Over 30 years of STEP: The Pittsburgh experience with first-episode psychosis.

AIMS: For over 30 years, combined research and treatment settings in the US have been critical to conceptualizing care for first-episode psychosis (FEP). Here we describe an early example of such a context, the Services for the Treatment of Early Psychosis (STEP) clinic, which is affiliated with the University of Pittsburgh. METHODS: We describe STEP's historical roots and establishment in the early 1990s; STEP's research and treatment contributions, alongside its growth and ongoing leadership. RESULTS: Research-based clinics, like STEP, preceded and helped pave the way for the Recovery After an Initial Schizophrenia Episode project in the US and the ensuing Coordinated Specialty Care (CSC) approach, now widely adopted in the US. Early clinic-based research at STEP helped establish protocols for psychopharmacology, the relevance of effective early treatment, including psychosocial approaches, and highlighted disparities in treatment outcomes across race/ethnicity. Multidisciplinary collaboration and dialogue with consumers contributed to early treatment, combining psychosocial and pharmacological approaches. STEP adopted CSC and is situated within a bi-state Learning Health System. STEP has retained a relatively unique 5-year treatment model and exists within continuum of care ideally suited to studying psychotic illness and treatment outcomes. CONCLUSIONS: STEP remains the largest academic FEP clinic in Pennsylvania. Academic FEP clinics like STEP will have a critical role within Learning Health Systems nationally to model participatory approaches, sustain early intervention treatment quality and ongoing treatment developments.

Diagnostically distinct resting state fMRI energy distributions: A subject-specific maximum entropy modeling study.

Objective Existing neuroimaging studies of psychotic and mood disorders have reported brain activation differences (first-order properties) and altered pairwise correlation based functional connectivity (second-order properties). However, both approaches have certain limitations that can be overcome by integrating them in a pairwise maximum entropy model (MEM) that better represents a comprehensive picture of fMRI signal patterns and provides a system-wide summary measure called energy. This study examines the applicability of individual-level MEM for psychiatry and identifies image-derived model coefficients related to model parameters. Method MEMs are fit to resting state fMRI data from each individual with schizophrenia/schizoaffective disorder, bipolar disorder, and major depression (n=132) and demographically matched healthy controls (n=132) from the UK Biobank to different subsets of the default mode network (DMN) regions. Results The model satisfactorily explained observed brain energy state occurrence probabilities across all participants, and model parameters were significantly correlated with image-derived coefficients for all groups. Within clinical groups, averaged energy level distributions were higher in schizophrenia/schizoaffective disorder but lower in bipolar disorder compared to controls for both bilateral and unilateral DMN. Major depression energy distributions were higher compared to controls only in the right hemisphere DMN. Conclusions Diagnostically distinct energy states suggest that probability distributions of temporal changes in synchronously active nodes may underlie each diagnostic entity. Subject-specific MEMs allow for factoring in the individual variations compared to traditional group-level inferences, offering an improved measure of biologically meaningful correlates of brain activity that may have potential clinical utility.

Energy in functional brain states correlates with cognition in adolescent schizophrenia and healthy persons.

Adolescent-onset schizophrenia (AOS) is a relatively rare and under-studied form of schizophrenia with more severe cognitive impairments and poorer outcome compared to adult-onset schizophrenia. Several neuroimaging studies have reported alterations in regional activations that account for activity in individual regions (first-order model) and functional connectivity that reveals pairwise co-activations (second-order model) in AOS compared to controls. The pairwise maximum entropy model, also called the Ising model, can integrate both first-order and second-order terms to elucidate a comprehensive picture of neural dynamics and captures both individual and pairwise activity measures into a single quantity known as energy, which is inversely related to the probability of state occurrence. We applied the MEM framework to task functional MRI data collected on 23 AOS individuals in comparison with 53 healthy control subjects while performing the Penn Conditional Exclusion Test (PCET), which measures executive function that has been repeatedly shown to be more impaired in AOS compared to adult-onset schizophrenia. Accuracy of PCET performance was significantly reduced among AOS compared to controls as expected. Average cumulative energy achieved for a participant over the course of the fMRI negatively correlated with task performance, and the association was stronger than any first-order associations. The AOS subjects spent more time in higher energy states that represent lower probability of occurrence and were associated with impaired executive function suggesting that the neural dynamics may be less efficient compared to controls who spent more time in lower energy states occurring with higher probability and hence are more stable and efficient. The energy landscapes in both conditions featured attractors that corresponded to two distinct subnetworks, namely fronto-temporal and parieto-motor. Attractor basins were larger in the controls than in AOS; moreover, fronto-temporal basin size was significantly correlated with cognitive performance in controls but not among the AOS. The single trial trajectories for the AOS group also showed higher variability in concordance with shallow attractor basins among AOS. These findings suggest that the neural dynamics of AOS features more frequent occurrence of less probable states with narrower attractors, which lack the relation to executive function associated with attractors in control subjects suggesting a diminished capacity of AOS to generate task-effective brain states.

Gene Expressions Preferentially Influence Cortical Thickness of Human Connectome Project Atlas Parcellated Regions in First-Episode Antipsychotic-Naïve Psychoses.

Altered gene expressions may mechanistically link genetic factors with brain morphometric alterations. Existing gene expression studies have examined selected morphometric features using low-resolution atlases in medicated schizophrenia. We examined the relationship of gene expression with cortical thickness (CT), surface area (SA), and gray matter volume (GMV) of first-episode antipsychotic-naïve psychosis patients (FEAP = 85) and 81 controls, hypothesizing that gene expressions often associated with psychosis will differentially associate with different morphometric features. We explored such associations among schizophrenia and non-schizophrenia subgroups within FEAP group compared to controls. We mapped 360 Human Connectome Project atlas-based parcellations on brain MRI on to the publicly available brain gene expression data from the Allen Brain Institute collection. Significantly correlated genes were investigated using ingenuity pathway analysis to elucidate molecular pathways. CT but not SA or GMV correlated with expression of 1137 out of 15 633 genes examined controlling for age, sex, and average CT. Among these ≈19%, ≈39%, and 8% of genes were unique to FEAP, schizophrenia, and non-schizophrenia, respectively. Variants of 10 among these 1137 correlated genes previously showed genome-wide-association with schizophrenia. Molecular pathways associated with CT were axonal guidance and sphingosine pathways (common to FEAP and controls), selected inflammation pathways (unique to FEAP), synaptic modulation (unique to schizophrenia), and telomere extension (common to NSZ and healthy controls). We demonstrate that different sets of genes and molecular pathways may preferentially influence CT in different diagnostic groups. Genes with altered expressions correlating with CT and associated pathways may be targets for pathophysiological investigations and novel treatment designs.

Multipronged investigation of morphometry and connectivity of hippocampal network in relation to risk for psychosis using ultrahigh field MRI.

Hippocampal abnormalities are associated with psychosis-risk states. Given the complexity of hippocampal anatomy, we conducted a multipronged examination of morphometry of regions connected with hippocampus, and structural covariance network (SCN) and diffusion-weighted circuitry among 27 familial high-risk (FHR) individuals who were past the highest risk for conversion to psychoses and 41 healthy controls using ultrahigh-field high-resolution 7 Tesla (7T) structural and diffusion MRI data. We obtained fractional anisotropy and diffusion streams of white matter connections and examined correspondence of diffusion streams with SCN edges. Nearly 89 % of the FHR group had an axis-I disorder including 5 with schizophrenia. Therefore, we compared the entire FHR group regardless of the diagnosis (All_FHR = 27) and FHR-without-schizophrenia (n = 22) with 41 controls in this integrative multimodal analysis. We found striking volume loss in bilateral hippocampus, particularly the head, bilateral thalamus, caudate, and prefrontal regions. All_FHR and FHR-without-SZ SCNs showed significantly lower assortativity and transitivity but higher diameter compared to controls, but FHR-without-SZ SCN differed on every graph metric compared to All_FHR suggesting disarrayed network with no hippocampal hubs. Fractional anisotropy and diffusion streams were lower in FHR suggesting white matter network impairment. White matter edges showed significantly higher correspondence with SCN edges in FHR compared to controls. These differences correlated with psychopathology and cognitive measures. Our data suggest that hippocampus may be a "neural hub" contributing to psychosis risk. Higher correspondence of white matter tracts with SCN edges suggest that shared volume loss may be more coordinated among regions within the hippocampal white matter circuitry.

Threshold Selection for Brain Connectomes.

Introduction: Structural and functional brain connectomes represent macroscale data collected through techniques such as magnetic resonance imaging (MRI). Connectomes may contain noise that contributes to false-positive edges, thereby obscuring structure-function relationships and data interpretation. Thresholding procedures can be applied to reduce network density by removing low-signal edges, but there is limited consensus on appropriate selection of thresholds. This article compares existing thresholding methods and introduces a novel alternative "objective function" thresholding method. Methods: The performance of thresholding approaches, based on percolation and objective functions, is assessed by (1) computing the normalized mutual information (NMI) of community structure between a known network and a simulated, perturbed networks to which various forms of thresholding have been applied, and by (2) comparing the density and the clustering coefficient (CC) between the baseline and thresholded networks. An application to empirical data is provided. Results: Our proposed objective function-based threshold exhibits the best performance in terms of resulting in high similarity between the underlying networks and their perturbed, thresholded counterparts, as quantified by NMI and CC analysis on the simulated functional networks. Discussion: Existing network thresholding methods yield widely different results when graph metrics are subsequently computed. Thresholding based on the objective function maintains a set of edges such that the resulting network shares the community structure and clustering features present in the original network. This outcome provides a proof of principle that objective function thresholding could offer a useful approach to reducing the network density of functional connectivity data.

Age-dependent effects of schizophrenia genetic risk on cortical thickness and cortical surface area: Evaluating evidence for neurodevelopmental and neurodegenerative models of schizophrenia.

Risk for schizophrenia peaks during early adulthood, a critical period for brain development. Although several influential theoretical models have been proposed for the developmental relationship between brain pathology and clinical onset, to our knowledge, no study has directly evaluated the predictions of these models for schizophrenia developmental genetic effects on brain structure. To address this question, we introduce a framework to estimate the effects of schizophrenia genetic variation on brain structure phenotypes across the life span. Five-hundred and six participants, including 30 schizophrenia probands, 200 of their relatives (aged 12-85 years) from 32 families with at least two first-degree schizophrenia relatives, and 276 unrelated controls, underwent MRI to assess regional cortical thickness (CT) and cortical surface area (CSA). Genetic variance decomposition analyses were conducted to distinguish among schizophrenia neurogenetic effects that are most salient before schizophrenia peak age-of-risk (i.e., early neurodevelopmental effects), after peak age-of-risk (late neurodevelopmental effects), and during the later plateau of age-of-risk (neurodegenerative effects). Genetic correlations between schizophrenia and cortical traits suggested early neurodevelopmental effects for frontal and insula CSA, late neurodevelopmental effects for overall CSA and frontal, parietal, and occipital CSA, and possible neurodegenerative effects for temporal CT and parietal CSA. Importantly, these developmental neurogenetic effects were specific to schizophrenia and not found with nonpsychotic depression. Our findings highlight the potentially dynamic nature of schizophrenia genetic effects across the lifespan and emphasize the utility of integrating neuroimaging methods with developmental behavior genetic approaches to elucidate the nature and timing of risk-conferring processes in psychopathology. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Age-dependent patterns of schizophrenia genetic risk affect cognition.

Cognition shares substantial genetic overlap with schizophrenia, yet it remains unclear whether such genetic effects become significant during developmental periods of elevated risk for schizophrenia, such as the peak age of onset. We introduce an investigative framework integrating epidemiological, developmental, and genetic approaches to determine whether genetic effects shared between schizophrenia and cognition are significant across periods of differing risk for schizophrenia onset, and whether these effects are shared with depression. 771 European-American participants, including 636 (ages 15-84 years) from families with at least two first-degree relatives with schizophrenia and 135 unrelated controls, were divided into three age-risk groups based on ages relative to epidemiological age of onset patterns for schizophrenia: Pre-Peak (before peak age-of-onset: 15 to 22 years), Post-Peak (after peak age-of-onset: 23-42 years), and Plateau (during plateau of age-of-onset: over 42 years). For general cognition and 11 specific cognitive traits, we estimated genetic correlations with schizophrenia and with depression within each age-risk group. Genetic effects shared between deficits in general cognition and schizophrenia were nonsignificant before peak age of onset, yet were high and significant after peak age of onset and during the plateau of onset. These age-dependent genetic effects were largely consistent across specific cognitive traits and not transdiagnostically shared with depression. Schizophrenia genetic effects appear to influence cognitive traits in an age-dependent manner, supporting late developmental and perhaps neurodegenerative models that hypothesize increased expression of schizophrenia risk genes during and after the peak age of risk. Our findings underscore the utility of cognitive traits for tracking schizophrenia genetic effects across the lifespan.

Neuroimaging in Schizophrenia.

Schizophrenia is a chronic psychotic disorder with a lifetime prevalence of about 1%. Onset is typically in adolescence or early adulthood; characteristic symptoms include positive symptoms, negative symptoms, and impairments in cognition. Neuroimaging studies have shown substantive evidence of brain structural, functional, and neurochemical alterations that are more pronounced in the association cortex and subcortical regions. These abnormalities are not sufficiently specific to be of diagnostic value, but there may be a role for imaging techniques to provide predictions of outcome. Incorporating multimodal imaging datasets using machine learning approaches may offer better diagnostic and predictive value in schizophrenia.

Regionally Distinct Alterations in Membrane Phospholipid Metabolism in Schizophrenia: A Meta-analysis of Phosphorus Magnetic Resonance Spectroscopy Studies.

BACKGROUND: Existing data on altered membrane phospholipid metabolism in schizophrenia are diverse. We conducted a meta-analysis of studies of phosphorus magnetic resonance spectroscopy, a noninvasive imaging approach that can assess molecular biochemistry of cortex by measuring phosphomonoester (PME) and phosphodiester (PDE) levels, which can provide evidence of altered biochemical processes involved in neuropil membrane expansion and contraction in schizophrenia. METHODS: We analyzed PME and PDE data in the frontal and temporal lobes in subjects with schizophrenia from 24 peer-reviewed publications using the MAVIS package in R by building random- and fixed-effects models. Heterogeneity of effect sizes, effects of publication bias, and file drawer analysis were also assessed. RESULTS: Subjects with schizophrenia showed lower PME levels in the frontal regions (p = .008) and elevated PDE levels in the temporal regions (p < .001) with significant heterogeneity. We noted significant publication bias and file drawer effect for frontal PME and PDE and temporal PDE levels, but not for temporal PME levels. Fail-safe analysis estimated that a high number of negative studies were required to provide nonsignificant results. CONCLUSIONS: Despite methodological differences, these phosphorus magnetic resonance spectroscopy studies demonstrate regionally specific imbalance in membrane phospholipid metabolism related to neuropil in subjects with schizophrenia compared with control subjects reflecting neuropil contraction. Specifically, decreased PME levels in the frontal regions and elevated PDE levels in the temporal regions provide evidence of decreased synthesis and increased degradation of neuropil membrane, respectively. Notwithstanding significant heterogeneity and publication bias, a large number of negative studies are required to render the results of this meta-analysis nonsignificant. These findings warrant further postmortem and animal studies.

The Association of Gabapentin Use and Dose With Substance Use Disorders Prior to Inpatient Mental Health Treatment: A Cross-Sectional Study.

OBJECTIVE: To investigate the relationship between gabapentin use and dose with substance use disorders (SUDs) prior to inpatient mental health treatment. METHODS: A cross-sectional study was performed in current gabapentin users admitted to inpatient psychiatry services from December 2015 through January 2017 in a large urban teaching hospital. The primary analysis examined rates and doses of gabapentin use in relation to SUD. A multinomial logistic regression was performed to assess a predictive model for SUD in gabapentin users. The secondary analysis examined trends of off-label gabapentin use. RESULTS: Of 1,483 admissions to inpatient psychiatry services, 345 subjects (23.1%) were prescribed gabapentin as an outpatient prior to admission. Current SUD was identified in 88.1% of the sample, with 65.2% identified as polysubstance positive. Mean daily doses of gabapentin were higher in subjects with positive SUD than in those with no history of SUD. Gabapentin doses ≥ 1,800 mg/d were associated with opiate misuse (P < .001), need for detoxification (P = .004), and positive hepatitis C status (P = .001). Multinomial linear regression revealed that use of gabapentin doses ≥ 1,800 mg/d was predictive of opiate misuse and positive hepatitis C status, with 68.7% positive predictive value. CONCLUSION: High-dose gabapentin use can be predictive of opiate misuse disorder. Requests for high-dose gabapentin from patients may signal potential opioid misuse.

Neuropil contraction in relation to Complement C4 gene copy numbers in independent cohorts of adolescent-onset and young adult-onset schizophrenia patients-a pilot study.

A recent report suggested Complement 4 (C4A) gene copy numbers (GCN) as risk factors for schizophrenia. Rodent model showed association of C4 with synaptic pruning suggesting its pathophysiological significance (Sekar, A. et al. (2016)). We, therefore, predicted that C4A GCN would be positively correlated with neuropil contraction in the human brain among schizophrenia patients showing more prominent correlations in ventral regions among young adults and dorsal regions among adolescents since neuromaturation progresses dorsoventrally. Whole-brain, multi-voxel, in vivo phosphorus magnetic resonance spectroscopy (31P MRS) assessed neuropil changes by estimating levels of membrane phospholipid (MPL) precursors and catabolites. Increased MPL catabolites and/or decreased MPL precursors indexed neuropil contraction. Digital droplet PCR-based assay was used to estimate C4A and C4B GCN. We evaluated two independent cohorts (young adult-onset early-course schizophrenia (YASZ = 15) and adolescent-onset schizophrenia (AOSZ = 12) patients), and controls matched for each group, n = 22 and 15, respectively. Separate forward stepwise linear regression models with Akaike information Criterion were built for MPL catabolites and precursors. YASZ cohort: Consistent with the rodent model (Sekar, A. et al. 2016)), C4A GCN positively correlated with neuropil contraction (increased pruning/decreased formation) in the inferior frontal cortex and inferior parietal lobule. AOSZ cohort: C4A GCN positively correlated with neuropil contraction in the dorsolateral prefrontal cortex and thalamus. Exploratory analysis of C4B GCN showed positive correlation with neuropil contraction in the cerebellum and superior temporal gyrus among YASZ while AOSZ showed neuropil contraction in the prefrontal and subcortical structures. Thus, C4A and C4B GCN are associated with neuropil contraction in regions often associated with schizophrenia, and may be neuromaturationally dependent.

Emotion discrimination in humans: Its association with HSV-1 infection and its improvement with antiviral treatment.

BACKGROUND: Herpes simplex virus, type 1 (HSV-1) infects over 3.4 billion people, world-wide. Though it can cause encephalitis, in the vast majority it is asymptomatic, with lifelong latent infection in neurons. HSV-1 infected individuals have greater cognitive dysfunction than uninfected individuals, particularly persons with schizophrenia - even without encephalitis. We investigated whether HSV-1 related cognitive dysfunction is progressive or remediable. METHODS: In a prospective naturalistic follow up sample (PNFU), temporal changes in cognitive functions were analyzed in relation to baseline HSV-1 infection in persons with/without schizophrenia (N=226). Independently, in a randomized controlled trial (RCT), HSV-1 infected, clinically stabilized SZ outpatients received Valacyclovir (VAL, an HSV-1 specific antiviral, 1.5G twice daily for 16weeks) or placebo (PLA) added to standard antipsychotic treatment, using a stratified randomization design, following placebo run-in (N=67). In both samples, HSV-1 infection (seropositivity) was estimated using serum IgG antibodies. Clinical evaluations were blinded to HSV-1 or treatment status. Standardized Z scores for accuracy on eight cognitive domains were analyzed for temporal trajectories using generalized linear models (PNFU) and VAL/PLA differences compared with intent to treat analyses (RCT). RESULTS: PNFU: At baseline, HSV-1 infected participants had significantly lower accuracy scores for Emotion Identification and Discrimination (EMOD), Spatial memory and Spatial ability, regardless of SZ diagnosis (p=0.025, 0.029, 0.046, respectively). They also had significantly steeper temporal worsening for EMOD (p=0.03). RCT: EMOD improved in VAL-treated patients (p=0.048, Cohen's d=0.43). CONCLUSIONS: A proportion of age related decline in EMOD is attributable to HSV-1 infection.

Altered resting state functional connectivity in early course schizophrenia.

Impaired connectivity is proposed to underlie pathophysiology of schizophrenia. Existing studies on functional connectivity show inconsistent results. We examined functional connectivity in a clinically homogenous sample of 34 early course schizophrenia patients compared with/to 19 healthy controls using resting state functional magnetic resonance imaging (rsfMRI). Mean duration of illness for schizophrenia patients was 4 ± 1.78 years. Following a comprehensive clinical assessment, rsfMRI data were acquired using a 3.0 T magnetic resonance imaging scanner, and analyzed using FSL version 5.01 software (FMRIB's Software Library, www.fmrib.ox.ac.uk/fsl). Compared to healthy controls, schizophrenia patients had significantly decreased functional connectivity in the left fronto-parietal network, lateral and medial visual network, motor network, default mode network and auditory network. Our data suggests significant functional hypoconnectivity in selected brain networks in early schizophrenia patients compared to controls. It is likely that the observed functional hypoconnectivity may be associated with features of schizophrenia other than those examined in this study. It is possible that hypoconnectivity is necessary but not sufficient to the clinical manifestation of schizophrenia. The examination of functional connectivity as a biomarker should be extended to a wider array of disease phenotypes to better understand its significance.

Generating testable hypotheses for schizophrenia and rheumatoid arthritis pathogenesis by integrating epidemiological, genomic, and protein interaction data.

Patients with schizophrenia and their relatives have reduced prevalence of rheumatoid arthritis. Schizophrenia and rheumatoid arthritis genome-wide association studies also indicate negative genetic correlations, suggesting that there may be shared pathogenesis at the DNA level or downstream. A portion of the inverse prevalence could be attributed to pleiotropy, i.e., variants of a single nucleotide polymorphism that could confer differential risk for these disorders. To study the basis for such an interrelationship, we initially compared lists of single nucleotide polymorphisms with significant genetic associations (p < 1e-8) for schizophrenia or rheumatoid arthritis, evaluating patterns of linkage disequilibrium and apparent pleiotropic risk profiles. Single nucleotide polymorphisms that conferred risk for both schizophrenia and rheumatoid arthritis were localized solely to the extended HLA region. Among single nucleotide polymorphisms that conferred differential risk for schizophrenia and rheumatoid arthritis, the majority were localized to HLA-B, TNXB, NOTCH4, HLA-C, HCP5, MICB, PSORS1C1, and C6orf10; published functional data indicate that HLA-B and HLA-C have the most plausible pathogenic roles in both disorders. Interactomes of these eight genes were constructed from protein-protein interaction information using publicly available databases and novel computational predictions. The genes harboring apparently pleiotropic single nucleotide polymorphisms are closely connected to rheumatoid arthritis and schizophrenia associated genes through common interacting partners. A separate and independent analysis of the interactomes of rheumatoid arthritis and schizophrenia genes showed a significant overlap between the two interactomes and that they share several common pathways, motivating functional studies suggesting a relationship in the pathogenesis of schizophrenia/rheumatoid arthritis.

Longitudinal functional brain imaging study in early course schizophrenia before and after cognitive enhancement therapy.

OBJECTIVE: Schizophrenia is characterized by impaired -social and non social cognition both of which lead to functional deficits. These deficits may benefit from cognitive remediation, but the neural underpinnings of such improvements have not been clearly delineated. METHODS: We conducted a functional magnetic resonance (fMRI) study in early course schizophrenia patients randomly assigned to cognitive enhancement therapy (CET) or enriched supportive therapy (EST) and treated for two years. Imaging data over three time points including fMRI blood oxygen level dependent (BOLD) data were acquired during performance of a cognitive control paradigm, the Preparing to Overcome Prepotency (POP) task, and functional connectivity data, were analyzed. RESULTS: During the two years of treatment, CET patients showed a continual increase in BOLD activity in the right dorsolateral prefrontal cortex (DLPFC), whereas EST patients tended to show no change in prefrontal brain function throughout treatment. Increases in right DLPFC activity were modestly associated with improved neurocognition (ß = .14, p = .041), but not social cognition. Functional connectivity analyses showed reduced connectivity between the DLPFC and the anterior cingulate cortex (ACC) in CET compared to EST over the two years of treatment, which was associated with neurocognitive improvement. CONCLUSIONS: These findings suggest that CET leads to enhanced neural activity in brain regions mediating cognitive control and increased efficiency in prefrontal circuits; such changes may be related to the observed therapeutic effects of CET on neurocognitive function.