Expression analysis in a rat psychosis model identifies novel candidate genes validated in a large case-control sample of schizophrenia

Hypoxia-sensing VGLL4 promotes LDHA-driven lactate production to ameliorate neuronal dysfunction in a cellular model relevant to Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disease where abnormal amyloidogenic processing of amyloid-β precursor protein (APP) occurs and has been linked to neuronal dysfunction. Hypometabolism of glucose in the brain can lead to synaptic loss and neuronal death, which in turn exacerbates energy deficiency and amyloid-β peptide (Aβ) accumulation. Lactate produced by anaerobic glycolysis serves as an energy substrate supporting neuronal function and facilitating neuronal repair. Vestigial-like family member 4 (VGLL4) has been recognized as a key regulator of the hypoxia-sensing pathway. However, the role of VGLL4 in AD remains unexplored. Here, we reported that the expression of VGLL4 protein was significantly decreased in the brain tissue of AD model mice and AD model cells. We further found that overexpression of VGLL4 reduced APP amyloidogenic processing and ameliorated neuronal synaptic damage. Notably, we identified a compromised hypoxia-sensitive capability of LDHA regulated by VGLL4 in the context of AD. Upregulation of VGLL4 increased the response of LDHA to hypoxia and enhanced the expression levels of LDHA and lactate by inhibiting the ubiquitination and degradation of LDHA. Furthermore, the inhibition of lactate production by using sodium oxamate, an inhibitor of LDHA, suppressed the neuroprotective function of VGLL4 by increasing APP amyloidogenic processing. Taken together, our findings demonstrate that VGLL4 exerts a neuroprotective effect by upregulating LDHA expression and consequently promoting lactate production. Thus, this study suggests that VGLL4 may be a novel player involved in molecular mechanisms relevant for ameliorating neurodegeneration.

Hippo Pathway in Schwann Cells and Regeneration of Peripheral Nervous System

Hippo pathway is an evolutionarily conserved signaling pathway comprising a series of MST/LATS kinase complexes. Its key transcriptional coactivators YAP and TAZ regulate transcription factors such as TEAD family to direct gene expression. The regulation of Hippo pathway, especially the nuclear level change of YAP and TAZ, significantly influences the cell fate switching from proliferation to differentiation, regeneration, and postinjury repair. This review outlines the main findings of Hippo pathway in peripheral nerve development, regeneration, and tumorigenesis, especially the studies in Schwann cells. We also summarize other roles of Hippo pathway in damage repair of the peripheral nerve system and discuss the potential future research which probably contributes to novel therapeutic strategies.

A brain atlas of synapse protein lifetime across the mouse lifespan

The lifetime of proteins in synapses is important for their signaling, maintenance, and remodeling, and for memory duration. We quantified the lifetime of endogenous PSD95, an abundant postsynaptic protein in excitatory synapses, at single-synapse resolution across the mouse brain and lifespan, generating the Protein Lifetime Synaptome Atlas. Excitatory synapses have a wide range of PSD95 lifetimes extending from hours to several months, with distinct spatial distributions in dendrites, neurons, and brain regions. Synapses with short protein lifetimes are enriched in young animals and in brain regions controlling innate behaviors, whereas synapses with long protein lifetimes accumulate during development, are enriched in the cortex and CA1 where memories are stored, and are preferentially preserved in old age. Synapse protein lifetime increases throughout the brain in a mouse model of autism and schizophrenia. Protein lifetime adds a further layer to synapse diversity and enriches prevailing concepts in brain development, aging, and disease.

Gene co-expression architecture in peripheral blood in a cohort of remitted first-episode schizophrenia patients

A better understanding of schizophrenia subtypes is necessary to stratify the patients according to clinical attributes. To explore the genomic architecture of schizophrenia symptomatology, we analyzed blood co-expression modules and their association with clinical data from patients in remission after a first episode of schizophrenia. In total, 91 participants of the 2EPS project were included. Gene expression was assessed using the Clariom S Human Array. Weighted-gene co-expression network analysis (WGCNA) was applied to identify modules of co-expressed genes and to test its correlation with global functioning, clinical symptomatology, and premorbid adjustment. Among the 25 modules identified, six modules were significantly correlated with clinical data. These modules could be clustered in two groups according to their correlation with clinical data. Hub genes in each group showing overlap with risk genes for schizophrenia were enriched in biological processes related to metabolic processes, regulation of gene expression, cellular localization and protein transport, immune processes, and neurotrophin pathways. Our results indicate that modules with significant associations with clinical data showed overlap with gene sets previously identified in differential gene-expression analysis in brain, indicating that peripheral tissues could reveal pathogenic mechanisms. Hub genes involved in these modules revealed multiple signaling pathways previously related to schizophrenia, which may represent the complex interplay in the pathological mechanisms behind the disease. These genes could represent potential targets for the development of peripheral biomarkers underlying illness traits in clinical remission stages after a first episode of schizophrenia.

Modeling sex differences in humans using isogenic induced pluripotent stem cells

Biological sex is a fundamental trait influencing development, reproduction, pathogenesis, and medical treatment outcomes. Modeling sex differences is challenging because of the masking effect of genetic variability and the hurdle of differentiating chromosomal versus hormonal effects. In this work we developed a cellular model to study sex differences in humans. Somatic cells from a mosaic Klinefelter syndrome patient were reprogrammed to generate isogenic induced pluripotent stem cell (iPSC) lines with different sex chromosome complements: 47,XXY/46,XX/46,XY/45,X0. Transcriptional analysis of the hiPSCs revealed novel and known genes and pathways that are sexually dimorphic in the pluripotent state and during early neural development. Female hiPSCs more closely resembled the naive pluripotent state than their male counterparts. Moreover, the system enabled differentiation between the contributions of X versus Y chromosome to these differences. Taken together, isogenic hiPSCs present a novel platform for studying sex differences in humans and bear potential to promote gender-specific medicine in the future.

Classification for psychiatric disorders including schizophrenia, bipolar disorder, and major depressive disorder using machine learning

Schizophrenia (SCZ), bipolar disorder (BP), and major depressive disorder (MDD) are the most common psychiatric disorders. Because there were lots of overlaps among these disorders from genetic epidemiology and molecular genetics, it is hard to realize the diagnoses of these psychiatric disorders. Currently, plenty of studies have been conducted for contributing to the diagnoses of these diseases. However, constructing a classification model with superior performance for differentiating SCZ, BP, and MDD samples is still a great challenge. In this study, the transcriptomic data was applied for discovering key genes and constructing a classification model. In this dataset, there were 268 samples including four groups (67 SCZ patients, 40 BP patients, 57 MDD patients, and 104 healthy controls), which were applied for constructing a classification model. First, 269 probes of differentially expressed genes (DEGs) among four sample groups were identified by the feature selection method. Second, these DEGs were validated by the literature review including disease relevance with the psychiatric disorders of these DEGs, the hub genes in the PPI (protein–protein interaction) network, and GO (gene ontology) terms and pathways. Third, a classification model was constructed using the identified DEGs by machine learning method to classify different groups. The ROC (receiver operator characteristic) curve and AUC (area under the curve) value were used to assess the classification capacity of the model. In summary, this classification model might provide clues for the diagnoses of these psychiatric disorders.

Region-based analysis of rare genomic variants in whole-genome sequencing datasets reveal two novel Alzheimer's disease-associated genes: DTNB and DLG2

Alzheimer's disease (AD) is a genetically complex disease for which nearly 40 loci have now been identified via genome-wide association studies (GWAS). We attempted to identify groups of rare variants (alternate allele frequency <0.01) associated with AD in a region-based, whole-genome sequencing (WGS) association study (rvGWAS) of two independent AD family datasets (NIMH/NIA; 2247 individuals; 605 families). Employing a sliding window approach across the genome, we identified several regions that achieved association p values <10^-6, using the burden test or the SKAT statistic. The genomic region around the dystobrevin beta (DTNB) gene was identified with the burden and SKAT test and replicated in case/control samples from the ADSP study reaching genome-wide significance after meta-analysis (p_meta = 4.74 × 10^-8). SKAT analysis also revealed region-based association around the Discs large homolog 2 (DLG2) gene and replicated in case/control samples from the ADSP study (p_meta = 1 × 10^-6). In conclusion, in a region-based rvGWAS of AD we identified two novel AD genes, DLG2 and DTNB, based on association with rare variants.

Overlap in genetic risk for cross-disorder vulnerability to mental disorders and genetic risk for altered subcortical brain volumes

BACKGROUND

There have been considerable recent advances in understanding the genetic architecture of psychiatric disorders as well as the underlying neurocircuitry. However, there is little work on the concordance of genetic variations that increase risk for cross-disorder vulnerability, and those that influence subcortical brain structures. We undertook a genome-wide investigation of the genetic overlap between cross-disorder vulnerability to psychiatric disorders (p-factor) and subcortical brain structures.

METHODS

Summary statistics were obtained from the PGC cross-disorder genome-wide association study (GWAS) (N_case= 232,964, N_control= 494,162) and the CHARGE-ENIGMA subcortical brain volumes GWAS (N=38,851). SNP effect concordance analysis (SECA) was used to assess pleiotropy and concordance. Linkage Disequilibrium (LD) Score Regression and ρ-HESS were used to assess genetic correlation and conditional false discovery (cFDR) was used to identify variants associated with p-factor, conditional on the variants association with subcortical brain volumes.

RESULTS

Evidence of global pleiotropy between p-factor and all subcortical brain regions was observed. Risk variants for p-factor correlated negatively with brainstem. A total of 787 LD-independent variants were significantly associated with p-factor when conditioned on the subcortical GWAS results. Gene set enrichment analysis of these variants implicated actin binding and neuronal regulation.

LIMITATIONS

SECA could be biased due to the potential presence of overlapping study participants in the p-factor and subcortical GWASs.

CONCLUSION

Findings of genome-wide pleiotropy and possible concordance between genetic variants that contribute to p-factor and smaller brainstem volumes, are consistent with previous work. cFDR results highlight actin binding and neuron regulation as key underlying mechanisms. Further fine-grained delineation of these mechanisms is needed to advance the field.

Quantitative endophenotypes as an alternative approach to understanding genetic risk in neurodegenerative diseases

Endophenotypes, as measurable intermediate features of human diseases, reflect underlying molecular mechanisms. The use of quantitative endophenotypes in genetic studies has improved our understanding of pathophysiological changes associated with diseases. The main advantage of the quantitative endophenotypes approach to study human diseases over a classic case-control study design is the inferred biological context that can enable the development of effective disease-modifying treatments. Here, we summarize recent progress on biomarkers for neurodegenerative diseases, including cerebrospinal fluid and blood-based, neuroimaging, neuropathological, and clinical studies. This review focuses on how endophenotypic studies have successfully linked genetic modifiers to disease risk, disease onset, or progression rate and provided biological context to genes identified in genome-wide association studies. Finally, we review critical methodological considerations for implementing this approach and future directions.

A DLG2 deficiency in mice leads to reduced sociability and increased repetitive behavior accompanied by aberrant synaptic transmission in the dorsal striatum

Background

DLG2, also known as postsynaptic density protein-93 (PSD-93) or chapsyn-110, is an excitatory postsynaptic scaffolding protein that interacts with synaptic surface receptors and signaling molecules. A recent study has demonstrated that mutations in the DLG2 promoter region are significantly associated with autism spectrum disorder (ASD). Although DLG2 is well known as a schizophrenia-susceptibility gene, the mechanisms that link DLG2 gene disruption with ASD-like behaviors remain unclear.

Methods

Mice lacking exon 14 of the Dlg2 gene (Dlg2^–/– mice) were used to investigate whether Dlg2 deletion leads to ASD-like behavioral abnormalities. To this end, we performed a battery of behavioral tests assessing locomotion, anxiety, sociability, and repetitive behaviors. In situ hybridization was performed to determine expression levels of Dlg2 mRNA in different mouse brain regions during embryonic and postnatal brain development. We also measured excitatory and inhibitory synaptic currents to determine the impacts of Dlg2 deletion on synaptic transmission in the dorsolateral striatum.

Results

Dlg2^–/– mice showed hypoactivity in a novel environment. They also exhibited decreased social approach, but normal social novelty recognition, compared with wild-type animals. In addition, Dlg2^–/– mice displayed strong self-grooming, both in home cages and novel environments. Dlg2 mRNA levels in the striatum were heightened until postnatal day 7 in mice, implying potential roles of DLG2 in the development of striatal connectivity. In addition, the frequency of excitatory, but not inhibitory, spontaneous postsynaptic currents in the Dlg2^–/– dorsolateral striatum was significantly reduced.

Conclusion

These results suggest that homozygous Dlg2 deletion in mice leads to ASD-like behavioral phenotypes, including social deficits and increased repetitive behaviors, as well as reductions in excitatory synaptic input onto dorsolateral spiny projection neurons, implying that the dorsal striatum is one of the brain regions vulnerable to the developmental dysregulation of DLG2.

The Relationship Between Polygenic Risk Scores and Cognition in Schizophrenia

BACKGROUND

Cognitive impairment is a clinically important feature of schizophrenia. Polygenic risk score (PRS) methods have demonstrated genetic overlap between schizophrenia, bipolar disorder (BD), major depressive disorder (MDD), educational attainment (EA), and IQ, but very few studies have examined associations between these PRS and cognitive phenotypes within schizophrenia cases.

METHODS

We combined genetic and cognitive data in 3034 schizophrenia cases from 11 samples using the general intelligence factor g as the primary measure of cognition. We used linear regression to examine the association between cognition and PRS for EA, IQ, schizophrenia, BD, and MDD. The results were then meta-analyzed across all samples. A genome-wide association studies (GWAS) of cognition was conducted in schizophrenia cases.

RESULTS

PRS for both population IQ (P = 4.39 × 10-28) and EA (P = 1.27 × 10-26) were positively correlated with cognition in those with schizophrenia. In contrast, there was no association between cognition in schizophrenia cases and PRS for schizophrenia (P = .39), BD (P = .51), or MDD (P = .49). No individual variant approached genome-wide significance in the GWAS.

CONCLUSIONS

Cognition in schizophrenia cases is more strongly associated with PRS that index cognitive traits in the general population than PRS for neuropsychiatric disorders. This suggests the mechanisms of cognitive variation within schizophrenia are at least partly independent from those that predispose to schizophrenia diagnosis itself. Our findings indicate that this cognitive variation arises at least in part due to genetic factors shared with cognitive performance in populations and is not solely due to illness or treatment-related factors, although our findings are consistent with important contributions from these factors.

Genetic Intersections of Language and Neuropsychiatric Conditions

PURPOSE OF REVIEW

To better understand the shared basis of language and mental health, this review examines the behavioral and neurobiological features of aberrant language in five major neuropsychiatric conditions. Special attention is paid to genes implicated in both language and neuropsychiatric disorders, as they reveal biological domains likely to underpin the processes controlling both.

RECENT FINDINGS

Abnormal language and communication are common manifestations of neuropsychiatric conditions, and children with impaired language are more likely to develop psychiatric disorders than their peers. Major themes in the genetics of both language and psychiatry include master transcriptional regulators, like FOXP2; key developmental regulators, like AUTS2; and mediators of neurotransmission, like GRIN2A and CACNA1C.

A screen of 1,049 schizophrenia and 30 Alzheimer's-associated variants for regulatory potential

Recent genome-wide association studies (GWAS) identified numerous schizophrenia (SZ) and Alzheimer's disease (AD) associated loci, most outside protein-coding regions and hypothesized to affect gene transcription. We used a massively parallel reporter assay to screen, 1,049 SZ and 30 AD variants in 64 and nine loci, respectively for allele differences in driving reporter gene expression. A library of synthetic oligonucleotides assaying each allele five times was transfected into K562 chronic myelogenous leukemia lymphoblasts and SK-SY5Y human neuroblastoma cells. One hundred forty eight variants showed allelic differences in K562 and 53 in SK-SY5Y cells, on average 2.6 variants per locus. Nine showed significant differences in both lines, a modest overlap reflecting different regulatory landscapes of these lines that also differ significantly in chromatin marks. Eight of nine were in the same direction. We observe no preference for risk alleles to increase or decrease expression. We find a positive correlation between the number of SNPs in linkage disequilibrium and the proportion of functional SNPs supporting combinatorial effects that may lead to haplotype selection. Our results prioritize future functional follow up of disease associated SNPs to determine the driver GWAS variant(s), at each locus and enhance our understanding of gene regulation dynamics.

Genetic architecture of subcortical brain structures in 38,851 individuals

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.

Genetic Control of Expression and Splicing in Developing Human Brain Informs Disease Mechanisms

Tissue-specific regulatory regions harbor substantial genetic risk for disease. Because brain development is a critical epoch for neuropsychiatric disease susceptibility, we characterized the genetic control of the transcriptome in 201 mid-gestational human brains, identifying 7,962 expression quantitative trait loci (eQTL) and 4,635 spliceQTL (sQTL), including several thousand prenatal-specific regulatory regions. We show that significant genetic liability for neuropsychiatric disease lies within prenatal eQTL and sQTL. Integration of eQTL and sQTL with genome-wide association studies (GWAS) via transcriptome-wide association identified dozens of novel candidate risk genes, highlighting shared and stage-specific mechanisms in schizophrenia (SCZ). Gene network analysis revealed that SCZ and autism spectrum disorder (ASD) affect distinct developmental gene co-expression modules. Yet, in each disorder, common and rare genetic variation converges within modules, which in ASD implicates superficial cortical neurons. More broadly, these data, available as a web browser and our analyses, demonstrate the genetic mechanisms by which developmental events have a widespread influence on adult anatomical and behavioral phenotypes.

Putamen gray matter volumes in neuropsychiatric and neurodegenerative disorders

Putamen is enriched with dopamine and associated with dopamine-related phenotypes including many neuropsychiatric and neurodegenerative disorders that manifest with motor impairment, impulsive behavior, and cognitive deficits. The gray matter volume of the putamen is age-dependent and genetically controlled. In most neuropsychiatric and neurodegenerative disorders, including Parkinson's spectrum disorders, Huntington's disease, dementia with Lewy bodies, Alzheimer's disease, multiple sclerosis, attention deficit hyperactivity disorder, developmental dyslexia, and major depression, the putamen volume is significantly reduced. On the other hand, in individuals with bipolar disorder, schizophrenia spectrum disorders, especially neuroleptics-medicated patients with schizophrenia, autism spectrum disorders, obsessive-compulsive spectrum disorders, and cocaine/amphetamine dependence, the putamen volume is significantly enlarged. Therefore, the putamen volume may serve as a structural neural marker for many neuropsychiatric and neurodegenerative disorders and a predictor of treatment outcomes in individuals afflicted with these conditions. We provided an overview of the genetic bases of putamen volume and explored potential mechanisms whereby altered putamen volume manifests in these neuropsychiatric and neurodegenerative conditions, with a specific focus on dopaminergic processes.

Astroglial correlates of neuropsychiatric disease: From astrocytopathy to astrogliosis

Complex roles for astrocytes in health and disease continue to emerge, highlighting this class of cells as integral to function and dysfunction of the nervous system. In particular, escalating evidence strongly implicates a range of changes in astrocyte structure and function associated with neuropsychiatric diseases including major depressive disorder, schizophrenia, and addiction. These changes can range from astrocytopathy, degeneration, and loss of function, to astrogliosis and hypertrophy, and can be either adaptive or maladaptive. Evidence from the literature indicates a myriad of changes observed in astrocytes from both human postmortem studies as well as preclinical animal models, including changes in expression of glial fibrillary protein, as well as changes in astrocyte morphology and astrocyte-mediated regulation of synaptic function. In this review, we seek to provide a comprehensive assessment of these findings and consequently evidence for common themes regarding adaptations in astrocytes associated with neuropsychiatric disease. While results are mixed across conditions and models, general findings indicate decreased astrocyte cellular features and gene expression in depression, chronic stress and anxiety, but increased inflammation in schizophrenia. Changes also vary widely in response to different drugs of abuse, with evidence reflective of features of astrocytopathy to astrogliosis, varying across drug classes, route of administration and length of withdrawal.

Association between one-carbon metabolism indices and DNA methylation status in maternal and cord blood

One-carbon metabolism is essential for multiple cellular processes and can be assessed by the concentration of folate metabolites in the blood. One-carbon metabolites serve as methyl donors that are required for epigenetic regulation. Deficiencies in these metabolites are associated with a variety of poor health outcomes, including adverse pregnancy complications. DNA methylation is known to vary with one-carbon metabolite concentration, and therefore may modulate the risk of adverse pregnancy outcomes. This study addresses changes in one-carbon indices over pregnancy and the relationship between maternal and child DNA methylation and metabolite concentrations by leveraging data from 24 mother-infant dyads. Five of the 13 metabolites measured from maternal blood and methylation levels of 993 CpG sites changed over the course of pregnancy. In dyads, maternal and fetal one-carbon concentrations were highly correlated, both early in pregnancy and at delivery. The 993 CpG sites whose methylation levels changed over pregnancy in maternal blood were also investigated for associations with metabolite concentrations in infant blood at delivery, where five CpG sites were associated with the concentration of at least one metabolite. Identification of CpG sites that change over pregnancy may result in better characterization of genes and pathways involved in maintaining a healthy, term pregnancy.

Enhancing Psychosis-Spectrum Nosology Through an International Data Sharing Initiative

The latent structure of schizotypy and psychosis-spectrum symptoms remains poorly understood. Furthermore, molecular genetic substrates are poorly defined, largely due to the substantial resources required to collect rich phenotypic data across diverse populations. Sample sizes of phenotypic studies are often insufficient for advanced structural equation modeling approaches. In the last 50 years, efforts in both psychiatry and psychological science have moved toward (1) a dimensional model of psychopathology (eg, the current Hierarchical Taxonomy of Psychopathology [HiTOP] initiative), (2) an integration of methods and measures across traits and units of analysis (eg, the RDoC initiative), and (3) powerful, impactful study designs maximizing sample size to detect subtle genomic variation relating to complex traits (the Psychiatric Genomics Consortium [PGC]). These movements are important to the future study of the psychosis spectrum, and to resolving heterogeneity with respect to instrument and population. The International Consortium of Schizotypy Research is composed of over 40 laboratories in 12 countries, and to date, members have compiled a body of schizotypy- and psychosis-related phenotype data from more than 30000 individuals. It has become apparent that compiling data into a protected, relational database and crowdsourcing analytic and data science expertise will result in significant enhancement of current research on the structure and biological substrates of the psychosis spectrum. The authors present a data-sharing infrastructure similar to that of the PGC, and a resource-sharing infrastructure similar to that of HiTOP. This report details the rationale and benefits of the phenotypic data collective and presents an open invitation for participation.

Epigenetics and early domestication: differences in hypothalamic DNA methylation between red junglefowl divergently selected for high or low fear of humans

Background

Domestication of animals leads to large phenotypic alterations within a short evolutionary time-period. Such alterations are caused by genomic variations, yet the prevalence of modified traits is higher than expected if they were caused only by classical genetics and mutations. Epigenetic mechanisms may also be important in driving domesticated phenotypes such as behavior traits. Gene expression can be modulated epigenetically by mechanisms such as DNA methylation, resulting in modifications that are not only variable and susceptible to environmental stimuli, but also sometimes transgenerationally stable. To study such mechanisms in early domestication, we used as model two selected lines of red junglefowl (ancestors of modern chickens) that were bred for either high or low fear of humans over five generations, and investigated differences in hypothalamic DNA methylation between the two populations.

Results

Twenty-two 1-kb windows were differentially methylated between the two selected lines at p < 0.05 after false discovery rate correction. The annotated functions of the genes within these windows indicated epigenetic regulation of metabolic and signaling pathways, which agrees with the changes in gene expression that were previously reported for the same tissue and animals.

Conclusions

Our results show that selection for an important domestication-related behavioral trait such as tameness can cause divergent epigenetic patterns within only five generations, and that these changes could have an important role in chicken domestication.

Electronic supplementary material

The online version of this article (10.1186/s12711-018-0384-z) contains supplementary material, which is available to authorized users.

RP5063, an atypical antipsychotic drug with a unique pharmacologic profile, improves declarative memory and psychosis in mouse models of schizophrenia

Various types of atypical antipsychotic drugs (AAPDs) modestly improve the cognitive impairment associated with schizophrenia (CIAS). RP5063 is an AAPD with a diverse and unique pharmacology, including partial agonism at dopamine (DA) D₂, D₃, D₄, serotonin (5-HT)_1A, and 5-HT_2A receptors (Rs), full agonism at α₄β₂ nicotinic acetylcholine (ACh)R (nAChR), and antagonism at 5-HT_2B, 5-HT₆, and 5-HT₇Rs. Most atypical APDs are 5-HT_2A inverse agonists. The efficacy of RP5063 in mouse models of psychosis and episodic memory were studied. RP5063 blocked acute phencyclidine (PCP)-as well as amphetamine-induced hyperactivity, indicating antipsychotic activity. Acute administration of RP5063 significantly reversed subchronic (sc)PCP-induced impairment in novel object recognition (NOR), a measure of episodic memory, but not reversal learning, a measure of executive function. Co-administration of a sub-effective dose (SED) of RP5063 with SEDs of a 5-HT₇R antagonist, a 5-HT_1BR antagonist, a 5-HT_2AR inverse agonist, or an α₄β₂ nAChR agonist, restored the ability of RP5063 to ameliorate the NOR deficit in scPCP mice. Pre-treatment with a 5-HT_1AR, a D₄R, antagonist, but not an α₄β₂ nAChR antagonist, blocked the ameliorating effect of RP5063. Further, co-administration of scRP5063 prior to each dose of PCP prevented the effect of PCP to produce a deficit in NOR for one week. RP5063, given to scPCP-treated mice for one week restored NOR for one week only. Acute administration of RP5063 significantly increased cortical DA efflux, which may be critical to some of its cognitive enhancing properties. These results indicate that RP5063, by itself, or as an adjunctive treatment has a multifaceted basis for improving some cognitive deficits associated with schizophrenia.

Transgenerational transmission and modification of pathological traits induced by prenatal immune activation

Prenatal exposure to infectious or inflammatory insults is increasingly recognized to contribute to the etiology of psychiatric disorders with neurodevelopmental components, including schizophrenia, autism and bipolar disorder. It remains unknown, however, if such immune-mediated brain anomalies can be transmitted to subsequent generations. Using an established mouse model of prenatal immune activation by the viral mimetic poly(I:C), we show that reduced sociability and increased cued fear expression are similarly present in the first- and second-generation offspring of immune-challenged ancestors. We further demonstrate that sensorimotor gating impairments are confined to the direct descendants of infected mothers, whereas increased behavioral despair emerges as a novel phenotype in the second generation. These transgenerational effects are mediated via the paternal lineage and are stable until the third generation, demonstrating transgenerational non-genetic inheritance of pathological traits following in-utero immune activation. Next-generation sequencing further demonstrated unique and overlapping genome-wide transcriptional changes in first- and second-generation offspring of immune-challenged ancestors. These transcriptional effects mirror the transgenerational effects on behavior, showing that prenatal immune activation leads to a transgenerational transmission (presence of similar phenotypes across generations) and modification (presence of distinct phenotypes across generations) of pathological traits. Together, our study demonstrates for, we believe, the first time that prenatal immune activation can negatively affect brain and behavioral functions in multiple generations. These findings thus highlight a novel pathological aspect of this early-life adversity in shaping disease risk across generations.

Gene expression profiling of the dorsolateral and medial orbitofrontal cortex in schizophrenia

Schizophrenia is a complex polygenic disorder of unknown etiology. Over 3,000 candidate genes associated with schizophrenia have been reported, most of which being mentioned only once. Alterations in cognitive processing - working memory, metacognition and mentalization - represent a core feature of schizophrenia, which indicates the involvement of the prefrontal cortex in the pathophysiology of this disorder. Hence we compared the gene expression in postmortem tissue from the left and right dorsolateral prefrontal cortex (DLPFC, Brodmann's area 46), and the medial part of the orbitofrontal cortex (MOFC, Brodmann's area 11/12), in six patients with schizophrenia and six control brains. Although in the past decade several studies performed transcriptome profiling in schizophrenia, this is the first study to investigate both hemispheres, providing new knowledge about possible brain asymmetry at the level of gene expression and its relation to schizophrenia. We found that in the left hemisphere, twelve genes from the DLPFC and eight genes from the MOFC were differentially expressed in patients with schizophrenia compared to controls. In the right hemisphere there was only one gene differentially expressed in the MOFC. We reproduce the involvement of previously reported genes TARDBP and HNRNPC in the pathogenesis of schizophrenia, and report seven novel genes: SART1, KAT7, C1D, NPM1, EVI2A, XGY2, and TTTY15. As the differentially expressed genes only partially overlap with previous studies that analyzed other brain regions, our findings indicate the importance of considering prefrontal cortical regions, especially those in the left hemisphere, for obtaining disease-relevant insights.

Bridging the Gap between Genes and Language Deficits in Schizophrenia: An Oscillopathic Approach

Schizophrenia is characterized by marked language deficits, but it is not clear how these deficits arise from the alteration of genes related to the disease. The goal of this paper is to aid the bridging of the gap between genes and schizophrenia and, ultimately, give support to the view that the abnormal presentation of language in this condition is heavily rooted in the evolutionary processes that brought about modern language. To that end we will focus on how the schizophrenic brain processes language and, particularly, on its distinctive oscillatory profile during language processing. Additionally, we will show that candidate genes for schizophrenia are overrepresented among the set of genes that are believed to be important for the evolution of the human faculty of language. These genes crucially include (and are related to) genes involved in brain rhythmicity. We will claim that this translational effort and the links we uncover may help develop an understanding of language evolution, along with the etiology of schizophrenia, its clinical/linguistic profile, and its high prevalence among modern populations.

Language deficits in schizophrenia and autism as related oscillatory connectomopathies: An evolutionary account

Schizophrenia (SZ) and autism spectrum disorders (ASD) are characterised by marked language deficits, but it is not clear how these arise from gene mutations associated with the disorders. Our goal is to narrow the gap between SZ and ASD and, ultimately, give support to the view that they represent abnormal (but related) ontogenetic itineraries for the human faculty of language. We will focus on the distinctive oscillatory profiles of the SZ and ASD brains, in turn using these insights to refine our understanding of how the brain implements linguistic computations by exploring a novel model of linguistic feature-set composition. We will argue that brain rhythms constitute the best route to interpreting language deficits in both conditions and mapping them to neural dysfunction and risk alleles of the genes. Importantly, candidate genes for SZ and ASD are overrepresented among the gene sets believed to be important for language evolution. This translational effort may help develop an understanding of the aetiology of SZ and ASD and their high prevalence among modern populations.

An Association Study Between Genetic Polymorphisms in Functional Regions of Five Genes and the Risk of Schizophrenia

Schizophrenia is a severe mental disorder that is likely to be strongly determined by genetic factors. To identify markers of disks, large homolog 2 (DLG2), FAT atypical cadherin 3 (FAT3), kinectin1 (KTN1), deleted in colorectal carcinoma (DCC), and glycogen synthase kinase-3β (GSK3β) that contribute to the genetic susceptibility to schizophrenia, we systematically screened for polymorphisms in the functional regions of these genes. A total of 22 functional single-nucleotide polymorphisms (SNPs) in 940 Chinese subjects were genotyped using SNaPshot. The results first suggested that the allelic and genotypic frequencies of the DCC polymorphism rs2229080 were nominally associated with schizophrenia. The patients were significantly less likely to be CC homozygous (P = 0.005, odds ratio [OR] = 0.635, 95 % confidence interval [95 % CI] = 0.462-0.873), and the schizophrenia subjects exhibited lower frequency of the C allele (P = 0.024, OR = 0.811, 95 % CI = 0.676-0.972). Regarding GSK3β, there was a significant difference in genotype distribution of rs3755557 between schizophrenia and healthy control subjects (P = 0.009). The patients exhibited a significantly lower frequency of the T allele of rs3755557 (P = 0.002, OR = 0.654, 95 % CI = 0.498-0.860). Our results point to the polymorphisms of DCC and GSK3β as contributors to the genetic basis of individual differences in the susceptibility to schizophrenia.

Gene expression profiling of the dorsolateral and medial orbitofrontal cortex in schizophrenia

Schizophrenia is a complex polygenic disorder of unknown etiology. Over 3,000 candidate genes associated with schizophrenia have been reported, most of which being mentioned only once. Alterations in cognitive processing - working memory, metacognition and mentalization - represent a core feature of schizophrenia, which indicates the involvement of the prefrontal cortex in the pathophysiology of this disorder. Hence we compared the gene expression in postmortem tissue from the left and right dorsolateral prefrontal cortex (DLPFC, Brodmann's area 46), and the medial part of the orbitofrontal cortex (MOFC, Brodmann's area 11/12), in six patients with schizophrenia and six control brains. Although in the past decade several studies performed transcriptome profiling in schizophrenia, this is the first study to investigate both hemispheres, providing new knowledge about possible brain asymmetry at the level of gene expression and its relation to schizophrenia. We found that in the left hemisphere, twelve genes from the DLPFC and eight genes from the MOFC were differentially expressed in patients with schizophrenia compared to controls. In the right hemisphere there was only one gene differentially expressed in the MOFC. We reproduce the involvement of previously reported genes TARDBP and HNRNPC in the pathogenesis of schizophrenia, and report seven novel genes: SART1, KAT7, C1D, NPM1, EVI2A, XGY2, and TTTY15. As the differentially expressed genes only partially overlap with previous studies that analyzed other brain regions, our findings indicate the importance of considering prefrontal cortical regions, especially those in the left hemisphere, for obtaining disease-relevant insights.