were performed on variability scores derived from resting state and Empathic Accuracy (EA) task functional connectivity data to determine potential predictors (e.g., age, sex, neurocognitive and social cognitive scores) of individual variability. RESULTS: Group comparison between SSD and controls showed greater SSD MCD during rest (p = 0.00038), while no diagnostic differences were observed during task (p = 0.063). Hierarchical regression analyses demonstrated the persistence of a significant diagnostic effect during rest (p = 0.008), contrasting with its non-significance during the task (p = 0.50), after social cognition was added to the model. Notably, social cognition exhibited significance in both resting state and task conditions (both p = 0.01). CONCLUSIONS: Diagnostic differences were more prevalent during unconstrained resting scans, whereas the task pushed participants into a more common pattern which better emphasized transdiagnostic differences in cognitive abilities. Focusing on variability may provide new opportunities for interventions targeting specific cognitive impairments to improve functional outcomes.

Tobacco smoking and nicotine vaping in persons with first episode psychosis.

Tobacco smoking is highly prevalent in persons with psychosis and is the leading cause of preventable mortality in this population. Less is known about tobacco smoking in persons with first episode psychosis (FEP) and there have been no estimates about the prevalence of nicotine vaping in FEP. This study reports rates of tobacco smoking and nicotine vaping in young people with FEP enrolled in Coordinated Specialty Care programs in Pennsylvania and Maryland. Using data collected from 2021 to 2023, we examined lifetime and recent smoking and vaping and compared smokers and vapers to nonusers on symptoms, functioning, and substance use. The sample included 445 participants aged 13-35 with recent psychosis onset. Assessments were collected by program staff. Overall, 28 % of participants engaged in either smoking or vaping within 30 days of the admission assessment. Smokers and vapers were disproportionately male, cannabis users, and had lower negative symptom severity than non-smokers. Vapers had higher role and social functioning. Both smoking and vaping were related to a longer time from psychosis onset to program enrollment. We compare these findings to previous studies and suggest steps for addressing smoking and vaping in this vulnerable population.

Functional magnetic resonance imaging in schizophrenia: current evidence, methodological advances, limitations and future directions.

Functional neuroimaging emerged with great promise and has provided fundamental insights into the neurobiology of schizophrenia. However, it has faced challenges and criticisms, most notably a lack of clinical translation. This paper provides a comprehensive review and critical summary of the literature on functional neuroimaging, in particular functional magnetic resonance imaging (fMRI), in schizophrenia. We begin by reviewing research on fMRI biomarkers in schizophrenia and the clinical high risk phase through a historical lens, moving from case-control regional brain activation to global connectivity and advanced analytical approaches, and more recent machine learning algorithms to identify predictive neuroimaging features. Findings from fMRI studies of negative symptoms as well as of neurocognitive and social cognitive deficits are then reviewed. Functional neural markers of these symptoms and deficits may represent promising treatment targets in schizophrenia. Next, we summarize fMRI research related to antipsychotic medication, psychotherapy and psychosocial interventions, and neurostimulation, including treatment response and resistance, therapeutic mechanisms, and treatment targeting. We also review the utility of fMRI and data-driven approaches to dissect the heterogeneity of schizophrenia, moving beyond case-control comparisons, as well as methodological considerations and advances, including consortia and precision fMRI. Lastly, limitations and future directions of research in the field are discussed. Our comprehensive review suggests that, in order for fMRI to be clinically useful in the care of patients with schizophrenia, research should address potentially actionable clinical decisions that are routine in schizophrenia treatment, such as which antipsychotic should be prescribed or whether a given patient is likely to have persistent functional impairment. The potential clinical utility of fMRI is influenced by and must be weighed against cost and accessibility factors. Future evaluations of the utility of fMRI in prognostic and treatment response studies may consider including a health economics analysis.

Relapse in clinically stable adult patients with schizophrenia or schizoaffective disorder: evidence-based criteria derived by equipercentile linking and diagnostic test accuracy meta-analysis.

BACKGROUND: There is no consensus on defining relapse in schizophrenia, and scale-derived criteria with unclear clinical relevance are widely used. We aimed to develop an evidence-based scale-derived set of criteria to define relapse in patients with schizophrenia or schizoaffective disorder. METHODS: We searched the Yale University Open Data Access (YODA) for randomised controlled trials (RCTs) in clinically stable adults with schizophrenia or schizoaffective disorder, and obtained individual participant data on Positive and Negative Syndrome Scale (PANSS), Clinical Global Impression Severity (CGI-S), Personal and Social Performance (PSP), and Social and Occupational Functioning Assessment Scale (SOFAS). Our main outcomes were PANSS-derived criteria based on worsening in PANSS total score. We examined their relevance using equipercentile linking with CGI-S and functioning scales, and their test-performance in defining relapse with diagnostic test accuracy meta-analysis against CGI-S worsening (≥1-point increase together with a score ≥4 points) and psychiatric hospitalisation. FINDINGS: Based on data from seven RCTs (2354 participants; 1348 men [57·3%] and 1006 women [42·7%], mean age of 39·5 years [SD 12·0, range 17-89]; 303 Asian [12.9%], 255 Black [10.8%], 1665 White [70.7%], and other or unspecified 131 [5.6%]), an increase of 12 points or more in PANSS total (range 30-210 points) corresponded to clinically important deterioration in global severity of illness (≥1 point increase in CGI-S, range 1-7) and functioning (≥10 points decline in PSP or SOFAS, range 1-100). The interpretation of percentage changes varied importantly across different baseline scores. An increase of 12 points or more in PANSS total had good sensitivity and specificity using CGI-S as reference standard (sensitivity 82·1% [95% CI 77·1-86·4], specificity 86·9% [82·9-90·3]), as well as good sensitivity but lower specificity compared to hospitalisation (sensitivity 81·7% [74·1-87·7], specificity 69·2% [60·5-76·9]). Requiring either an increase in PANSS total or in specific items for positive and disorganization symptoms further improved test-performance. Cutoffs for situations where high sensitivity or specificity is needed are presented. INTERPRETATION: An increase of either 12 points or more in the PANSS total score, or worsening of specific positive and disorganisation symptom items could be a reasonable evidence-based definition of relapse in schizophrenia, potentially linking symptoms used to define remission and relapse. Percentage changes should not be used to define relapse because their interpretation depends on baseline scores. FUNDING: German Research Foundation (grant number: 428509362).

Potential Role of Smartphone Technology in Advancing Work on Neurological Soft Signs with a Focus on Schizophrenia.

LEARNING OBJECTIVE AFTER PARTICIPATING IN THIS CME ACTIVITY, THE PSYCHIATRIST SHOULD BE BETTER ABLE TO: • Outline and Identify potential benefits of using neurological soft signs (NSS) as biomarkers of schizophrenia. ABSTRACT: Since the late 1960s, NSS have been a focus of study across psychiatric illnesses, including depression, bipolar disorder, and schizophrenia in particular. Utilizing these subtle neurological impairments as biomarkers of illness has numerous benefits; NSS offer a direct connection between clinical presentation and neurological functioning, and assessments are cost-effective. However, incongruent measurement scales, confounding variables, and rating system subjectivity have hindered the advancement and scalability of NSS research and clinical implementation. This article provides a brief overview of the literature on NSS as related to schizophrenia, and proposes utilizing smartphone sensing technology to create standardized NSS assessments with objective scoring. Incorporating digital phenotyping into NSS assessment offers the potential to make measurement more scalable, accessible, and directly comparable across locations, cultures, and demographics. We conducted a narrative search in PubMed and APA PsycInfo using the following keywords: neurological soft signs, schizophrenia spectrum disorders, and psychotic illnesses. No date limitations were used. There is no other direct work on NSS and new smartphone methods like digital phenotyping; though, there is related work in neurology. Harnessing advances in smartphone technology could provide greater insight into and further our understanding of specific aspects of the NSS field. For instance, it could help us distinguish trait vs. state markers and better understand how distinct groups of signs may reflect different aspects of psychiatric illness and neurological impairment. In addition, such technology can help advance research on the capabilities of NSS as an effective diagnostic tool.

Clozapine and neutrophil response in patients of African descent: A six-month, multinational, prospective, open-label clinical trial.

INTRODUCTION: Clozapine is the most effective antipsychotic for treatment-resistant schizophrenia, but it is markedly underutilized, particularly in the US Black population, partly because of concern over clozapine-associated low absolute neutrophil count (ANC). People of African descent have a lower normative ANC range than the White population, which is associated with a specific "ACKR1-null" ("Duffy null") CC genotype (SNP rs2814778) on the ACKR1 gene, termed benign ethnic neutropenia (BEN). The range of ANC variability and safety of clozapine have not been established in people with BEN or examined prospectively in people of African descent. METHODS: We completed a multisite, 6-month, prospective, open-label clinical trial of clozapine treatment in people of African descent with schizophrenia spectrum disorders for whom clozapine was clinically indicated, with or without the ACKR1-null genotype. We examined clozapine safety and weekly ANC during clozapine treatment and evaluated ANC variability by ACKR1-null genotype, sex, study site, and clozapine dosing using repeated measures analysis of covariance. Genotype was assayed using TaqMan® technology. RESULTS: We enrolled 274 participants, of whom 227 (82.8 %) completed 6 months of clozapine treatment. There was one case of severe neutropenia (<500 cells/mm3) (0.36 %) over 1467.6 person-months of clozapine exposure. This participant recovered without sequelae after discontinuation of clozapine. Of the 249 participants with known genotypes, 199 (79.9 %) had the ACKR1-null genotype. Neutropenia (<1500 cells/mm3) occurred significantly more often in the ACKR1-null group (33 % [65/199]) than in those with the T allele (6 % (3/50); p < 0.001). Fourteen (5 %) patients discontinued due to adverse events. Rates of infection and fever were low and sialorrhea was the commonest side effect (N = 187, 68 %). CONCLUSION: To our knowledge, this is the largest prospective clozapine trial in people of African descent. Severe neutropenia was rare, despite the high prevalence (80 %) of the ACKR1-null genotype. Our findings suggest that clozapine can be used safely in Black patients including those with BEN.

Tryptophan challenge in individuals with schizophrenia and healthy controls: acute effects on circulating kynurenine and kynurenic acid, cognition and cerebral blood flow.

Cognitive impairments predict poor functional outcomes in people with schizophrenia. These impairments may be causally related to increased levels of kynurenic acid (KYNA), a major metabolic product of tryptophan (TRYP). In the brain, KYNA acts as an antagonist of the of α7-nicotinic acetylcholine and NMDA receptors, both of which are involved in cognitive processes. To examine whether KYNA plays a role in the pathophysiology of schizophrenia, we compared the acute effects of a single oral dose of TRYP (6 g) in 32 healthy controls (HC) and 37 people with either schizophrenia (Sz), schizoaffective or schizophreniform disorder, in a placebo-controlled, randomized crossover study. We examined plasma levels of KYNA and its precursor kynurenine; selected cognitive measures from the MATRICS Consensus Cognitive Battery; and resting cerebral blood flow (CBF) using arterial spin labeling imaging. In both cohorts, the TRYP challenge produced significant, time-dependent elevations in plasma kynurenine and KYNA. The resting CBF signal (averaged across all gray matter) was affected differentially, such that TRYP was associated with higher CBF in HC, but not in participants with a Sz-related disorder. While TRYP did not significantly impair cognitive test performance, there was a trend for TRYP to worsen visuospatial memory task performance in HC. Our results demonstrate that oral TRYP challenge substantially increases plasma levels of kynurenine and KYNA in both groups, but exerts differential group effects on CBF. Future studies are required to investigate the mechanisms underlying these CBF findings, and to evaluate the impact of KYNA fluctuations on brain function and behavior. (Clinicaltrials.gov: NCT02067975).

Characterization of the extracellular free water signal in schizophrenia using multi-site diffusion MRI harmonization.

Studies applying Free Water Imaging have consistently reported significant global increases in extracellular free water (FW) in populations of individuals with early psychosis. However, these published studies focused on homogenous clinical participant groups (e.g., only first episode or chronic), thereby limiting our understanding of the time course of free water elevations across illness stages. Moreover, the relationship between FW and duration of illness has yet to be directly tested. Leveraging our multi-site diffusion magnetic resonance imaging(dMRI) harmonization approach, we analyzed dMRI scans collected by 12 international sites from 441 healthy controls and 434 individuals diagnosed with schizophrenia-spectrum disorders at different illness stages and ages (15-58 years). We characterized the pattern of age-related FW changes by assessing whole brain white matter in individuals with schizophrenia and healthy controls. In individuals with schizophrenia, average whole brain FW was higher than in controls across all ages, with the greatest FW values observed from 15 to 23 years (effect size range = [0.70-0.87]). Following this peak, FW exhibited a monotonic decrease until reaching a minima at the age of 39 years. After 39 years, an attenuated monotonic increase in FW was observed, but with markedly smaller effect sizes when compared to younger patients (effect size range = [0.32-0.43]). Importantly, FW was found to be negatively associated with duration of illness in schizophrenia (p = 0.006), independent of the effects of other clinical and demographic data. In summary, our study finds in a large, age-diverse sample that participants with schizophrenia with a shorter duration of illness showed higher FW values compared to participants with more prolonged illness. Our findings provide further evidence that elevations in the FW are present in individuals with schizophrenia, with the greatest differences in the FW being observed in those at the early stages of the disorder, which might suggest acute extracellular processes.

Multivariate Associations Among White Matter, Neurocognition, and Social Cognition Across Individuals With Schizophrenia Spectrum Disorders and Healthy Controls.

BACKGROUND AND HYPOTHESIS: Neurocognitive and social cognitive abilities are important contributors to functional outcomes in schizophrenia spectrum disorders (SSDs). An unanswered question of considerable interest is whether neurocognitive and social cognitive deficits arise from overlapping or distinct white matter impairment(s). STUDY DESIGN: We sought to fill this gap, by harnessing a large sample of individuals from the multi-center Social Processes Initiative in the Neurobiology of the Schizophrenia(s) (SPINS) dataset, unique in its collection of advanced diffusion imaging and an extensive battery of cognitive assessments. We applied canonical correlation analysis to estimates of white matter microstructure, and cognitive performance, across people with and without an SSD. STUDY RESULTS: Our results established that white matter circuitry is dimensionally and strongly related to both neurocognition and social cognition, and that microstructure of the uncinate fasciculus and the rostral body of the corpus callosum may assume a "privileged role" subserving both. Further, we found that participant-wise estimates of white matter microstructure, weighted by cognitive performance, were largely consistent with participants' categorical diagnosis, and predictive of (cross-sectional) functional outcomes. CONCLUSIONS: The demonstrated strength of the relationship between white matter circuitry and neurocognition and social cognition underscores the potential for using relationships among these variables to identify biomarkers of functioning, with potential prognostic and therapeutic implications.

Clinical and cortical similarities identified between bipolar disorder I and schizophrenia: A multivariate approach.

Background: Structural neuroimaging studies have identified similarities in the brains of individuals diagnosed with schizophrenia (SZ) and bipolar I disorder (BP), with overlap in regions of gray matter (GM) deficits between the two disorders. Recent studies have also shown that the symptom phenotypes associated with SZ and BP may allow for a more precise categorization than the current diagnostic criteria. In this study, we sought to identify GM alterations that were unique to each disorder and whether those alterations were also related to unique symptom profiles. Materials and methods: We analyzed the GM patterns and clinical symptom presentations using independent component analysis (ICA), hierarchical clustering, and n-way biclustering in a large (N ∼ 3,000), merged dataset of neuroimaging data from healthy volunteers (HV), and individuals with either SZ or BP. Results: Component A showed a SZ and BP < HV GM pattern in the bilateral insula and cingulate gyrus. Component B showed a SZ and BP < HV GM pattern in the cerebellum and vermis. There were no significant differences between diagnostic groups in these components. Component C showed a SZ < HV and BP GM pattern bilaterally in the temporal poles. Hierarchical clustering of the PANSS scores and the ICA components did not yield new subgroups. N-way biclustering identified three unique subgroups of individuals within the sample that mapped onto different combinations of ICA components and symptom profiles categorized by the PANSS but no distinct diagnostic group differences. Conclusion: These multivariate results show that diagnostic boundaries are not clearly related to structural differences or distinct symptom profiles. Our findings add support that (1) BP tend to have less severe symptom profiles when compared to SZ on the PANSS without a clear distinction, and (2) all the gray matter alterations follow the pattern of SZ < BP < HV without a clear distinction between SZ and BP.

Tryptophan Challenge in Healthy Controls and People with Schizophrenia: Acute Effects on Plasma Levels of Kynurenine, Kynurenic Acid and 5-Hydroxyindoleacetic Acid.

The pivotal tryptophan (TRP) metabolite kynurenine is converted to several neuroactive compounds, including kynurenic acid (KYNA), which is elevated in the brain and cerebrospinal fluid of people with schizophrenia (SZ) and may contribute to cognitive abnormalities in patients. A small proportion of TRP is metabolized to serotonin and further to 5-hydroxyindoleacetic acid (5-HIAA). Notably, KP metabolism is readily affected by immune stimulation. Here, we assessed the acute effects of an oral TRP challenge (6 g) on peripheral concentrations of kynurenine, KYNA and 5-HIAA, as well as the cytokines interferon-γ, TNF-α and interleukin-6, in 22 participants with SZ and 16 healthy controls (HCs) using a double-blind, placebo-controlled, crossover design. TRP raised the levels of kynurenine, KYNA and 5-HIAA in a time-dependent manner, causing >20-fold, >130-fold and 1.5-fold increases in kynurenine, KYNA and 5-HIAA concentrations, respectively, after 240 min. According to multivariate analyses, neither baseline levels nor the stimulating effects of TRP differed between participants with SZ and HC. Basal cytokine levels did not vary between groups, and remained unaffected by TRP. Although unlikely to be useful diagnostically, measurements of circulating metabolites following an acute TRP challenge may be informative for assessing the in vivo efficacy of drugs that modulate the neosynthesis of KYNA and other products of TRP degradation.

Cognitive deficits, clinical variables, and white matter microstructure in schizophrenia: a multisite harmonization study.

Cognitive deficits are among the best predictors of real-world functioning in schizophrenia. However, our understanding of how cognitive deficits relate to neuropathology and clinical presentation over the disease lifespan is limited. Here, we combine multi-site, harmonized cognitive, imaging, demographic, and clinical data from over 900 individuals to characterize a) cognitive deficits across the schizophrenia lifespan and b) the association between cognitive deficits, clinical presentation, and white matter (WM) microstructure. Multimodal harmonization was accomplished using T-scores for cognitive data, previously reported standardization methods for demographic and clinical data, and an established harmonization method for imaging data. We applied t-tests and correlation analysis to describe cognitive deficits in individuals with schizophrenia. We then calculated whole-brain WM fractional anisotropy (FA) and utilized regression-mediation analyses to model the association between diagnosis, FA, and cognitive deficits. We observed pronounced cognitive deficits in individuals with schizophrenia (p < 0.006), associated with more positive symptoms and medication dosage. Regression-mediation analyses showed that WM microstructure mediated the association between schizophrenia and language/processing speed/working memory/non-verbal memory. In addition, processing speed mediated the influence of diagnosis and WM microstructure on the other cognitive domains. Our study highlights the critical role of cognitive deficits in schizophrenia. We further show that WM is crucial when trying to understand the role of cognitive deficits, given that it explains the association between schizophrenia and cognitive deficits (directly and via processing speed).

A longitudinal multi-scanner multimodal human neuroimaging dataset.

Human neuroimaging has led to an overwhelming amount of research into brain function in healthy and clinical populations. However, a better appreciation of the limitations of small sample studies has led to an increased number of multi-site, multi-scanner protocols to understand human brain function. As part of a multi-site project examining social cognition in schizophrenia, a group of "travelling human phantoms" had structural T1, diffusion, and resting-state functional MRIs obtained annually at each of three sites. Scan protocols were carefully harmonized across sites prior to the study. Due to scanner upgrades at each site (all sites acquired PRISMA MRIs during the study) and one participant being replaced, the end result was 30 MRI scans across 4 people, 6 MRIs, and 4 years. This dataset includes multiple neuroimaging modalities and repeated scans across six MRIs. It can be used to evaluate differences across scanners, consistency of pipeline outputs, or test multi-scanner harmonization approaches.