What genes are differentially expressed in individuals with schizophrenia? A systematic review

Functional Connectome Hierarchy in Schizotypy and Its Associations With Expression of Schizophrenia-Related Genes

BACKGROUND AND HYPOTHESIS

Schizotypy has been conceptualized as a continuum of symptoms with marked genetic, neurobiological, and sensory-cognitive overlaps to schizophrenia. Hierarchical organization represents a general organizing principle for both the cortical connectome supporting sensation-to-cognition continuum and gene expression variability across the cortex. However, a mapping of connectome hierarchy to schizotypy remains to be established. Importantly, the underlying changes of the cortical connectome hierarchy that mechanistically link gene expressions to schizotypy are unclear.

STUDY DESIGN

The present study applied novel connectome gradient on resting-state fMRI data from 1013 healthy young adults to investigate schizotypy-associated sensorimotor-to-transmodal connectome hierarchy and assessed its similarity with the connectome hierarchy of schizophrenia. Furthermore, normative and differential postmortem gene expression data were utilized to examine transcriptional profiles linked to schizotypy-associated connectome hierarchy.

STUDY RESULTS

We found that schizotypy was associated with a compressed functional connectome hierarchy. Moreover, the pattern of schizotypy-related hierarchy exhibited a positive correlation with the connectome hierarchy observed in schizophrenia. This pattern was closely colocated with the expression of schizophrenia-related genes, with the correlated genes being enriched in transsynaptic, receptor signaling and calcium ion binding.

CONCLUSIONS

The compressed connectome hierarchy suggests diminished functional system differentiation, providing a novel and holistic system-level basis for various sensory-cognition deficits in schizotypy. Importantly, its linkage with schizophrenia-altered hierarchy and schizophrenia-related gene expression yields new insights into the neurobiological continuum of psychosis. It also provides mechanistic insight into how gene variation may drive alterations in functional hierarchy, mediating biological vulnerability of schizotypy to schizophrenia.

Polygenicity in a box: Copy number variants, neural circuit development, and neurodevelopmental disorders

Clinically defined neurodevelopmental disorders (cd-NDDs), including Autistic Spectrum Disorder (ASD) and Schizophrenia (Scz), are primarily polygenic: Multiple risk genes distributed across the genome, in potentially infinite combinations, account for variable pathology. Polygenicity raises a fundamental question: Can "core" cd-NDD pathogenic mechanisms be identified given this genomic complexity? With the right models and analytic targets, a distinct class of polygenic mutations-Copy Number Variants (CNVs): contiguous gene deletions or duplications associated with cd-NDD risk-provide a singular opportunity to define cd-NDD pathology. CNVs orthologous to those that confer cd-NDD risk have been engineered in animals as well as human stem cells. Using these tools, one can determine how altered function of multiple genes cause serial stumbles over cell biological steps typically taken to build optimal "polygenic" neural circuits. Thus, cd-NDD pathology may be a consequence of polygenic deviations-stumbles-that exceed limits of adaptive variation for key developmental steps.

Integrated Transcriptome Analysis Reveals Novel Molecular Signatures for Schizophrenia Characterization

Schizophrenia (SCZ) is a complex psychiatric disorder presenting challenges for characterization. The current study aimed to identify and evaluate disease-responsive essential genes (DREGs) to enhance the molecular characterization of SCZ. RNA-sequencing data from PsychENCODE (536 SCZ patients, 832 controls) and peripheral blood transcriptome data from 144 recruited subjects (59 SCZ patients, 6 non-SCZ psychiatric patients, 79 controls) are analyzed. Shared differential expression genes are obtained using three algorithms. Support vector machine (SVM)-based recursive feature elimination is employed to identify DREGs. The biological relevance of these DREGs is examined through protein-protein interaction network, pathway enrichment, polygenic scoring, and brain tissue expression. Key DREGs are validated in SCZ animal models. A DREGs-based machine-learning model for SCZ characterization is developed and its performance is assessed using multiple datasets. The analysis identified 184 DREGs forming an interconnected network involved in synaptic plasticity, inflammation, neuronal development, and neurotransmission. DREGs exhibited distinct expression in SCZ-related brain regions and animal models. Their genetic contributions are comparable to genome-wide polygenic risk scores. The DREG-based SVM model demonstrated high performance (AUC 85% for SCZ characterization, 79% for specificity). These findings provide new insights into the molecular mechanisms underlying SCZ and emphasize the potential of DREGs in improving SCZ characterization.

Exploring the Intersection of Schizophrenia, Machine Learning, and Genomics: Scoping Review

BACKGROUND

An increasing body of literature highlights the integration of machine learning with genomic data in psychiatry, particularly for complex mental health disorders such as schizophrenia. These advanced techniques offer promising potential for uncovering various facets of these disorders. A comprehensive review of the current applications of machine learning in conjunction with genomic data within this context can significantly enhance our understanding of the current state of research and its future directions.

OBJECTIVE

This study aims to conduct a systematic scoping review of the use of machine learning algorithms with genomic data in the field of schizophrenia.

METHODS

To conduct a systematic scoping review, a search was performed in the electronic databases MEDLINE, Web of Science, PsycNet (PsycINFO), and Google Scholar from 2013 to 2024. Studies at the intersection of schizophrenia, genomic data, and machine learning were evaluated.

RESULTS

The literature search identified 2437 eligible articles after removing duplicates. Following abstract screening, 143 full-text articles were assessed, and 121 were subsequently excluded. Therefore, 21 studies were thoroughly assessed. Various machine learning algorithms were used in the identified studies, with support vector machines being the most common. The studies notably used genomic data to predict schizophrenia, identify schizophrenia features, discover drugs, classify schizophrenia amongst other mental health disorders, and predict the quality of life of patients.

CONCLUSIONS

Several high-quality studies were identified. Yet, the application of machine learning with genomic data in the context of schizophrenia remains limited. Future research is essential to further evaluate the portability of these models and to explore their potential clinical applications.

Current progress in understanding schizophrenia using genomics and pluripotent stem cells: A meta-analytical overview

Schizophrenia (SCZ) is a complex, heritable and polygenic neuropsychiatric disease, which disables the patients as well as decreases their life expectancy and quality of life. Common and rare variants studies on SCZ subjects have provided >100 genomic loci that hold importance in the context of SCZ pathophysiology. Transcriptomic studies from clinical samples have informed about the differentially expressed genes (DEGs) and non-coding RNAs in SCZ patients. Despite these advancements, no causative genes for SCZ were found and hence SCZ is difficult to recapitulate in animal models. In the last decade, induced Pluripotent Stem Cells (iPSCs)-based models have helped in understanding the neural phenotypes of SCZ by studying patient iPSC-derived 2D neuronal cultures and 3D brain organoids. Here, we have aimed to provide a simplistic overview of the current progress and advancements after synthesizing the enormous literature on SCZ genetics and SCZ iPSC-based models. Although further understanding of SCZ genetics and pathophysiological mechanisms using these technological advancements is required, the recent approaches have allowed to delineate important cellular mechanisms and biological pathways affected in SCZ.

Upregulated solute-carrier family genes in the hippocampus of schizophrenia can be rescued by antipsychotic medications

BACKGROUND AND HYPOTHESIS

Our previous studies have found that functional changes in the hippocampal circuit from dentate gyrus (DG) to cornu ammonis 3 and 1 (CA3, CA1) are highly associated with schizophrenia (SZ). However, no studies have explored the genetic expression across the three and two human hippocampal subfields (DG-CA3-CA1 and CA3-CA1) between subjects with SZ and healthy controls (CT).

STUDY DESIGN

We matched cohorts between CT (n = 13) and SZ (n = 13). Among SZ, 6 subjects were on antipsychotics (AP) while 7 were off AP. We combined RNA-seq data from all three and two hippocampal subfields and performed differentially expressed gene analyses across DG-CA3-CA1 and CA3-CA1 affected by either SZ or AP.

STUDY RESULTS

We found that differentially expressed genes (DEGs) from effects of SZ and AP across DG-CA3-CA1 and CA3-CA1 were highly associated with gene ontology terms related to hormonal and immune signaling, cellular mitosis and apoptosis, ion and amino acid transports, and protein modification and degradation. Additionally, we found that multiple genes related to solute-carrier family and immune signaling were significantly upregulated across DG-CA3-CA1 and CA3-CA1 in patients with SZ relative to CT, and AP consistently and robustly repressed the expression of these upregulated genes in the DG-CA3-CA1 and CA3-CA1 from subjects with SZ.

CONCLUSIONS

Together, these data suggest that the upregulated solute-carrier family genes in the hippocampus might have important roles in the pathophysiology of SZ, and that AP may reduce the symptoms of psychosis in SZ via rescuing the solute-carrier gene expression.

Role of different omics data in the diagnosis of schizophrenia disorder: A machine learning study

Schizophrenia is a serious mental disorder that affects millions of people worldwide. This disorder slowly disintegrates thinking ability and changes behaviours of patients. These patients will show some psychotic symptoms such as hallucinations, delusions, thought disorder and movement disorder. These symptoms are in common with some other psychiatric disorders such as bipolar disorder, major depressive disorder and mood spectrum disorder. As patients would require immediate treatment, an on-time diagnosis is critical. This study explores the use of omics data in diagnosis of schizophrenia. Transcriptome, miRNA and epigenome data are used in diagnosis of patients with schizophrenia with the aid of machine learning algorithms. As the data is in high dimension, mutual information and feature importance are independently used for selecting relevant features for the study. Selected sets of features (biomarkers) are individually used with different machine learning algorithms and their performances are compared to select the best-performing model. This study shows that the top 140 miRNA features selected using mutual information along with support vector machines give the highest accuracy (0.86 ± 0.07) in the diagnosis of schizophrenia. All reported accuracies are validated using 5-fold cross validation. They are further validated using leave one out cross validation and the accuracies are reported in the supplementary material.

Accelerated Cortical Thinning in Schizophrenia Is Associated With Rare and Common Predisposing Variation to Schizophrenia and Neurodevelopmental Disorders

BACKGROUND

Schizophrenia is a highly heritable disorder characterized by increased cortical thinning throughout the life span. Studies have reported a shared genetic basis between schizophrenia and cortical thickness. However, no genes whose expression is related to abnormal cortical thinning in schizophrenia have been identified.

METHODS

We conducted linear mixed models to estimate the rates of accelerated cortical thinning across 68 regions from the Desikan-Killiany atlas in individuals with schizophrenia compared with healthy control participants from a large longitudinal sample (ncases = 169 and ncontrols = 298, ages 16-70 years). We studied the correlation between gene expression data from the Allen Human Brain Atlas and accelerated thinning estimates across cortical regions. Finally, we explored the functional and genetic underpinnings of the genes that contribute most to accelerated thinning.

RESULTS

We found a global pattern of accelerated cortical thinning in individuals with schizophrenia compared with healthy control participants. Genes underexpressed in cortical regions that exhibit this accelerated thinning were downregulated in several psychiatric disorders and were enriched for both common and rare disrupting variation for schizophrenia and neurodevelopmental disorders. In contrast, none of these enrichments were observed for baseline cross-sectional cortical thickness differences.

CONCLUSIONS

Our findings suggest that accelerated cortical thinning, rather than cortical thickness alone, serves as an informative phenotype for neurodevelopmental disruptions in schizophrenia. We highlight the genetic and transcriptomic correlates of this accelerated cortical thinning, emphasizing the need for future longitudinal studies to elucidate the role of genetic variation and the temporal-spatial dynamics of gene expression in brain development and aging in schizophrenia.

The impact of sex on gene expression in the brain of schizophrenic patients: a systematic review and meta-analysis of transcriptomic studies

BACKGROUND

Schizophrenia is a severe neuropsychiatric disorder characterized by altered perception, mood, and behavior that profoundly impacts patients and society despite its relatively low prevalence. Sex-based differences have been described in schizophrenia epidemiology, symptomatology and outcomes. Different studies explored the impact of schizophrenia in the brain transcriptome, however we lack a consensus transcriptomic profile that considers sex and differentiates specific cerebral regions.

METHODS

We performed a systematic review on bulk RNA-sequencing studies of post-mortem brain samples. Then, we fulfilled differential expression analysis on each study and summarized their results with regions-specific meta-analyses (prefrontal cortex and hippocampus) and a global all-studies meta-analysis. Finally, we used the consensus transcriptomic profiles to functionally characterize the impact of schizophrenia in males and females by protein-protein interaction networks, enriched biological processes and dysregulated transcription factors.

RESULTS

We discovered the sex-based dysregulation of 265 genes in the prefrontal cortex, 1.414 genes in the hippocampus and 66 genes in the all-studies meta-analyses. The functional characterization of these gene sets unveiled increased processes related to immune response functions in the prefrontal cortex in male and the hippocampus in female schizophrenia patients and the overexpression of genes related to neurotransmission and synapses in the prefrontal cortex of female schizophrenia patients. Considering a meta-analysis of all brain regions available, we encountered the relative overexpression of genes related to synaptic plasticity and transmission in females and the overexpression of genes involved in organizing genetic information and protein folding in male schizophrenia patients. The protein-protein interaction networks and transcription factors activity analyses supported these sex-based profiles.

CONCLUSIONS

Our results report multiple sex-based transcriptomic alterations in specific brain regions of schizophrenia patients, which provides new insight into the role of sex in schizophrenia. Moreover, we unveil a partial overlapping of inflammatory processes in the prefrontal cortex of males and the hippocampus of females.

Multimorbidity in Severe Mental Illness as Part of the Neurodevelopmental Continuum: Physical Health-Related Endophenotypes of Schizophrenia-A Narrative Review

BACKGROUND

The majority of deaths in patients with schizophrenia and other severe mental illnesses (SMIs) are caused by natural causes, such as cardiovascular diseases (CVDs). The increased risk of CVD and other somatic diseases in SMIs cannot be fully explained by the contribution of traditional risk factors, behavioral risk factors, patients' lifestyle peculiarities, and the influence of antipsychotics. The present review has the following main objectives: (1) to aggregate evidence that neurodevelopmental disorders are the basis of SMIs; (2) to provide a review of studies that have addressed the shared genetic architecture of SMI and cardiovascular disease; and (3) to propose and substantiate the consideration of somatic diseases as independent endophenotypes of SMIs, which will make it possible to place the research of somatic diseases in SMIs within the framework of the concepts of the "neurodevelopmental continuum and gradient" and "endophenotype".

METHODS

A comprehensive literature search was performed on 1 July 2024. The search was performed using PubMed and Google Scholar databases up to June 2024.

RESULTS

The current literature reveals considerable overlap between the genetic susceptibility loci for SMIs and CVDs. We propose that somatic diseases observed in SMIs that have a shared genetic architecture with SMIs can be considered distinct physical health-related endophenotypes.

CONCLUSIONS

In this narrative review, the results of recent studies of CVDs in SMIs are summarized. Reframing schizophrenia as a multisystem disease should contribute to the activation of new research on somatic diseases in SMIs.

Human-Induced Pluripotent Stem Cell (iPSC)-Derived GABAergic Neuron Differentiation in Bipolar Disorder

Bipolar disorder (BP) is a recurring psychiatric condition characterized by alternating episodes of low energy (depressions) followed by manias (high energy). Cortical network activity produced by GABAergic interneurons may be critical in maintaining the balance in excitatory/inhibitory activity in the brain during development. Initially, GABAergic signaling is excitatory; with maturation, these cells undergo a functional switch that converts GABAA channels from depolarizing (excitatory) to hyperpolarizing (inhibitory), which is controlled by the intracellular concentration of two chloride transporters. The earliest, NKCC1, promotes chloride entry into the cell and depolarization, while the second (KCC2) stimulates movement of chloride from the neuron, hyperpolarizing it. Perturbations in the timing or expression of NKCC1/KCC2 may affect essential morphogenetic events including cell proliferation, migration, synaptogenesis and plasticity, and thereby the structure and function of the cortex. We derived induced pluripotent stem cells (iPSC) from BP patients and undiagnosed control (C) individuals, then modified a differentiation protocol to form GABAergic interneurons, harvesting cells at sequential stages of differentiation. qRT-PCR and RNA sequencing indicated that after six weeks of differentiation, controls transiently expressed high levels of NKCC1. Using multi-electrode array (MEA) analysis, we observed that BP neurons exhibit increased firing, network bursting and decreased synchrony compared to C. Understanding GABA signaling in differentiation may identify novel approaches and new targets for treatment of neuropsychiatric disorders such as BP.

Mutual effects of gestational diabetes and schizophrenia: how can one promote the other?: A review

Although the physical complications of gestational diabetes mellitus (GDM) are well known, emerging evidence suggests a significant link with psychiatric conditions such as schizophrenia (SCZ). This review aimed to explore the extent, nature, and implications of the association between GDM and SCZ, exploring how the 2 conditions may reciprocally influence each other. We conducted a comprehensive literature review and, analyzed clinical and mechanistic evidence supporting the mutual effects of GDM and SCZ. This review examined factors such as neurodevelopment and the impact of antipsychotics. The study found that Maternal GDM increases the risk of SCZ in offspring. Conversely, women with SCZ were more prone to hyperglycemic pregnancies. The research highlights significant regional variations in GDM prevalence, with the highest rate in the Middle East, North Africa, and South-East Asia regions. These regional variations may have an impact on the epidemiology of SCZ. Furthermore, this review identifies the potential biological and environmental mechanisms underlying these associations. There is a bidirectional relationship between GDM and SCZ, with each disorder potentially exacerbating the others. This relationship has significant implications for maternal and offspring health, particularly in regions with high GDM prevalence. These findings underline the need for integrated care approaches for women with SCZ during pregnancy and the importance of monitoring and managing GDM to mitigate the risk of SCZ in the offspring. Notably, this study recognizes the need for further research to fully understand these complex interactions and their implications for healthcare.

Genetic knowledge and attitudes towards genetic testing among final-year medical students at a public university in Ecuador

Background

Genetics plays a crucial role in the field of medicine, offering numerous applications. However, health professionals often have insufficient knowledge in this area. Therefore, it is essential to provide appropriate genetics education during university studies.

Aim

This study aimed to assess the knowledge and attitudes towards genetic testing among final-year medical students at a public university in Ecuador.

Methods

A cross-sectional study was conducted involving final-year medical students from a public university in Ecuador. The third version of the Genetic Literacy and Attitudes Survey was administered between April and May 2022. The study examined sociodemographic characteristics, genetic knowledge, and attitudes towards genetic testing.

Results

The study included 153 medical students, of which 58.2% identified as female. Most participants fell within the age range of 22 to 25 years old (85.0%). Regarding genetic knowledge, three-quarters of the participants (75.2%) demonstrated intermediate proficiency, while only 9.80% possessed a high level of knowledge. Attitudes towards the clinical and therapeutic applications of genetics, scientific advancements, access to conventional medicine, and other related topics were found to be appropriate.

Conclusion

The findings suggest that most final-year medical students at a public university in Ecuador have intermediate genetic knowledge and hold appropriate attitudes towards genetic testing. However, higher education institutions should conduct a comprehensive analysis and restructure their curricula to better prepare students for the medical and technological challenges of the 21st century.

Cortical gene expression architecture links healthy neurodevelopment to the imaging, transcriptomics and genetics of autism and schizophrenia

Human brain organization involves the coordinated expression of thousands of genes. For example, the first principal component (C1) of cortical transcription identifies a hierarchy from sensorimotor to association regions. In this study, optimized processing of the Allen Human Brain Atlas revealed two new components of cortical gene expression architecture, C2 and C3, which are distinctively enriched for neuronal, metabolic and immune processes, specific cell types and cytoarchitectonics, and genetic variants associated with intelligence. Using additional datasets (PsychENCODE, Allen Cell Atlas and BrainSpan), we found that C1-C3 represent generalizable transcriptional programs that are coordinated within cells and differentially phased during fetal and postnatal development. Autism spectrum disorder and schizophrenia were specifically associated with C1/C2 and C3, respectively, across neuroimaging, differential expression and genome-wide association studies. Evidence converged especially in support of C3 as a normative transcriptional program for adolescent brain development, which can lead to atypical supragranular cortical connectivity in people at high genetic risk for schizophrenia.

lute: estimating the cell composition of heterogeneous tissue with varying cell sizes using gene expression

Relative cell type fraction estimates in bulk RNA-sequencing data are important to control for cell composition differences across heterogenous tissue samples. Current computational tools estimate relative RNA abundances rather than cell type proportions in tissues with varying cell sizes, leading to biased estimates. We present lute, a computational tool to accurately deconvolute cell types with varying sizes. Our software wraps existing deconvolution algorithms in a standardized framework. Using simulated and real datasets, we demonstrate how lute adjusts for differences in cell sizes to improve the accuracy of cell composition. Software is available from https://bioconductor.org/packages/lute.

The 3-hit animal models of schizophrenia: Improving strategy to decipher and treat the disease?

Schizophrenia is a complex disease related to combination and interactions between genetic and environmental factors, with an epigenetic influence. After the development of the first mono-factorial animal models of schizophrenia (1-hit), that reproduced patterns of either positive, negative and/or cognitive symptoms, more complex models combining two factors (2-hit) have been developed to better fit with the multifactorial etiology of the disease. In the two past decades, a new way to design animal models of schizophrenia have emerged by adding a third hit (3-hit). This review aims to discuss the relevance of the risk factors chosen for the tuning of the 3-hit animal models, as well as the validities measurements and their contribution to schizophrenia understanding. We intended to establish a comprehensive overview to help in the choice of factors for the design of multiple-hit animal models of schizophrenia.

The schizophrenia syndrome, circa 2024: What we know and how that informs its nature

With new data about different aspects of schizophrenia being continually generated, it becomes necessary to periodically revisit exactly what we know. Along with a need to review what we currently know about schizophrenia, there is an equal imperative to evaluate the construct itself. With these objectives, we undertook an iterative, multi-phase process involving fifty international experts in the field, with each step building on learnings from the prior one. This review assembles currently established findings about schizophrenia (construct, etiology, pathophysiology, clinical expression, treatment) and posits what they reveal about its nature. Schizophrenia is a heritable, complex, multi-dimensional syndrome with varying degrees of psychotic, negative, cognitive, mood, and motor manifestations. The illness exhibits a remitting and relapsing course, with varying degrees of recovery among affected individuals with most experiencing significant social and functional impairment. Genetic risk factors likely include thousands of common genetic variants that each have a small impact on an individual's risk and a plethora of rare gene variants that have a larger individual impact on risk. Their biological effects are concentrated in the brain and many of the same variants also increase the risk of other psychiatric disorders such as bipolar disorder, autism, and other neurodevelopmental conditions. Environmental risk factors include but are not limited to urban residence in childhood, migration, older paternal age at birth, cannabis use, childhood trauma, antenatal maternal infection, and perinatal hypoxia. Structural, functional, and neurochemical brain alterations implicate multiple regions and functional circuits. Dopamine D-2 receptor antagonists and partial agonists improve psychotic symptoms and reduce risk of relapse. Certain psychological and psychosocial interventions are beneficial. Early intervention can reduce treatment delay and improve outcomes. Schizophrenia is increasingly considered to be a heterogeneous syndrome and not a singular disease entity. There is no necessary or sufficient etiology, pathology, set of clinical features, or treatment that fully circumscribes this syndrome. A single, common pathophysiological pathway appears unlikely. The boundaries of schizophrenia remain fuzzy, suggesting the absence of a categorical fit and need to reconceptualize it as a broader, multi-dimensional and/or spectrum construct.

Influence of TMX2-CTNND1 polymorphism on cortical thickness in schizophrenia patients and unaffected siblings: an exploratory study based on target region sequencing

OBJECTIVE

The advancement of neuroimaging and genetic research has revealed the presence of morphological abnormalities and numerous risk genes, along with their associations. We aimed to estimate magnetic resonance imaging-derived cortical thickness across multiple brain regions.

METHODS

The cortical thickness of 129 schizophrenia patients, 42 of their unaffected siblings, and 112 healthy controls was measured and the candidate genes were sequenced. Comparisons were made of cortical thickness (including 68 regions of the Desikan-Killiany Atlas) and genetic variants (in 108 risk genes for schizophrenia) among the three groups, and correlation analyses were performed regarding cortical thickness, clinical symptoms, cognitive tests (such as the N-back task and the logical memory test), and genetic variants.

RESULTS

Schizophrenia patients had significantly thinner bilateral frontal, temporal, and parietal gyri than healthy controls and unaffected siblings. Association analyses in target genes showed that four single nucleotide variants (SNVs) were significantly associated with schizophrenia, including thioredoxin-related transmembrane protein 2-catenin, cadherin-associated protein, delta 1 (SNV20673) (positive false discovery rate [PFDR] = 0.008) and centromere protein M (rs35542507, rs41277477, rs73165153) (PFDR = 0.030). Additionally, cortical thickness in the right pars triangularis was lower in carriers of the SNV20673 variant than in non-carriers (PFDR = 0.048). Finally, a positive correlation was found between right pars triangularis cortical thickness and logical memory in schizophrenia patients (r = 0.199, p = 0.032).

CONCLUSIONS

This study identified regional morphological abnormalities in schizophrenia, including the right homologue of Broca's area, which was associated with a risk variant that affected delta-1 catenin and logical memory. These findings suggest a potential association between candidate gene loci, cortical thickness, and schizophrenia.

Transcriptomics : Approaches to Quantifying Gene Expression and Their Application to Studying the Human Brain

To date, the field of transcriptomics has been characterized by rapid methods development and technological advancement, with new technologies continuously rendering older ones obsolete.This chapter traces the evolution of approaches to quantifying gene expression and provides an overall view of the current state of the field of transcriptomics, its applications to the study of the human brain, and its place in the broader emerging multiomics landscape.

Microglia at the Tripartite Synapse during Postnatal Development: Implications for Autism Spectrum Disorders and Schizophrenia

Synapses are the fundamental structures of neural circuits that control brain functions and behavioral and cognitive processes. Synapses undergo formation, maturation, and elimination mainly during postnatal development via a complex interplay with neighboring astrocytes and microglia that, by shaping neural connectivity, may have a crucial role in the strengthening and weakening of synaptic functions, that is, the functional plasticity of synapses. Indeed, an increasing number of studies have unveiled the roles of microglia and astrocytes in synapse formation, maturation, and elimination as well as in regulating synaptic function. Over the past 15 years, the mechanisms underlying the microglia- and astrocytes-dependent regulation of synaptic plasticity have been thoroughly studied, and researchers have reported that the disruption of these glial cells in early postnatal development may underlie the cause of synaptic dysfunction that leads to neurodevelopmental disorders such as autism spectrum disorder (ASD) and schizophrenia.

Molecular mapping of a core transcriptional signature of microglia-specific genes in schizophrenia

Besides playing a central role in neuroinflammation, microglia regulate synaptic development and is involved in plasticity. Converging lines of evidence suggest that these different processes play a critical role in schizophrenia. Furthermore, previous studies reported altered transcription of microglia genes in schizophrenia, while microglia itself seems to be involved in the etiopathology of the disease. However, the regional specificity of these brain transcriptional abnormalities remains unclear. Moreover, it is unknown whether brain and peripheral expression of microglia genes are related. Thus, we investigated the expression of a pre-registered list of 10 genes from a core signature of human microglia both at brain and peripheral levels. We included 9 independent Gene Expression Omnibus datasets (764 samples obtained from 266 individuals with schizophrenia and 237 healthy controls) from 8 different brain regions and 3 peripheral tissues. We report evidence of a widespread transcriptional alteration of microglia genes both in brain tissues (we observed a decreased expression in the cerebellum, associative striatum, hippocampus, and parietal cortex of individuals with schizophrenia compared with healthy controls) and whole blood (characterized by a mixed altered expression pattern). Our results suggest that brain underexpression of microglia genes may represent a candidate transcriptional signature for schizophrenia. Moreover, the dual brain-whole blood transcriptional alterations of microglia/macrophage genes identified support the model of schizophrenia as a whole-body disorder and lend weight to the use of blood samples as a potential source of biological peripheral biomarkers.

A novel therapeutic approach to prevent Helicobacter pylori induced gastric cancer using networking biology, molecular docking, and simulation approaches

Helicobacter pylori infects 50% of the world population and in 80% of cases, the infection progresses to the point where an ulcer develops leading to gastric cancer (GC). This study aimed to prevent GC by predicting Hub genes that are inducing GC. Furthermore, the study objective was to screen inhibitory molecules that block the function of predicted genes through several biophysical approaches. These proteins, such as Mucin 4 (MUC4) and Baculoviral IAP repeat containing 3 (BIRC3), had LogFC values of 2.28 and 3.39, respectively, and were found to be substantially expressed in those who had H. pylori infection. The MUC4 and BIRC3 inhibit apoptosis of infected cells and promote cancerous cell survival. The proteins were examined for their Physico-chemical characteristics, 3D structure and secondary structure analysis, solvent assessable surface area (SASA), active site identification, and network analysis. The MUC4 and BIRC3 expression was inhibited by docking eighty different compounds collected from the ZINC database. Fifty-seven compounds were successfully docked into the active site resulting in the lowest binding energy scores. The ZINC585267910 and ZINC585268691 compounds showed the lowest binding energy of -8.5 kcal/mol for MUC4 and -7.1 kcal/mol for BIRC3, respectively, and were considered best-docked solutions for molecular dynamics simulations. The mean root mean square deviation (RMSD) value for the ZINC585267910-MUC4 complex was 0.86 Å and the ZINC585268691-BIRC3 complex was 1.01 Å. The net MM/GBSA energy value of the ZINC585267910-MUC4 complex estimated was -46.84 kcal/mol and that of the ZINC585268691-BIRC3 complex was -44.84 kcal/mol. In a nutshell, the compounds might be investigated further as an inhibitor of the said proteins to stop the progress of GC induced by H. pylori.Communicated by Ramaswamy H. Sarma.

Lateral Septal Circuits Govern Schizophrenia-Like Effects of Ketamine on Social Behavior

Schizophrenia is marked by poor social functioning that can have a severe impact on quality of life and independence, but the underlying neural circuity is not well understood. Here we used a translational model of subanesthetic ketamine in mice to delineate neural pathways in the brain linked to social deficits in schizophrenia. Mice treated with chronic ketamine (30 mg/kg/day for 10 days) exhibit profound social and sensorimotor deficits as previously reported. Using three- dimensional c-Fos immunolabeling and volume imaging (iDISCO), we show that ketamine treatment resulted in hypoactivation of the lateral septum (LS) in response to social stimuli. Chemogenetic activation of the LS rescued social deficits after ketamine treatment, while chemogenetic inhibition of previously active populations in the LS (i.e. social engram neurons) recapitulated social deficits in ketamine-naïve mice. We then examined the translatome of LS social engram neurons and found that ketamine treatment dysregulated genes implicated in neuronal excitability and apoptosis, which may contribute to LS hypoactivation. We also identified 38 differentially expressed genes (DEGs) in common with human schizophrenia, including those involved in mitochondrial function, apoptosis, and neuroinflammatory pathways. Chemogenetic activation of LS social engram neurons induced downstream activity in the ventral part of the basolateral amygdala, subparafascicular nucleus of the thalamus, intercalated amygdalar nucleus, olfactory areas, and dentate gyrus, and it also reduces connectivity of the LS with the piriform cortex and caudate-putamen. In sum, schizophrenia-like social deficits may emerge via changes in the intrinsic excitability of a discrete subpopulation of LS neurons that serve as a central hub to coordinate social behavior via downstream projections to reward, fear extinction, motor and sensory processing regions of the brain.

Schizophrenia in Women: Clinical Considerations

Men and women, for biologic and sociocultural reasons, differ in the nature of their risks for schizophrenia and also in their care needs. Women with schizophrenia have several reproduction-associated risks and care needs that require special clinical consideration. They also have several specific risks related to antipsychotics and gender-associated needs not necessarily related to biology. These require clinicians' diagnostic acumen, treatment skills, cultural sensitivity, and advocacy know-how. Although this does not pertain to everyone, awareness on the part of clinicians is essential. This article addresses the current evidence for difference.

Up-Regulation of S100 Gene Family in Brain Samples of a Subgroup of Individuals with Schizophrenia: Meta-analysis

The S100 proteins family is known to affect neuroinflammation and astrocyte activation, which have been suggested to be contributors to the pathogenesis of schizophrenia. We conducted a systematic meta-analysis of S100 genes differential expression in postmortem samples of patients with schizophrenia vs. healthy controls, following the commonly used Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Twelve microarray datasets met the inclusion criteria (overall 511 samples, 253 schizophrenia and 258 controls were analyzed). Nine out of 21 genes were significantly up-regulated or with tendency for up-regulation. A per-sample fold change analysis indicated that the S100 genes' up-regulation was concentrated in a subgroup of the patients. None of the genes have been found to be down-regulated. ANXA3, which encodes Annexin 3 protein and was associated with neuroinflammation, was up-regulated and positively correlated with the S100 genes' expression pattern. In addition, astrocytes and endothelial cell markers were significantly correlated with S100A8 expression. S100 correlation with ANXA3 and endothelial cell markers suggests that the up-regulation we detected reflects increased inflammation. However, it might also reflect astrocytes abundance or activation. The fact that S100 proteins were shown to be up-regulated in blood samples and other body fluids of patients with schizophrenia suggests a potential role as biomarkers, which might help disease subtyping, and the development of etiological treatments for immune dysregulation in schizophrenia.

Influence of antipsychotic medications on hyperlipidemia risk in patients with schizophrenia: evidence from a population-based cohort study and in vitro hepatic lipid homeostasis gene expression

Introduction

Schizophrenia increases the risk of mortality and cardiovascular disease (CVD) risk. However, the correlation between antipsychotics (APs) and CVD remains controversial. Hyperlipidemia is a significant risk factor for CVD.

Methods

We conducted a nationwide population-based retrospective cohort study to investigate the effects of APs on the risk of hyperlipidemia and lipid homeostasis gene expression. We used data from the Longitudinal Health Insurance Database of Taiwan on new-onset schizophrenia patients and a comparison cohort without schizophrenia. We used a Cox proportional hazards regression model to analyze the differences in hyperlipidemia development between the two cohorts. Furthermore, we examined the effects of APs on the hepatic expression of lipid homeostasis-related genes.

Results

After adjusting for potential interrelated confounding factors, the case group (N = 4,533) was found to have a higher hyperlipidemia risk than the control cohort (N = 4,533) [adjusted hazard ratio (aHR), 1.30, p < 0.001]. Patients with schizophrenia without APs had a significantly higher risk of hyperlipidemia (aHR, 2.16; p < 0.001). However, patients receiving APs had a significantly lower risk of hyperlipidemia than patients not receiving APs (all aHR ≤ 0.42, p < 0.001). First-generation antipsychotics (FGAs) induce the expression of hepatic lipid catabolism genes in an in vitro model.

Discussion

Patients with schizophrenia had a higher risk of hyperlipidemia than controls; however, compared with non-treated patients, AP users had a lower risk of hyperlipidemia. Early diagnosis and management of hyperlipidemia may help prevent CVD.

Patients with schizophrenia and bipolar disorder display a similar global gene expression signature in whole blood that reflects elevated proportion of immature neutrophil cells with association to lipid changes

Schizophrenia (SCZ) and bipolar disorder (BD) share clinical characteristics, genetic susceptibility, and immune alterations. We aimed to identify differential transcriptional patterns in peripheral blood cells of patients with SCZ or BD versus healthy controls (HC). We analyzed microarray-based global gene expression data in whole blood from a cohort of SCZ (N = 329), BD (N = 203) and HC (N = 189). In total, 65 genes were significantly differentially expressed in SCZ and 125 in BD, as compared to HC, with similar ratio of up- and downregulated genes in both disorders. Among the top differentially expressed genes, we found an innate immunity signature that was shared between SCZ and BD, consisting of a cluster of upregulated genes (e.g., OLFM4, ELANE, BPI and MPO) that indicate an increased fraction of immature neutrophils. Several of these genes displayed sex differences in the expression pattern, and post-hoc analysis demonstrated a positive correlation with triglyceride and a negative correlation with HDL cholesterol. We found that many of the downregulated genes in SCZ and BD were associated with smoking. These findings of neutrophil granulocyte-associated transcriptome signatures in both SCZ and BD point at altered innate immunity pathways with association to lipid changes and potential for clinical translation.

Dysregulation of Long Intergenic Non-Coding RNA Expression in the Schizophrenia Brain

BACKGROUND

Transcriptomic studies of the brains of schizophrenia (SZ) patients have produced abundant but largely inconsistent findings about the disorders pathophysiology. These inconsistencies might stem not only from the heterogeneous nature of the disorder, but also from the unbalanced focus on particular cortical regions and protein-coding genes. Compared to protein-coding transcripts, long intergenic non-coding RNA (lincRNA) display substantially greater brain region and disease response specificity, positioning them as prospective indicators of SZ-associated alterations. Further, a growing understanding of the systemic character of the disorder calls for a more systematic screening involving multiple diverse brain regions.

AIM

We aimed to identify and interpret alterations of the lincRNA expression profiles in SZ by examining the transcriptomes of 35 brain regions.

METHODS

We measured the transcriptome of 35 brain regions dissected from eight adult brain specimens, four SZ patients, and four healthy controls, using high-throughput RNA sequencing. Analysis of these data yielded 861 annotated human lincRNAs passing the detection threshold.

RESULTS

Of the 861 detected lincRNA, 135 showed significant region-dependent expression alterations in SZ (two-way ANOVA, BH-adjusted p 0.05) and 37 additionally showed significant differential expression between HC and SZ individuals in at least one region (post hoc Tukey test, p 0.05). For these 37 differentially expressed lincRNAs (DELs), 88% of the differences occurred in a cluster of brain regions containing axon-rich brain regions and cerebellum. Functional annotation of the DEL targets further revealed stark enrichment in neurons and synaptic transmission terms and pathways.

CONCLUSION

Our study highlights the utility of a systematic brain transcriptome analysis relying on the expression profiles measured across multiple brain regions and singles out white matter regions as a prospective target for further SZ research.

Disclosing common biological signatures and predicting new therapeutic targets in schizophrenia and obsessive-compulsive disorder by integrated bioinformatics analysis

Schizophrenia (SCZ) is a severe mental illness mainly characterized by a number of psychiatric symptoms. Obsessive-compulsive disorder (OCD) is a long-lasting and devastating mental disorder. SCZ has high co-occurrence with OCD resulting in the emergence of a concept entitled "schizo-obsessive disorder" as a new specific clinical entity with more severe psychiatric symptoms. Many studies have been done on SCZ and OCD, but the common pathogenesis between them is not clear yet. Therefore, this study aimed to identify shared genetic basis, potential biomarkers and therapeutic targets between these two disorders. Gene sets were extracted from the Geneweaver and Harmonizome databases for each disorder. Interestingly, the combination of both sets revealed 89 common genes between SCZ and OCD, the most important of which were BDNF, SLC6A4, GAD1, HTR2A, GRIN2B, DRD2, SLC6A3, COMT, TH and DLG4. Then, we conducted a comprehensive bioinformatics analysis of the common genes. Receptor activity as the molecular functions, neuron projection and synapse as the cellular components as well as serotonergic synapse, dopaminergic synapse and alcoholism as the pathways were the most significant commonalities in enrichment analyses. In addition, transcription factor (TFs) analysis predicted significant TFs such as HMGA1, MAPK14, HINFP and TEAD2. Hsa-miR-3121-3p and hsa-miR-495-3p were the most important microRNAs (miRNAs) associated with both disorders. Finally, our study predicted 19 existing drugs (importantly, Haloperidol, Fluoxetine and Melatonin) that may have a potential influence on this co-occurrence. To summarize, this study may help us to better understand and handle the co-occurrence of SCZ and OCD by identifying potential biomarkers and therapeutic targets.

Infections, Inflammation, and Psychiatric Illness: Review of Postmortem Evidence

While there is an abundance of epidemiological evidence implicating infectious agents in the etiology of severe mental illnesses, postmortem studies have not yet detected an increased incidence of microbial nucleic acid or proteins in the brains of people with mental illness. Nevertheless, abnormally expressed immune and inflammatory markers have consistently been found in the postmortem brain of patients with schizophrenia and mood disorders. Some of these abnormalities may be the result of an infection in utero or early in life that not only impacted the developing immune system but also the developing neurons of the brain. Some of the immune markers that are consistently found to be upregulated in schizophrenia implicate a possible viral infection and the blood brain barrier in the etiology and neuropathology of the disorder.

Schizophrenia: A Narrative Review of Etiopathogenetic, Diagnostic and Treatment Aspects

Although schizophrenia is currently conceptualized as being characterized as a syndrome that includes a collection of signs and symptoms, there is strong evidence of heterogeneous and complex underpinned etiological, etiopathogenetic, and psychopathological mechanisms, which are still under investigation. Therefore, the present viewpoint review is aimed at providing some insights into the recently investigated schizophrenia research fields in order to discuss the potential future research directions in schizophrenia research. The traditional schizophrenia construct and diagnosis were progressively revised and revisited, based on the recently emerging neurobiological, genetic, and epidemiological research. Moreover, innovative diagnostic and therapeutic approaches are pointed to build a new construct, allowing the development of better clinical and treatment outcomes and characterization for schizophrenic individuals, considering a more patient-centered, personalized, and tailored-based dimensional approach. Further translational studies are needed in order to integrate neurobiological, genetic, and environmental studies into clinical practice and to help clinicians and researchers to understand how to redesign a new schizophrenia construct.

Immune-Related Genomic Schizophrenic Subtyping Identified in DLPFC Transcriptome

Well-documented evidence of the physiologic, genetic, and behavioral heterogeneity of schizophrenia suggests that diagnostic subtyping may clarify the underlying pathobiology of the disorder. Recent studies have demonstrated that increased inflammation may be a prominent feature of a subset of schizophrenics. However, these findings are inconsistent, possibly due to evaluating schizophrenics as a single group. In this study, we segregated schizophrenic patients into two groups ("Type 1", "Type 2") by their gene expression in the dorsolateral prefrontal cortex and explored biological differences between the subgroups. The study included post-mortem tissue samples that were sequenced in multiple, publicly available gene datasets using different sequencing methods. To evaluate the role of inflammation, the expression of genes in multiple components of neuroinflammation were examined: complement cascade activation, glial cell activation, pro-inflammatory mediator secretion, blood-brain barrier (BBB) breakdown, chemokine production and peripheral immune cell infiltration. The Type 2 schizophrenics showed widespread abnormal gene expression across all the neuroinflammation components that was not observed in Type 1 schizophrenics. Our results demonstrate the importance of separating schizophrenic patients into their molecularly defined subgroups and provide supporting evidence for the involvement of the immune-related pathways in a schizophrenic subset.