Showing papers in "Molecular Psychiatry in 2019"

Genetics of attention deficit hyperactivity disorder

Abstract: Decades of research show that genes play an vital role in the etiology of attention deficit hyperactivity disorder (ADHD) and its comorbidity with other disorders. Family, twin, and adoption studies show that ADHD runs in families. ADHD’s high heritability of 74% motivated the search for ADHD susceptibility genes. Genetic linkage studies show that the effects of DNA risk variants on ADHD must, individually, be very small. Genome-wide association studies (GWAS) have implicated several genetic loci at the genome-wide level of statistical significance. These studies also show that about a third of ADHD’s heritability is due to a polygenic component comprising many common variants each having small effects. From studies of copy number variants we have also learned that the rare insertions or deletions account for part of ADHD’s heritability. These findings have implicated new biological pathways that may eventually have implications for treatment development.

Depression and obesity: evidence of shared biological mechanisms

Abstract: Depression and obesity are common conditions with major public health implications that tend to co-occur within individuals. The relationship between these conditions is bidirectional: the presence of one increases the risk for developing the other. It has thus become crucial to gain a better understanding of the mechanisms responsible for the intertwined downward physiological spirals associated with both conditions. The present review focuses specifically on shared biological pathways that may mechanistically explain the depression–obesity link, including genetics, alterations in systems involved in homeostatic adjustments (HPA axis, immuno-inflammatory activation, neuroendocrine regulators of energy metabolism including leptin and insulin, and microbiome) and brain circuitries integrating homeostatic and mood regulatory responses. Furthermore, the review addresses interventional opportunities and questions to be answered by future research that will enable a comprehensive characterization and targeting of the biological links between depression and obesity.

Excitation-inhibition balance as a framework for investigating mechanisms in neuropsychiatric disorders

Abstract: In 2003 Rubenstein and Merzenich hypothesized that some forms of Autism (ASD) might be caused by a reduction in signal-to-noise in key neural circuits, which could be the result of changes in excitatory-inhibitory (E-I) balance. Here, we have clarified the concept of E-I balance, and updated the original hypothesis in light of the field’s increasingly sophisticated understanding of neuronal circuits. We discuss how specific developmental mechanisms, which reduce inhibition, affect cortical and hippocampal functions. After describing how mutations of some ASD genes disrupt inhibition in mice, we close by suggesting that E-I balance represents an organizing framework for understanding findings related to pathophysiology and for identifying appropriate treatments.

Healthy dietary indices and risk of depressive outcomes: a systematic review and meta-analysis of observational studies

Abstract: With depression being the psychiatric disorder incurring the largest societal costs in developed countries, there is a need to gather evidence on the role of nutrition in depression, to help develop recommendations and guide future psychiatric health care. The aim of this systematic review was to synthesize the link between diet quality, measured using a range of predefined indices, and depressive outcomes. Medline, Embase and PsychInfo were searched up to 31st May 2018 for studies that examined adherence to a healthy diet in relation to depressive symptoms or clinical depression. Where possible, estimates were pooled using random effect meta-analysis with stratification by observational study design and dietary score. A total of 20 longitudinal and 21 cross-sectional studies were included. These studies utilized an array of dietary measures, including: different measures of adherence to the Mediterranean diet, the Healthy Eating Index (HEI) and Alternative HEI (AHEI), the Dietary Approaches to Stop Hypertension, and the Dietary Inflammatory Index. The most compelling evidence was found for the Mediterranean diet and incident depression, with a combined relative risk estimate of highest vs. lowest adherence category from four longitudinal studies of 0.67 (95% CI 0.55-0.82). A lower Dietary Inflammatory Index was also associated with lower depression incidence in four longitudinal studies (relative risk 0.76; 95% CI: 0.63-0.92). There were fewer longitudinal studies using other indices, but they and cross-sectional evidence also suggest an inverse association between healthy diet and depression (e.g., relative risk 0.65; 95% CI 0.50-0.84 for HEI/AHEI). To conclude, adhering to a healthy diet, in particular a traditional Mediterranean diet, or avoiding a pro-inflammatory diet appears to confer some protection against depression in observational studies. This provides a reasonable evidence base to assess the role of dietary interventions to prevent depression. This systematic review was registered in the PROSPERO International Prospective Register of Systematic Reviews under the number CRD42017080579.

The role of adult hippocampal neurogenesis in brain health and disease

Abstract: Adult neurogenesis in the dentate gyrus of the hippocampus is highly regulated by a number of environmental and cell-intrinsic factors to adapt to environmental changes. Accumulating evidence suggests that adult-born neurons may play distinct physiological roles in hippocampus-dependent functions, such as memory encoding and mood regulation. In addition, several brain diseases, such as neurological diseases and mood disorders, have deleterious effects on adult hippocampal neurogenesis, and some symptoms of those diseases can be partially explained by the dysregulation of adult hippocampal neurogenesis. Here we review a possible link between the physiological functions of adult-born neurons and their roles in pathological conditions.

Tau PET imaging in neurodegenerative tauopathies—still a challenge

Abstract: The accumulation of pathological misfolded tau is a feature common to a collective of neurodegenerative disorders known as tauopathies, of which Alzheimer’s disease (AD) is the most common. Related tauopathies include progressive supranuclear palsy (PSP), corticobasal syndrome (CBS), Down’s syndrome (DS), Parkinson’s disease (PD), and dementia with Lewy bodies (DLB). Investigation of the role of tau pathology in the onset and progression of these disorders is now possible due the recent advent of tau-specific ligands for use with positron emission tomography (PET), including first- (e.g., [18F]THK5317, [18F]THK5351, [18F]AV1451, and [11C]PBB3) and second-generation compounds [namely [18F]MK-6240, [18F]RO-948 (previously referred to as [18F]RO69558948), [18F]PI-2620, [18F]GTP1, [18F]PM-PBB3, and [18F]JNJ64349311 ([18F]JNJ311) and its derivative [18F]JNJ-067)]. In this review we describe and discuss findings from in vitro and in vivo studies using both initial and new tau ligands, including their relation to biomarkers for amyloid-β and neurodegeneration, and cognitive findings. Lastly, methodological considerations for the quantification of in vivo ligand binding are addressed, along with potential future applications of tau PET, including therapeutic trials.

Big data approaches to decomposing heterogeneity across the autism spectrum

Abstract: Autism is a diagnostic label based on behavior. While the diagnostic criteria attempt to maximize clinical consensus, it also masks a wide degree of heterogeneity between and within individuals at multiple levels of analysis. Understanding this multi-level heterogeneity is of high clinical and translational importance. Here we present organizing principles to frame research examining multi-level heterogeneity in autism. Theoretical concepts such as ‘spectrum’ or ‘autisms’ reflect non-mutually exclusive explanations regarding continuous/dimensional or categorical/qualitative variation between and within individuals. However, common practices of small sample size studies and case–control models are suboptimal for tackling heterogeneity. Big data are an important ingredient for furthering our understanding of heterogeneity in autism. In addition to being ‘feature-rich’, big data should be both ‘broad’ (i.e., large sample size) and ‘deep’ (i.e., multiple levels of data collected on the same individuals). These characteristics increase the likelihood that the study results are more generalizable and facilitate evaluation of the utility of different models of heterogeneity. A model’s utility can be measured by its ability to explain clinically or mechanistically important phenomena, and also by explaining how variability manifests across different levels of analysis. The directionality for explaining variability across levels can be bottom-up or top-down, and should include the importance of development for characterizing changes within individuals. While progress can be made with ‘supervised’ models built upon a priori or theoretically predicted distinctions or dimensions of importance, it will become increasingly important to complement such work with unsupervised data-driven discoveries that leverage unknown and multivariate distinctions within big data. A better understanding of how to model heterogeneity between autistic people will facilitate progress towards precision medicine for symptoms that cause suffering, and person-centered support.

Brain age and other bodily ‘ages’: implications for neuropsychiatry

Abstract: As our brains age, we tend to experience cognitive decline and are at greater risk of neurodegenerative disease and dementia. Symptoms of chronic neuropsychiatric diseases are also exacerbated during ageing. However, the ageing process does not affect people uniformly; nor, in fact, does the ageing process appear to be uniform even within an individual. Here, we outline recent neuroimaging research into brain ageing and the use of other bodily ageing biomarkers, including telomere length, the epigenetic clock, and grip strength. Some of these techniques, using statistical approaches, have the ability to predict chronological age in healthy people. Moreover, they are now being applied to neurological and psychiatric disease groups to provide insights into how these diseases interact with the ageing process and to deliver individualised predictions about future brain and body health. We discuss the importance of integrating different types of biological measurements, from both the brain and the rest of the body, to build more comprehensive models of the biological ageing process. Finally, we propose seven steps for the field of brain-ageing research to take in coming years. This will help us reach the long-term goal of developing clinically applicable statistical models of biological processes to measure, track and predict brain and body health in ageing and disease.

Psychiatric genetics and the structure of psychopathology.

Abstract: For over a century, psychiatric disorders have been defined by expert opinion and clinical observation. The modern DSM has relied on a consensus of experts to define categorical syndromes based on clusters of symptoms and signs, and, to some extent, external validators, such as longitudinal course and response to treatment. In the absence of an established etiology, psychiatry has struggled to validate these descriptive syndromes, and to define the boundaries between disorders and between normal and pathologic variation. Recent advances in genomic research, coupled with large-scale collaborative efforts like the Psychiatric Genomics Consortium, have identified hundreds of common and rare genetic variations that contribute to a range of neuropsychiatric disorders. At the same time, they have begun to address deeper questions about the structure and classification of mental disorders: To what extent do genetic findings support or challenge our clinical nosology? Are there genetic boundaries between psychiatric and neurologic illness? Do the data support a boundary between disorder and normal variation? Is it possible to envision a nosology based on genetically informed disease mechanisms? This review provides an overview of conceptual issues and genetic findings that bear on the relationships among and boundaries between psychiatric disorders and other conditions. We highlight implications for the evolving classification of psychopathology and the challenges for clinical translation.

A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence

Abstract: Intelligence, or general cognitive function, is phenotypically and genetically correlated with many traits, including a wide range of physical, and mental health variables. Education is strongly genetically correlated with intelligence (rg = 0.70). We used these findings as foundations for our use of a novel approach—multi-trait analysis of genome-wide association studies (MTAG; Turley et al. 2017)—to combine two large genome-wide association studies (GWASs) of education and intelligence, increasing statistical power and resulting in the largest GWAS of intelligence yet reported. Our study had four goals: first, to facilitate the discovery of new genetic loci associated with intelligence; second, to add to our understanding of the biology of intelligence differences; third, to examine whether combining genetically correlated traits in this way produces results consistent with the primary phenotype of intelligence; and, finally, to test how well this new meta-analytic data sample on intelligence predicts phenotypic intelligence in an independent sample. By combining datasets using MTAG, our functional sample size increased from 199,242 participants to 248,482. We found 187 independent loci associated with intelligence, implicating 538 genes, using both SNP-based and gene-based GWAS. We found evidence that neurogenesis and myelination—as well as genes expressed in the synapse, and those involved in the regulation of the nervous system—may explain some of the biological differences in intelligence. The results of our combined analysis demonstrated the same pattern of genetic correlations as those from previous GWASs of intelligence, providing support for the meta-analysis of these genetically-related phenotypes.

Effects of medication-assisted treatment on mortality among opioids users: a systematic review and meta-analysis.

Abstract: Opioid use disorder (OUD) is associated with a high risk of premature death. Medication-assisted treatment (MAT) is the primary treatment for opioid dependence. We comprehensively assessed the effects of different MAT-related characteristics on mortality among those with OUD by a systematic review and meta-analysis. The all-cause and overdose crude mortality rates (CMRs) and relative risks (RRs) by treatment status, different type, period, and dose of medication, and retention time were pooled using random effects, subgroup analysis, and meta-regression. Thirty cohort studies involving 370,611 participants (1,378,815 person-years) were eligible in the meta-analysis. From 21 studies, the pooled all-cause CMRs were 0.92 per 100 person-years (95% CI: 0.79-1.04) while receiving MAT, 1.69 (1.47-1.91) after cessation, and 4.89 (3.54-6.23) for untreated period. Based on 16 studies, the pooled overdose CMRs were 0.24 (0.20-0.28) while receiving MAT, 0.68 (0.55-0.80) after cessation of MAT, and 2.43 (1.72-3.15) for untreated period. Compared with patients receiving MAT, untreated participants had higher risk of all-cause mortality (RR 2.56 [95% CI: 1.72-3.80]) and overdose mortality (8.10 [4.48-14.66]), and discharged participants had higher risk of all-cause death (2.33 [2.02-2.67]) and overdose death (3.09 [2.37-4.01]). The all-cause CMRs during and after opioid substitution treatment with methadone or buprenorphine were 0.93 (0.76-1.10) and 1.79 (1.47-2.10), and corresponding estimate for antagonist naltrexone treatment were 0.26 (0-0.59) and 1.97 (0-5.18), respectively. Retention in MAT of over 1-year was associated with a lower mortality rate than that with retention ≤1 year (1.62, 1.31-1.93 vs. 5.31, -0.09-10.71). Improved coverage and adherence to MAT and post-treatment follow-up are crucial to reduce the mortality. Long-acting naltrexone showed positive advantage on prevention of premature death among persons with OUD.

Glutamatergic neurometabolite levels in major depressive disorder: a systematic review and meta-analysis of proton magnetic resonance spectroscopy studies

Abstract: Alterations in glutamatergic neurotransmission are implicated in the pathophysiology of depression, and the glutamatergic system represents a treatment target for depression. To summarize the nature of glutamatergic alterations in patients with depression, we conducted a meta-analysis of proton magnetic resonance (1H-MRS) spectroscopy studies examining levels of glutamate. We used the search terms: depress* AND (MRS OR “magnetic resonance spectroscopy”). The search was performed with MEDLINE, Embase, and PsycINFO. The inclusion criteria were 1H-MRS studies comparing levels of glutamate + glutamine (Glx), glutamate, or glutamine between patients with depression and healthy controls. Standardized mean differences (SMD) were calculated to assess group differences in the levels of glutamatergic neurometabolites. Forty-nine studies met the eligibility criteria, which included 1180 patients and 1066 healthy controls. There were significant decreases in Glx within the medial frontal cortex (SMD = −0.38; 95% CI, −0.69 to −0.07) in patients with depression compared with controls. Subanalyses revealed that there was a significant decrease in Glx in the medial frontal cortex in medicated patients with depression (SMD = −0.50; 95% CI, −0.80 to −0.20), but not in unmedicated patients (SMD = −0.27; 95% CI, −0.76 to 0.21) compared with controls. Overall, decreased levels of glutamatergic metabolites in the medial frontal cortex are linked with the pathophysiology of depression. These findings are in line with the hypothesis that depression may be associated with abnormal glutamatergic neurotransmission.

The ASD Living Biology: from cell proliferation to clinical phenotype

Abstract: Autism spectrum disorder (ASD) has captured the attention of scientists, clinicians and the lay public because of its uncertain origins and striking and unexplained clinical heterogeneity. Here we review genetic, genomic, cellular, postmortem, animal model, and cell model evidence that shows ASD begins in the womb. This evidence leads to a new theory that ASD is a multistage, progressive disorder of brain development, spanning nearly all of prenatal life. ASD can begin as early as the 1st and 2nd trimester with disruption of cell proliferation and differentiation. It continues with disruption of neural migration, laminar disorganization, altered neuron maturation and neurite outgrowth, disruption of synaptogenesis and reduced neural network functioning. Among the most commonly reported high-confidence ASD (hcASD) genes, 94% express during prenatal life and affect these fetal processes in neocortex, amygdala, hippocampus, striatum and cerebellum. A majority of hcASD genes are pleiotropic, and affect proliferation/differentiation and/or synapse development. Proliferation and subsequent fetal stages can also be disrupted by maternal immune activation in the 1st trimester. Commonly implicated pathways, PI3K/AKT and RAS/ERK, are also pleiotropic and affect multiple fetal processes from proliferation through synapse and neural functional development. In different ASD individuals, variation in how and when these pleiotropic pathways are dysregulated, will lead to different, even opposing effects, producing prenatal as well as later neural and clinical heterogeneity. Thus, the pathogenesis of ASD is not set at one point in time and does not reside in one process, but rather is a cascade of prenatal pathogenic processes in the vast majority of ASD toddlers. Despite this new knowledge and theory that ASD biology begins in the womb, current research methods have not provided individualized information: What are the fetal processes and early-age molecular and cellular differences that underlie ASD in each individual child? Without such individualized knowledge, rapid advances in biological-based diagnostic, prognostic, and precision medicine treatments cannot occur. Missing, therefore, is what we call ASD Living Biology. This is a conceptual and paradigm shift towards a focus on the abnormal prenatal processes underlying ASD within each living individual. The concept emphasizes the specific need for foundational knowledge of a living child’s development from abnormal prenatal beginnings to early clinical stages. The ASD Living Biology paradigm seeks this knowledge by linking genetic and in vitro prenatal molecular, cellular and neural measurements with in vivo post-natal molecular, neural and clinical presentation and progression in each ASD child. We review the first such study, which confirms the multistage fetal nature of ASD and provides the first in vitro fetal-stage explanation for in vivo early brain overgrowth. Within-child ASD Living Biology is a novel research concept we coin here that advocates the integration of in vitro prenatal and in vivo early post-natal information to generate individualized and group-level explanations, clinically useful prognoses, and precision medicine approaches that are truly beneficial for the individual infant and toddler with ASD.

Conceptualizing mental disorders as deviations from normative functioning

Abstract: Normative models are a class of emerging statistical techniques useful for understanding the heterogeneous biology underlying psychiatric disorders at the level of the individual participant. Analogous to normative growth charts used in paediatric medicine for plotting child development in terms of height or weight as a function of age, normative models chart variation in clinical cohorts in terms of mappings between quantitative biological measures and clinically relevant variables. An emerging body of literature has demonstrated that such techniques are excellent tools for parsing the heterogeneity in clinical cohorts by providing statistical inferences at the level of the individual participant with respect to the normative range. Here, we provide a unifying review of the theory and application of normative modelling for understanding the biological and clinical heterogeneity underlying mental disorders. We first provide a statistically grounded yet non-technical overview of the conceptual underpinnings of normative modelling and propose a conceptual framework to link the many different methodological approaches that have been proposed for this purpose. We survey the literature employing these techniques, focusing principally on applications of normative modelling to quantitative neuroimaging-based biomarkers in psychiatry and, finally, we provide methodological considerations and recommendations to guide future applications of these techniques. We show that normative modelling provides a means by which the importance of modelling individual differences can be brought from theory to concrete data analysis procedures for understanding heterogeneous mental disorders and ultimately a promising route towards precision medicine in psychiatry.

Ketamine has distinct electrophysiological and behavioral effects in depressed and healthy subjects

Abstract: Ketamine’s mechanism of action was assessed using gamma power from magnetoencephalography (MEG) as a proxy measure for homeostatic balance in 35 unmedicated subjects with major depressive disorder (MDD) and 25 healthy controls enrolled in a double-blind, placebo-controlled, randomized cross-over trial of 0.5 mg/kg ketamine. MDD subjects showed significant improvements in depressive symptoms, and healthy control subjects exhibited modest but significant increases in depressive symptoms for up to 1 day after ketamine administration. Both groups showed increased resting gamma power following ketamine. In MDD subjects, gamma power was not associated with the magnitude of the antidepressant effect. However, baseline gamma power was found to moderate the relationship between post-ketamine gamma power and antidepressant response; specifically, higher post-ketamine gamma power was associated with better response in MDD subjects with lower baseline gamma, with an inverted relationship in MDD subjects with higher baseline gamma. This relationship was observed in multiple regions involved in networks hypothesized to be involved in the pathophysiology of MDD. This finding suggests biological subtypes based on the direction of homeostatic dysregulation and has important implications for inferring ketamine’s mechanism of action from studies of healthy controls alone.

Synaptic loss in schizophrenia: a meta-analysis and systematic review of synaptic protein and mRNA measures.

Abstract: Although synaptic loss is thought to be core to the pathophysiology of schizophrenia, the nature, consistency and magnitude of synaptic protein and mRNA changes has not been systematically appraised. Our objective was thus to systematically review and meta-analyse findings. The entire PubMed database was searched for studies from inception date to the 1st of July 2017. We selected case-control postmortem studies in schizophrenia quantifying synaptic protein or mRNA levels in brain tissue. The difference in protein and mRNA levels between cases and controls was extracted and meta-analysis conducted. Among the results, we found a significant reduction in synaptophysin in schizophrenia in the hippocampus (effect size: −0.65, p < 0.01), frontal (effect size: −0.36, p = 0.04), and cingulate cortices (effect size: −0.54, p = 0.02), but no significant changes for synaptophysin in occipital and temporal cortices, and no changes for SNAP-25, PSD-95, VAMP, and syntaxin in frontal cortex. There were insufficient studies for meta-analysis of complexins, synapsins, rab3A and synaptotagmin and mRNA measures. Findings are summarised for these, which generally show reductions in SNAP-25, PSD-95, synapsin and rab3A protein levels in the hippocampus but inconsistency in other regions. Our findings of moderate–large reductions in synaptophysin in hippocampus and frontal cortical regions, and a tendency for reductions in other pre- and postsynaptic proteins in the hippocampus are consistent with models that implicate synaptic loss in schizophrenia. However, they also identify potential differences between regions and proteins, suggesting synaptic loss is not uniform in nature or extent.

Cerebrospinal fluid markers of inflammation and infections in schizophrenia and affective disorders: a systematic review and meta-analysis

Abstract: Following publication of this paper, the authors realised that there were some errors in the reporting of the results on IL-6. This article has now been updated to include the correct values, following re-running of all analyses. For details of the changes made, please see the associated correction. This article was also originally published under standard licence, but has now been made available under a [CC BY 4.0] licence. The PDF and HTML versions of the paper have been modified accordingly.

Treatment strategies for ADHD: an evidence-based guide to select optimal treatment

Abstract: Attention-deficit/hyperactivity disorder (ADHD) is a common and impairing disorder affecting children, adolescents, and adults. Several treatment strategies are available that can successfully ameliorate symptoms, ranging from pharmacological to dietary interventions. Due to the increasing range of available options, an informed selection or prioritization of treatments is becoming harder for clinicians. This review aims to provide an evidence-based appraisal of the literature on ADHD treatment, supplemented by expert opinion on plausibility. We outline proposed mechanisms of action of established pharmacologic and non-pharmacologic treatments, and we review targets of novel treatments. The most relevant evidence supporting efficacy and safety of each treatment strategy is discussed. We review the individualized features of the patient that should guide the selection of treatments in a shared decision-making continuum. We provide guidance for optimizing initiation of treatment and follow-up of patients in clinical settings.

Deep neural networks in psychiatry.

Abstract: Machine and deep learning methods, today’s core of artificial intelligence, have been applied with increasing success and impact in many commercial and research settings. They are powerful tools for large scale data analysis, prediction and classification, especially in very data-rich environments (“big data”), and have started to find their way into medical applications. Here we will first give an overview of machine learning methods, with a focus on deep and recurrent neural networks, their relation to statistics, and the core principles behind them. We will then discuss and review directions along which (deep) neural networks can be, or already have been, applied in the context of psychiatry, and will try to delineate their future potential in this area. We will also comment on an emerging area that so far has been much less well explored: by embedding semantically interpretable computational models of brain dynamics or behavior into a statistical machine learning context, insights into dysfunction beyond mere prediction and classification may be gained. Especially this marriage of computational models with statistical inference may offer insights into neural and behavioral mechanisms that could open completely novel avenues for psychiatric treatment.

Memory and cognition in schizophrenia

Abstract: Episodic memory deficits are consistently documented as a core aspect of cognitive dysfunction in schizophrenia patients, present from the onset of the illness and strongly associated with functional disability. Over the past decade, research using approaches from experimental cognitive neuroscience revealed disproportionate episodic memory impairments in schizophrenia (Sz) under high cognitive demand relational encoding conditions and relatively unimpaired performance under item-specific encoding conditions. These specific deficits in component processes of episodic memory reflect impaired activation and connectivity within specific elements of frontal-medial temporal lobe circuits, with a central role for the dorsolateral prefrontal cortex (DLPFC), relatively intact function of ventrolateral prefrontal cortex and variable results in the hippocampus. We propose that memory deficits can be understood within the broader context of cognitive deficits in Sz, where impaired DLPFC-related cognitive control has a broad impact across multiple cognitive domains. The therapeutic implications of these findings are discussed.

Endogenous opioid system dysregulation in depression: implications for new therapeutic approaches

Abstract: The United States is in the midst of an opioid addiction and overdose crisis precipitated and exacerbated by use of prescription opioid medicines. The majority of opioid prescriptions are dispensed to patients with comorbid mood disorders including major depressive disorder (MDD). A growing body of research indicates that the endogenous opioid system is directly involved in the regulation of mood and is dysregulated in MDD. This involvement of the endogenous opioid system may underlie the disproportionate use of opioids among patients with mood disorders. Emerging approaches to address endogenous opioid dysregulation in MDD may yield novel therapeutics that have a low or absent risk of abuse and addiction relative to µ-opioid agonists. Moreover, agents targeting the endogenous opioid system would be expected to yield clinical benefits qualitatively different from conventional monaminergic antidepressants. The development of safe and effective agents to treat MDD-associated endogenous opioid dysregulation may represent a distinct and currently underappreciated means of addressing treatment resistant depression with the potential to attenuate the on-going opioid crisis.

Does playing violent video games cause aggression? A longitudinal intervention study.

Abstract: It is a widespread concern that violent video games promote aggression, reduce pro-social behaviour, increase impulsivity and interfere with cognition as well as mood in its players. Previous experimental studies have focussed on short-term effects of violent video gameplay on aggression, yet there are reasons to believe that these effects are mostly the result of priming. In contrast, the present study is the first to investigate the effects of long-term violent video gameplay using a large battery of tests spanning questionnaires, behavioural measures of aggression, sexist attitudes, empathy and interpersonal competencies, impulsivity-related constructs (such as sensation seeking, boredom proneness, risk taking, delay discounting), mental health (depressivity, anxiety) as well as executive control functions, before and after 2 months of gameplay. Our participants played the violent video game Grand Theft Auto V, the non-violent video game The Sims 3 or no game at all for 2 months on a daily basis. No significant changes were observed, neither when comparing the group playing a violent video game to a group playing a non-violent game, nor to a passive control group. Also, no effects were observed between baseline and posttest directly after the intervention, nor between baseline and a follow-up assessment 2 months after the intervention period had ended. The present results thus provide strong evidence against the frequently debated negative effects of playing violent video games in adults and will therefore help to communicate a more realistic scientific perspective on the effects of violent video gaming.

Synaptic and transcriptionally downregulated genes are associated with cortical thickness differences in autism.

Abstract: Differences in cortical morphology—in particular, cortical volume, thickness and surface area—have been reported in individuals with autism. However, it is unclear what aspects of genetic and transcriptomic variation are associated with these differences. Here we investigate the genetic correlates of global cortical thickness differences (ΔCT) in children with autism. We used Partial Least Squares Regression (PLSR) on structural MRI data from 548 children (166 with autism, 295 neurotypical children and 87 children with ADHD) and cortical gene expression data from the Allen Institute for Brain Science to identify genetic correlates of ΔCT in autism. We identify that these genes are enriched for synaptic transmission pathways and explain significant variation in ΔCT. These genes are also significantly enriched for genes dysregulated in the autism post-mortem cortex (Odd Ratio (OR) = 1.11, Pcorrected 10−14), driven entirely by downregulated genes (OR = 1.87, Pcorrected 10−15). We validated the enrichment for downregulated genes in two independent data sets: Validation 1 (OR = 1.44, Pcorrected = 0.004) and Validation 2 (OR = 1.30; Pcorrected = 0.001). We conclude that transcriptionally downregulated genes implicated in autism are robustly associated with global changes in cortical thickness variability in children with autism.

Pharmacological treatment of adult bipolar disorder.

Abstract: We summarize evidence supporting contemporary pharmacological treatment of phases of BD, including: mania, depression, and long-term recurrences, emphasizing findings from randomized, controlled trials (RCTs). Effective treatment of acute or dysphoric mania is provided by modern antipsychotics, some anticonvulsants (divalproex and carbamazepine), and lithium salts. Treatment of BD-depression remains unsatisfactory but includes some modern antipsychotics (particularly lurasidone, olanzapine + fluoxetine, and quetiapine) and the anticonvulsant lamotrigine; value and safety of antidepressants remain controversial. Long-term prophylactic treatment relies on lithium, off-label use of valproate, and growing use of modern antipsychotics. Lithium has unique evidence of antisuicide effects. Methods of evaluating treatments for BD rely heavily on meta-analysis, which is convenient but with important limitations. Underdeveloped treatment for BD-depression may reflect an assumption that effects of antidepressants are similar in BD as in unipolar major depressive disorder. Effective prophylaxis of BD is limited by the efficacy of available treatments and incomplete adherence owing to adverse effects, costs, and lack of ongoing symptoms. Long-term treatment of BD also is limited by access to, and support of expert, comprehensive clinical programs. Pursuit of improved, rationally designed pharmacological treatments for BD, as for most psychiatric disorders, is fundamentally limited by lack of coherent pathophysiology or etiology.

Animal models of PTSD: a challenge to be met

Abstract: 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.

Altered TAOK2 activity causes autism-related neurodevelopmental and cognitive abnormalities through RhoA signaling

Abstract: Atypical brain connectivity is a major contributor to the pathophysiology of neurodevelopmental disorders (NDDs) including autism spectrum disorders (ASDs). TAOK2 is one of several genes in the 16p11.2 microdeletion region, but whether it contributes to NDDs is unknown. We performed behavioral analysis on Taok2 heterozygous (Het) and knockout (KO) mice and found gene dosage-dependent impairments in cognition, anxiety, and social interaction. Taok2 Het and KO mice also have dosage-dependent abnormalities in brain size and neural connectivity in multiple regions, deficits in cortical layering, dendrite and synapse formation, and reduced excitatory neurotransmission. Whole-genome and -exome sequencing of ASD families identified three de novo mutations in TAOK2 and functional analysis in mice and human cells revealed that all the mutations impair protein stability, but they differentially impact kinase activity, dendrite growth, and spine/synapse development. Mechanistically, loss of Taok2 activity causes a reduction in RhoA activation, and pharmacological enhancement of RhoA activity rescues synaptic phenotypes. Together, these data provide evidence that TAOK2 is a neurodevelopmental disorder risk gene and identify RhoA signaling as a mediator of TAOK2-dependent synaptic development.

Determinants of treatment response in first-episode psychosis: an 18 F-DOPA PET study

Abstract: Psychotic illnesses show variable responses to treatment. Determining the neurobiology underlying this is important for precision medicine and the development of better treatments. It has been proposed that dopaminergic differences underlie variation in response, with striatal dopamine synthesis capacity (DSC) elevated in responders and unaltered in non-responders. We therefore aimed to test this in a prospective cohort, with a nested case-control comparison. 40 volunteers (26 patients with first-episode psychosis and 14 controls) received an 18F-DOPA Positron Emission Tomography scan to measure DSC (Kicer) prior to antipsychotic treatment. Clinical assessments (Positive and Negative Syndrome Scale, PANSS, and Global Assessment of Functioning, GAF) occurred at baseline and following antipsychotic treatment for a minimum of 4 weeks. Response was defined using improvement in PANSS Total score of >50%. Patients were followed up for at least 6 months, and remission criteria applied. There was a significant effect of group on Kicer in associative striatum (F(2, 37) = 7.9, p = 0.001). Kicer was significantly higher in responders compared with non-responders (Cohen’s d = 1.55, p = 0.01) and controls (Cohen’s d = 1.31, p = 0.02). Kicer showed significant positive correlations with improvements in PANSS-positive (r = 0.64, p < 0.01), PANSS negative (rho = 0.51, p = 0.01), and PANSS total (rho = 0.63, p < 0.01) ratings and a negative relationship with change in GAF (r = −0.55, p < 0.01). Clinical response is related to baseline striatal dopaminergic function. Differences in dopaminergic function between responders and non-responders are present at first episode of psychosis, consistent with dopaminergic and non-dopaminergic sub-types in psychosis, and potentially indicating a neurochemical basis to stratify psychosis.

Genetics of intellectual disability in consanguineous families

Abstract: Autosomal recessive (AR) gene defects are the leading genetic cause of intellectual disability (ID) in countries with frequent parental consanguinity, which account for about 1/7th of the world population. Yet, compared to autosomal dominant de novo mutations, which are the predominant cause of ID in Western countries, the identification of AR-ID genes has lagged behind. Here, we report on whole exome and whole genome sequencing in 404 consanguineous predominantly Iranian families with two or more affected offspring. In 219 of these, we found likely causative variants, involving 77 known and 77 novel AR-ID (candidate) genes, 21 X-linked genes, as well as 9 genes previously implicated in diseases other than ID. This study, the largest of its kind published to date, illustrates that high-throughput DNA sequencing in consanguineous families is a superior strategy for elucidating the thousands of hitherto unknown gene defects underlying AR-ID, and it sheds light on their prevalence.

Data-driven biological subtypes of depression: systematic review of biological approaches to depression subtyping

Abstract: Research into major depressive disorder (MDD) is complicated by population heterogeneity, which has motivated the search for more homogeneous subtypes through data-driven computational methods to identify patterns in data. In addition, data on biological differences could play an important role in identifying clinically useful subtypes. This systematic review aimed to summarize evidence for biological subtypes of MDD from data-driven studies. We undertook a systematic literature search of PubMed, PsycINFO, and Embase (December 2018). We included studies that identified (1) data-driven subtypes of MDD based on biological variables, or (2) data-driven subtypes based on clinical features (e.g., symptom patterns) and validated these with biological variables post-hoc. Twenty-nine publications including 24 separate analyses in 20 unique samples were identified, including a total of ~ 4000 subjects. Five out of six biochemical studies indicated that there might be depression subtypes with and without disturbed neurotransmitter levels, and one indicated there might be an inflammatory subtype. Seven symptom-based studies identified subtypes, which were mainly determined by severity and by weight gain vs. loss. Two studies compared subtypes based on medication response. These symptom-based subtypes were associated with differences in biomarker profiles and functional connectivity, but results have not sufficiently been replicated. Four out of five neuroimaging studies found evidence for groups with structural and connectivity differences, but results were inconsistent. The single genetic study found a subtype with a distinct pattern of SNPs, but this subtype has not been replicated in an independent test sample. One study combining all aforementioned types of data discovered a subtypes with different levels of functional connectivity, childhood abuse, and treatment response, but the sample size was small. Although the reviewed work provides many leads for future research, the methodological differences across studies and lack of replication preclude definitive conclusions about the existence of clinically useful and generalizable biological subtypes.

Is psychosis a multisystem disorder? A meta-review of central nervous system, immune, cardiometabolic, and endocrine alterations in first-episode psychosis and perspective on potential models.

Abstract: People with psychotic disorders show abnormalities in several organ systems in addition to the central nervous system (CNS); and this contributes to excess mortality. However, it is unclear how strong the evidence is for alterations in non-CNS systems at the onset of psychosis, how the alterations in non-CNS systems compare to those in the CNS, or how they relate to symptoms. Here, we consider these questions, and suggest potential models to account for findings. We conducted a systematic meta-review to summarize effect sizes for both CNS (focusing on brain structural, neurophysiological, and neurochemical parameters) and non-CNS dysfunction (focusing on immune, cardiometabolic, and hypothalamic–pituitary–adrenal (HPA) systems) in first-episode psychosis (FEP). Relevant meta-analyses were identified in a systematic search of Pubmed and the methodological quality of these was assessed using the AMSTAR checklist (A Measurement Tool to Assess Systematic Reviews). Case–control data were extracted from studies included in these meta-analyses. Random effects meta-analyses were re-run and effect size magnitudes for individual parameters were calculated, as were summary effect sizes for each CNS and non-CNS system. We also grouped studies to obtain overall effect sizes for non-CNS and CNS alterations. Robustness of data for non-CNS and CNS parameters was assessed using Rosenthal’s fail-safe N. We next statistically compared summary effect size for overall CNSand overall non-CNS alterations, as well as for each organ system separately. We also examined how non-CNS alterations correlate CNS alterations, and with psychopathological symptoms. Case-control data were extracted for 165 studies comprising a total sample size of 13,440. For people with first episode psychosis compared with healthy controls, we observed alterations in immune parameters (summary effect size: g = 1.19), cardiometabolic parameters (g = 0.23); HPA parameters (g = 0.68); brain structure (g = 0.40); neurophysiology (g = 0.80); and neurochemistry (g = 0.43). Grouping non-CNS organ systems together provided an effect size for overall non-CNS alterations in patients compared with controls (g = 0.58), which was not significantly different from the overall CNS alterations effect size (g = 0.50). However, the summary effect size for immune alterations was significantly greater than that for brain structural (P < 0.001) and neurochemical alterations (P < 0.001), while the summary effect size for cardiometabolic alterations was significantly lower than neurochemical (P = 0.04), neurophysiological (P < 0.001), and brain structural alterations (P = 0.001). The summary effect size for HPA alterations was not significantly different from brain structural (P = 0.14), neurophysiological (P = 0.54), or neurochemical alterations (P = 0.22). These outcomes remained similar in antipsychotic naive sensitivity analyses. We found some, but limited and inconsistent, evidence that non-CNS alterations were associated with CNS changes and symptoms in first episode psychosis. Our findings indicate that there are robust alterations in non-CNS systems in psychosis, and that these are broadly similar in magnitude to a range of CNS alterations. We consider models that could account for these findings and discuss implications for future research and treatment.