Failed drug discovery in psychiatry: time for human genome-guided solutions

The neoliberal leaning of the neuroscience discourse when it deals with mental health and learning disorders

Neuroscience attracted increasing attention in mass media during the last decades. Indeed, neuroscience advances raise high expectations in society concerning major societal issues such as mental health and learning difficulties. Unfortunately, according to leading experts, neuroscience advances have not yet benefited patients, students and socially deprived families. Yet, neuroscience findings are widely overstated and misrepresented in the media. Academic studies, briefly described here, showed that most data misrepresentations were already present in the neuroscience literature before spreading in mass media. This triumphalist neuroscience discourse reinforces a neuro-essentialist conception of mental disorders and of learning difficulties. By emphasizing brain plasticity, this discourse fuels the neoliberal ethics that overvalue autonomy, rationality, flexibility and individual responsibility. According to this unrealistic rhetoric, neuroscience-based techniques will soon bring inexpensive private solutions to enduring social problems. When considering the social consequences of this rhetoric, neuroscientists should refrain from overstating the interpretation of their observations in their scientific publications and in their exchanges with journalists.

Silver Nanoparticles Cause Neural and Vascular Disruption by Affecting Key Neuroactive Ligand-Receptor Interaction and VEGF Signaling Pathways

Introduction

Silver nanoparticles (AgNP) are widely used as coating materials. However, the potential risks of AgNP to human health, especially for neural and vascular systems, are still poorly understood.

Methods

The vascular and neurotoxicity of various concentrations of AgNP in zebrafish were examined using fluorescence microscopy. In addition, Illumina high-throughput global transcriptome analysis was performed to explore the transcriptome profiles of zebrafish embryos after exposure to AgNP. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to elucidate the top 3000 differentially expressed genes (DEGs) between AgNP-exposed and control groups.

Results

We systematically investigated the neural and vascular developmental toxicities of AgNP exposure in zebrafish. The results demonstrated that AgNP exposure could cause neurodevelopmental anomalies, including a small-eye phenotype, neuronal morphology defects, and inhibition of athletic abilities. In addition, we found that AgNP exposure induces angiogenesis malformation in zebrafish embryos. Further RNA-seq revealed that DEGs were mainly enriched in the neuroactive ligand-receptor interaction and vascular endothelial growth factor (Vegf) signaling pathways in AgNP-treated zebrafish embryos. Specifically, the mRNA levels of the neuroactive ligand-receptor interaction pathway and Vegf signaling pathway-related genes, including si:ch73-55i23.1, nfatc2a, prkcg, si:ch211-132p1.2, lepa, mchr1b, pla2g4aa, rac1b, p2ry6, adrb2, chrnb1, and chrm1b, were significantly regulated in AgNP-treated zebrafish embryos.

Conclusion

Our findings indicate that AgNP exposure transcriptionally induces developmental toxicity in neural and vascular development by disturbing neuroactive ligand-receptor interactions and the Vegf signaling pathway in zebrafish embryos.

Exploring the underlying molecular mechanism of tri(1,3-dichloropropyl) phosphate-induced neurodevelopmental toxicity via thyroid hormone disruption in zebrafish by multi-omics analysis

Tri(1,3-dichloropropyl) phosphate (TDCPP) is widespread in the environment as a typical thyroid hormone-disrupting chemical. Here, we aimed to explore the toxicological mechanisms of the thyroid hormone-disrupting effects induced by TDCPP in zebrafish embryos/larvae using multi-omics analysis. The results showed that TDCPP (400 and 600 µg/L) induced phenotypic alteration and thyroid hormone imbalance in zebrafish larvae. It resulted in behavioral abnormalities during zebrafish embryonic development, suggesting that this chemical might exhibit neurodevelopmental toxicity. Transcriptomic and proteomic analysis provided consistent evidence at the gene and protein levels that neurodevelopmental disorders were significantly enhanced by TDCPP exposure (p < 0.05). Additionally, multi-omics data indicated that membrane thyroid hormone receptor (mTR)-mediated non-genomic pathways, including cell communication (ECM-receptor interactions, focal adhesion, etc.) and signal transduction pathways (MAPK signaling pathway, calcium signaling pathway, neuroactive ligand-receptor interaction pathway, etc.), were significantly disturbed (p < 0.05) and might contribute to the neurodevelopmental toxicity induced by TDCPP. Therefore, behavioral abnormalities and neurodevelopmental disorders might be important phenotypic characteristics of TDCPP-induced thyroid hormone disruption, and mTR-mediated non-genomic networks might participate in the disruptive effects of this chemical. This study provides new insights into the toxicological mechanisms of TDCPP-induced thyroid hormone disruption and proposes a theoretical basis for risk management of this chemical.

Improvement of Spatial Memory and Cognitive Function in Mice via the Intervention of Milk Fat Globule Membrane

With the improvement of living standards, dietary interventions have become an appropriate approach to enhance memory and cognitive performance. The present study investigated the potential mechanisms of spatial memory and cognitive function improvement with the milk fat globule membrane (MFGM) intervention in mice. The Morris water maze experiment revealed that the trajectories of mice in group M were more disordered. Also, the immunohistochemical results demonstrated a significantly higher number of neurons in group M compared with group C, especially in the hippocampal dentate gyrus (DG) area. It is suggested that MFGM enhanced mice's spatial memory and cognition from macroscopic behavior and microscopic cytology, respectively. Meanwhile, 47 differentially expressed proteins (DEPs) were identified, including 20 upregulated and 27 downregulated proteins. Upregulated (Sorbs 2, Rab 39, and Cacna 1e) and downregulated (Hp and Lrg 1) DEPs may improve spatial memory and cognition in mice by promoting synapse formation and increasing neurotransmitter receptors. KEGG enrichment analysis of the DEPs identified seven signaling pathways that were significantly enriched (p < 0.05). One of these pathways was neuroactive ligand-receptor interactions, which are strongly associated with improved spatial memory and cognitive performance. These findings give some new insights and references to the potential mechanisms of spatial memory and cognitive enhancement by MFGM.

Identification and validation of oxidative stress and immune-related hub genes in Alzheimer's disease through bioinformatics analysis

Alzheimer's disease (AD) is the leading cause of dementia in aged population. Oxidative stress and neuroinflammation play important roles in the pathogenesis of AD. Investigation of hub genes for the development of potential therapeutic targets and candidate biomarkers is warranted. The differentially expressed genes (DEGs) in AD were screened in GSE48350 dataset. The differentially expressed oxidative stress genes (DEOSGs) were analyzed by intersection of DEGs and oxidative stress-related genes. The immune-related DEOSGs and hub genes were identified by weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) analysis, respectively. Enrichment analysis was performed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. The diagnostic value of hub genes was assessed by receiver operating characteristic analysis and validated in GSE1297. The mRNA expression of diagnostic genes was determined by qRT-PCR analysis. Finally, we constructed the drug, transcription factors (TFs), and microRNA network of the diagnostic genes. A total of 1160 DEGs (259 up-regulated and 901 down-regulated) were screened in GSE48350. Among them 111 DEOSGs were identified in AD. Thereafter, we identified significant difference of infiltrated immune cells (effector memory CD8 T cell, activated B cell, memory B cell, natural killer cell, CD56 bright natural killer cell, natural killer T cell, plasmacytoid dendritic cell, and neutrophil) between AD and control samples. 27 gene modules were obtained through WGCNA and turquoise module was the most relevant module. We obtained 66 immune-related DEOSGs by intersecting turquoise module with the DEOSGs and identified 15 hub genes through PPI analysis. Among them, 9 hub genes (CCK, CNR1, GAD1, GAP43, NEFL, NPY, PENK, SST, and TAC1) were identified with good diagnostic values and verified in GSE1297. qRT-PCR analysis revealed the downregulation of SST, NPY, GAP43, CCK, and PENK and upregulation of NEFL in AD. Finally, we identified 76 therapeutic agents, 152 miRNAs targets, and 91 TFs regulatory networks. Our study identified 9 key genes associated with oxidative stress and immune reaction in AD pathogenesis. The findings may help to provide promising candidate biomarkers and therapeutic targets for AD.

Encore: Behavioural animal models of stress, depression and mood disorders

Animal studies over the past two decades have led to extensive advances in our understanding of pathogenesis of depressive and mood disorders. Among these, rodent behavioural models proved to be of highest informative value. Here, we present a comprehensive overview of the most popular behavioural models with respect to physiological, circuit, and molecular biological correlates. Behavioural stress paradigms and behavioural tests are assessed in terms of outcomes, strengths, weaknesses, and translational value, especially in the domain of pharmacological studies.

Do DSM classifications help or hinder drug development?

Development and regulatory approval of psychotropic drugs targets individuals with syndromes described in the current Diagnostic and Statistical Manual of Mental Disorders (DSM). This helps drug developers and regulators to communicate with prescribers, and prescribers to match a specific psychotropic with the individual patient(s) most likely to benefit from it. However, this practice has been criticized on the grounds that DSM syndromes are too heterogenous biologically, and the effects of psychotropics are too nonspecific to allow for an effective match. This review considers the advantages and disadvantages of the current practice and the possible alternatives. It concludes that efforts should be made to explore psychotropic development transdiagnostically, free of the DSM boundaries. However, currently there exists no alternative diagnostic system that is clearly superior to the DSM in terms of communications between the stakeholders in drug development.


Systematic Review and Methodological Considerations for the Use of Single Prolonged Stress and Fear Extinction Retention in Rodents

Posttraumatic stress disorder (PTSD) is a mental health condition triggered by experiencing or witnessing a terrifying event that can lead to lifelong burden that increases mortality and adverse health outcomes. Yet, no new treatments have reached the market in two decades. Thus, screening potential interventions for PTSD is of high priority. Animal models often serve as a critical translational tool to bring new therapeutics from bench to bedside. However, the lack of concordance of some human clinical trial outcomes with preclinical animal efficacy findings has led to a questioning of the methods of how animal studies are conducted and translational validity established. Thus, we conducted a systematic review to determine methodological variability in studies that applied a prominent animal model of trauma-like stress, single prolonged stress (SPS). The SPS model has been utilized to evaluate a myriad of PTSD-relevant outcomes including extinction retention. Rodents exposed to SPS express an extinction retention deficit, a phenotype identified in humans with PTSD, in which fear memory is aberrantly retained after fear memory extinction. The current systematic review examines methodological variation across all phases of the SPS paradigm, as well as strategies for behavioral coding, data processing, statistical approach, and the depiction of data. Solutions for key challenges and sources of variation within these domains are discussed. In response to methodological variation in SPS studies, an expert panel was convened to generate methodological considerations to guide researchers in the application of SPS and the evaluation of extinction retention as a test for a PTSD-like phenotype. Many of these guidelines are applicable to all rodent paradigms developed to model trauma effects or learned fear processes relevant to PTSD, and not limited to SPS. Efforts toward optimizing preclinical model application are essential for enhancing the reproducibility and translational validity of preclinical findings, and should be conducted for all preclinical psychiatric research models.

Mismatch negativity as EEG biomarker supporting CNS drug development: a transnosographic and translational study

The lack of translation from basic research into new medicines is a major challenge in CNS drug development. The need to use novel approaches relying on (i) patient clustering based on neurobiology irrespective to symptomatology and (ii) quantitative biomarkers focusing on evolutionarily preserved neurobiological systems allowing back-translation from clinical to nonclinical research has been highlighted. Here we sought to evaluate the mismatch negativity (MMN) response in schizophrenic (SZ) patients, Alzheimer's disease (AD) patients, and age-matched healthy controls. To evaluate back-translation of the MMN response, we developed EEG-based procedures allowing the measurement of MMN-like responses in a rat model of schizophrenia and a mouse model of AD. Our results indicate a significant MMN attenuation in SZ but not in AD patients. Consistently with the clinical findings, we observed a significant attenuation of deviance detection (~104.7%) in rats subchronically exposed to phencyclidine, while no change was observed in APP/PS1 transgenic mice when compared to wild type. This study provides new insight into the cross-disease evaluation of the MMN response. Our findings suggest further investigations to support the identification of neurobehavioral subtypes that may help patients clustering for precision medicine intervention. Furthermore, we provide evidence that MMN could be used as a quantitative/objective efficacy biomarker during both preclinical and clinical stages of SZ drug development.

Avolition as the core negative symptom in schizophrenia: relevance to pharmacological treatment development

Negative symptoms have long been considered a core component of schizophrenia. Modern conceptualizations of the structure of negative symptoms posit that there are at least two broad dimensions (motivation and pleasure and diminished expression) or perhaps five separable domains (avolition, anhedonia, asociality, blunted affect, alogia). The current review synthesizes a body of emerging research indicating that avolition may have a special place among these dimensions, as it is generally associated with poorer outcomes and may have distinct neurobiological mechanisms. Network analytic findings also indicate that avolition is highly central and interconnected with the other negative symptom domains in schizophrenia, and successfully remediating avolition results in global improvement in the entire constellation of negative symptoms. Avolition may therefore reflect the most critical treatment target within the negative symptom construct. Implications for targeted treatment development and clinical trial design are discussed.

A way forward for anxiolytic drug development: Testing candidate anxiolytics with anxiety-potentiated startle in healthy humans

This review introduces a research strategy that may radically transform the pursuit of new anxiolytics, via the use of human models of anxiety in healthy individuals. Despite enormous investments in developing novel pharmacological treatments for anxiety disorders, pharmacotherapy for these conditions remains suboptimal. Most candidate anxiolytics from animal studies fail in clinical trials. We propose an additional screening step to help select candidate anxiolytics before launching clinical trials. This intermediate step moves the evidence for the potential anxiolytic property of candidate drugs from animals to humans, using experimental models of anxiety in healthy individuals. Anxiety-potentiated startle is a robust translational model of anxiety. The review of its face, construct, and predictive validity as well as its psychometric properties in humans establishes it as a promising tool for anxiolytic drug development. In conclusion, human models of anxiety may stir a faster, more efficient path for the development of clinically effective anxiolytics.

High-dimensionality Data Analysis of Pharmacological Systems Associated with Complex Diseases

It is widely accepted that molecular reductionist views of highly complex human physiologic activity, e.g., the aging process, as well as therapeutic drug efficacy are largely oversimplifications. Currently some of the most effective appreciation of biologic disease and drug response complexity is achieved using high-dimensionality (H-D) data streams from transcriptomic, proteomic, metabolomics, or epigenomic pipelines. Multiple H-D data sets are now common and freely accessible for complex diseases such as metabolic syndrome, cardiovascular disease, and neurodegenerative conditions such as Alzheimer's disease. Over the last decade our ability to interrogate these high-dimensionality data streams has been profoundly enhanced through the development and implementation of highly effective bioinformatic platforms. Employing these computational approaches to understand the complexity of age-related diseases provides a facile mechanism to then synergize this pathologic appreciation with a similar level of understanding of therapeutic-mediated signaling. For informative pathology and drug-based analytics that are able to generate meaningful therapeutic insight across diverse data streams, novel informatics processes such as latent semantic indexing and topological data analyses will likely be important. Elucidation of H-D molecular disease signatures from diverse data streams will likely generate and refine new therapeutic strategies that will be designed with a cognizance of a realistic appreciation of the complexity of human age-related disease and drug effects. We contend that informatic platforms should be synergistic with more advanced chemical/drug and phenotypic cellular/tissue-based analytical predictive models to assist in either de novo drug prioritization or effective repurposing for the intervention of aging-related diseases. SIGNIFICANCE STATEMENT: All diseases, as well as pharmacological mechanisms, are far more complex than previously thought a decade ago. With the advent of commonplace access to technologies that produce large volumes of high-dimensionality data (e.g., transcriptomics, proteomics, metabolomics), it is now imperative that effective tools to appreciate this highly nuanced data are developed. Being able to appreciate the subtleties of high-dimensionality data will allow molecular pharmacologists to develop the most effective multidimensional therapeutics with effectively engineered efficacy profiles.

The Contribution of Rat Studies to Current Knowledge of Major Depressive Disorder: Results From Citation Analysis

Major depressive disorder (MDD) is the most severe depression type and one of the leading causes of morbidity worldwide. Animal models are widely used to understand MDD etiology, pathogenesis, and treatment, but the efficacy of this research for patients has barely been systematically evaluated. Such evaluation is important given the resource consumption and ethical concerns incurred by animal use. We used the citation tracking facilities within Web of Science and Scopus to locate citations of original research papers on rats related to MDD published prior to 2013—to allow adequate time for citations—identified in PubMed and Scopus by relevant search terms. Resulting citations were thematically coded in eight categories, and descriptive statistics were calculated. 178 publications describing relevant rat studies were identified. They were cited 8,712 times. More than half (4,633) of their citations were by other animal studies. 794 (less than 10%) were by human medical papers. Citation analysis indicates that rat model research has contributed very little to the contemporary clinical understanding of MDD. This suggests a misuse of limited funding hence supporting a change in allocation of research and development funds targeting this disorder to maximise benefits for patients.

Low-Dose Exposure of Silica Nanoparticles Induces Neurotoxicity via Neuroactive Ligand-Receptor Interaction Signaling Pathway in Zebrafish Embryos

Objective

Silica nanoparticles (SiO₂ NPs) have been extensively employed in biomedical field. SiO₂ NPs are primarily designed to enter the circulatory system; however, little information is available on potential adverse effects of SiO₂ NPs on the nervous system.

Methods

The neurotoxicity of SiO₂ NPs at different concentrations (3, 6, 12 ng/nL) on zebrafish embryos was determined using immunofluorescence and microarray techniques, and subsequently confirmed by qRT-PCR.

Results

SiO₂ NPs disrupt the axonal integrity and decrease the length of axons in Tg (NBT: EGFP) transgenic lines. The number of apoptotic cells in the brain and central nervous system of zebrafish embryos was increased in the presence of 12 ng/nL of SiO₂ NPs, but the difference did not reach statistical significance. Screening for changes in the expression of genes involved in the neuroactive ligand–receptor interaction pathway was performed by microarray and confirmed by qRT-PCR. These analyses demonstrated that SiO₂ NPs markedly downregulated genes associated with neural function (grm6a, drd1b, chrnb3b, adrb2a, grin2ab, npffr2.1, npy8br, gabrd, chrma3, gabrg3, gria3a, grm1a, adra2b, and glra3).

Conclusion

The obtained results documented that SiO₂ NPs can induce developmental neurotoxicity by affecting the neuroactive ligand–receptor interaction signaling pathway. This new evidence may help to clarify the mechanism of SiO₂ NPs-mediated neurotoxicity.

Translating GWAS findings into therapies for depression and anxiety disorders: gene-set analyses reveal enrichment of psychiatric drug classes and implications for drug repositioning

BACKGROUND

Depression and anxiety disorders (AD) are the first and sixth leading causes of disability worldwide. Despite their high prevalence and significant disability resulted, there are limited advances in new drug development. Recently, genome-wide association studies (GWAS) have greatly advanced our understanding of the genetic basis underlying psychiatric disorders.

METHODS

Here we employed gene-set analyses of GWAS summary statistics for drug repositioning. We explored five related GWAS datasets, including two on major depressive disorder (MDD2018 and MDD-CONVERGE, with the latter focusing on severe melancholic depression), one on AD, and two on depressive symptoms and neuroticism in the population. We extracted gene-sets associated with each drug from DSigDB and examined their association with each GWAS phenotype. We also performed repositioning analyses on meta-analyzed GWAS data, integrating evidence from all related phenotypes.

RESULTS

Importantly, we showed that the repositioning hits are generally enriched for known psychiatric medications or those considered in clinical trials. Enrichment was seen for antidepressants and anxiolytics but also for antipsychotics. We also revealed new candidates or drug classes for repositioning, some of which were supported by experimental or clinical studies. For example, the top repositioning hit using meta-analyzed p values was fendiline, which was shown to produce antidepressant-like effects in mouse models by inhibition of acid sphingomyelinase.

CONCLUSION

Taken together, our findings suggest that human genomic data such as GWAS are useful in guiding drug discoveries for depression and AD.

Selection of Models: Evolution and the Choice of Species for Translational Research

Evolutionary thinking can inform the choice and assessment of model species in neuroscience, particularly when such models are intended to generate knowledge that will translate to humans. Avoiding errors that arise from oversimplified notions of phylogeny or genotype-phenotype mapping is one contribution; evolutionary biology also offers positive guidance. The challenge of finding adequate non-human models for translational research is particularly acute in neuroscience: neurobiological and behavioral phenotypes are complex and plastic, and many traits important in humans are absent, radically different, or difficult to assess in other species. Evolutionary perspectives help to articulate and address these challenges. Darwin's description of "descent with modification" points to two aspects of evolution that can help us assess the matching between a prospective model species and its intended target. One is trees that represent the structure of phylogenetic relationships; the other is phenotypic traits, i.e. the unique characteristics of each species' evolved biology and natural history. Mapping traits onto a phylogeny is the first step toward analyzing the source of similarities between a target and a potential model. Whether similar traits arise from shared ancestry or from adaptive convergence has important implications for what kinds of inferences can be justified, and for the likely translatability of findings. Evolution offers both a rich source of possible models, and guidance for choosing the best ones for a given purpose. Considering model choice from an evolutionary angle not only helps to answer the question "What species might be a good model for studying x?" but also suggests additional questions we should be asking to assess the utility of both potential and current models. Recognizing the diverse ways model organisms can function expands our search image as we seek species to study that can both extend general knowledge, and generate translatable insights relevant to human neurobiology and disease.

Scalable Measurements of Intrinsic Excitability in Human iPS Cell-Derived Excitatory Neurons Using All-Optical Electrophysiology

Induced pluripotent stem (iPS) cells offer the exciting opportunity for modeling neurological disorders in vitro in the context of a human genetic background. While significant progress has been made in advancing the use of iPS cell-based disease models, there remains an unmet need to characterize the electrophysiological profile of individual neurons with sufficient throughput to enable statistically robust assessment of disease phenotypes and pharmacological modulation. Here, we describe the Optopatch platform technology that utilizes optogenetics to both stimulate and record action potentials (APs) from human iPS cell-derived excitatory neurons with similar information content to manual patch clamp electrophysiology, but with ~  3 orders of magnitude greater throughput. Cortical excitatory neurons were produced using the NGN2 transcriptional programming approach and cultured in the presence of rodent glial cells. Characterization of the neuronal preparations using immunocytochemistry and qRT-PCR assays reveals an enrichment of neuronal and glutamatergic markers as well as select ion channels. We demonstrate the scale of our intrinsic cellular excitability assay using pharmacological assessment with select ion channel modulators quinidine and retigabine, by measuring changes in both spike timing and waveform properties. The Optopatch platform in human iPS cell-derived cortical excitatory neurons has the potential for detailed phenotype and pharmacology evaluation, which can serve as the basis of cellular disease model exploration for drug discovery and phenotypic screening efforts.

Animal models of PTSD: a challenge to be met

Recent years have seen increased interest in psychopathologies related to trauma exposure. Specifically, there has been a growing awareness to posttraumatic stress disorder (PTSD) in part due to terrorism, climate change-associated natural disasters, the global refugee crisis, and increased violence in overpopulated urban areas. However, notwithstanding the increased awareness to the disorder, the increasing number of patients, and the devastating impact on the lives of patients and their families, the efficacy of available treatments remains limited and highly unsatisfactory. A major scientific effort is therefore devoted to unravel the neural mechanisms underlying PTSD with the aim of paving the way to developing novel or improved treatment approaches and drugs to treat PTSD. One of the major scientific tools used to gain insight into understanding physiological and neuronal mechanisms underlying diseases and for treatment development is the use of animal models of human diseases. While much progress has been made using these models in understanding mechanisms of conditioned fear and fear memory, the gained knowledge has not yet led to better treatment options for PTSD patients. This poor translational outcome has already led some scientists and pharmaceutical companies, who do not in general hold opinions against animal models, to propose that those models should be abandoned. Here, we critically examine aspects of animal models of PTSD that may have contributed to the relative lack of translatability, including the focus on the exposure to trauma, overlooking individual and sex differences, and the contribution of risk factors. Based on findings from recent years, we propose research-based modifications that we believe are required in order to overcome some of the shortcomings of previous practice. These modifications include the usage of animal models of PTSD which incorporate risk factors and of the behavioral profiling analysis of individuals in a sample. These modifications are aimed to address factors such as individual predisposition and resilience, thus taking into consideration the fact that only a fraction of individuals exposed to trauma develop PTSD. We suggest that with an appropriate shift of practice, animal models are not only a valuable tool to enhance our understanding of fear and memory processes, but could serve as effective platforms for understanding PTSD, for PTSD drug development and drug testing.

Integrated genetic, epigenetic, and gene set enrichment analyses identify NOTCH as a potential mediator for PTSD risk after trauma: Results from two independent African cohorts

The risk of developing posttraumatic stress disorder (PTSD) increases with the number of traumatic event types experienced (trauma load) in interaction with other psychobiological risk factors. The NOTCH (neurogenic locus notch homolog proteins) signaling pathway, consisting of four different trans‐membrane receptor proteins (NOTCH1–4), constitutes an evolutionarily well‐conserved intercellular communication pathway (involved, e.g., in cell–cell interaction, inflammatory signaling, and learning processes). Its association with fear memory consolidation makes it an interesting candidate for PTSD research. We tested for significant associations of common genetic variants of NOTCH1–4 (investigated by microarray) and genomic methylation of saliva‐derived DNA with lifetime PTSD risk in independent cohorts from Northern Uganda (N₁ = 924) and Rwanda (N₂ = 371), and investigated whether NOTCH‐related gene sets were enriched for associations with lifetime PTSD risk. We found associations of lifetime PTSD risk with single nucleotide polymorphism (SNP) rs2074621 (NOTCH3) (p_uncorrected = 0.04) in both cohorts, and with methylation of CpG site cg17519949 (NOTCH3) (p_uncorrected = 0.05) in Rwandans. Yet, none of the (epi‐)genetic associations survived multiple testing correction. Gene set enrichment analyses revealed enrichment for associations of two NOTCH pathways with lifetime PTSD risk in Ugandans: NOTCH binding (p_corrected = 0.003) and NOTCH receptor processing (p_corrected = 0.01). The environmental factor trauma load was significant in all analyses (all p < 0.001). Our integrated methodological approach suggests NOTCH as a possible mediator of PTSD risk after trauma. The results require replication, and the precise underlying pathophysiological mechanisms should be illuminated in future studies.

Integrating genetic, epigenetic, and gene set enrichment analyses, while accounting for the environmental factor traumatic load, we identified stress‐ and memory‐associated neurogenic locus notch homolog protein (NOTCH) genes and related gene sets as potential risk mediators for the development of posttraumatic stress disorder (PTSD) after trauma. Thus, our results strengthen the presumed role of memory‐ and inflammation‐associated genes in PTSD development, and revealed a promising target for future treatment studies. Furthermore, we demonstrated the importance of traumatic load in PTSD etiology, and of an integrated approach in order to obtain a more comprehensive understanding of the functionality of PTSD‐associated markers.

Genetic estimators of DNA methylation provide insights into the molecular basis of polygenic traits

The large biological distance between genetic risk loci and their mechanistic consequences in the tissue of interest limits the ability to establish functionality of susceptibility variants for genetically complex traits. Such a biological gap may be reduced through the systematic study of molecular mediators of genomic action, such as epigenetic modification. Here, we report the identification of robust genetic estimators of whole-blood CpG methylation, which can serve as intermediate molecular traits amenable to association testing with other genetically complex traits. We describe the relationship between these estimators and gene expression, demonstrate their genome-wide applicability to association testing even in the absence of individual genotypic data, and show that these estimators powerfully identify methylation-related genomic loci associated with polygenic traits and common diseases, such as schizophrenia. The use of genetic estimators for blood DNA methylation, which are made publically available, can serve as a valuable tool for the identification of epigenetic underpinnings of complex traits.

Innovative approaches to bipolar disorder and its treatment

All psychiatric disorders have suffered from a dearth of truly novel pharmacological interventions. In bipolar disorder, lithium remains a mainstay of treatment, six decades since its effects were serendipitously discovered. The lack of progress reflects several factors, including ignorance of the disorder's pathophysiology and the complexities of the clinical phenotype. After reviewing the current status, we discuss some ways forward. First, we highlight the need for a richer characterization of the clinical profile, facilitated by novel devices and new forms of data capture and analysis; such data are already promoting a reevaluation of the phenotype, with an emphasis on mood instability rather than on discrete clinical episodes. Second, experimental medicine can provide early indications of target engagement and therapeutic response, reducing the time, cost, and risk involved in evaluating potential mood stabilizers. Third, genomic data can inform target identification and validation, such as the increasing evidence for involvement of calcium channel genes in bipolar disorder. Finally, new methods and models relevant to bipolar disorder, including stem cells and genetically modified mice, are being used to study key pathways and drug effects. A combination of these approaches has real potential to break the impasse and deliver genuinely new treatments.

Translating genome-wide association findings into new therapeutics for psychiatry

Genome-wide association studies (GWAS) in psychiatry, once they reach sufficient sample size and power, have been enormously successful. The Psychiatric Genomics Consortium (PGC) aims for mega-analyses with sample sizes that will grow to >1 million individuals in the next 5 years. This should lead to hundreds of new findings for common genetic variants across nine psychiatric disorders studied by the PGC. The new targets discovered by GWAS have the potential to restart largely stalled psychiatric drug development pipelines, and the translation of GWAS findings into the clinic is a key aim of the recently funded phase 3 of the PGC. This is not without considerable technical challenges. These approaches complement the other main aim of GWAS studies, risk prediction approaches for improving detection, differential diagnosis, and clinical trial design. This paper outlines the motivations, technical and analytical issues, and the plans for translating PGC phase 3 findings into new therapeutics.

Animal models in psychiatric research: The RDoC system as a new framework for endophenotype-oriented translational neuroscience

The recently proposed Research Domain Criteria (RDoC) system defines psychopathologies as phenomena of multilevel neurobiological existence and assigns them to 5 behavioural domains characterizing a brain in action. We performed an analysis on this contemporary concept of psychopathologies in respect to a brain phylogeny and biological substrates of psychiatric diseases. We found that the RDoC system uses biological determinism to explain the pathogenesis of distinct psychiatric symptoms and emphasises exploration of endophenotypes but not of complex diseases. Therefore, as a possible framework for experimental studies it allows one to evade a major challenge of translational studies of strict disease-to-model correspondence. The system conforms with the concept of a normality and pathology continuum, therefore, supports basic studies. The units of analysis of the RDoC system appear as a novel matrix for model validation. The general regulation and arousal, positive valence, negative valence, and social interactions behavioural domains of the RDoC system show basic construct, network, and phenomenological homologies between human and experimental animals. The nature and complexity of the cognitive behavioural domain of the RDoC system deserve further clarification. These homologies in the 4 domains justifies the validity, reliably and translatability of animal models appearing as endophenotypes of the negative and positive affect, social interaction and general regulation and arousal systems’ dysfunction.

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The RDoC system encourages endophenotype-oriented experimental studies in human and animals.

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The system conforms with the normality-pathology continuum concept.

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The RDoC system appears to be a suitable framework for basic research.

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Four RDoC domains show construct and phenomenological homology in human and animals.

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Endophenotype-based models of affective psychopathologies appear most reliable.

[The Research Domain Criteria (Rdoc), reductionism and clinical psychiatry]

The focus of the advocates of the Research Domain Critria (RDoC) on faulty brain circuits has led some to suspect it of being a reductionist enterprise. And because RDoC will eventually impact clinical psychiatry, some have feared that it will transform clinical psychiatry in a mindless and applied neurobehavioral science. We argue that if RDoC is officially endorsing a kind of reductionism, the particular kind of reductionism it endorses is not suffering from the shortcomings of more classical forms of reductionism. Because of that, at least in principle, RDoC could enrich rather than impoverish clinical psychiatry. This paper raises few potential problems of the RDoC for clinical psychiatry caused by its implicit epistemological reductionism.

Expectations for the methodology and translation of animal research: a survey of the general public, medical students and animal researchers in North America

To determine what are considered acceptable standards for animal research (AR) methodology and translation rate to humans, a validated survey was sent to: a) a sample of the general public, via Sampling Survey International (SSI; Canada), Amazon Mechanical Turk (AMT; USA), a Canadian city festival (CF) and a Canadian children's hospital (CH); b) a sample of medical students (two first-year classes); and c) a sample of scientists (corresponding authors and academic paediatricians). There were 1379 responses from the general public sample (SSI, n = 557; AMT, n = 590; CF, n = 195; CH, n = 102), 205/330 (62%) medical student responses, and 23/323 (7%, too few to report) scientist responses. Asked about methodological quality, most of the general public and medical student respondents expect that: AR is of high quality (e.g. anaesthesia and analgesia are monitored, even overnight, and 'humane' euthanasia, optimal statistical design, comprehensive literature review, randomisation and blinding, are performed), and costs and difficulty are not acceptable justifications for lower quality (e.g. costs of expert consultation, or more laboratory staff). Asked about their expectations of translation to humans (of toxicity, carcinogenicity, teratogenicity and treatment findings), most expect translation more than 60% of the time. If translation occurred less than 20% of the time, a minority disagreed that this would "significantly reduce your support for AR". Medical students were more supportive of AR, even if translation occurred less than 20% of the time. Expectations for AR are much higher than empirical data show to have been achieved.

Functional Genomic Analyses Identify Pathways Dysregulated in Animal Model of Autism

BACKGROUND

Autism spectrum disorders (ASDs) are a heterogeneous group of neurodevelopmental disorders that display complicated behavioral symptoms.

METHODS

Using gene expressing profiling and the weighted gene co-expression network analysis (WGCNA), we studied genes coregulated by similar factors such as genetic variants or environmental effects in the hippocampus in an animal model of autism.

RESULTS

From microarray data, we identified 21,388 robustly expressed genes of which 721 genes were found to be differently expressed in the valproic acid-treated group compared to the control group. WGCNA identified multiple co-expression modules known to associate with cognitive function, inflammation, synaptic, and positive regulation of protein kinase activating. Many of these modules, however, have not been previously linked to autism spectrum disorders which included G-protein signaling, immunity, and neuroactive ligand-receptor interaction pathway. The downregulation of the highly connected (hub) genes Taar7h and Taar7b in neuroactive ligand-receptor interaction pathway was validated by qRT-PCR. Immunoblotting and immunohistochemistry further showed that TAAR7 expression was downregulated not only in valproic acid-treated animals, but also BTBR T+tf/J mice.

CONCLUSIONS

This study highlights the advantages of gene microarrays to uncover co-expression modules associated with autism and suggests that Taars and related gene regulation networks may play a significant role in autism.

Decoding Advances in Psychiatric Genetics: A Focus on Neural Circuits in Rodent Models

Appropriately powered genome-wide association studies combined with deep-sequencing technologies offer the prospect of real progress in revealing the complex biological underpinnings of schizophrenia and other psychiatric disorders. Meanwhile, recent developments in genome engineering, including CRISPR, constitute better tools to move forward with investigating these genetic leads. This review aims to assess how these advances can inform the development of animal models for psychiatric disease, with a focus on schizophrenia and in vivo electrophysiological circuit-level measures with high potential as disease biomarkers.

Reinforcement learning in depression: A review of computational research

Despite being considered primarily a mood disorder, major depressive disorder (MDD) is characterized by cognitive and decision making deficits. Recent research has employed computational models of reinforcement learning (RL) to address these deficits. The computational approach has the advantage in making explicit predictions about learning and behavior, specifying the process parameters of RL, differentiating between model-free and model-based RL, and the computational model-based functional magnetic resonance imaging and electroencephalography. With these merits there has been an emerging field of computational psychiatry and here we review specific studies that focused on MDD. Considerable evidence suggests that MDD is associated with impaired brain signals of reward prediction error and expected value ('wanting'), decreased reward sensitivity ('liking') and/or learning (be it model-free or model-based), etc., although the causality remains unclear. These parameters may serve as valuable intermediate phenotypes of MDD, linking general clinical symptoms to underlying molecular dysfunctions. We believe future computational research at clinical, systems, and cellular/molecular/genetic levels will propel us toward a better understanding of the disease.