Identification of blood biomarkers for psychosis using convergent functional genomics

Sex linked behavioral and hippocampal transcriptomic changes in mice with cell-type specific Egr1 loss

The transcription factor EGR1 is instrumental in numerous neurological processes, encompassing learning and memory as well as the reaction to stress. Egr1 complete knockout mice demonstrate decreased depressive or anxiety-like behavior and impaired performance in spatial learning and memory. Nevertheless, the specific functions of Egr1 in distinct cell types have been largely underexplored. In this study, we cataloged the behavioral and transcriptomic character of Nestin-Cre mediated Egr1 conditional knockout (Egr1cKO) mice together with their controls. Although the conditional knockout did not change nociceptive or anxiety responses, it triggered changes in female exploratory activity during anxiety testing. Hippocampus-dependent spatial learning in the object location task was unaffected, but female Egr1cKO mice did exhibit poorer retention during testing on a contextual fear conditioning task compared to males. RNA-seq data analyses revealed that the presence of the floxed Egr1 cassette or Nestin-Cre driver alone exerts a subtle influence on hippocampal gene expression. The sex-related differences were amplified in Nestin-Cre mediated Egr1 conditional knockout mice and female mice are more sensitive to the loss of Egr1 gene. Differentially expressed genes resulted from the loss of Egr1 in neuronal cell lineage were significantly associated with the regulation of Wnt signaling pathway, extracellular matrix, and axon guidance. Altogether, our results demonstrate that Nestin-Cre and the loss of Egr1 in neuronal cell lineage have distinct impacts on hippocampal gene expression in a sex-specific manner.

Identification of immune-related biomarkers in peripheral blood of schizophrenia using bioinformatic methods and machine learning algorithms

Schizophrenia is a group of severe neurodevelopmental disorders. Identification of peripheral diagnostic biomarkers is an effective approach to improving diagnosis of schizophrenia. In this study, four datasets of schizophrenia patients' blood or serum samples were downloaded from the GEO database and merged and de-batched for the analyses of differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WCGNA). The WGCNA analysis showed that the cyan module, among 9 modules, was significantly related to schizophrenia, which subsequently yielded 317 schizophrenia-related key genes by comparing with the DEGs. The enrichment analyses on these key genes indicated a strong correlation with immune-related processes. The CIBERSORT algorithm was adopted to analyze immune cell infiltration, which revealed differences in eosinophils, M0 macrophages, resting mast cells, and gamma delta T cells. Furthermore, by comparing with the immune genes obtained from online databases, 95 immune-related key genes for schizophrenia were screened out. Moreover, machine learning algorithms including Random Forest, LASSO, and SVM-RFE were used to further screen immune-related hub genes of schizophrenia. Finally, CLIC3 was found as an immune-related hub gene of schizophrenia by the three machine learning algorithms. A schizophrenia rat model was established to validate CLIC3 expression and found that CLIC3 levels were reduced in the model rat plasma and brains in a brain-regional dependent manner, but can be reversed by an antipsychotic drug risperidone. In conclusion, using various bioinformatic and biological methods, this study found an immune-related hub gene of schizophrenia - CLIC3 that might be a potential diagnostic biomarker and therapeutic target for schizophrenia.

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.

Age, sex, and apolipoprotein E isoform alter contextual fear learning, neuronal activation, and baseline DNA damage in the hippocampus

Age, female sex, and apolipoprotein E4 (E4) are risk factors to develop Alzheimer's disease (AD). There are three major human apoE isoforms: E2, E3, and E4. Compared to E3, E4 increases while E2 decreases AD risk. However, E2 is associated with increased risk and severity of post-traumatic stress disorder (PTSD). In cognitively healthy adults, E4 carriers have greater brain activation during learning and memory tasks in the absence of behavioral differences. Human apoE targeted replacement (TR) mice display differences in fear extinction that parallel human data: E2 mice show impaired extinction, mirroring heightened PTSD symptoms in E2 combat veterans. Recently, an adaptive role of DNA double strand breaks (DSBs) in immediate early gene expression (IEG) has been described. Age and disease synergistically increase DNA damage and decrease DNA repair. As the mechanisms underlying the relative risks of apoE, sex, and their interactions in aging are unclear, we used young (3 months) and middle-aged (12 months) male and female TR mice to investigate the influence of these factors on DSBs and IEGs at baseline and following contextual fear conditioning. We assessed brain-wide changes in neural activation following fear conditioning using whole-brain cFos imaging in young female TR mice. E4 mice froze more during fear conditioning and had lower cFos immunoreactivity across regions important for somatosensation and contextual encoding compared to E2 mice. E4 mice also showed altered co-activation compared to E3 mice, corresponding to human MRI and cognitive data, and indicating that there are differences in brain activity and connectivity at young ages independent of fear learning. There were increased DSB markers in middle-aged animals and alterations to cFos levels dependent on sex and isoform, as well. The increase in hippocampal DSB markers in middle-aged animals and female E4 mice may play a role in the risk for developing AD.

Acute psilocybin increased cortical activities in rats

Psilocybin, a naturally occurring hallucinogenic component of magic mushrooms, has significant psychoactive effects in both humans and rodents. But the underlying mechanisms are not fully understood. Blood-oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is a useful tool in many preclinical and clinical trials to investigate psilocybin-induced changes of brain activity and functional connectivity (FC) due to its noninvasive nature and widespread availability. However, fMRI effects of psilocybin on rats have not been carefully investigated. This study aimed to explore how psilocybin affects resting-state brain activity and FC, through a combination of BOLD fMRI and immunofluorescence (IF) of EGR1, an immediate early gene (IEG) closely related to depressive symptoms. Ten minutes after psilocybin hydrochloride injection (2.0 mg/kg, i.p.), positive brain activities were observed in the frontal, temporal, and parietal cortex (including the cingulate cortex and retrosplenial cortex), hippocampus, and striatum. And a region-of-interest (ROI) -wise FC analysis matrix suggested increased interconnectivity of several regions, such as the cingulate cortex, dorsal striatum, prelimbic, and limbic regions. Further seed-based analyses revealed increased FC of cingulate cortex within the cortical and striatal areas. Consistently, acute psilocybin increased the EGR1 level throughout the brain, indicating a consistent activation thought the cortical and striatal areas. In conclusion, the psilocybin-induced hyperactive state of rats is congruent to that of humans, and may be responsible for its pharmacological effects.

Efficacy, safety, and tolerability of ulotaront (SEP-363856, a trace amine-associated receptor 1 agonist) for the treatment of schizophrenia and other mental disorders with similar pathophysiology: a systematic review of preclinical and clinical trials

INTRODUCTION

Schizophrenia is a mental illness that can disrupt emotions, perceptions, cognition, and reduce quality of life. The classical approach to treat schizophrenia uses typical and atypical antipsychotics; however, limitations include low efficacy in mitigating negative symptoms and cognitive dysfunctions, and a range of adverse effects. Evidence has accumulated on trace amine-associated receptor 1 (TAAR1) as a novel therapeutic target for treating schizophrenia. This systematic review investigates the available evidence on a TAAR1 agonist, ulotaront, as a treatment for schizophrenia.

METHODS

A systematic search was conducted on PubMed/MEDLINE, and Ovid databases for English-published articles from inception to December 18, 2022. Literature focusing on the association between ulotaront and schizophrenia were evaluated based on an inclusion/exclusion criterion. Selected studies were assessed for risk of bias, using Cochrane Collaboration tool, and summarized in a table to generate discussion topics.

RESULTS

Three clinical, two comparative, and five preclinical studies examining ulotaront's pharmacology, tolerability and safety, and/or efficacy were identified. Results indicate that ulotaront has a differing adverse effects profile from other antipsychotics, may mitigate metabolic-related adverse effects commonly associated with antipsychotics, and may be effective for treating positive and negative symptoms.

CONCLUSIONS

Findings from available literature present ulotaront as a potential and promising alternative treatment method for schizophrenia. Despite this, our results were limited due to lack of clinical trials on ulotaront's long-term efficacy and mechanisms of action. Future research should focus on these limitations to elucidate ulotaront's efficacy and safety for the treatment of schizophrenia and other mental disorders with similar pathophysiology.

Establishment of a schizophrenia classifier based on peripheral blood signatures and investigation of pathogenic miRNA-mRNA regulation

To date, the diagnosis of schizophrenia (SCZ) mainly relies on patients' or guardians' self-reports and clinical observation, and the pathogenesis of SCZ remains elusive. In this study, we sought to develop a reliable classifier for diagnosing SCZ patients and provide clues to the etiology and pathogenesis of SCZ. Based on the high throughput sequencing analysis of peripheral blood miRNA expression profile and weighted gene co-expression network analysis (WGCNA) in our previous study, we selected eleven hub miRNAs for validation by qRT-PCR in 51 SCZ patients and 51 controls. miR-939-5p, miR-4732-3p let-7d-3p, and miR-142-3p were confirmed to be significantly up-regulated, and miR-30e-3p and miR-23a-3p were down-regulated in SCZ patients. miR-30e-3p with the most considerable fold change and statistically significance was selected for targeting validation. We first performed bioinformatics prediction followed by qRT-PCR and verified the up-regulation of potential target mRNAs (ABI1, NMT1, HMGB1) expression. Next, we found that the expression level of ABI1 was significantly up-regulated in SH-SY5Y cells transfected with miR-30e-3p mimics. Lastly, we conducted a luciferase assay in 293T cells confirming that miR-30e-3p could directly bind with the 3'untranslated region (3'-UTR) of ABI1, revealing that miR-30e-3p might play a role in the polymerization of neuronal actin and the reconstruction of the cytoskeleton via the downstream regulation of ABI1. In addition, we constructed a classifier by a series of bioinformatics algorithms and evaluated its diagnostic performance. It appears that the classifier consists of miRNAs and mRNAs possess a better discrimination performance than individual miRNA or mRNA in SCZ.

Identification of potential biomarkers and their correlation with immune infiltration cells in schizophrenia using combinative bioinformatics strategy

Many studies have identified changes in gene expression in brains of schizophrenia patients and their altered molecular processes, but the findings in different datasets were inconsistent and diverse. Here we performed the most comprehensive analysis of gene expression patterns to explore the underlying mechanisms and the potential biomarkers for early diagnosis in schizophrenia. We focused on 10 gene expression datasets in post-mortem human brain samples of schizophrenia downloaded from gene expression omnibus (GEO) database using the integrated bioinformatics analyses including robust rank aggregation (RRA) algorithm, Weighted gene co-expression network analysis (WGCNA) and CIBERSORT. Machine learning algorithm was used to construct the risk prediction model for early diagnosis of schizophrenia. We identified 15 key genes (SLC1A3, AQP4, GJA1, ALDH1L1, SOX9, SLC4A4, EGR1, NOTCH2, PVALB, ID4, ABCG2, METTL7A, ARC, F3 and EMX2) in schizophrenia by performing multiple bioinformatics analysis algorithms. Moreover, the interesting part of the study is that there is a correlation between the expression of hub genes and the immune infiltrating cells estimated by CIBERSORT. Besides, the risk prediction model was constructed by using both these genes and the immune cells with a high accuracy of 0.83 in the training set, and achieved a high AUC of 0.77 for the test set. Our study identified several potential biomarkers for diagnosis of SCZ based on multiple bioinformatics algorithms, and the constructed risk prediction model using these biomarkers achieved high accuracy. The results provide evidence for an improved understanding of the molecular mechanism of schizophrenia.

Allostatic load and systemic comorbidities in psychiatric disorders

Psychiatric disorders are complex, disabling, and chronic conditions that are often accompanied by one or more systemic medical comorbidities. In this narrative review, we provide an overview of the allostatic load concept, which represents a multi-system dysregulation in response to chronic stress and link it to systemic comorbidities associated with psychiatric disorders. We synthesized published literature gathered using Medline (Ovid), Scopus, and PsychInfo and identified a high frequency of systemic comorbidities for both mood and psychotic disorders. The identified cardiovascular, metabolic, and immune comorbidities may represent the result of chronic wear and tear caused by a complex interaction between chronic psychosocial stress, health risk behaviors, pharmacological stressors, and the biological systems involved in the development of allostatic load. These findings support the notion that psychiatric disorders should be re-conceptualized as systemic disorders, affecting the brain and systemic biological pathways in an interconnected fashion to result in systemic comorbidities. We suggest that the multi-systemic and multi-dimensional approach that drives the allostatic load concept should be considered for understanding comorbidities in vulnerable psychiatric patients.

Identification of potential blood biomarkers for early diagnosis of schizophrenia through RNA sequencing analysis

Schizophrenia (SCZ) is a highly heritable, polygenic complex mental disorder with imprecise diagnostic boundaries. Finding sensitive and specific novel biomarkers to improve the biological homogeneity of SCZ diagnosis is still one of the research hotspots. To identify the blood specific diagnostic biomarkers of SCZ, we performed RNA sequencing (RNA-seq) on 30 peripheral blood samples from 15 first-episode drug-naïve SCZ patients and 15 healthy controls (CTL). By performing multiple bioinformatics analysis algorithms based on RNA-seq data and microarray datasets, including differential expression genes (DEGs) analysis, WGCNA and CIBERSORT, we first identified 6 specific key genes (TOMM7, SNRPG, KRT1, AQP10, TMEM14B and CLEC12A) in SCZ. Moreover, we found that the proportions of lymphocyte, monocyte and neutrophils were significantly distinct in SCZ patients with CTL samples. Therefore, combining various features including age, sex and the novel blood biomarkers, we constructed the risk prediction model with three classifiers (RF: Random Forest; SVM: support vector machine; DT: decision tree) through repeated k-fold cross validation ensuring better generalizability. Finest result of Area under Receiver Operating Characteristic (AUROC) score of 0.91 was achieved by RF classifier and with a comparable good performance of AUROC 0.77 in external validation dataset. A lower AUROC of 0.63 was demonstrated when it was further applied to a Bipolar disorder (BPD) cohort. In conclusion, the study identified three peripheral core immunocytes and six key genes associated with the occurrence of SCZ, and further studies are required to test and validate these novel biomarkers for early diagnosis and treatment of SCZ.

Categorical versus dimensional models of early psychosis

AIM

Early psychosis is typically operationalized as a categorical construct by dividing people into one of three diagnostic statuses: low-risk, clinical high-risk, and first episode psychosis. We empirically assess whether an alternative dimensional approach focused on observed symptom severity may be more desirable for clinical and research purposes.

METHODS

Participants were 152 help-seeking youths ages 12-22 years old. Structured interview for psychosis risk syndromes interviews were used to obtain dimensional psychosis symptom severity ratings, and to classify participants by categorical psychosis risk status. Twenty-five participants were classified as having a diagnosable psychotic disorder, 52 participants as clinical high-risk, and 75 participants as help-seeking controls. We assessed the relation between categorical and dimensional measurements of psychosis severity, and then compared categorical versus dimensional psychosis severity in their ability to predict social and role functioning.

RESULTS

On average, dimensional psychosis symptom severity increased along with categorical risk status (help-seeking control < clinical high-risk < diagnosable psychotic disorder). There was, however, considerable overlap between categories, with people at clinical high-risk being particularly hard to distinguish from people with diagnosable psychotic disorders on the basis of symptom severity. Dimensional symptom severity was more predictive of functioning than categorical risk status.

CONCLUSIONS

Categorical risk status and psychosis symptom severity are related but not interchangeable, and dimensional models of psychosis may be more predictive of functional outcomes. Adopting a dimensional rather than categorical approach to the psychosis risk spectrum may facilitate better predictive models and a richer theoretical understanding of early psychosis.

Cannabidiol prevents disruptions in sensorimotor gating induced by psychotomimetic drugs that last for 24-h with probable involvement of epigenetic changes in the ventral striatum

Cannabidiol (CBD), a major non-psychotomimetic component of the Cannabis sativa plant, shows therapeutic potential in several psychiatric disorders, including schizophrenia. The molecular mechanisms underlying the antipsychotic-like effects of CBD are not fully understood. Schizophrenia and antipsychotic treatment can modulate DNA methylation in the blood and brain, resulting in altered expression of diverse genes associated with this complex disorder. However, to date, the possible involvement of DNA methylation in the antipsychotic-like effects of CBD has not been investigated. Therefore, this study aimed at evaluating in mice submitted to the prepulse inhibition (PPI) model: i) the effects of a single injection of CBD or clozapine followed by AMPH or MK-801 on PPI and global DNA methylation changes in the ventral striatum and prefrontal cortex (PFC); and ii). if the acute antipsychotic-like effects of CBD would last for 24-h. AMPH (5 mg/kg) and MK-801 (0.5 mg/kg) impaired PPI. CBD (30 and 60 mg/kg), similar to clozapine (5 mg/kg), attenuated AMPH- and MK801-induced PPI disruption. AMPH, but not MK-801, increased global DNA methylation in the ventral striatum, an effect prevented by CBD. CBD and clozapine increased, by themselves, DNA methylation in the prefrontal cortex. The acute effects of CBD (30 or 60 mg/kg) on the PPI impairment induced by AMPH or MK-801 was also detectable 24 h later. Altogether, the results show that CBD induces acute antipsychotic-like effects that last for 24-h. It also modulates DNA methylation in the ventral striatum, suggesting a new potential mechanism for its antipsychotic-like effects.

The Etiology of Auditory Hallucinations in Schizophrenia: From Multidimensional Levels

Enormous efforts have been made to unveil the etiology of auditory hallucinations (AHs), and multiple genetic and neural factors have already been shown to have their own roles. Previous studies have shown that AHs in schizophrenia vary from those in other disorders, suggesting that they have unique features and possibly distinguishable mechanisms worthy of further investigation. In this review, we intend to offer a comprehensive summary of current findings related to AHs in schizophrenia from aspects of genetics and transcriptome, neurophysiology (neurometabolic and electroencephalogram studies), and neuroimaging (structural and functional magnetic resonance imaging studies and transcriptome–neuroimaging association study). Main findings include gene polymorphisms, glutamate level change, electroencephalographic alterations, and abnormalities of white matter fasciculi, cortical structure, and cerebral activities, especially in multiple regions, including auditory and language networks. More solid and comparable research is needed to replicate and integrate ongoing findings from multidimensional levels.

Identifying the biomarkers and pathways associated with hepatocellular carcinoma based on an integrated analysis approach

BACKGROUND AND AIMS

Hepatocellular carcinoma (HCC) is one of the most common causes of cancer-related death worldwide. The molecular mechanism underlying HCC is still unclear. In this study, we conducted a comprehensive analysis to explore the genes, pathways and their interactions involved in HCC.

METHODS

We analysed the gene expression datasets corresponding to 488 samples from 10 studies on HCC and identified the genes differentially expressed in HCC samples. Then, the genes were compared against Phenolyzer and GeneCards to screen those potentially associated with HCC. The features of the selected genes were explored by mapping them onto the human protein-protein interaction network, and a subnetwork related to HCC was constructed. Hub genes in this HCC specific subnetwork were identified, and their relevance with HCC was investigated by survival analysis.

RESULTS

We identified 444 differentially expressed genes (177 upregulated and 267 downregulated) related to HCC. Functional enrichment analysis revealed that pathways like p53 signalling and chemical carcinogenesis were eriched in HCC genes. In the subnetwork related to HCC, five disease modules were detected. Further analysis identified six hub genes from the HCC specific subnetwork. Survival analysis showed that the expression levels of these genes were negatively correlated with survival rate of HCC patients.

CONCLUSIONS

Based on a systems biology framework, we identified the genes, pathways, as well as the disease specific network related to HCC. We also found novel biomarkers whose expression patterns were correlated with progression of HCC, and they could be candidates for further investigation.

Clinical, pathological and genetic characteristics of Perry disease-new cases and literature review

BACKGROUND AND PURPOSE

Perry disease (or Perry syndrome) is an autosomal dominant neurodegenerative disorder characterized by parkinsonism, neuropsychiatric symptoms, central hypoventilation, weight loss and distinct TDP-43 pathology. It is caused by mutations of the DCTN1 gene encoding an essential component of axonal transport. The objectives were to provide the current state of knowledge on clinical, pathological and genetic aspects of Perry disease, as well as practical suggestions for the management of the disease.

METHODS

Data on new patients from New Zealand, Poland and Colombia were collected, including autopsy report. Also all of the published papers since the original work by Perry in 1975 were gathered and analyzed.

RESULTS

Parkinsonism was symmetrical, progressed rapidly and was poorly responsive to L-Dopa; nonetheless, a trial with high doses of L-Dopa is warranted. Depression was severe, associated with suicidal ideations, and benefited from antidepressants and L-Dopa. Respiratory symptoms were the leading cause of death, and artificial ventilation or a diaphragm pacemaker prolonged survival. Weight loss occurred in most patients and was of multifactorial etiology. Autonomic dysfunction was frequent but underdiagnosed. There was a clinical overlap with other neurodegenerative disorders. An autopsy showed distinctive pallidonigral degeneration with TDP-43 pathology. Genetic testing provided evidence of a common founder for two families. There was striking phenotypic variability in DCTN1-related disorders. It is hypothesized that oligogenic or polygenic inheritance is at play.

CONCLUSIONS

Perry disease and other DCTN1-related diseases are increasingly diagnosed worldwide. Relatively effective symptomatic treatments are available. Further studies are needed to pave the way toward curative/gene therapy.

Changes in the Brain Extracellular Matrix Composition in schizophrenia: A Pathophysiological Dysregulation and a Potential Therapeutic Target

The brain extracellular matrix (ECM) is involved in crucial processes of neural support, neuronal and synaptic plasticity, extrasynaptic transmission, and neurotransmission. ECM is a tridimensional fibrillary meshwork composed of macromolecules that determine its bioactivity and give it unique characteristics. The characterization of the brain ECM is critical to understand its dynamic in SZ. Thus, a comparative study was developed with 71 patients with schizophrenia (SZ) and 70 healthy controls. Plasma of participants was analysed by label-free liquid chromatography-tandem mass spectrometry, and the results were validated using the classical western blot method. Lastly, immunostaining of post-mortem human brain tissue was performed to analyse the distribution of the brain ECM proteins by confocal microscopy. The analysis identified four proteins: fibronectin, lumican, nidogen-1, and secreted protein acidic and rich in cysteine (SPARC) as components of the brain ECM. Statistical significance was found for fibronectin (P = 0.0166), SPARC (P = 0.0003), lumican (P = 0.0012), and nidogen-1 (P < 0.0001) that were decreased in the SZ group. Fluorescence imaging of prefrontal cortex (PFC) sections revealed a lower expression of ECM proteins in SZ. Our study proposes a pathophysiological dysregulation of proteins of the brain ECM, whose abnormal composition leads to a progressive neuronal impairment and consequently to neurodegenerative processes due to lack of neurophysiological support and dysregulation of neuronal homeostasis. Moreover, the brain ECM and its components are potential pharmacological targets to develop new therapeutic approaches to treat SZ.

Comprehensive Integrative Analyses Identify TIGD5 rs75547282 as a Risk Variant for Autism Spectrum Disorder

Although recent genome-wide association studies have identified risk loci that strongly associates with autism spectrum disorder (ASD), how to pinpoint the causal genes remains a challenge. We aimed to pinpoint the potential causal genes and explore the possible susceptibility and mechanism. A convergent functional genomics (CFG) method was used to prioritize the candidate genes by combining lines of evidence, including Sherlock analysis, spatio-temporal expression patterns, expression analysis, protein-protein interactions, co-expression and association with brain structure. A higher score in the CFG approach suggested that more evidence supported this gene as an ASD risk gene. We screened genes with higher CFG scores for candidate functional single nucleotide polymorphisms (SNPs). A genotyping experiment (602 ASD children and 604 healthy sex-matched children) and the dual-luciferase reporter gene assay were followed to validate the effects of SNPs. We identified three genes (MAPT, ZNF285, and TIGD5) as candidate causal genes using the CFG approach. The genotyping experiment showed that TIGD5 rs75547282 was associated with an increased risk of ASD under the dominant model (OR = 1.37, 95% CI = 1.09-1.72, P = 0.006) though the statistical power was limited (5.2%). The T allele of rs75547282 activated the expression of TIGD5 compared with the C allele in the dual-luciferase reporter assay. Our study indicates that such comprehensive integrative analyses may be an effective way to explore promising ASD susceptibility variants and needs to be further investigated in future research. Genotyping experiments should, however, be based on a larger population sample to increase statistical power. LAY SUMMARY: We set out to pinpoint the potential causal genes of ASD and explore the possible susceptibility and mechanism by combining lines of evidence from different analyses. Our results show that TIGD5 rs75547282 is associated with the risk of ASD in the Han Chinese population. In addition, a similar framework to seek promising ASD risk variants could be further investigated in future research Autism Res 2021, 14: 631-644. © 2021 International Society for Autism Research and Wiley Periodicals LLC.

Precision medicine for mood disorders: objective assessment, risk prediction, pharmacogenomics, and repurposed drugs

Mood disorders (depression, bipolar disorders) are prevalent and disabling. They are also highly co-morbid with other psychiatric disorders. Currently there are no objective measures, such as blood tests, used in clinical practice, and available treatments do not work in everybody. The development of blood tests, as well as matching of patients with existing and new treatments, in a precise, personalized and preventive fashion, would make a significant difference at an individual and societal level. Early pilot studies by us to discover blood biomarkers for mood state were promising [1], and validated by others [2]. Recent work by us has identified blood gene expression biomarkers that track suicidality, a tragic behavioral outcome of mood disorders, using powerful longitudinal within-subject designs, validated them in suicide completers, and tested them in independent cohorts for ability to assess state (suicidal ideation), and ability to predict trait (future hospitalizations for suicidality) [3-6]. These studies showed good reproducibility with subsequent independent genetic studies [7]. More recently, we have conducted such studies also for pain [8], for stress disorders [9], and for memory/Alzheimer's Disease [10]. We endeavored to use a similar comprehensive approach to identify more definitive biomarkers for mood disorders, that are transdiagnostic, by studying mood in psychiatric disorders patients. First, we used a longitudinal within-subject design and whole-genome gene expression approach to discover biomarkers which track mood state in subjects who had diametric changes in mood state from low to high, from visit to visit, as measured by a simple visual analog scale that we had previously developed (SMS-7). Second, we prioritized these biomarkers using a convergent functional genomics (CFG) approach encompassing in a comprehensive fashion prior published evidence in the field. Third, we validated the biomarkers in an independent cohort of subjects with clinically severe depression (as measured by Hamilton Depression Scale, (HAMD)) and with clinically severe mania (as measured by the Young Mania Rating Scale (YMRS)). Adding the scores from the first three steps into an overall convergent functional evidence (CFE) score, we ended up with 26 top candidate blood gene expression biomarkers that had a CFE score as good as or better than SLC6A4, an empirical finding which we used as a de facto positive control and cutoff. Notably, there was among them an enrichment in genes involved in circadian mechanisms. We further analyzed the biological pathways and networks for the top candidate biomarkers, showing that circadian, neurotrophic, and cell differentiation functions are involved, along with serotonergic and glutamatergic signaling, supporting a view of mood as reflecting energy, activity and growth. Fourth, we tested in independent cohorts of psychiatric patients the ability of each of these 26 top candidate biomarkers to assess state (mood (SMS-7), depression (HAMD), mania (YMRS)), and to predict clinical course (future hospitalizations for depression, future hospitalizations for mania). We conducted our analyses across all patients, as well as personalized by gender and diagnosis, showing increased accuracy with the personalized approach, particularly in women. Again, using SLC6A4 as the cutoff, twelve top biomarkers had the strongest overall evidence for tracking and predicting depression after all four steps: NRG1, DOCK10, GLS, PRPS1, TMEM161B, GLO1, FANCF, HNRNPDL, CD47, OLFM1, SMAD7, and SLC6A4. Of them, six had the strongest overall evidence for tracking and predicting both depression and mania, hence bipolar mood disorders. There were also two biomarkers (RLP3 and SLC6A4) with the strongest overall evidence for mania. These panels of biomarkers have practical implications for distinguishing between depression and bipolar disorder. Next, we evaluated the evidence for our top biomarkers being targets of existing psychiatric drugs, which permits matching patients to medications in a targeted fashion, and the measuring of response to treatment. We also used the biomarker signatures to bioinformatically identify new/repurposed candidate drugs. Top drugs of interest as potential new antidepressants were pindolol, ciprofibrate, pioglitazone and adiphenine, as well as the natural compounds asiaticoside and chlorogenic acid. The last 3 had also been identified by our previous suicidality studies. Finally, we provide an example of how a report to doctors would look for a patient with depression, based on the panel of top biomarkers (12 for depression and bipolar, one for mania), with an objective depression score, risk for future depression, and risk for bipolar switching, as well as personalized lists of targeted prioritized existing psychiatric medications and new potential medications. Overall, our studies provide objective assessments, targeted therapeutics, and monitoring of response to treatment, that enable precision medicine for mood disorders.

Modulation of cognition and neuronal plasticity in gain- and loss-of-function mouse models of the schizophrenia risk gene Tcf4

The transcription factor TCF4 was confirmed in several large genome-wide association studies as one of the most significant schizophrenia (SZ) susceptibility genes. Transgenic mice moderately overexpressing Tcf4 in forebrain (Tcf4tg) display deficits in fear memory and sensorimotor gating. As second hit, we exposed Tcf4tg animals to isolation rearing (IR), chronic social defeat (SD), enriched environment (EE), or handling control (HC) conditions and examined mice with heterozygous deletion of the exon 4 (Tcf4Ex4δ^+/-) to unravel gene-dosage effects. We applied multivariate statistics for behavioral profiling and demonstrate that IR and SD cause strong cognitive deficits of Tcf4tg mice, whereas EE masked the genetic vulnerability. We observed enhanced long-term depression in Tcf4tg mice and enhanced long-term potentiation in Tcf4Ex4δ^+/- mice indicating specific gene-dosage effects. Tcf4tg mice showed higher density of immature spines during development as assessed by STED nanoscopy and proteomic analyses of synaptosomes revealed concurrently increased levels of proteins involved in synaptic function and metabolic pathways. We conclude that environmental stress and Tcf4 misexpression precipitate cognitive deficits in 2-hit mouse models of relevance for schizophrenia.

The Role of Brain Microvascular Endothelial Cell and Blood-Brain Barrier Dysfunction in Schizophrenia

BACKGROUND

Despite decades of research, little clarity exists regarding pathogenic mechanisms related to schizophrenia. Investigations on the disease biology of schizophrenia have primarily focused on neuronal alterations. However, there is substantial evidence pointing to a significant role for the brain's microvasculature in mediating neuroinflammation in schizophrenia.

SUMMARY

Brain microvascular endothelial cells (BMEC) are a central element of the microvasculature that forms the blood-brain barrier (BBB) and shields the brain against toxins and immune cells via paracellular, transcellular, transporter, and extracellular matrix proteins. While evidence for BBB dysfunction exists in brain disorders, including schizophrenia, it is not known if BMEC themselves are functionally compromised and lead to BBB dysfunction.

KEY MESSAGES

Genome-wide association studies, postmortem investigations, and gene expression analyses have provided some insights into the role of the BBB in schizophrenia pathophysiology. However, there is a significant gap in our understanding of the role that BMEC play in BBB dysfunction. Recent advances differentiating human BMEC from induced pluripotent stem cells (iPSC) provide new avenues to examine the role of BMEC in BBB dysfunction in schizophrenia.

Convergent Functional Genomics approach to prioritize molecular targets of risk in early life stress-related psychiatric disorders

There is an overwhelming evidence proving that mental disorders are not the product of a single risk factor - i.e. genetic variants or environmental factors, including exposure to maternal perinatal mental health problems or childhood adverse events - rather the product of a trajectory of cumulative and multifactorial insults occurring during development, such as exposures during the foetal life to adverse mental condition in the mother, or exposures to adverse traumatic events during childhood or adolescence. In this review, we aim to highlight the potential utility of a Convergent Functional Genomics (CFG) approach to clarify the complex brain-relevant molecular mechanisms and alterations induced by early life stress (ELS). We describe different studies based on CFG in psychiatry and neuroscience, and we show how this 'hypothesis-free' tool can prioritize a stringent number of genes modulated by ELS, that can be tested as potential candidates for Gene x Environment (GxE) interaction studies. We discuss the results obtained by using a CFG approach identifying FoxO1 as a gene where genetic variability can mediate the effect of an adverse environment on the development of depression. Moreover, we also demonstrate that FoxO1 has a functional relevance in stress-induced reduction of neurogenesis, and can be a potential target for the prevention or treatment of stress-related psychiatric disorders. Overall, we suggest that CFG approach could include trans-species and tissues data integration and we also propose the application of CFG to examine in depth and to prioritize top candidate genes that are affected by ELS across lifespan and generations.

Blood biomarkers for memory: toward early detection of risk for Alzheimer disease, pharmacogenomics, and repurposed drugs

Short-term memory dysfunction is a key early feature of Alzheimer's disease (AD). Psychiatric patients may be at higher risk for memory dysfunction and subsequent AD due to the negative effects of stress and depression on the brain. We carried out longitudinal within-subject studies in male and female psychiatric patients to discover blood gene expression biomarkers that track short term memory as measured by the retention measure in the Hopkins Verbal Learning Test. These biomarkers were subsequently prioritized with a convergent functional genomics approach using previous evidence in the field implicating them in AD. The top candidate biomarkers were then tested in an independent cohort for ability to predict state short-term memory, and trait future positive neuropsychological testing for cognitive impairment. The best overall evidence was for a series of new, as well as some previously known genes, which are now newly shown to have functional evidence in humans as blood biomarkers: RAB7A, NPC2, TGFB1, GAP43, ARSB, PER1, GUSB, and MAPT. Additional top blood biomarkers include GSK3B, PTGS2, APOE, BACE1, PSEN1, and TREM2, well known genes implicated in AD by previous brain and genetic studies, in humans and animal models, which serve as reassuring de facto positive controls for our whole-genome gene expression discovery approach. Biological pathway analyses implicate LXR/RXR activation, neuroinflammation, atherosclerosis signaling, and amyloid processing. Co-directionality of expression data provide new mechanistic insights that are consistent with a compensatory/scarring scenario for brain pathological changes. A majority of top biomarkers also have evidence for involvement in other psychiatric disorders, particularly stress, providing a molecular basis for clinical co-morbidity and for stress as an early precipitant/risk factor. Some of them are modulated by existing drugs, such as antidepressants, lithium and omega-3 fatty acids. Other drug and nutraceutical leads were identified through bioinformatic drug repurposing analyses (such as pioglitazone, levonorgestrel, salsolidine, ginkgolide A, and icariin). Our work contributes to the overall pathophysiological understanding of memory disorders and AD. It also opens new avenues for precision medicine- diagnostics (assement of risk) as well as early treatment (pharmacogenomically informed, personalized, and preventive).

Integrative In Silico Analysis of Genome-Wide DNA Methylation Profiles in Schizophrenia

Schizophrenia (SZ) is a complex and severe psychiatric disorder, which has a global lifetime prevalence of 0.4% and a heritability of around 0.81. A number of epigenome-wide association studies (EWAS) have been carried out for SZ, with discordant results. The main aim of this study was to carry out an integrative in silico analysis of available genome-wide DNA methylation profiles in schizophrenia. In this work, an integration of multiple lines of evidence (top candidate genes from several EWAS and genome-wide expression and association data) was carried out, in order to identify top differentially methylated (DM) genes for SZ. In addition, functional enrichment and protein-protein interaction analyses were carried out. Several top differentially methylated genes, such as APC, CACNB2, and PRKN, were found, and an enrichment of binding sites for brain-expressed transcription factors, such as FOXO1, MYB, and ZIC3, was also observed. Moreover, a protein-protein interaction network showed a central role for DISC1 and ZNF688 genes, and experimentally validated targets of MIR-137, such as and KCNB2, NRXN1, and SYN2, were identified among DM genes. This is the first integrative in silico analysis of available genome-wide DNA methylation profiles in schizophrenia. This work identified novel candidate genes and pathways for SZ and provides the basis to explore their role in the pathogenesis of SZ in future studies.

A Novel Role of CD38 and Oxytocin as Tandem Molecular Moderators of Human Social Behavior

Oxytocin is an important modulator of human affiliative behaviors, including social skills, human pair bonding, and friendship. CD38 will be discussed as an immune marker and then in more detail the mechanisms of CD38 on releasing brain oxytocin. Mention is made of the paralogue of oxytocin, vasopressin, that has often overlapping and complementary functions with oxytocin on social behavior. Curiously, vasopressin does not require CD38 to be released from the brain. This review discusses the social salience hypothesis of oxytocin action, a novel view of how this molecule influences much of human social behaviors often in contradictory ways. The oxytocinergic-vasopressinergic systems are crucial modulators of broad aspects of human personality. Of special interest are studies of these two hormones in trust related behavior observed using behavioral economic games. This review also covers the role of oxytocin in parenting and parental attachment. In conclusion, the effects of oxytocin on human behavior depend on the individual's social context and importantly as well, the individual's cultural milieu, viz. East and West. ACRONYMS: ACC = Anterior Cingulate ADP = Adenosine diphosphate AQ = Autism Quotient cADPR = Cyclic ADP-ribose CNS = Central nervous system DA = Dopamine eQTLC = Expression Quantitative Trait Loci LC-NE = Locus Coeruleus-Norepinephrine MRI = Magnetic Resonance Imaging OFC = Orbitofrontal cortices OXT = Oxytocin RAGE = Receptor for advanced glycation end-products SARM1 = Sterile Alpha and toll/interleukin-1 receptor motif-containing 1 TRPM2= Transient Receptor Potential Cation Channel Subfamily M Member 2 AVP = Vasopressin.

A Novel Cosegregating DCTN1 Splice Site Variant in a Family with Bipolar Disorder May Hold the Key to Understanding the Etiology

A novel cosegregating splice site variant in the Dynactin-1 (DCTN1) gene was discovered by Next Generation Sequencing (NGS) in a family with a history of bipolar disorder (BD) and major depressive diagnosis (MDD). Psychiatric illness in this family follows an autosomal dominant pattern. DCTN1 codes for the largest dynactin subunit, namely p150^Glued, which plays an essential role in retrograde axonal transport and in neuronal autophagy. A GT→TT transversion in the DCTN1 gene, uncovered in the present work, is predicted to disrupt the invariant canonical splice donor site IVS22 + 1G > T and result in intron retention and a premature termination codon (PTC). Thus, this splice site variant is predicted to trigger RNA nonsense-mediated decay (NMD) and/or result in a C-terminal truncated p150^Glued protein (ct-p150^Glued), thereby negatively impacting retrograde axonal transport and neuronal autophagy. BD prophylactic medications, and most antipsychotics and antidepressants, are known to enhance neuronal autophagy. This variant is analogous to the dominant-negative GLUED Gl¹ mutation in Drosophila, which is responsible for a neurodegenerative phenotype. The newly identified variant may reflect an autosomal dominant cause of psychiatric pathology in this affected family. Factors that affect alternative splicing of the DCTN1 gene, leading to NMD and/or ct-p150^Glued, may be of fundamental importance in contributing to our understanding of the etiology of BD as well as MDD.

Gene expression changes associated with trajectories of psychopathology in a longitudinal cohort of children and adolescents

We aimed to identify blood gene expression patterns associated to psychopathological trajectories retrieved from a large community, focusing on the emergence and remission of general psychiatric symptoms. Hundred and three individuals from the Brazilian High-Risk Cohort Study (BHRCS) for mental disorders were classified in four groups according to Child Behavior Checklist (CBCL) total score at the baseline (w0) and after 3 years (w1): low-high (L-H) (N = 27), high-low (H-L) (N = 12), high-high (H-H) (N = 34) and low-low (L-L) groups (N = 30). Blood gene expression profile was measured using Illumina HT-12 Beadchips, and paired analyses comparing w0 and w1 were performed for each group. Results: 98 transcripts were differentially expressed comparing w0 and w1 in the L-H, 33 in the H-L, 177 in the H-H and 273 in the L-L. Of these, 66 transcripts were differentially expressed exclusively in the L-H; and 6 only in the H-L. Cross-Lagged Panel Models analyses revealed that RPRD2 gene expression at w1 might be influenced by the CBCL score at w0. Moreover, COX5B, SEC62, and NDUFA2 were validated with another technique and were also differentially regulated in postmortem brain of subjects with mental disorders, indicating that they might be important not only to specific disorders, but also to general psychopathology and symptoms trajectories. Whereas genes related to metabolic pathways seem to be associated with the emergence of psychiatric symptoms, mitochondrial inner membrane genes might be important over the course of normal development. These results suggest that changes in gene expression can be detected in blood in different psychopathological trajectories.

Rett Syndrome, a Neurodevelopmental Disorder, Whole-Transcriptome, and Mitochondrial Genome Multiomics Analyses Identify Novel Variations and Disease Pathways

Rett syndrome (RTT) is a severe neurodevelopmental disorder reported worldwide in diverse populations. RTT is diagnosed primarily in females, with clinical findings manifesting early in life. Despite the variable rates across populations, RTT has an estimated prevalence of ∼1 in 10,000 live female births. Among 215 Saudi Arabian patients with neurodevelopmental and autism spectrum disorders, we identified 33 patients with RTT who were subsequently examined by genome-wide transcriptome and mitochondrial genome variations. To the best of our knowledge, this is the first in-depth molecular and multiomics analyses of a large cohort of Saudi RTT cases with a view to informing the underlying mechanisms of this disease that impact many patients and families worldwide. The patients were unrelated, except for 2 affected sisters, and comprised of 25 classic and eight atypical RTT cases. The cases were screened for methyl-CpG binding protein 2 (MECP2), CDKL5, FOXG1, NTNG1, and mitochondrial DNA (mtDNA) variants, as well as copy number variations (CNVs) using a genome-wide experimental strategy. We found that 15 patients (13 classic and two atypical RTT) have MECP2 mutations, 2 of which were novel variants. Two patients had novel FOXG1 and CDKL5 variants (both atypical RTT). Whole mtDNA sequencing of the patients who were MECP2 negative revealed two novel mtDNA variants in two classic RTT patients. Importantly, the whole-transcriptome analysis of our RTT patients' blood and further comparison with previous expression profiling of brain tissue from patients with RTT revealed 77 significantly dysregulated genes. The gene ontology and interaction network analysis indicated potentially critical roles of MAPK9, NDUFA5, ATR, SMARCA5, RPL23, SRSF3, and mitochondrial dysfunction, oxidative stress response and MAPK signaling pathways in the pathogenesis of RTT genes. This study expands our knowledge on RTT disease networks and pathways as well as presents novel mutations and mtDNA alterations in RTT in a population sample that was not previously studied.

Peripheral Blood Leukocyte RNA-Seq Identifies a Set of Genes Related to Abnormal Psychomotor Behavior Characteristics in Patients with Schizophrenia

BACKGROUND Schizophrenia is a multigene disease with a complex etiology and different clinical manifestations. It is of great significance to understand the etiology and pathogenesis of schizophrenia patients from different clinical dimensions and to interpret the potential molecular changes of schizophrenia patients from different clinical dimensions. MATERIAL AND METHODS RNA-Seq was performed on peripheral blood leukocytes of 50 patients with schizophrenia and 50 healthy controls. Phenotypic information of patients with schizophrenia was collected during blood sampling. Differentially expressed genes (DEGs) were screened by the edgeR package of R software. To better analyze the correlation between DEG expression values, explore the potential association between differential genes and clinical dimensions of schizophrenia, and identify hub genes, we constructed a DEG co-expression network using weighted gene co-expression network analysis (WGCNA). RESULTS We provide the transcription profiles of peripheral blood leukocytes in patients with schizophrenia and found a gene module (including 89 genes) closely related to the clinical dimension of abnormal psychomotor behavior in schizophrenia. CONCLUSIONS The findings enhance our understanding of the biological processes of schizophrenia, enabling us to identify specific clinical dimensions of genes for diagnosis and prognostic markers and possibly for targeted therapy.

Regulation of inflammatory pathways in schizophrenia: A comparative study with bipolar disorder and healthy controls

Background

Immune-inflammatory processes have been implicated in schizophrenia (SCH), but their specificity is not clear.

Main aim

To identify potential differential intra-/intercellular biochemical pathways controlling immune-inflammatory response and their oxidative-nitrosative impact on SCH patients, compared with bipolar disorder (BD) patients and healthy controls (HC).

Methods

Cross-sectional, naturalistic study of a cohort of SCH patients (n=123) and their controls [BD (n=102) and HC (n=80)].

Statistical analysis

ANCOVA (or Quade test) controlling for age and gender when comparing the three groups, and controlling for age, gender, length of illness, cigarettes per day, and body mass index (BMI) when comparing SCH and BD.

Results

Pro-inflammatory biomarkers: Expression of COX-1 was statistically higher in SCH and BD than HC (P<0.0001; P<0.0001); NFκB and PGE2 were statistically higher in SCH compared with BD (P=0.001; P<0.0001) and HC (P=0.003; P<0.0001); NLRP3 was higher in BD than HC (P=0.005); and CPR showed a gradient among the three groups. Anti-inflammatory biomarkers: BD patients had lower PPARγ and higher 15d-PGJ2 levels than SCH (P=0.005; P=0.008) and HC (P=0.001; P=0.001). Differences between SCH and BD: previous markers of SCH (NFκB and PGE2) and BD (PPARγ and 15d-PGJ2) remained statistically significant and, interestingly, iNOS and COX-2 (pro-inflammatory biomarkers) levels were statistically higher in SCH than BD (P=0.019; P=0.040).

Conclusions

This study suggests a specific immune-inflammatory biomarker pattern for established SCH (NFκB, PGE2, iNOS, and COX-2) that differentiates it from BD and HC. In future, their pharmacological modulation may constitute a promising therapeutic target.

Time dependent expression of the blood biomarkers EIF2D and TOX in patients with schizophrenia

BACKGROUND

During last years, there has been an intensive search for blood biomarkers in schizophrenia to assist in diagnosis, prognosis and clinical management of the disease.

METHODS

In this study, we first conducted a weighted gene coexpression network analysis to address differentially expressed genes in peripheral blood from patients with chronic schizophrenia (n = 30) and healthy controls (n = 15). The discriminating performance of the candidate genes was further tested in an independent cohort of patients with first-episode schizophrenia (n = 124) and healthy controls (n = 54), and in postmortem brain samples (cingulate and prefrontal cortices) from patients with schizophrenia (n = 34) and healthy controls (n = 35).

RESULTS

The expression of the Eukaryotic Translation Initiation Factor 2D (EIF2D) gene, which is involved in protein synthesis regulation, was increased in the chronic patients of schizophrenia. On the contrary, the expression of the Thymocyte Selection-Associated High Mobility Group Box (TOX) gene, involved in immune function, was reduced. EIF2D expression was also altered in first-episode schizophrenia patients, but showing reduced levels. Any of the postmortem brain areas studied did not show differences of expression of both genes.

CONCLUSIONS

EIF2D and TOX are putative blood markers of chronic patients of schizophrenia, which expression change from the onset to the chronic disease, unraveling new biological pathways that can be used for the development of new intervention strategies in the diagnosis and prognosis of schizophrenia disease.

Integrative analyses of major histocompatibility complex loci in the genome-wide association studies of major depressive disorder

Recent European genome-wide association studies (GWAS) have revealed strong statistical correlations between MDD and numerous zero-to-high linked variants in the genomic region containing major histocompatibility complex (MHC) genes (MHC region), but the underlying biological mechanisms are still unclear. To better understand the roles of this genomic region in the neurobiology of MDD, we applied a convergent functional genomics approach to integrate GWAS data of MDD relevant biological phenotypes, gene-expression analyses results obtained from brain samples, and genetic analyses of independent Chinese MDD samples. We observed that independent MDD risk variants in the MHC region were also significantly associated with the relevant biological phenotypes in the predicted directions, including the emotional and cognitive-related phenotypes. Gene-expression analyses further revealed that mRNA expression levels of several MHC region genes in the human brain were associated with MDD risk SNPs and diagnostic status. For instance, a brain-enriched gene ZNF603P consistently showed lower mRNA levels in the individuals carrying MDD risk alleles and in MDD patients. Remarkably, we further found that independent MDD risk SNPs in the MHC region likely converged to affect the mRNA level(s) of the same gene(s), and Europeans and Han Chinese populations have a substantial shared genetic and molecular basis underlying MDD risk associations in the MHC region. These results highlighted several potential pivotal genes at the MHC region in the pathogenesis of MDD. Their common impacts on multiple psychiatric relevant phenotypes also implicated the neurological processes shared by different psychological processes, such as mood and/or cognition, shedding lights on their potential biological mechanisms.

Functional characterization of two variants in the 3'-untranslated region (UTR) of transcription factor 4 gene and their association with schizophrenia in sib-pairs from multiplex families

Transcription factor 4 (TCF4) gene plays an important role in nervous system development and it always associated with the risk of schizophrenia. Since miRNAs regulate targetgenes by binding to 3'UTRs of target mRNAs, the functional variants located in 3'UTR of TCF4 are highly suggested to affect the gene expressions in schizophrenia. To test the hypothesis regarding the effects of the variants located in 3'UTR of TCF4, we conducted an in silico analysis to identify the functional variants and their predicted functions. In this study, we sequenced the 3'UTR of TCF4 in 13 multiplex schizophrenia families and 14 control families. We found two functional variants carried by three unrelated patients. We determined that the C allele of rs1272363 and the TC insert of rs373174214 might suppress post- transcriptional expression. Secondly, we cloned the region that flanked these two variants into a dual luciferase reporter system and compared the luciferase activities between the pmirGLO-TCF4 (control), pmirGLO-TCF4-rs373174214 and pmirGLO-TCF4-rs1273263. Both pmirGLO-TCF4-rs373174214 and pmirGLO-TCF4-rs1273263 caused lower reporter gene activities, as compared to the control. However, only the C allele of rs1272363 reduced the luciferase activity significantly (p = 0.0231). Our results suggested that rs1273263 is a potential regulator of TCF4 expression, and might be associated with schizophrenia.

Identification of miR-22-3p, miR-92a-3p, and miR-137 in peripheral blood as biomarker for schizophrenia

MicroRNAs (miRNAs) are a class of endogenous and non-coding single-stranded RNAs with length of about 22 nucleotides, and many are evolutionarily conserved. Although postmortem brain samples provide direct evidence of miRNA dysregulation within the brain, peripheral tissue samples can be obtained from living subjects and have the potential to yield biomarkers that could be used as diagnostic tools. To verify and detect additional miRNAs differentially expressed in peripheral blood and further explore their diagnostic value and function for schizophrenia, we performed a next-generation sequencing approach in combination with a literature search to select appropriate miRNAs. We then used real-time quantitative polymerase chain reaction (RT-qPCR) to identify miRNAs expressed aberrantly in schizophrenia. Binary regression analysis identified miR-22-3p, miR-92a-3p, and miR-137. Analysis of receiver operating characteristics (ROC) indicated that these three miRNAs could be used in combination as a biomarker for schizophrenia. Bioinformatic analyses of these genes and gene ontology (GO) enrichment revealed that the combination of miR-22-3p, miR-92a-3p, and miR-137 was closely associated with synaptic structure and function, which play important roles in the etiology and pathophysiology of schizophrenia.

Immediate Early Genes, Memory and Psychiatric Disorders: Focus on c-Fos, Egr1 and Arc

Many psychiatric disorders, despite their specific characteristics, share deficits in the cognitive domain including executive functions, emotional control and memory. However, memory deficits have been in many cases undervalued compared with other characteristics. The expression of Immediate Early Genes (IEGs) such as, c-fos, Egr1 and arc are selectively and promptly upregulated in learning and memory among neuronal subpopulations in regions associated with these processes. Changes in expression in these genes have been observed in recognition, working and fear related memories across the brain. Despite the enormous amount of data supporting changes in their expression during learning and memory and the importance of those cognitive processes in psychiatric conditions, there are very few studies analyzing the direct implication of the IEGs in mental illnesses. In this review, we discuss the role of some of the most relevant IEGs in relation with memory processes affected in psychiatric conditions.

Integrative genomic analysis of methylphenidate response in attention-deficit/hyperactivity disorder

Methylphenidate (MPH) is the most frequently used pharmacological treatment in children with attention-deficit/hyperactivity disorder (ADHD). However, a considerable interindividual variability exists in clinical outcome. Thus, we performed a genome-wide association study of MPH efficacy in 173 ADHD paediatric patients. Although no variant reached genome-wide significance, the set of genes containing single-nucleotide polymorphisms (SNPs) nominally associated with MPH response (P < 0.05) was significantly enriched for candidates previously studied in ADHD or treatment outcome. We prioritised the nominally significant SNPs by functional annotation and expression quantitative trait loci (eQTL) analysis in human brain, and we identified 33 SNPs tagging cis-eQTL in 32 different loci (referred to as eSNPs and eGenes, respectively). Pathway enrichment analyses revealed an over-representation of genes involved in nervous system development and function among the eGenes. Categories related to neurological diseases, psychological disorders and behaviour were also significantly enriched. We subsequently meta-analysed the association with clinical outcome for the 33 eSNPs across the discovery sample and an independent cohort of 189 ADHD adult patients (target sample) and we detected 15 suggestive signals. Following this comprehensive strategy, our results provide a better understanding of the molecular mechanisms implicated in MPH treatment effects and suggest promising candidates that may encourage future studies.

The importance of TCF4 gene in the etiology of recurrent depressive disorders

BACKGROUND

A recurrent depressive disorder is one of the most commonly diagnosed disease entities among psychiatric disorders. The prevalence and morbidity of depression are constantly increasing. Numerous studies have demonstrated the role of genetic factors in the etiology of depressive disorders. Many studies are being conducted to identify genes that predispose to depression. The purpose of this study was to investigate the role of TCF4 gene in the etiology of recurrent depressive disorders and, in particular, to assess expression of the TCF4 gene at the mRNA and protein level in patients with recurrent depressive disorders versus healthy individuals.

MATERIAL AND METHODS

The examined population consisted of 170 individuals suffering from depression and 90 healthy individuals. The expressions of the TCF4 gene at the mRNA and protein level were assessed.

RESULTS

Decreased TCF4 expression at the mRNA and protein level was found in patients with depressive disorder versus healthy individuals. Expression of the studied gene was not affected by the patients' sex and age. The statistical analysis also showed no correlation between the expression of TCF4 at the mRNA and protein level and the number of episodes or the severity of symptoms. Among the clinical manifestations of depression, only the duration of the illness correlated with the expression of TCF4 at the mRNA level.

CONCLUSIONS

Expression of TCF4 at the mRNA and protein level may be significant in the pathomechanism of recurrent depressive disorder and it is not dependent on sex and age.

Understanding and Predicting Antidepressant Response: Using Animal Models to Move Toward Precision Psychiatry

There are two important gaps of knowledge in depression treatment, namely the lack of biomarkers predicting response to antidepressants and the limited knowledge of the molecular mechanisms underlying clinical improvement. However, individually tailored treatment strategies and individualized prescription are greatly needed given the huge socio-economic burden of depression, the latency until clinical improvement can be observed and the response variability to a particular compound. Still, individual patient-level antidepressant treatment outcomes are highly unpredictable. In contrast to other therapeutic areas and despite tremendous efforts during the past years, the genomics era so far has failed to provide biological or genetic predictors of clinical utility for routine use in depression treatment. Specifically, we suggest to (1) shift the focus from the group patterns to individual outcomes, (2) use dimensional classifications such as Research Domain Criteria, and (3) envision better planning and improved connections between pre-clinical and clinical studies within translational research units. In contrast to studies in patients, animal models enable both searches for peripheral biosignatures predicting treatment response and in depth-analyses of the neurobiological pathways shaping individual antidepressant response in the brain. While there is a considerable number of animal models available aiming at mimicking disease-like conditions such as those seen in depressive disorder, only a limited number of preclinical or truly translational investigations is dedicated to the issue of heterogeneity seen in response to antidepressant treatment. In this mini-review, we provide an overview on the current state of knowledge and propose a framework for successful translational studies into antidepressant treatment response.

Common genes associated with antidepressant response in mouse and man identify key role of glucocorticoid receptor sensitivity

Response to antidepressant treatment in major depressive disorder (MDD) cannot be predicted currently, leading to uncertainty in medication selection, increasing costs, and prolonged suffering for many patients. Despite tremendous efforts in identifying response-associated genes in large genome-wide association studies, the results have been fairly modest, underlining the need to establish conceptually novel strategies. For the identification of transcriptome signatures that can distinguish between treatment responders and nonresponders, we herein submit a novel animal experimental approach focusing on extreme phenotypes. We utilized the large variance in response to antidepressant treatment occurring in DBA/2J mice, enabling sample stratification into subpopulations of good and poor treatment responders to delineate response-associated signature transcript profiles in peripheral blood samples. As a proof of concept, we translated our murine data to the transcriptome data of a clinically relevant human cohort. A cluster of 259 differentially regulated genes was identified when peripheral transcriptome profiles of good and poor treatment responders were compared in the murine model. Differences in expression profiles from baseline to week 12 of the human orthologues selected on the basis of the murine transcript signature allowed prediction of response status with an accuracy of 76% in the patient population. Finally, we show that glucocorticoid receptor (GR)-regulated genes are significantly enriched in this cluster of antidepressant-response genes. Our findings point to the involvement of GR sensitivity as a potential key mechanism shaping response to antidepressant treatment and support the hypothesis that antidepressants could stimulate resilience-promoting molecular mechanisms. Our data highlight the suitability of an appropriate animal experimental approach for the discovery of treatment response-associated pathways across species.

Major depression is the second leading cause of disability worldwide. However, only one-third of patients with depression benefit from the first antidepressant compound they are prescribed. It is a fundamental problem that the outcomes of individual antidepressant treatments are still highly unpredictable. In clinical studies, discovery of biomarkers for antidepressant response is hampered by confounding factors such as the heterogeneity of the disease phenotype and additional environmental factors, e.g., previous life events and different schedules of psychopharmacological treatment, which reduce the power to detect true response biomarkers. To overcome some of these limitations, we have established a conceptually novel approach that allows the selection of extreme phenotypes in an antidepressant-responsive mouse strain. In the first step, we identify signatures in the transcriptome of peripheral blood associated with responses following stratification into good and poor treatment responders. As proof of concept, we translate the murine data to a population of depressed patients. We show that differences in expression profiles from baseline to week 12 of the human orthologues predict response status in patients. We finally provide evidence that sensitivity of the glucocorticoid receptor could be a potential key mechanism shaping response to antidepressant treatment.

Health and well-being management in the military: a systematic review of genetic studies

BACKGROUND

Genetic research may have therapeutic value for mental and physical disorders and could have an indicative or preventative capacity. Little is known about the extent, form and utility of military-specific genetic research.

METHOD

A systematic review was conducted to evaluate existing genetic well-being studies of service personnel. The review specifically aimed to ascertain the current state of knowledge and feasibility of using genetics to aid recruitment and health management within military populations. Databases searched included MEDLINE, Embase, PsycINFO and Web of Science for relevant studies. Papers were rated using a genetics-specific quality assessment framework.

RESULTS

Ten papers were included within the final review, with seven mental-health-focused and three physical-health-focused genetic studies found within military populations. Eight papers considered candidate genes, one gene expression and one study was an outline of a future study of significant interest. Genetic commonalties were derived to yield shared physiological pathways. The 10 reviewed papers revealed moderate quality based on quality assessment.

CONCLUSIONS

Current genetic research within military populations is limited. Further studies on genetics, cost effectiveness, ethics and continual monitoring need to be explored before considering any movement toward clinical translation.

Genetic Basis of Positive and Negative Symptom Domains in Schizophrenia

Schizophrenia is a highly heritable disorder, the genetic etiology of which has been well established. Yet despite significant advances in genetics research, the pathophysiological mechanisms of this disorder largely remain unknown. This gap has been attributed to the complexity of the polygenic disorder, which has a heterogeneous clinical profile. Examining the genetic basis of schizophrenia subphenotypes, such as those based on particular symptoms, is thus a useful strategy for decoding the underlying mechanisms. This review of literature examines the recent advances (from 2011) in genetic exploration of positive and negative symptoms in schizophrenia. We searched electronic databases PubMed, Web of Science, and Cumulative Index to Nursing and Allied Health Literature using key words schizophrenia, symptoms, positive symptoms, negative symptoms, cognition, genetics, genes, genetic predisposition, and genotype in various combinations. We identified 115 articles, which are included in the review. Evidence from these studies, most of which are genetic association studies, identifies shared and unique gene associations for the symptom domains. Genes associated with neurotransmitter systems and neuronal development/maintenance primarily constitute the shared associations. Needed are studies that examine the genetic basis of specific symptoms within the broader domains in addition to functional mechanisms. Such investigations are critical to developing precision treatment and care for individuals afflicted with schizophrenia.

The Role of Early Growth Response 1 (EGR1) in Brain Plasticity and Neuropsychiatric Disorders

It is now clearly established that complex interactions between genes and environment are involved in multiple aspects of neuropsychiatric disorders, from determining an individual's vulnerability to onset, to influencing its response to therapeutic intervention. In this perspective, it appears crucial to better understand how the organism reacts to environmental stimuli and provide a coordinated and adapted response. In the central nervous system, neuronal plasticity and neurotransmission are among the major processes integrating such complex interactions between genes and environmental stimuli. In particular, immediate early genes (IEGs) are critical components of these interactions as they provide the molecular framework for a rapid and dynamic response to neuronal activity while opening the possibility for a lasting and sustained adaptation through regulation of the expression of a wide range of genes. As a result, IEGs have been tightly associated with neuronal activity as well as a variety of higher order processes within the central nervous system such as learning, memory and sensitivity to reward. The immediate early gene and transcription factor early growth response 1 (EGR1) has thus been revealed as a major mediator and regulator of synaptic plasticity and neuronal activity in both physiological and pathological conditions. In this review article, we will focus on the role of EGR1 in the central nervous system. First, we will summarize the different factors influencing its activity. Then, we will analyze the amount of data, including genome-wide, that has emerged in the recent years describing the wide variety of genes, pathways and biological functions regulated directly or indirectly by EGR1. We will thus be able to gain better insights into the mechanisms underlying EGR1's functions in physiological neuronal activity. Finally, we will discuss and illustrate the role of EGR1 in pathological states with a particular interest in cognitive functions and neuropsychiatric disorders.

Effect on the expression of drd2 and drd3 after neonatal lesion in the lymphocytes, nucleus accumbens, hippocampus and prefrontal cortex: comparative analysis between juvenile and adult Wistar rats

Background

Neonatal lesion in the ventral hippocampus (NLVH) is a validated animal model to study schizophrenia from a neurodevelopmental perspective. This animal model is also used to investigate how neonatal lesions may alter the genetic expression of dopaminergic receptors. The present study compares mRNA expression levels of dopamine receptors (drd2 and drd3) in lymphocytes and brain of NLVH animals at two different age stages: young and adult.

Methods

The NLVH procedure was performed on 20 male Wistar rats at postnatal days 5–7. The mRNA expression levels of drd2 and drd3 genes in lymphocytes, nucleus accumbens, hippocampus and prefrontal cortex were measured and analyzed at postnatal days 45 and 90. The results were compared and contrasted with respective sham groups.

Results

In lymphocytes, only in NLVH-adult group we observed drd2 mRNA expression, while drd2 mRNA expression was not observed in the NLVH-juvenile rats; on the other hand, the drd3 mRNA expression did not show significant statistical differences. In hippocampus no differences were observed between drd2 mRNA or drd3 mRNA expression when comparing juvenile/adult shams with NLVH groups. In the prefrontal area, a decrease in drd2 mRNA expression levels were observed in the NLVH-adult group (F(1,3) = 52.83, p = 0,005) in comparison to the sham-adult group. Finally, in the nucleus accumbens, a strong decrease of drd3 mRNA expression was observed in the NLVH-adult group in comparison to the sham-adult group (F(1,3) = 123,2, p < 0.001).

Conclusions

Our results show that differences in drd2 and drd3 mRNA levels in NLVH-adults are patent when compared to the sham-adult group or with the NLVH-juvenile group. These findings suggest that the expression levels may be regulated during adulthood, leading to behavioral and neurochemical changes related to schizophrenia. Therefore, more studies are necessary to determine the role of dopamine receptors as possible molecular markers for neurodevelopmental changes associated with schizophrenia.

Interaction of multiple gene variants and their effects on schizophrenia phenotypes

BACKGROUND

Schizophrenia is a clinically heterogeneous disorder and may be explained by its complex genetic architecture. Many schizophrenia susceptibility genes were identified but the picture remains unclear due to inconsistent or contradictory genetic association studies. This confusion may, in part, be because symptoms result from the combined interaction of many genes and these interacting genes are associated with specific sub-phenotypes of schizophrenia rather than schizophrenia as a whole. This study investigates the relationship between schizophrenia susceptibility genes and schizophrenia sub-phenotypes by identifying multiple gene variant interactions.

MATERIALS AND METHODS

Fifty SNPs from 21 genes were genotyped in 235 Australian participants with schizophrenia screened for various phenotypes. Schizophrenia participants were grouped into relevant phenotype clusters using cluster analysis and normalized phenotype cluster scores were calculated for each patient. The relationship between genotypes and normalized phenotype cluster scores were analyzed by linear regression analysis.

RESULTS

Three phenotype clusters were identified. There was some overlap in symptoms between phenotype clusters, particularly for depression. However, cluster 1 appears to be characterized by speech disorder and affective behavior symptoms, cluster 2 has predominantly hallucination symptoms and cluster 3 has mainly delusion symptoms. Interaction of five SNPs was found to have an effect on cluster 1 symptoms; ten SNPs on cluster 2 symptoms; and eight SNPs on cluster 3 symptoms.

CONCLUSION

The interaction of specific susceptibility genes is likely to lead to specific clinical sub-phenotypes of schizophrenia. Larger patient cohorts with more extensive clinical data will improve the detection of gene interactions and the resultant schizophrenia clinical phenotypes.

Transcriptome sequencing of the choroid plexus in schizophrenia

The choroid plexus (CP) has a key role in maintaining brain homeostasis by producing cerebrospinal fluid (CSF), by mediating transport of nutrients and removing metabolic products from the central nervous system and by responding to peripheral inflammatory signals. Although abnormal markers of immune response and inflammation are apparent in individuals with schizophrenia, the CP of these individuals has not been characterized. We therefore sequenced mRNA from the CP from two independent collections of individuals with schizophrenia and unaffected controls. Genes related to immune function and inflammation were upregulated in both collections. In addition, a co-expression module related to immune/inflammation response that was generated by combining mRNA-Seq data from both collections was significantly associated with disease status. The immune/inflammation-related co-expression module was positively correlated with levels of C-reactive protein (CRP), cortisol and several immune modulator proteins in the serum of the same individuals and was also positively correlated with CRP, cortisol and pro-inflammatory cytokines in the frontal cortex of the same individuals. In addition, we found a substantial number of nodes (genes) that were common to our schizophrenia-associated immune/inflammation module from the pooled data and a module we generated from lippopolysaccharides-treated mouse model data. These results suggest that the CP of individuals with schizophrenia are responding to signals from the periphery by upregulating immune/inflammation-related genes to protect the brain and maintain the homeostasis but nevertheless fails to completely prevent immune/inflammation related changes in the brain.

Tcf4 Controls Neuronal Migration of the Cerebral Cortex through Regulation of Bmp7

Background: Transcription factor 4 (TCF4) is found to be associated with schizophrenia. TCF4 mutations also cause Pitt-Hopkins Syndrome, a neurodevelopmental disorder associated with severe mental retardation. However, the function of TCF4 during brain development remains unclear.

Results: Here, we report that Tcf4 is expressed in the developing cerebral cortex. In utero suppression of Tcf4 arrested neuronal migration, leading to accumulation of ectopic neurons in the intermediate zone. Knockdown of Tcf4 impaired leading process formation. Furthermore, Bone Morphogenetic Protein 7 (Bmp7) is upregulated in Tcf4-deficient neurons. In vivo gain of function and rescue experiments demonstrated that Bmp7 is the major downstream effector of Tcf4 required for neuronal migration.

Conclusion: Thus, we have uncovered a new Tcf4/Bmp7-dependent mechanism underlying neuronal migration, and provide insights into the pathogenesis of neurodevelopmental disorders.