Gyrification across psychotic disorders: A bipolar-schizophrenia network of intermediate phenotypes study.

BACKGROUND: The profiles of cortical gyrification across schizophrenia, bipolar I disorder, and schizoaffective disorder have been studied to a limited extent, report discordant findings, and are rarely compared in the same study. Here we assess gyrification in a large dataset of psychotic disorder probands, categorized according to the DSM-IV. Furthermore, we explore gyrification changes with age across healthy controls and probands. METHODS: Participants were recruited within the Bipolar-Schizophrenia Network of Intermediate Phenotypes study and received T1-MPRAGE and clinical assessment. Gyrification was measured using FreeSurfer 7.1.0. Pairwise t-tests were conducted in R, and age-related gyrification changes were analyzed in MATLAB. P values <0.05 after false discovery rate correction were considered significant. RESULTS: Significant hypogyria in schizophrenia, bipolar disorder, and schizoaffective disorder probands compared to controls was found, with a significant difference bilaterally in the frontal lobe between schizophrenia and bipolar disorder probands. Verbal memory was associated with gyrification in the right frontal and right cingulate cortex in schizophrenia. Age-fitted gyrification curves differed significantly among psychotic disorders and controls. CONCLUSIONS: Findings indicate hypogyria in DSM-IV psychotic disorders compared to controls and suggest differential patterns of gyrification across the different diagnoses. The study extends age related models of gyrification to psychotic disorder probands and supports that age-related differences in gyrification may differ across diagnoses. Fitted gyrification curves among probands categorized by DSM-IV significantly deviate from controls, with the model capturing early hypergyria and later hypogyria in schizophrenia compared to controls; this suggests unique disease and age-related changes in gyrification across psychotic disorders.

Evidence from comprehensive independent validation studies for smooth pursuit dysfunction as a sensorimotor biomarker for psychosis.

Smooth pursuit eye movements are considered a well-established and quantifiable biomarker of sensorimotor function in psychosis research. Identifying psychotic syndromes on an individual level based on neurobiological markers is limited by heterogeneity and requires comprehensive external validation to avoid overestimation of prediction models. Here, we studied quantifiable sensorimotor measures derived from smooth pursuit eye movements in a large sample of psychosis probands (N = 674) and healthy controls (N = 305) using multivariate pattern analysis. Balanced accuracies of 64% for the prediction of psychosis status are in line with recent results from other large heterogenous psychiatric samples. They are confirmed by external validation in independent large samples including probands with (1) psychosis (N = 727) versus healthy controls (N = 292), (2) psychotic (N = 49) and non-psychotic bipolar disorder (N = 36), and (3) non-psychotic affective disorders (N = 119) and psychosis (N = 51) yielding accuracies of 65%, 66% and 58%, respectively, albeit slightly different psychosis syndromes. Our findings make a significant contribution to the identification of biologically defined profiles of heterogeneous psychosis syndromes on an individual level underlining the impact of sensorimotor dysfunction in psychosis.

Enlarged pituitary gland volume: a possible state rather than trait marker of psychotic disorders.

BACKGROUND: Enlarged pituitary gland volume could be a marker of psychotic disorders. However, previous studies report conflicting results. To better understand the role of the pituitary gland in psychosis, we examined a large transdiagnostic sample of individuals with psychotic disorders. METHODS: The study included 751 participants (174 with schizophrenia, 114 with schizoaffective disorder, 167 with psychotic bipolar disorder, and 296 healthy controls) across six sites in the Bipolar-Schizophrenia Network on Intermediate Phenotypes consortium. Structural magnetic resonance images were obtained, and pituitary gland volumes were measured using the MAGeT brain algorithm. Linear mixed models examined between-group differences with controls and among patient subgroups based on diagnosis, as well as how pituitary volumes were associated with symptom severity, cognitive function, antipsychotic dose, and illness duration. RESULTS: Mean pituitary gland volume did not significantly differ between patients and controls. No significant effect of diagnosis was observed. Larger pituitary gland volume was associated with greater symptom severity (F = 13.61, p = 0.0002), lower cognitive function (F = 4.76, p = 0.03), and higher antipsychotic dose (F = 5.20, p = 0.02). Illness duration was not significantly associated with pituitary gland volume. When all variables were considered, only symptom severity significantly predicted pituitary gland volume (F = 7.54, p = 0.006). CONCLUSIONS: Although pituitary volumes were not increased in psychotic disorders, larger size may be a marker associated with more severe symptoms in the progression of psychosis. This finding helps clarify previous inconsistent reports and highlights the need for further research into pituitary gland-related factors in individuals with psychosis.

Differentiating Biomarker Features and Familial Characteristics of B-SNIP Psychosis Biotypes.

Idiopathic psychosis shows considerable biological heterogeneity across cases. B-SNIP used psychosis-relevant biomarkers to identity psychosis Biotypes, which will aid etiological and targeted treatment investigations. Psychosis probands from the B-SNIP consortium (n = 1907), their first-degree biological relatives (n = 705), and healthy participants (n = 895) completed a biomarker battery composed of cognition, saccades, and auditory EEG measurements. ERP quantifications were substantially modified from previous iterations of this approach. Multivariate integration reduced multiple biomarker outcomes to 11 "bio-factors". Twenty-four different approaches indicated bio-factor data among probands were best distributed as three subgroups. Numerical taxonomy with k-means constructed psychosis Biotypes, and rand indices evaluated consistency of Biotype assignments. Psychosis subgroups, their non-psychotic first-degree relatives, and healthy individuals were compared across bio-factors. The three psychosis Biotypes differed significantly on all 11 bio-factors, especially prominent for general cognition, antisaccades, ERP magnitude, and intrinsic neural activity. Rand indices showed excellent consistency of clustering membership when samples included at least 1100 subjects. Canonical discriminant analysis described composite bio-factors that simplified group comparisons and captured neural dysregulation, neural vigor, and stimulus salience variates. Neural dysregulation captured Biotype-2, low neural vigor captured Biotype-1, and deviations of stimulus salience captured Biotype-3. First-degree relatives showed similar patterns as their Biotyped proband relatives on general cognition, antisaccades, ERP magnitudes, and intrinsic brain activity. Results extend previous efforts by the B-SNIP consortium to characterize biologically distinct psychosis Biotypes. They also show that at least 1100 observations are necessary to achieve consistent outcomes. First-degree relative data implicate specific bio-factor deviations to the subtype of their proband and may inform studies of genetic risk.

Clinical characterization and differentiation of B-SNIP psychosis Biotypes: Algorithmic Diagnostics for Efficient Prescription of Treatments (ADEPT)-1.

Clinically defined psychosis diagnoses are neurobiologically heterogeneous. The B-SNIP consortium identified and validated more neurobiologically homogeneous psychosis Biotypes using an extensive battery of neurocognitive and psychophysiological laboratory measures. However, typically the first step in any diagnostic evaluation is the clinical interview. In this project, we evaluated if psychosis Biotypes have clinical characteristics that can support their differentiation in addition to obtaining laboratory testing. Clinical interview data from 1907 individuals with a psychosis Biotype were used to create a diagnostic algorithm. The features were 58 ratings from standard clinical scales. Extremely randomized tree algorithms were used to evaluate sensitivity, specificity, and overall classification success. Biotype classification accuracy peaked at 91 % with the use of 57 items on average. A reduced feature set of 28 items, though, also showed 81 % classification accuracy. Using this reduced item set, we found that only 10-11 items achieved a one-vs-all (Biotype-1 or not, Biotype-2 or not, Biotype-3 or not) area under the sensitivity-specificity curve of .78 to .81. The top clinical characteristics for differentiating psychosis Biotypes, in order of importance, were (i) difficulty in abstract thinking, (ii) multiple indicators of social functioning, (iii) conceptual disorganization, (iv) severity of hallucinations, (v) stereotyped thinking, (vi) suspiciousness, (vii) unusual thought content, (viii) lack of spontaneous speech, and (ix) severity of delusions. These features were remarkably different from those that differentiated DSM psychosis diagnoses. This low-burden adaptive algorithm achieved reasonable classification accuracy and will support Biotype-specific etiological and treatment investigations even in under-resourced clinical and research environments.

Double dissociation between P300 components and task switch error type in healthy but not psychosis participants.

Event-related potentials (ERPs) during oddball tasks and the behavioral performance on the Penn Conditional Exclusion Task (PCET) measure context-appropriate responding: P300 ERPs to oddball targets reflect detection of input changes and context updating in working memory, and PCET performance indexes detection, adherence, and maintenance of mental set changes. More specifically, PCET variables quantify cognitive functions including inductive reasoning (set 1 completion), mental flexibility (perseverative errors), and working memory maintenance (regressive errors). Past research showed that both P300 ERPs and PCET performance are disrupted in psychosis. This study probed the possible neural correlates of 3 PCET abnormalities that occur in participants with psychosis via the overlapping cognitive demands of the two study paradigms. In a two-tiered analysis, psychosis (n = 492) and healthy participants (n = 244) were first divided based on completion of set 1 - which measures subjects' ability to use inductive reasoning to arrive at the correct set. Results showed that participants who failed set 1 produced lower parietal P300, independent of clinical status. In the second tier of analysis, a double dissociation was found among healthy set 1 completers: frontal P300 amplitudes were negatively associated with perseverative errors, and parietal P300 was negatively associated with regressive errors. In contrast, psychosis participants showed global P300 reductions regardless of PCET performance. From this we conclude that in psychosis, overall activations evoked by the oddball task are reduced while the cognitive functions required by PCET are still somewhat supported, showing some level of independence or compensatory physiology in psychosis between neural activities underlying the two tasks.

Supervised machine learning classification of psychosis biotypes based on brain structure: findings from the Bipolar-Schizophrenia network for intermediate phenotypes (B-SNIP).

Traditional diagnostic formulations of psychotic disorders have low correspondence with underlying disease neurobiology. This has led to a growing interest in using brain-based biomarkers to capture biologically-informed psychosis constructs. Building upon our prior work on the B-SNIP Psychosis Biotypes, we aimed to examine whether structural MRI (an independent biomarker not used in the Biotype development) can effectively classify the Biotypes. Whole brain voxel-wise grey matter density (GMD) maps from T1-weighted images were used to train and test (using repeated randomized train/test splits) binary L2-penalized logistic regression models to discriminate psychosis cases (n = 557) from healthy controls (CON, n = 251). A total of six models were evaluated across two psychosis categorization schemes: (i) three Biotypes (B1, B2, B3) and (ii) three DSM diagnoses (schizophrenia (SZ), schizoaffective (SAD) and bipolar (BD) disorders). Above-chance classification accuracies were observed in all Biotype (B1 = 0.70, B2 = 0.65, and B3 = 0.56) and diagnosis (SZ = 0.64, SAD = 0.64, and BD = 0.59) models. However, the only model that showed evidence of specificity was B1, i.e., the model was able to discriminate B1 vs. CON and did not misclassify other psychosis cases (B2 or B3) as B1 at rates above nominal chance. The GMD-based classifier evidence for B1 showed a negative association with an estimate of premorbid general intellectual ability, regardless of group membership, i.e. psychosis or CON. Our findings indicate that, complimentary to clinical diagnoses, the B-SNIP Psychosis Biotypes may offer a promising approach to capture specific aspects of psychosis neurobiology.

A pilot study to investigate the efficacy and tolerability of lesion network guided transcranial electrical stimulation in outpatients with psychosis spectrum illness.

BACKGROUND: Transcranial electrical stimulation (tES) may improve psychosis symptoms, but few investigations have targeted brain regions causally linked to psychosis symptoms. We implemented a novel montage targeting the extrastriate visual cortex (eVC) previously identified by lesion network mapping in the manifestation of visual hallucinations. OBJECTIVE: To determine if lesion network guided High Definition-tES (HD-tES) to the eVC is safe and efficacious in reducing symptoms related to psychosis. METHODS: We conducted a single-blind crossover pilot study (NCT04870710) in patients with psychosis spectrum disorders. Participants first received HD-tDCS (direct current), followed by 4 weeks of wash out, then 2 Hz HD-tACS (alternating current). Participants received 5 days of daily (2×20 min) stimulation bilaterally to the eVC. Primary outcomes included the Positive and Negative Syndrome Scale (PANSS), biological motion task, and Event Related Potentials (ERP) from a steady state visual evoked potential (SSVEP) paradigm. Secondary outcomes included the Montgomery-Asperg Depression Rating Scale, Global Assessment of Functioning (GAF), velocity discrimination and visual working memory task, and emotional ERP. RESULTS: HD-tDCS improved PANSS general psychopathology in the short-term (d=0.47; pfdr=0.03), with long-term improvements in general psychopathology (d=0.62; pfdr=0.05) and GAF (d=-0.56; pfdr=0.04) with HD-tACS. HD-tDCS reduced SSVEP P1 (d=0.25; pfdr=0.005), which correlated with general psychopathology (ß = 0.274, t = 3.59, p = 0.04). No significant differences in safety or tolerability measures were identified. CONCLUSION: Lesion network guided HD-tES to the eVC is a safe, efficacious, and promising approach for reducing general psychopathology via changes in neuroplasticity. These results highlight the need for larger clinical trials implementing novel targeting methodologies for the treatments of psychosis.

Peripheral inflammatory subgroup differences in anterior Default Mode network and multiplex functional network topology are associated with cognition in psychosis.

INTRODUCTION: High-inflammation subgroups of patients with psychosis demonstrate cognitive deficits and neuroanatomical alterations. Systemic inflammation assessed using IL-6 and C-reactive protein may alter functional connectivity within and between resting-state networks, but the cognitive and clinical implications of these alterations remain unknown. We aim to determine the relationships of elevated peripheral inflammation subgroups with resting-state functional networks and cognition in psychosis spectrum disorders. METHODS: Serum and resting-state fMRI were collected from psychosis probands (schizophrenia, schizoaffective, psychotic bipolar disorder) and healthy controls (HC) from the B-SNIP1 (Chicago site) study who were stratified into inflammatory subgroups based on factor and cluster analyses of 13 cytokines (HC Low n = 32, Proband Low n = 65, Proband High n = 29). Nine resting-state networks derived from independent component analysis were used to assess functional and multilayer connectivity. Inter-network connectivity was measured using Fisher z-transformation of correlation coefficients. Network organization was assessed by investigating networks of positive and negative connections separately, as well as investigating multilayer networks using both positive and negative connections. Cognition was assessed using the Brief Assessment of Cognition in Schizophrenia. Linear regressions, Spearman correlations, permutations tests and multiple comparison corrections were used for analyses in R. RESULTS: Anterior default mode network (DMNa) connectivity was significantly reduced in the Proband High compared to Proband Low (Cohen's d = -0.74, p = 0.002) and HC Low (d = -0.85, p = 0.0008) groups. Inter-network connectivity between the DMNa and the right-frontoparietal networks was lower in Proband High compared to Proband Low (d = -0.66, p = 0.004) group. Compared to Proband Low, the Proband High group had lower negative (d = 0.54, p = 0.021) and positive network (d = 0.49, p = 0.042) clustering coefficient, and lower multiplex network participation coefficient (d = -0.57, p = 0.014). Network findings in high inflammation subgroups correlate with worse verbal fluency, verbal memory, symbol coding, and overall cognition. CONCLUSION: These results expand on our understanding of the potential effects of peripheral inflammatory signatures and/or subgroups on network dysfunction in psychosis and how they relate to worse cognitive performance. Additionally, the novel multiplex approach taken in this study demonstrated how inflammation may disrupt the brain's ability to maintain healthy co-activation patterns between the resting-state networks while inhibiting certain connections between them.

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.

Efficacy and Tolerability of Lesion Network Guided Transcranial Electrical Stimulation in Outpatients with Psychosis Spectrum Illness: A Nonrandomized Controlled Trial.

Importance: Transcranial electrical stimulation (tES) may improve psychosis symptoms, but few investigations have targeted brain regions causally linked to psychosis symptoms. We implemented a novel montage targeting the extrastriate visual cortex (eVC) previously identified by lesion network mapping in the manifestation of visual hallucinations. Objective: To determine if lesion network guided HD-tES to the eVC is safe and efficacious in reducing symptoms related to psychosis. Design Setting and Participants: Single-center, nonrandomized, single-blind trial using a crossover design conducted in two 4-week phases beginning November 2020, and ending January 2022. Participants were adults 18-55 years of age with a diagnosis of schizophrenia, schizoaffective or psychotic bipolar disorder as confirmed by the Structured Clinical Interview for DSM-V, without an antipsychotic medication change for at least 4 weeks. A total of 8 participants consented and 6 participants enrolled. Significance threshold set to <0.1 due to small sample size. Interventions: 6 Participants first received HD-tDCS (direct current), followed by 4 weeks of wash out, then 4 received 2Hz HD-tACS (alternating current). Participants received 5 consecutive days of daily (2 × 20min) stimulation applied bilaterally to the eVC. Main Outcomes and Measures: Primary outcomes included the Positive and Negative Syndrome Scale (PANSS) total, positive, negative, and general scores, biological motion task, and Event Related Potential (ERP) measures obtained from a steady state visual evoked potential (SSVEP) task across each 4-week phase. Secondary outcomes included the Montgomery-Asperg Depression Rating Scale (MADRS), Global Assessment of Functioning (GAF), velocity discrimination task, visual working memory task, and emotional ERP across each 4-week phase. Results: HD-tDCS improved general psychopathology in the short-term (d=0.47; p fdr =0.03), with long-term improvements in general psychopathology (d=0.62; p fdr =0.05) and GAF (d=-0.56; p fdr =0.04) with HD-tACS. HD-tDCS reduced SSVEP P1 (d=0.25; p fdr =0.005), which correlated with general psychopathology (ß=0.274, t=3.59, p=0.04). No significant differences in safety or tolerability measures were identified. Conclusions and Relevance: Lesion network guided HD-tES to the eVC is a safe, efficacious, and promising approach for reducing general psychopathology via changes in neuroplasticity. These results highlight the need for larger clinical trials implementing novel targeting methodologies for the treatments of psychosis. Trial Registration: ClinicalTrials.gov Identifier: NCT04870710. Key Points: Question: Is lesion network guided neurostimulation an efficacious, safe, and targeted approach for treating psychosis?Findings: In this single-center, nonrandomized, crossover, single-blind trial of 6 outpatients with psychosis, improvement in general psychopathology was seen in the short-term with HD-tDCS (high-definition transcranial direct current stimulation) and long-term with HD-tACS (alternating current) targeting the extrastriate visual cortex (eVC). HD-tDCS reduced early visual evoked responses which linked to general psychopathology improvements. Overall, both stimulations were well tolerated.Meaning: Study findings suggest that lesion network guided HD-tES to the eVC is a safe, efficacious, and promising approach for reducing general psychopathology via neuroplastic changes.

Peripheral inflammation is associated with impairments of inhibitory behavioral control and visual sensorimotor function in psychotic disorders.

Elevated markers of peripheral inflammation are common in psychosis spectrum disorders and have been associated with brain anatomy, pathology, and physiology as well as clinical outcomes. Preliminary evidence suggests a link between inflammatory cytokines and C-reactive protein (CRP) with generalized cognitive impairments in a subgroup of individuals with psychosis. Whether these patients with elevated peripheral inflammation demonstrate deficits in specific cognitive domains remains unclear. To examine this, seventeen neuropsychological and sensorimotor tasks and thirteen peripheral inflammatory and microvascular markers were quantified in a subset of B-SNIP consortium participants (129 psychosis, 55 healthy controls). Principal component analysis was conducted across the inflammatory markers, resulting in five inflammation factors. Three discrete latent cognitive domains (Visual Sensorimotor, General Cognitive Ability, and Inhibitory Behavioral Control) were characterized based on the neurobehavioral battery and examined in association with inflammation factors. Hierarchical clustering analysis identified cognition-sensitive high/low inflammation subgroups. Among persons with psychotic disorders but not healthy controls, higher inflammation scores had significant associations with impairments of Inhibitory Control (R2 = 0.100, p-value = 2.69e-4, q-value = 0.004) and suggestive associations with Visual Sensorimotor function (R2 = 0.039, p-value = 0.024, q-value = 0.180), but not with General Cognitive Ability (R2 = 0.015, p-value = 0.162). Greater deficits in Inhibitory Control were observed in the high inflammation patient subgroup, which represented 30.2 % of persons with psychotic disorders, as compared to the low inflammation psychosis subgroup. These findings indicate that inflammation dysregulation may differentially impact specific neurobehavioral domains across psychotic disorders, particularly performance on tasks requiring ongoing behavioral monitoring and control.

Characterization of childhood trauma, hippocampal mediation and Cannabis use in a large dataset of psychosis and non-psychosis individuals.

BACKGROUND: Cannabis use (CA) and childhood trauma (CT) independently increase the risk of earlier psychosis onset; but their interaction in relation to psychosis risk and association with endocannabinoid-receptor rich brain regions, i.e. the hippocampus (HP), remains unclear. The objective was to determine whether lower age of psychosis onset (AgePsyOnset) is associated with CA and CT through mediation by the HP volumes, and genetic risk, as measured by schizophrenia polygene scores (SZ-PGRS). METHODS: Cross-sectional, case-control, multicenter sample from 5 metropolitan US regions. Participants (n = 1185) included 397 controls not affected by psychosis (HC); 209 participants with bipolar disorder type-1; 279 with schizoaffective disorder; and 300 with schizophrenia (DSM IV-TR). CT was assessed using the Childhood Trauma Questionnaire (CTQ); CA was assessed by self-reports and trained clinical interviewers. Assessment included neuroimaging, symptomatology, cognition and calculation of the SZ polygenic risk score (SZ-PGRS). RESULTS: In survival analysis, CT and CA exposure interact to be associated with lower AgePsyOnset. At high CT or CA, CT or CA are individually sufficient to affect AgePsyOnset. CT relation with AgePsyOnset is mediated in part by the HP in CA users before AgePsyOnset. CA before AgePsyOnset is associated with higher SZ-PGRS and correlated with younger age at CA usage. DISCUSSION: CA and CT interact to increase risk when moderate; while severe CT and/or CA abuse/dependence are each sufficient to affect AgePsyOnset, indicating a ceiling effect. Probands with/out CA before AgePsyOnset differ on biological variables, suggesting divergent pathways to psychosis. FUNDING: MH077945; MH096942; MH096913; MH077862; MH103368; MH096900; MH122759.

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).

Reduced task-evoked pupillary response in preparation for an executive cognitive control response among individuals across the psychosis spectrum.

Task-evoked pupillary response (TEPR) is a measure of physiological arousal modulated by cognitive demand. Healthy individuals demonstrate greater TEPR prior to correct versus error antisaccade trials and correct antisaccade versus visually guided saccade (VGS) trials. The relationship between TEPR and antisaccade performance in individuals with psychotic disorders and their relatives has not been investigated. Probands with schizophrenia, schizoaffective disorder, psychotic bipolar disorder, their first-degree relatives, and controls from the B-SNIP study completed antisaccade and VGS tasks. TEPR prior to execution of responses on these tasks was evaluated among controls compared to probands and relatives according to diagnostic groups and neurobiologically defined subgroups (biotypes). Controls demonstrated greater TEPR on antisaccade correct versus error versus VGS trials. TEPR was not differentiated between antisaccade correct versus error trials in bipolar or schizophrenia probands, though was greater on antisaccade compared to prosaccade trials. There was no modulation of TEPR in schizoaffective probands. Relatives of schizophrenia and schizoaffective probands and those with elevated psychosis spectrum traits failed to demonstrate differential TEPR on antisaccade correct versus error trials. No proband or relative biotypes demonstrated differential TEPR on antisaccade correct versus error trials, and only proband biotype 3 and relative biotypes 3 and 2 demonstrated greater TEPR on antisaccade versus VGS trials. Our findings suggest that aberrant modulation of preparatory activity prior to saccade execution contributes to impaired executive cognitive control across the psychosis spectrum, including nonpsychotic relatives with elevated clinical risk. Reduced pupillary modulation under cognitive challenge may thus be a biomarker for the psychosis phenotype.

Regional and Sex-Specific Alterations in the Visual Cortex of Individuals With Psychosis Spectrum Disorders.

BACKGROUND: Impairments of the visual system are implicated in psychotic disorders. However, studies exploring visual cortex (VC) morphology in this population are limited. Using data from the Bipolar-Schizophrenia Network on Intermediate Phenotypes consortium, we examined VC structure in psychosis probands and their first-degree relatives (RELs), sex differences in VC measures, and their relationships with cognitive and peripheral inflammatory markers. METHODS: Cortical thickness, surface area, and volume of the primary (Brodmann area 17/V1) and secondary (Brodmann area 18/V2) visual areas and the middle temporal (V5/MT) region were quantified using FreeSurfer version 6.0 in psychosis probands (n = 530), first-degree RELs (n = 544), and healthy control subjects (n = 323). Familiality estimates were determined for probands and RELs. General cognition, response inhibition, and emotion recognition functions were assessed. Systemic inflammation was measured in a subset of participants. RESULTS: Psychosis probands demonstrated significant area, thickness, and volume reductions in V1, V2, and MT, and their first-degree RELs demonstrated area and volume reductions in MT compared with control subjects. There was a higher degree of familiality for VC area than thickness. Area and volume reductions in V1 and V2 were sex dependent, affecting only female probands in a regionally specific manner. Reductions in some VC regions were correlated with poor general cognition, worse response inhibition, and increased C-reactive protein levels. CONCLUSIONS: The visual cortex is a site of significant pathology in psychotic disorders, with distinct patterns of area and thickness changes, sex-specific and regional effects, potential contributions to cognitive impairments, and association with C-reactive protein levels.

Inflammation subtypes in psychosis and their relationships with genetic risk for psychiatric and cardiometabolic disorders.

Cardiometabolic disorders have known inflammatory implications, and peripheral measures of inflammation and cardiometabolic disorders are common in persons with psychotic disorders. Inflammatory signatures are also related to neurobiological and behavioral changes in psychosis. Relationships between systemic inflammation and cardiometabolic genetic risk in persons with psychosis have not been examined. Thirteen peripheral inflammatory markers and genome-wide genotyping were assessed in 122 participants (n â€‹= â€‹86 psychosis, n â€‹= â€‹36 healthy controls) of European ancestry. Cluster analyses of inflammatory markers classified higher and lower inflammation subgroups. Single-trait genetic risk scores (GRS) were constructed for each participant using previously reported GWAS summary statistics for the following traits: schizophrenia, bipolar disorder, major depressive disorder, coronary artery disease, type-2 diabetes, low-density lipoprotein, high-density lipoprotein, triglycerides, and waist-to-hip ratio. Genetic correlations across traits were quantified. Principal component (PC) analysis of the cardiometabolic GRSs generated six PC loadings used in regression models to examine associations with inflammation markers. Functional module discovery explored biological mechanisms of the inflammation association of cardiometabolic GRS genes. A subgroup of 38% persons with psychotic disorders was characterized with higher inflammation status. These higher inflammation individuals had lower BACS scores (p â€‹= â€‹0.038) compared to those with lower inflammation. The first PC of the cardiometabolic GRS matrix was related to higher inflammation status in persons with psychotic disorders (OR â€‹= â€‹2.037, p â€‹= â€‹0.001). Two of eight modules within the functional interaction network of cardiometabolic GRS genes were enriched for immune processes. Cardiometabolic genetic risk may predispose some individuals with psychosis to elevated inflammation which adversely impacts cognition associated with illness.

A subtype of institutionalized patients with schizophrenia characterized by pronounced subcortical and cognitive deficits.

Some patients with schizophrenia have severe cognitive impairment and functional deficits that require long-term institutional care. The patterns of brain-behavior alterations in these individuals, and their differences from patients living successfully in the community, remain poorly understood. Previous cognition-based studies for stratifying schizophrenia patients highlight the importance of subcortical structures in the context of illness heterogeneity. In the present study, subcortical volumes from 96 institutionalized patients with long-term schizophrenia were evaluated using cluster analysis to test for heterogeneity. These data were compared to those from two groups of community-dwelling individuals with schizophrenia for comparison purposes, including 68 long-term ill and 126 first-episode individuals. A total of 290 demographically matched healthy participants were included as normative references at a 1:1 ratio for each patient sample. A subtype of institutionalized patients was identified based on their pattern of subcortical alterations. Using a machine learning algorithm developed to discriminate the two groups of institutionalized patients, all three patient samples were found to have similar rates of patients assigned to the two subtypes (approximately 50% each). In institutionalized patients, only the subtype with the identified pattern of subcortical alterations had greater neocortical and cognitive abnormalities than those in the similarity classified community-dwelling patients with long-term illness. Thus, for the subtype of patients with a distinctive pattern of subcortical alterations, when the distinct pattern of subcortical alterations is present and particularly severe, it is associated with cognitive impairments that may contribute to persistent disability and institutionalization.

Using psychosis biotypes and the Framingham model for parsing psychosis biology.

The Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) has invested in the collection and use of multiple biomarkers in individuals with psychosis. We expect psychosis biology and its distinctive types to be reflected in the biomarkers, as they are the 'behaviors' of the brain. Like infectious diseases, we expect the etiologies of these biomarker-driven entities to be multiple and complex. Biomarkers have not yet been annotated with disease characteristics and need to be. As a model, we seek to adopt aspects of the Framingham Heart Study (FHS) to guide and organize these observations.