Gene expression changes following chronic antipsychotic exposure in single cells from mouse striatum

Transcriptomic Evaluation of a Stress Vulnerability Network using Single Cell RNA-Seq in mouse Prefrontal Cortex

BACKGROUND

Increased vulnerability to stress is a major risk factor for several mood disorders, including major depressive disorder (MDD). Although cellular and molecular mechanisms associated with depressive behaviors following stress have been identified, little is known about the mechanisms conferring vulnerability that predisposes individuals to future damage from chronic stress.

METHODS

We used multi-site in vivo neurophysiology in freely behaving male and female C57BL/6 mice (n=12) to measure electrical brain network activity previously identified as indicating a latent stress vulnerability brain state. We combined this neurophysiological approach with single-cell RNA sequencing (scRNA-Seq) of the prefrontal cortex (PFC) to identify distinct transcriptomic differences between groups of mice with inherent high and low stress vulnerability.

RESULTS

We identified hundreds of differentially expressed genes (padj <0.05) across five major cell types between animals with high and low stress vulnerability brain network activity. This unique analysis revealed that GABAergic neuron gene expression contributes most to the network activity of the stress vulnerability brain state. Upregulation of mitochondrial and metabolic pathways also distinguished high and low vulnerability brain states, especially in inhibitory neurons. Importantly, genes that were differentially regulated with vulnerability network activity significantly overlapped (above chance) with those identified by genome-wide association studies (GWAS) as having SNPs significantly associated with depression as well as genes more highly expressed in post-mortem PFC of patients with MDD.

CONCLUSIONS

This is the first study to identify cell types and genes involved in a latent stress vulnerability state in the brain.

Disentangling associations between complex traits and cell types with seismic

Integrating single-cell RNA sequencing (scRNA-seq) with Genome-Wide Association Studies (GWAS) can help reveal GWAS-associated cell types, furthering our understanding of the cell-type-specific biological processes underlying complex traits and disease. However, current methods have technical limitations that hinder them from making systematic, scalable, interpretable disease-cell-type associations. In order to rapidly and accurately pinpoint associations, we develop a novel framework, seismic, which characterizes cell types using a new specificity score. We compare seismic with alternative methods across over 1,000 cell type characterizations at different granularities and 28 traits, demonstrating that seismic both corroborates findings and identifies trait-relevant cell groups which are not apparent through other methodologies. Furthermore, as part of the seismic framework, the specific genes driving cell type-trait associations can easily be accessed and analyzed, enabling further biological insights. The advantages of seismic are particularly salient in neurodegenerative diseases such as Parkinson's and Alzheimer's, where disease pathology has not only cell-specific manifestations, but also brain region-specific differences. Interestingly, a case study of Alzheimer's disease reveals the importance of considering GWAS endpoints, as studies relying on clinical diagnoses consistently identify microglial associations, while GWAS with a tau biomarker endpoint reveals neuronal associations. In general, seismic is a computationally efficient, powerful, and interpretable approach for identifying associations between complex traits and cell type-specific expression.

The polymorphisms of candidate pharmacokinetic and pharmacodynamic genes and their pharmacogenetic impacts on the effectiveness of risperidone maintenance therapy among Saudi children with autism

BACKGROUND

Antipsychotics, including risperidone (RIS), are frequently indicated for various autism spectrum disorder (ASD) manifestations; however, "actionable" PGx testing in psychiatry regarding antipsychotic dosing and selection has limited applications in routine clinical practice because of the lack of standard guidelines, mostly due to the inconsistency and scarcity of genetic variant data. The current study is aimed at examining the association of RIS effectiveness, according to ABC-CV and CGI indexes, with relevant pharmacokinetics (PK) and pharmacodynamics (PD) genes.

METHODS

Eighty-nine ASD children who received a consistent RIS-based regimen for at least 8 weeks were included. The Axiom PharmacoFocus Array technique was employed to generate accurate star allele-predicted phenotypes of 3 PK genes (CYP3A4, CYP3A5, and CYP2D6). Genotype calls for 5 candidate PD receptor genes (DRD1, DRD2, DRD3, HTR2C, and HTR2A) were obtained and reported as wild type, heterozygous, or homozygous for 11 variants.

RESULTS

Based on the ABC total score, 42 (47.2%) children were classified as responders, while 47 (52.8%) were classified as nonresponders. Multivariate logistic regression analyses, adjusted for nongenetic factors, suggested nonsignificant impacts of the star allele-predicted phenotypes of all 3 PK genes on improvement in ASD symptoms or CGI scores. However, significant positive or negative associations of certain PD variants involved in dopaminergic and serotonergic pathways were observed with specific ASD core and noncore symptom subdomains. Our significant polymorphism findings, mainly those in DRD2 (rs1800497, rs1799978, and rs2734841), HTR2C (rs3813929), and HTR2A (rs6311), were largely consistent with earlier findings (predictors of RIS effectiveness in adult schizophrenia patients), confirming their validity for identifying ASD children with a greater likelihood of core symptom improvement compared to noncarriers/wild types. Other novel findings of this study, such as significant improvements in DRD3 rs167771 carriers, particularly in ABC total and lethargy/social withdrawal scores, and DRD1 rs1875964 homozygotes and DRD2 rs1079598 wild types in stereotypic behavior, warrant further verification in biochemical and clinical studies to confirm their feasibility for inclusion in a PGx panel.

CONCLUSION

In conclusion, we provide evidence of potential genetic markers involved in clinical response variability to RIS therapy in ASD children. However, replication in prospective samples with greater ethnic diversity and sample sizes is necessary.

A Cre-dependent massively parallel reporter assay allows for cell-type specific assessment of the functional effects of non-coding elements in vivo

The function of regulatory elements is highly dependent on the cellular context, and thus for understanding the function of elements associated with psychiatric diseases these would ideally be studied in neurons in a living brain. Massively Parallel Reporter Assays (MPRAs) are molecular genetic tools that enable functional screening of hundreds of predefined sequences in a single experiment. These assays have not yet been adapted to query specific cell types in vivo in a complex tissue like the mouse brain. Here, using a test-case 3'UTR MPRA library with genomic elements containing variants from autism patients, we developed a method to achieve reproducible measurements of element effects in vivo in a cell type-specific manner, using excitatory cortical neurons and striatal medium spiny neurons as test cases. This targeted technique should enable robust, functional annotation of genetic elements in the cellular contexts most relevant to psychiatric disease.

Single Cell Transcriptome of Stress Vulnerability Network in mouse Prefrontal Cortex

Increased vulnerability to stress is a major risk factor for the manifestation of several mood disorders, including major depressive disorder (MDD). Despite the status of MDD as a significant donor to global disability, the complex integration of genetic and environmental factors that contribute to the behavioral display of such disorders has made a thorough understanding of related etiology elusive. Recent developments suggest that a brain-wide network approach is needed, taking into account the complex interplay of cell types spanning multiple brain regions. Single cell RNA-sequencing technologies can provide transcriptomic profiling at the single-cell level across heterogenous samples. Furthermore, we have previously used local field potential oscillations and machine learning to identify an electrical brain network that is indicative of a predisposed vulnerability state. Thus, this study combined single cell RNA-sequencing (scRNA-Seq) with electrical brain network measures of the stress-vulnerable state, providing a unique opportunity to access the relationship between stress network activity and transcriptomic changes within individual cell types. We found especially high numbers of differentially expressed genes between animals with high and low stress vulnerability brain network activity in astrocytes and glutamatergic neurons but we estimated that vulnerability network activity depends most on GABAergic neurons. High vulnerability network activity included upregulation of microglia and mitochondrial and metabolic pathways, while lower vulnerability involved synaptic regulation. Genes that were differentially regulated with vulnerability network activity significantly overlapped with genes identified as having significant SNPs by human GWAS for depression. Taken together, these data provide the gene expression architecture of a previously uncharacterized stress vulnerability brain state, enabling new understanding and intervention of predisposition to stress susceptibility.

Minocycline and antipsychotics inhibit inflammatory responses in BV-2 microglia activated by LPS via regulating the MAPKs/ JAK-STAT signaling pathway

BACKGROUND

Abnormal activation of microglia is involved in the pathogenesis of schizophrenia. Minocycline and antipsychotics have been reported to be effective in inhibiting the activation of microglia and thus alleviating the negative symptoms of patients with schizophrenia. However, the specific molecular mechanism by which minocycline and antipsychotics inhibit microglial activation is not clear. In this study, we aimed to explore the molecular mechanism of treatment effect of minocycline and antipsychotics on schizophrenia.

METHODS

Microglia cells were activated by lipopolysaccharide (LPS) and further treated with minocycline, haloperidol, and risperidone. Then cell morphology, specific marker, cytokines, and nitric oxide production process, and the proteins in related molecular signaling pathways in LPS-activated microglia were compared among groups.

RESULTS

The study found that minocycline, risperidone, and haloperidol significantly inhibited morphological changes and reduced the expression of OX-42 protein induced by LPS. Minocycline significantly decreased the production of interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and interleukin-1beta (IL-1β). Risperidone also showed significant decrease in the production of IL-6 and TNF-α, while haloperidol only showed significant decrease in the production of IL-6. Minocycline, risperidone, and haloperidol were found to significantly inhibit nitric oxide (NO) expression, but had no effect on inducible nitric oxide synthase (iNOS) expression. Both minocycline and risperidone were effective in decreasing the activity of c‑Jun N‑terminal kinase (JNK) and extracellular signal-regulated kinase (ERK) in the mitogen-activated protein kinases (MAPKs) signal pathway. Additionally, minocycline and risperidone were found to increase the activity of phosphorylated-p38. In contrast, haloperidol only suppressed the activity of ERK. Minocycline also suppressed the activation of janus kinase 2 (JAK2) and signal transducer and activator of transcription 3 (STAT3), while risperidone and haloperidol only suppressed the activation of STAT3.

CONCLUSIONS

The results demonstrated that minocycline and risperidone exert stronger anti-inflammatory and neuroprotective effects stronger than haloperidol, through MAPKs and Janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling pathways in BV2 cells stimulated with LPS, revealing the underlying mechanisms of minocycline and atypical antipsychotics in the treatment of negative schizophrenia symptoms.

Hypothalamic JNK1-hepatic fatty acid synthase axis mediates a metabolic rewiring that prevents hepatic steatosis in male mice treated with olanzapine via intraperitoneal: Additional effects of PTP1B inhibition

Olanzapine (OLA), a widely used second-generation antipsychotic (SGA), causes weight gain and metabolic alterations when administered orally to patients. Recently, we demonstrated that, contrarily to the oral treatment which induces weight gain, OLA administered via intraperitoneal (i.p.) in male mice resulted in body weight loss. This protection was due to an increase in energy expenditure (EE) through a mechanism involving the modulation of hypothalamic AMPK activation by higher OLA levels reaching this brain region compared to those of the oral treatment. Since clinical studies have shown hepatic steatosis upon chronic treatment with OLA, herein we further investigated the role of the hypothalamus-liver interactome upon OLA administration in wild-type (WT) and protein tyrosine phosphatase 1B knockout (PTP1B-KO) mice, a preclinical model protected against metabolic syndrome. WT and PTP1B-KO male mice were fed an OLA-supplemented diet or treated via i.p. Mechanistically, we found that OLA i.p. treatment induces mild oxidative stress and inflammation in the hypothalamus in a JNK1-independent and dependent manner, respectively, without features of cell dead. Hypothalamic JNK activation up-regulated lipogenic gene expression in the liver though the vagus nerve. This effect concurred with an unexpected metabolic rewiring in the liver in which ATP depletion resulted in increased AMPK/ACC phosphorylation. This starvation-like signature prevented steatosis. By contrast, intrahepatic lipid accumulation was observed in WT mice treated orally with OLA; this effect being absent in PTP1B-KO mice. We also demonstrated an additional benefit of PTP1B inhibition against hypothalamic JNK activation, oxidative stress and inflammation induced by chronic OLA i.p. treatment, thereby preventing hepatic lipogenesis. The protection conferred by PTP1B deficiency against hepatic steatosis in the oral OLA treatment or against oxidative stress and neuroinflammation in the i.p. treatment strongly suggests that targeting PTP1B might be also a therapeutic strategy to prevent metabolic comorbidities in patients under OLA treatment in a personalized manner.

Unraveling Psychiatric Disorders through Neural Single-Cell Transcriptomics Approaches

The development of single-cell and single-nucleus transcriptome technologies is enabling the unraveling of the molecular and cellular heterogeneity of psychiatric disorders. The complexity of the brain and the relationships between different brain regions can be better understood through the classification of individual cell populations based on their molecular markers and transcriptomic features. Analysis of these unique cell types can explain their involvement in the pathology of psychiatric disorders. Recent studies in both human and animal models have emphasized the importance of transcriptome analysis of neuronal cells in psychiatric disorders but also revealed critical roles for non-neuronal cells, such as oligodendrocytes and microglia. In this review, we update current findings on the brain transcriptome and explore molecular studies addressing transcriptomic alterations identified in human and animal models in depression and stress, neurodegenerative disorders (Parkinson's and Alzheimer's disease), schizophrenia, opioid use disorder, and alcohol and psychostimulant abuse. We also comment on potential future directions in single-cell and single-nucleus studies.

MicroRNA schizophrenia: Etiology, biomarkers and therapeutic targets

The three sets of symptoms associated with schizophrenia-positive, negative, and cognitive-are burdensome and have serious effects on public health, which affects up to 1% of the population. It is now commonly believed that in addition to the traditional dopaminergic mesolimbic pathway, the etiology of schizophrenia also includes neuronal networks, such as glutamate, GABA, serotonin, BDNF, oxidative stress, inflammation and the immune system. Small noncoding RNA molecules called microRNAs (miRNAs) have come to light as possible participants in the pathophysiology of schizophrenia in recent years by having an impact on these systems. These small RNAs regulate the stability and translation of hundreds of target transcripts, which has an impact on the entire gene network. There may be improved approaches to treat and diagnose schizophrenia if it is understood how these changes in miRNAs alter the critical related signaling pathways that drive the development and progression of the illness.

New insight in the cross-talk between microglia and schizophrenia: From the perspective of neurodevelopment

Characterized by psychotic symptoms, negative symptoms and cognitive deficits, schizophrenia had a catastrophic effect on patients and their families. Multifaceted reliable evidence indicated that schizophrenia is a neurodevelopmental disorder. Microglia, the immune cells in central nervous system, related to many neurodevelopmental diseases. Microglia could affect neuronal survival, neuronal death and synaptic plasticity during neurodevelopment. Anomalous microglia during neurodevelopment may be associated with schizophrenia. Therefore, a hypothesis proposes that the abnormal function of microglia leads to the occurrence of schizophrenia. Nowadays, accumulating experiments between microglia and schizophrenia could afford unparalleled probability to assess this hypothesis. Herein, this review summarizes the latest supporting evidence in order to shed light on the mystery of microglia in schizophrenia.