Clozapine Induces Agranulocytosis via Inflammatory and Hematopoietic Cytokine Induction of the JAK-STAT Signaling Pathway: Evidence From Network Pharmacology and Molecular Docking.

Background: Clozapine exhibits significant therapeutic efficacy in schizophrenia, especially treatment-resistant schizophrenia. However, clozapine can cause agranulocytosis, a fatal adverse effect, and the aim of this study is to explore this mechanism based on network pharmacology and molecular docking.

Method: Six and two databases were used to identify targets associated with clozapine and agranulocytosis, respectively.

Network pharmacology and molecular docking to explore mechanisms of clozapine-induced cardiac arrest.

Background: Clozapine is superior to all other antipsychotics in treating schizophrenia in terms of its curative efficacy; however, this drug is prescribed only as a last resort in the treatment of schizophrenia, given its potential to induce cardiac arrest. The mechanism of clozapine-induced cardiac arrest remains unclear, so we aimed to elucidate the potential mechanisms of clozapine-induced cardiac arrest using network pharmacology and molecular docking.

Methods: We identified and analyzed the overlap between potential cardiac arrest-related target genes and clozapine target genes.

Exploring the molecular targets of fingolimod and siponimod for treating the impaired cognition of schizophrenia using network pharmacology and molecular docking.

The treatment of cognitive impairment in schizophrenia is an unaddressed need due to the absence of novel treatments. Recent studies demonstrated that fingolimod and siponimod have neuroprotective effects in several neuropsychiatric disorders; however, their pharmacological mechanisms are unclear. The objective of this study was to identify potential molecular mechanisms of fingolimod and siponimod for improving cognition of schizophrenia through network pharmacology and molecular docking.

Molecular mechanisms of quetiapine bidirectional regulation of bipolar depression and mania based on network pharmacology and molecular docking: Evidence from computational biology.

Background: Quetiapine monotherapy is recommended as the first-line option for acute mania and acute bipolar depression. However, the mechanism of action of quetiapine is unclear. Network pharmacology and molecular docking were employed to determine the molecular mechanisms of quetiapine bidirectional regulation of bipolar depression and mania.

Homotopic functional connectivity disruptions in schizophrenia and their associated gene expression.

It has been revealed that abnormal voxel-mirrored homotopic connectivity (VMHC) is present in patients with schizophrenia, yet there are inconsistencies in the relevant findings. Moreover, little is known about their association with brain gene expression profiles. In this study, transcription-neuroimaging association analyses using gene expression data from Allen Human Brain Atlas and case-control VMHC differences from both the discovery (meta-analysis, including 9 studies with a total of 386 patients and 357 controls) and replication (separate group-level comparisons within two datasets, including a total of 258 patients and 287 controls) phases were performed to identify genes associated with VMHC alterations.

Microglia and cognitive impairment in schizophrenia: translating scientific progress into novel therapeutic interventions.

Cognitive impairment is a core clinical feature of schizophrenia, exerting profound adverse effects on social functioning and quality of life in a large proportion of patients with schizophrenia. However, the mechanisms underlying the pathogenesis of schizophrenia-related cognitive impairment are not well understood. Microglia, the primary resident macrophages in the brain, have been shown to play important roles in psychiatric disorders, including schizophrenia.

Psychosis brain subtypes validated in first-episode cohorts and related to illness remission: results from the PHENOM consortium.

Using machine learning, we recently decomposed the neuroanatomical heterogeneity of established schizophrenia to discover two volumetric subgroups-a 'lower brain volume' subgroup (SG1) and an 'higher striatal volume' subgroup (SG2) with otherwise normal brain structure. In this study, we investigated whether the MRI signatures of these subgroups were also already present at the time of the first-episode of psychosis (FEP) and whether they were related to clinical presentation and clinical remission over 1-, 3-, and 5-years. We included 572 FEP and 424 healthy controls (HC) from 4 sites (Sao Paulo, Santander, London, Melbourne) of the PHENOM consortium.

Baseline global brain structural and functional alterations at the time of symptom onset can predict subsequent cognitive deterioration in drug-naïve first-episode schizophrenia patients: Evidence from a follow-up study.

Alterations in the global brain gray matter volume (gGMV) and global functional connectivity density (gFCD) play a pivotal role in the cognitive impairment and further deterioration in schizophrenia. This study aimed to assess the correlation between alterations in the gGMV and gFCD at baseline (ΔgGMV and ΔgFCD), and the subsequent alterations of cognitive function in schizophrenia patients after 2-year antipsychotic treatment. Global-brain magnetic resonance imaging scans were acquired from 877 drug-naïve, first-episode schizophrenia patients at baseline and after two years of antipsychotic treatment with adequate dosage and duration, and 200 healthy controls.

Testing the validity and reliability of the Chinese version of the Staden schizophrenia anxiety rating scale.

Accurate assessment of anxiety disorders and their symptomatology in schizophrenic patients is important for prognosis and treatment. Measuring anxiety on the traditional anxiety assessment scales such as the Hamilton Anxiety Rating (HAMA) Scale or the self-rating depression scale (SAS) is challenging and often considered unsuitable for assessing anxiety symptoms in patients with schizophrenia. The Staden schizophrenia anxiety rating scale (S-SARS) has been shown to reliably measure specified and undifferentiated anxiety in schizophrenia.

Schizophrenia Imaging Signatures and Their Associations With Cognition, Psychopathology, and Genetics in the General Population.

Objective: The prevalence and significance of schizophrenia-related phenotypes at the population level is debated in the literature. Here, the authors assessed whether two recently reported neuroanatomical signatures of schizophrenia-signature 1, with widespread reduction of gray matter volume, and signature 2, with increased striatal volume-could be replicated in an independent schizophrenia sample, and investigated whether expression of these signatures can be detected at the population level and how they relate to cognition, psychosis spectrum symptoms, and schizophrenia genetic risk.

Methods: This cross-sectional study used an independent schizophrenia-control sample (N=347; ages 16-57 years) for replication of imaging signatures, and then examined two independent population-level data sets: typically developing youths and youths with psychosis spectrum symptoms in the Philadelphia Neurodevelopmental Cohort (N=359; ages 16-23 years) and adults in the UK Biobank study (N=836; ages 44-50 years).

Differential effects of alcohol-drinking patterns on the structure and function of the brain and cognitive performance in young adult drinkers: A pilot study.

Introduction: This study was aimed to determine how different patterns of alcohol consumption drive changes to brain structure and function and their correlation with cognitive impairments in young adult alcohol drinkers.

Methods: In this study, we enrolled five groups participants and defined as: long-term abstinence from alcohol (LA), binge drinking (BD), long-term low dosage alcohol consumption but exceeding the safety drinking dosage (LD), long-term alcohol consumption of damaging dosage (LDD), and long-term heavy drinking (HD). All participants underwent magnetic resonance imaging (MRI) and functional MRI (fMRI) to acquire data on brain structure and function, including gray matter volume (GMV), fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), functional connectivity (FC), and brain network properties.

Deep Generative Medical Image Harmonization for Improving Cross-Site Generalization in Deep Learning Predictors.

Background: In the medical imaging domain, deep learning-based methods have yet to see widespread clinical adoption, in part due to limited generalization performance across different imaging devices and acquisition protocols. The deviation between estimated brain age and biological age is an established biomarker of brain health and such models may benefit from increased cross-site generalizability.

Purpose: To develop and evaluate a deep learning-based image harmonization method to improve cross-site generalizability of deep learning age prediction.

Clozapine induces metformin-resistant prediabetes/diabetes that is associated with poor clinical efficacy in patients with early treatment-resistant schizophrenia.

Background: Two distinct subtypes of treatment-resistant schizophrenia (TRS) have been recently reported, including early-treatment resistance (E-TR) and late-treatment resistance (L-TR). This study was to assess clozapine-induced metformin-resistant prediabetes/diabetes and its correlation with clinical efficacy in schizophrenia E-TR subtype.

Methods: This prospective cohort study enrolled 230 patients with schizophrenia E-TR subtype and they were treated with adequate doses of clozapine for 16 weeks, during which patients with prediabetes/diabetes were assigned to receive add-on metformin.

Novel Risk Loci Associated With Genetic Risk for Bipolar Disorder Among Han Chinese Individuals: A Genome-Wide Association Study and Meta-analysis.

Importance: The genetic basis of bipolar disorder (BD) in Han Chinese individuals is not fully understood.

Objective: To explore the genetic basis of BD in the Han Chinese population.

Design, Setting, And Participants: A genome-wide association study (GWAS), followed by independent replication, was conducted to identify BD risk loci in Han Chinese individuals.

MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14 468 individuals worldwide.

Deep learning has emerged as a powerful approach to constructing imaging signatures of normal brain ageing as well as of various neuropathological processes associated with brain diseases. In particular, MRI-derived brain age has been used as a comprehensive biomarker of brain health that can identify both advanced and resilient ageing individuals via deviations from typical brain ageing. Imaging signatures of various brain diseases, including schizophrenia and Alzheimer's disease, have also been identified using machine learning.

Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning.

Neurobiological heterogeneity in schizophrenia is poorly understood and confounds current analyses. We investigated neuroanatomical subtypes in a multi-institutional multi-ethnic cohort, using novel semi-supervised machine learning methods designed to discover patterns associated with disease rather than normal anatomical variation. Structural MRI and clinical measures in established schizophrenia (n = 307) and healthy controls (n = 364) were analysed across three sites of PHENOM (Psychosis Heterogeneity Evaluated via Dimensional Neuroimaging) consortium.

Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan.

As medical imaging enters its information era and presents rapidly increasing needs for big data analytics, robust pooling and harmonization of imaging data across diverse cohorts with varying acquisition protocols have become critical. We describe a comprehensive effort that merges and harmonizes a large-scale dataset of 10,477 structural brain MRI scans from participants without a known neurological or psychiatric disorder from 18 different studies that represent geographic diversity. We use this dataset and multi-atlas-based image processing methods to obtain a hierarchical partition of the brain from larger anatomical regions to individual cortical and deep structures and derive age trends of brain structure through the lifespan (3-96 years old).

Polymorphisms in Dopaminergic Genes in Schizophrenia and Their Implications in Motor Deficits and Antipsychotic Treatment.

Dopaminergic system dysfunction is involved in schizophrenia (SCZ) pathogenesis and can mediate SCZ-related motor disorders. Recent studies have gradually revealed that SCZ susceptibility and the associated motor symptoms can be mediated by genetic factors, including dopaminergic genes. More importantly, polymorphisms in these genes are associated with both antipsychotic drug sensitivity and adverse effects.