Transport mechanism and pharmacology of the human GlyT1.

The glycine transporter 1 (GlyT1) plays a crucial role in the regulation of both inhibitory and excitatory neurotransmission by removing glycine from the synaptic cleft. Given its close association with glutamate/glycine co-activated NMDA receptors (NMDARs), GlyT1 has emerged as a central target for the treatment of schizophrenia, which is often linked to hypofunctional NMDARs. Here, we report the cryo-EM structures of GlyT1 bound with substrate glycine and drugs ALX-5407, SSR504734, and PF-03463275. These structures, captured at three fundamental states of the transport cycle-outward-facing, occluded, and inward-facing-enable us to illustrate a comprehensive blueprint of the conformational change associated with glycine reuptake. Additionally, we identified three specific pockets accommodating drugs, providing clear insights into the structural basis of their inhibitory mechanism and selectivity. Collectively, these structures offer significant insights into the transport mechanism and recognition of substrate and anti-schizophrenia drugs, thus providing a platform to design small molecules to treat schizophrenia.

Predictive Processing: A Circuit Approach to Psychosis.

Predictive processing is a computational framework that aims to explain how the brain processes sensory information by making predictions about the environment and minimizing prediction errors. It can also be used to explain some of the key symptoms of psychotic disorders such as schizophrenia. In recent years, substantial advances have been made in our understanding of the neuronal circuitry that underlies predictive processing in cortex. In this review, we summarize these findings and how they might relate to psychosis and to observed cell type-specific effects of antipsychotic drugs. We argue that quantifying the effects of antipsychotic drugs on specific neuronal circuit elements is a promising approach to understanding not only the mechanism of action of antipsychotic drugs but also psychosis. Finally, we outline some of the key experiments that should be done. The aims of this review are to provide an overview of the current circuit-based approaches to psychosis and to encourage further research in this direction.

Regulation of Zbp1 by miR-99b-5p in microglia controls the development of schizophrenia-like symptoms in mice.

Current approaches to the treatment of schizophrenia have mainly focused on the protein-coding part of the genome; in this context, the roles of microRNAs have received less attention. In the present study, we analyze the microRNAome in the blood and postmortem brains of schizophrenia patients, showing that the expression of miR-99b-5p is downregulated in both the prefrontal cortex and blood of patients. Lowering the amount of miR-99b-5p in mice leads to both schizophrenia-like phenotypes and inflammatory processes that are linked to synaptic pruning in microglia. The microglial miR-99b-5p-supressed inflammatory response requires Z-DNA binding protein 1 (Zbp1), which we identify as a novel miR-99b-5p target. Antisense oligonucleotides against Zbp1 ameliorate the pathological effects of miR-99b-5p inhibition. Our findings indicate that a novel miR-99b-5p-Zbp1 pathway in microglia might contribute to the pathogenesis of schizophrenia.

Genetic mechanisms for impaired synaptic plasticity in schizophrenia revealed by computational modeling.

Schizophrenia phenotypes are suggestive of impaired cortical plasticity in the disease, but the mechanisms of these deficits are unknown. Genomic association studies have implicated a large number of genes that regulate neuromodulation and plasticity, indicating that the plasticity deficits have a genetic origin. Here, we used biochemically detailed computational modeling of postsynaptic plasticity to investigate how schizophrenia-associated genes regulate long-term potentiation (LTP) and depression (LTD). We combined our model with data from postmortem RNA expression studies (CommonMind gene-expression datasets) to assess the consequences of altered expression of plasticity-regulating genes for the amplitude of LTP and LTD. Our results show that the expression alterations observed post mortem, especially those in the anterior cingulate cortex, lead to impaired protein kinase A (PKA)-pathway-mediated LTP in synapses containing GluR1 receptors. We validated these findings using a genotyped electroencephalogram (EEG) dataset where polygenic risk scores for synaptic and ion channel-encoding genes as well as modulation of visual evoked potentials were determined for 286 healthy controls. Our results provide a possible genetic mechanism for plasticity impairments in schizophrenia, which can lead to improved understanding and, ultimately, treatment of the disorder.

Analysis of Evolutionary Conservation, Expression Level, and Genetic Association at a Genome-wide Scale Reveals Heterogeneity Across Polygenic Phenotypes.

Understanding the expression level and evolutionary rate of associated genes with human polygenic diseases provides crucial insights into their disease-contributing roles. In this work, we leveraged genome-wide association studies (GWASs) to investigate the relationship between the genetic association and both the evolutionary rate (dN/dS) and expression level of human genes associated with the two polygenic diseases of schizophrenia and coronary artery disease. Our findings highlight a distinct variation in these relationships between the two diseases. Genes associated with both diseases exhibit a significantly greater variance in evolutionary rate compared to those implicated in monogenic diseases. Expanding our analyses to 4,756 complex traits in the GWAS atlas database, we unraveled distinct trait categories with a unique interplay among the evolutionary rate, expression level, and genetic association of human genes. In most polygenic traits, highly expressed genes were more associated with the polygenic phenotypes compared to lowly expressed genes. About 69% of polygenic traits displayed a negative correlation between genetic association and evolutionary rate, while approximately 30% of these traits showed a positive correlation between genetic association and evolutionary rate. Our results demonstrate the presence of a spectrum among complex traits, shaped by natural selection. Notably, at opposite ends of this spectrum, we find metabolic traits being more likely influenced by purifying selection, and immunological traits that are more likely shaped by positive selection. We further established the polygenic evolution portal (evopolygen.de) as a resource for investigating relationships and generating hypotheses in the field of human polygenic trait evolution.

Shared patterns of glial transcriptional dysregulation link Huntington's disease and schizophrenia.

Huntington's disease and juvenile-onset schizophrenia have long been regarded as distinct disorders. However, both manifest cell-intrinsic abnormalities in glial differentiation, with resultant astrocytic dysfunction and hypomyelination. To assess whether a common mechanism might underlie the similar glial pathology of these otherwise disparate conditions, we used comparative correlation network approaches to analyse RNA-sequencing data from human glial progenitor cells (hGPCs) produced from disease-derived pluripotent stem cells. We identified gene sets preserved between Huntington's disease and schizophrenia hGPCs yet distinct from normal controls that included 174 highly connected genes in the shared disease-associated network, focusing on genes involved in synaptic signalling. These synaptic genes were largely suppressed in both schizophrenia and Huntington's disease hGPCs, and gene regulatory network analysis identified a core set of upstream regulators of this network, of which OLIG2 and TCF7L2 were prominent. Among their downstream targets, ADGRL3, a modulator of glutamatergic synapses, was notably suppressed in both schizophrenia and Huntington's disease hGPCs. Chromatin immunoprecipitation sequencing confirmed that OLIG2 and TCF7L2 each bound to the regulatory region of ADGRL3, whose expression was then rescued by lentiviral overexpression of these transcription factors. These data suggest that the disease-associated suppression of OLIG2 and TCF7L2-dependent transcription of glutamate signalling regulators may impair glial receptivity to neuronal glutamate. The consequent loss of activity-dependent mobilization of hGPCs may yield deficient oligodendrocyte production, and hence the hypomyelination noted in these disorders, as well as the disrupted astrocytic differentiation and attendant synaptic dysfunction associated with each. Together, these data highlight the importance of convergent glial molecular pathology in both the pathogenesis and phenotypic similarities of two otherwise unrelated disorders, Huntington's disease and schizophrenia.

Adaptive coding of reward in schizophrenia, its change over time and relationship to apathy.

Adaptive coding of reward is the process by which neurons adapt their response to the context of available compensations. Higher rewards lead to a stronger brain response, but the increase of the response depends on the range of available rewards. A steeper increase is observed in a narrow range and a more gradual slope in a wider range. In schizophrenia, adaptive coding appears to be affected in different domains, especially in the reward domain. Here, we tested adaptive coding of reward in a large group of patients with schizophrenia (n = 86) and control subjects (n = 66). We assessed: (i) the association between adaptive coding deficits and symptoms; (ii) the longitudinal stability of deficits (the same task was performed 3 months apart); and (iii) the stability of results between two experimental sites. We used functional MRI and the monetary incentive delay task to assess adaptation of participants to two different reward ranges: a narrow range and a wide range. We used a region-of-interest analysis to evaluate adaptation within striatal and visual regions. Patients and control subjects underwent a full demographic and clinical assessment. We found reduced adaptive coding in patients, with a decreased slope in the narrow reward range with respect to that of control participants, in striatal but not visual regions. This pattern was observed at both research sites. Upon retesting, patients increased their narrow-range slopes, showing improved adaptive coding, whereas control subjects slightly reduced them. At retesting, patients with overly steep slopes in the narrow range also showed higher levels of negative symptoms. Our data confirm deficits in reward adaptation in schizophrenia and reveal an effect of practice in patients, leading to improvement, with steeper slopes upon retesting. However, in some patients, an excessively steep slope may result in poor discriminability of larger rewards, owing to early saturation of the brain response. Together, the loss of precision of reward representation in new (first exposure, underadaptation) and more familiar (retest, overadaptation) situations might contribute to the multiple motivational symptoms in schizophrenia.

The identification of novel schizophrenia-related metabolites using untargeted lipidomics.

Human lipidome still remains largely unexplored among Chinese schizophrenia patients. We aimed to identify novel lipid molecules associated with schizophrenia and cognition among schizophrenia patients. The current study included 96 male schizophrenia patients and 96 gender-matched healthy controls. Untargeted lipidomics profiling was conducted among all participants. Logistic regression models were used to assess metabolite associations with schizophrenia. We further assessed the incremental predictive value of identified metabolites beyond conventional risk factors on schizophrenia status. In addition, identified metabolites were tested for association with cognitive function among schizophrenia patients using linear regression models. A total of 34 metabolites were associated with schizophrenia. Addition of these identified metabolites to age, body mass index, smoking, and education significantly increased the risk reclassification of schizophrenia. Among the schizophrenia-related metabolites, 10 were further associated with cognition in schizophrenia patients, including four metabolites associated with immediate memory, two metabolites associated with delayed memory, three metabolites associated with visuospatial, four metabolites associated with language, one metabolite associated with attention, and two metabolites associated with the total score. Our findings provide novel insights into the biological mechanisms of schizophrenia, suggesting that lipid metabolites may serve as potential diagnostic or therapeutic targets of schizophrenia.

Dysfunction of thalamocortical circuits in early-onset schizophrenia.

Previous studies have demonstrated that the thalamus is involved in multiple functional circuits in participants with schizophrenia. However, less is known about the thalamocortical circuit in the rare subtype of early-onset schizophrenia. A total of 110 participants with early-onset schizophrenia (47 antipsychotic-naive patients) and 70 matched healthy controls were recruited and underwent resting-state functional and diffusion-weighted magnetic resonance imaging scans. A data-driven parcellation method that combined the high spatial resolution of diffusion magnetic resonance imaging and the high sensitivity of functional magnetic resonance imaging was used to divide the thalamus. Next, the functional connectivity between each thalamic subdivision and the cortex/cerebellum was investigated. Compared to healthy controls, individuals with early-onset schizophrenia exhibited hypoconnectivity between subdivisions of the thalamus and the frontoparietal network, visual network, ventral attention network, somatomotor network and cerebellum, and hyperconnectivity between subdivisions of thalamus and the parahippocampal and temporal gyrus, which were included in limbic network. The functional connectivity between the right posterior cingulate cortex and 1 subdivision of the thalamus (region of interest 1) was positively correlated with the general psychopathology scale score. This study showed that the specific thalamocortical dysconnection in individuals with early-onset schizophrenia involves the prefrontal, auditory and visual cortices, and cerebellum. This study identified thalamocortical connectivity as a potential biomarker and treatment target for early-onset schizophrenia.

The associations of peripheral interleukin alterations and hippocampal subfield volume deficits in schizophrenia.

The hippocampus is one of the brain regions most vulnerable to inflammatory insults, and the relationships between peripheral inflammation and hippocampal subfields in patients with schizophrenia remain unclear. In this study, forty-six stably medicated patients with schizophrenia and 48 demographically matched healthy controls (HCs) were recruited. The serum levels of IL - 1ß, IL-6, IL-10, and IL-12p70 were measured, and 3D high-resolution T1-weighted magnetic resonance imaging was performed. The IL levels and hippocampal subfield volumes were both compared between patients and HCs. The associations of altered IL levels with hippocampal subfield volumes were assessed in patients. Patients with schizophrenia demonstrated higher serum levels of IL-6 and IL-10 but lower levels of IL-12p70 than HCs. In patients, the levels of IL-6 were positively correlated with the volumes of the left granule cell layer of the dentate gyrus (GCL) and cornu Ammonis (CA) 4, while the levels of IL-10 were negatively correlated with the volumes of those subfields. IL-6 and IL-10 might have antagonistic roles in atrophy of the left GCL and CA4. This suggests a complexity of peripheral cytokine dysregulation and the potential for its selective effects on hippocampal substructures, which might be related to the pathophysiology of schizophrenia.

Resolving heterogeneity in schizophrenia, bipolar I disorder, and attention-deficit/hyperactivity disorder through individualized structural covariance network analysis.

Disruptions in large-scale brain connectivity are hypothesized to contribute to psychiatric disorders, including schizophrenia, bipolar I disorder, and attention-deficit/hyperactivity disorder. However, high inter-individual variation among patients with psychiatric disorders hinders achievement of unified findings. To this end, we adopted a newly proposed method to resolve heterogeneity of differential structural covariance network in schizophrenia, bipolar I disorder, and attention-deficit/hyperactivity disorder. This method could infer individualized structural covariance aberrance by assessing the deviation from healthy controls. T1-weighted anatomical images of 114 patients with psychiatric disorders (schizophrenia: n = 37; bipolar I disorder: n = 37; attention-deficit/hyperactivity disorder: n = 37) and 110 healthy controls were analyzed to obtain individualized differential structural covariance network. Patients exhibited tremendous heterogeneity in profiles of individualized differential structural covariance network. Despite notable heterogeneity, patients with the same disorder shared altered edges at network level. Moreover, individualized differential structural covariance network uncovered two distinct psychiatric subtypes with opposite differences in structural covariance edges, that were otherwise obscured when patients were merged, compared with healthy controls. These results provide new insights into heterogeneity and have implications for the nosology in psychiatric disorders.

Using normative modeling to assess pharmacological treatment effect on brain state in patients with schizophrenia.

Quantifying individual differences in neuroimaging metrics is attracting interest in clinical studies with mental disorders. Schizophrenia is diagnosed exclusively based on symptoms, and the biological heterogeneity makes it difficult to accurately assess pharmacological treatment effects on the brain state. Using the Cambridge Centre for Ageing and Neuroscience data set, we built normative models of brain states and mapped the deviations of the brain characteristics of each patient, to test whether deviations were related to symptoms, and further investigated the pharmacological treatment effect on deviation distributions. Specifically, we found that the patients can be divided into 2 groups: the normalized group had a normalization trend and milder symptoms at baseline, and the other group showed a more severe deviation trend. The baseline severity of the depression as well as the overall symptoms could predict the deviation of the static characteristics for the dorsal and ventral attention networks after treatment. In contrast, the positive symptoms could predict the deviations of the dynamic fluctuations for the default mode and dorsal attention networks after treatment. This work evaluates the effect of pharmacological treatment on static and dynamic brain states using an individualized approach, which may assist in understanding the heterogeneity of the illness pathology as well as the treatment response.

The relationship between gray/white matter contrast and cognitive performance in first-episode schizophrenia.

Previous postmortem brain studies have revealed disturbed myelination in the intracortical regions in patients with schizophrenia, possibly reflecting anomalous brain maturational processes. However, it currently remains unclear whether this anomalous myelination is already present in early illness stages and/or progresses during the course of the illness. In this magnetic resonance imaging study, we examined gray/white matter contrast (GWC) as a potential marker of intracortical myelination in 63 first-episode schizophrenia (FESz) patients and 77 healthy controls (HC). Furthermore, we investigated the relationships between GWC findings and clinical/cognitive variables in FESz patients. GWC in the bilateral temporal, parietal, occipital, and insular regions was significantly higher in FESz patients than in HC, which was partly associated with the durations of illness and medication, the onset age, and lower executive and verbal learning performances. Because higher GWC implicates lower myelin in the deeper layers of the cortex, these results suggest that schizophrenia patients have less intracortical myelin at the time of their first psychotic episode, which underlies lower cognitive performance in early illness stages.

Neural dysfunction underlying working memory processing at different stages of the illness course in schizophrenia: a comparative meta-analysis.

Schizophrenia, as a chronic and persistent disorder, exhibits working memory deficits across various stages of the disorder, yet the neural mechanisms underlying these deficits remain elusive with inconsistent neuroimaging findings. We aimed to compare the brain functional changes of working memory in patients at different stages: clinical high risk, first-episode psychosis, and long-term schizophrenia, using meta-analyses of functional magnetic resonance imaging studies. Following a systematic literature search, 56 whole-brain task-based functional magnetic resonance imaging studies (15 for clinical high risk, 16 for first-episode psychosis, and 25 for long-term schizophrenia) were included. The separate and pooled neurofunctional mechanisms among clinical high risk, first-episode psychosis, and long-term schizophrenia were generated by Seed-based d Mapping toolbox. The clinical high risk and first-episode psychosis groups exhibited overlapping hypoactivation in the right inferior parietal lobule, right middle frontal gyrus, and left superior parietal lobule, indicating key lesion sites in the early phase of schizophrenia. Individuals with first-episode psychosis showed lower activation in left inferior parietal lobule than those with long-term schizophrenia, reflecting a possible recovery process or more neural inefficiency. We concluded that SCZ represent as a continuum in the early stage of illness progression, while the neural bases are inversely changed with the development of illness course to long-term course.

Functional myelin in cognition and neurodevelopmental disorders.

In vertebrates, oligodendrocytes (OLs) are glial cells of the central nervous system (CNS) responsible for the formation of the myelin sheath that surrounds the axons of neurons. The myelin sheath plays a crucial role in the transmission of neuronal information by promoting the rapid saltatory conduction of action potentials and providing neurons with structural and metabolic support. Saltatory conduction, first described in the peripheral nervous system (PNS), is now generally recognized as a universal evolutionary innovation to respond quickly to the environment: myelin helps us think and act fast. Nevertheless, the role of myelin in the central nervous system, especially in the brain, may not be primarily focused on accelerating conduction speed but rather on ensuring precision. Its principal function could be to coordinate various neuronal networks, promoting their synchronization through oscillations (or rhythms) relevant for specific information processing tasks. Interestingly, myelin has been directly involved in different types of cognitive processes relying on brain oscillations, and myelin plasticity is currently considered to be part of the fundamental mechanisms for memory formation and maintenance. However, despite ample evidence showing the involvement of myelin in cognition and neurodevelopmental disorders characterized by cognitive impairments, the link between myelin, brain oscillations, cognition and disease is not yet fully understood. In this review, we aim to highlight what is known and what remains to be explored to understand the role of myelin in high order brain processes.

Insights for disease modeling from single-cell transcriptomics of iPSC-derived Ngn2-induced neurons and astrocytes across differentiation time and co-culture.

BACKGROUND: Trans-differentiation of human-induced pluripotent stem cells into neurons via Ngn2-induction (hiPSC-N) has become an efficient system to quickly generate neurons a likely significant advance for disease modeling and in vitro assay development. Recent single-cell interrogation of Ngn2-induced neurons, however, has revealed some similarities to unexpected neuronal lineages. Similarly, a straightforward method to generate hiPSC-derived astrocytes (hiPSC-A) for the study of neuropsychiatric disorders has also been described. RESULTS: Here, we examine the homogeneity and similarity of hiPSC-N and hiPSC-A to their in vivo counterparts, the impact of different lengths of time post Ngn2 induction on hiPSC-N (15 or 21 days), and the impact of hiPSC-N/hiPSC-A co-culture. Leveraging the wealth of existing public single-cell RNA-seq (scRNA-seq) data in Ngn2-induced neurons and in vivo data from the developing brain, we provide perspectives on the lineage origins and maturation of hiPSC-N and hiPSC-A. While induction protocols in different labs produce consistent cell type profiles, both hiPSC-N and hiPSC-A show significant heterogeneity and similarity to multiple in vivo cell fates, and both more precisely approximate their in vivo counterparts when co-cultured. Gene expression data from the hiPSC-N show enrichment of genes linked to schizophrenia (SZ) and autism spectrum disorders (ASD) as has been previously shown for neural stem cells and neurons. These overrepresentations of disease genes are strongest in our system at early times (day 15) in Ngn2-induction/maturation of neurons, when we also observe the greatest similarity to early in vivo excitatory neurons. We have assembled this new scRNA-seq data along with the public data explored here as an integrated biologist-friendly web-resource for researchers seeking to understand this system more deeply: https://nemoanalytics.org/p?l=DasEtAlNGN2&g=NES . CONCLUSIONS: While overall we support the use of the investigated cellular models for the study of neuropsychiatric disease, we also identify important limitations. We hope that this work will contribute to understanding and optimizing cellular modeling for complex brain disorders.

Enhancing schizophrenia phenotype prediction from genotype data through knowledge-driven deep neural network models.

This article explores deep learning model design, drawing inspiration from the omnigenic model and genetic heterogeneity concepts, to improve schizophrenia prediction using genotype data. It introduces an innovative three-step approach leveraging neural networks' capabilities to efficiently handle genetic interactions. A locally connected network initially routes input data from variants to their corresponding genes. The second step employs an Encoder-Decoder to capture relationships among identified genes. The final model integrates knowledge from the first two and incorporates a parallel component to consider the effects of additional genes. This expansion enhances prediction scores by considering a larger number of genes. Trained models achieved an average AUC of 0.83, surpassing other genotype-trained models and matching gene expression dataset-based approaches. Additionally, tests on held-out sets reported an average sensitivity of 0.72 and an accuracy of 0.76, aligning with schizophrenia heritability predictions. Moreover, the study addresses genetic heterogeneity challenges by considering diverse population subsets.

Beyond dopamine: Novel strategies for schizophrenia treatment.

Despite extensive research efforts aimed at discovering novel antipsychotic compounds, a satisfactory pharmacological strategy for schizophrenia treatment remains elusive. All the currently available drugs act by modulating dopaminergic neurotransmission, leading to insufficient management of the negative and cognitive symptoms of the disorder. Due to these challenges, several attempts have been made to design agents with innovative, non-dopaminergic mechanisms of action. Consequently, a number of promising compounds are currently progressing through phases 2 and 3 of clinical trials. This review aims to examine the rationale behind the most promising of these strategies while simultaneously providing a comprehensive survey of study results. We describe the versatility behind the cholinergic neurotransmission modulation through the activation of M1 and M4 receptors, exemplified by the prospective drug candidate KarXT. Our discussion extends to the innovative approach of activating TAAR1 receptors via ulotaront, along with the promising outcomes of iclepertin, a GlyT-1 inhibitor with the potential to become the first treatment option for cognitive impairment associated with schizophrenia. Finally, we evaluate the 5-HT2A antagonist paradigm, assessing two recently developed serotonergic agents, pimavanserin and roluperidone. We present the latest advancements in developing novel solutions to the complex challenges posed by schizophrenia, offering an additional perspective on the diverse investigated drug candidates.

Triglyceride-rich lipoprotein, remnant cholesterol, and apolipoproteins CII, CIII, and E in patients with schizophrenia.

Patients with schizophrenia show a disproportionally increased risk of cardiovascular disease. Hypertriglyceridemia is prevalent in this population; however, how this relates to levels of remnant cholesterol, triglyceride (TG)-rich lipoprotein (TRL) particle size and composition, TG turnover, and apolipoprotein (apo) and angiopoietin-like protein (ANGPTL) concentrations is unknown. Fasting levels of cholesterol (total [TC], LDL-C, HDL-C, non-HDL-C and remnant cholesterol) and TG were determined in 110 patients diagnosed with schizophrenia, and 46 healthy controls. TRL particle size, concentration and composition, and ß-hydroxybutyrate (TG turnover marker) were assessed by NMR. Levels of apoCII, apoCIII, apoE, ANGPTL3, ANGPTL4, and ANGPTL8 were measured by ELISA, and apoCII, apoCIII and apoE were further evaluated in HDL and non-HDL fractions. Patients with schizophrenia had significantly elevated TG, TG:apoB ratio, non-HDL-C, remnant cholesterol, non-HDL-apoCII and non-HDL-apoCIII, and HDL-apoE (all P < 0.05), lower HDL-C and apoA-I (all P < 0.001), and comparable apoB, TC, TC:apoB ratio, LDL-C, ß-hydroxybutyrate, ANGPTL3, ANGPTL4 and ANGPTL8 to healthy controls. Patients had a 12.0- and 2.5-fold increase in the concentration of large and medium TRL particles respectively, but similar cholesterol:TG ratio within each particle. Plasma TG, remnant cholesterol, and large and medium TRL particle concentrations correlated strongly with apoCII, apoCIII, and apoE in the non-HDL fraction, and with apoCIII and apoE in the HDL fraction in patients with schizophrenia. Differences in TG, HDL-C, TRL particle concentrations, apoCIII, and apoE persisted after adjustment for conventional risk factors. These results are consistent with impaired TRL lipolysis and clearance in patients with schizophrenia which may be responsive to targeting apoCIII.