Medicine. The future of psychiatric research: genomes and neural circuits

Autism-associated neuroligin-3 mutations commonly impair striatal circuits to boost repetitive behaviors

In humans, neuroligin-3 mutations are associated with autism, whereas in mice, the corresponding mutations produce robust synaptic and behavioral changes. However, different neuroligin-3 mutations cause largely distinct phenotypes in mice, and no causal relationship links a specific synaptic dysfunction to a behavioral change. Using rotarod motor learning as a proxy for acquired repetitive behaviors in mice, we found that different neuroligin-3 mutations uniformly enhanced formation of repetitive motor routines. Surprisingly, neuroligin-3 mutations caused this phenotype not via changes in the cerebellum or dorsal striatum but via a selective synaptic impairment in the nucleus accumbens/ventral striatum. Here, neuroligin-3 mutations increased rotarod learning by specifically impeding synaptic inhibition onto D1-dopamine receptor-expressing but not D2-dopamine receptor-expressing medium spiny neurons. Our data thus suggest that different autism-associated neuroligin-3 mutations cause a common increase in acquired repetitive behaviors by impairing a specific striatal synapse and thereby provide a plausible circuit substrate for autism pathophysiology.

Network plasticity in adaptive filtering and behavioral habituation

The ability of organisms to seamlessly ignore familiar, inconsequential stimuli improves their selective attention and response to salient features of the environment. Here, I propose that this fundamental but unexplained phenomenon substantially derives from the ability of any pattern of neural excitation to create an enhanced inhibitory (or "negative") image of itself through target-specific scaling of inhibitory inputs onto active excitatory neurons. Familiar stimuli encounter strong negative images and are therefore less likely to be transmitted to higher brain centers. Integrating historical and recent observations, the negative-image model described here provides a mechanistic framework for understanding habituation, which is connected to ideas on dynamic predictive coding. In addition, it suggests insights for understanding autism spectrum disorders.

Advanced diffusion MRI fiber tracking in neurosurgical and neurodegenerative disorders and neuroanatomical studies: A review

Diffusion MRI enabled in vivo microstructural imaging of the fiber tracts in the brain resulting in its application in a wide range of settings, including in neurological and neurosurgical disorders. Conventional approaches such as diffusion tensor imaging (DTI) have been shown to have limited applications due to the crossing fiber problem and the susceptibility of their quantitative indices to partial volume effects. To overcome these limitations, the recent focus has shifted to the advanced acquisition methods and their related analytical approaches. Advanced white matter imaging techniques provide superior qualitative data in terms of demonstration of multiple crossing fibers in their spatial orientation in a three dimensional manner in the brain. In this review paper, we discuss the advancements in diffusion MRI and introduce their roles. Using examples, we demonstrate the role of advanced diffusion MRI-based fiber tracking in neuroanatomical studies. Results from its preliminary application in the evaluation of intracranial space occupying lesions, including with respect to future directions for prognostication, are also presented. Building upon the previous DTI studies assessing white matter disease in Huntington's disease and Amyotrophic lateral sclerosis; we also discuss approaches which have led to encouraging preliminary results towards developing an imaging biomarker for these conditions.

Interventional psychiatry: why now?

Interventional psychiatry offers substantial therapeutic benefits in some neuropsychiatric disorders and enormous potential in treating others. However, as interventional diagnostics and therapeutics require specialized knowledge and skill foreign to many psychiatrists, the emerging subspecialty of interventional psychiatry must be more formally integrated into the continuum of psychiatric training to ensure both safe application and continued growth. By establishing training paradigms for interventional psychiatry, academic medical centers can help fill this knowledge gap. The cultivation of a properly trained cohort of interventional psychiatrists will better meet the challenges of treatment-resistant psychiatric illness through safe and ethical practice, while facilitating a more informed development and integration of novel neuromodulation techniques.

Evidence-based psychotherapies II: changes in models of treatment and treatment delivery

Decades of psychotherapy research have yielded a few hundred interventions with strong evidence on their behalf. In the prior companion article, methodological and substantive concerns were raised in relation to what we can say about evidence-based psychotherapies and their impact. Among the methodological concerns are the control conditions to which evidence-based psychotherapies are compared, selective reporting of measures, and the paucity of evidence that evidence-based psychotherapies have clinically significant impact. Among the substantive concerns are limited findings to help direct patients to treatments from which they are likely to profit and to understand the mechanisms responsible for therapeutic change. In this article, two shifts in evidence-based psychotherapy research are highlighted to convey novel and needed directions to augment the impact of treatment and the scale on which it can be delivered. First, transdiagnosis and transtreatment are discussed as a departure from traditional evidence-based psychotherapy research by emphasizing interventions that can be applied across multiple domains. Common biological, psychological, and environmental underpinnings of many disorders and select treatments showing reliable changes across multiple problems are altering evidence-based psychotherapy research. Second, novel models of treatment delivery have emerged from global health care, business, economics, and the media, and are well outside of mainstream mental health professions. Two models (task shifting and best-buy interventions) illustrate how different ways of delivering treatment are essential to reach large and diverse swaths of unserved individuals and have impact on the burden of mental illness.

[Biologism controversy: ethical implications for psychiatry]

Current biological psychiatry, it is frequently claimed by its opponents, is "biologistic" and unduly narrows psychological disorders to neurobiology and molecular biology. They deem a complete neuroscientific reduction of the mental phenomena to be impossible because of the impossibility of reducing certain phenomena, such as the individual subjective experience. If such a reduction is nevertheless undertaken it is ultimately to the disadvantage of the patients. We argue in this article that the very term "biologism" has to be put under scrutiny in the first place. As a result it becomes obvious that "biologism", as a subclass of "philosophical naturalism", is ultimately quite unproblematic. Biologism is dangerous only if it implies an eliminative rejection or an inappropriate underestimation of the relevance of the psyche. On closer examination it gets evident that such implications do not follow necessarily from biologism but cannot be precluded either. To better identify and possibly prevent such dangers, a more differentiated terminology seems helpful.

Imaging the pathophysiology of major depressive disorder - from localist models to circuit-based analysis

The neuroimaging literature of Major Depressive Disorder (MDD) has grown substantially over the last several decades, facilitating great advances in the identification of specific brain regions, neurotransmitter systems and networks associated with depressive illness. Despite this progress, fundamental questions remain about the pathophysiology and etiology of MDD. More importantly, this body of work has yet to directly influence clinical practice. It has long been a goal for the fields of clinical psychology and psychiatry to have a means of making objective diagnoses of mental disorders. Frustratingly little movement has been achieved on this front, however, and the 'gold-standard’ of diagnostic validity and reliability remains expert consensus. In light of this challenge, the focus of the current review is to provide a critical summary of key findings from different neuroimaging approaches in MDD research, including structural, functional and neurochemical imaging studies. Following this summary, we discuss some of the current conceptual obstacles to better understanding the pathophysiology of depression, and conclude with recommendations for future neuroimaging research.

Biological markers in noninvasive brain stimulation trials in major depressive disorder: a systematic review

OBJECTIVES

The therapeutic effects of transcranial magnetic stimulation (TMS) and transcranial direct current stimulation in patients with major depression have shown promising results; however, there is a lack of mechanistic studies using biological markers (BMs) as an outcome. Therefore, our aim was to review noninvasive brain stimulation trials in depression using BMs.

METHODS

The following databases were used for our systematic review: MEDLINE, Web of Science, Cochrane, and SCIELO. We examined articles published before November 2012 that used TMS and transcranial direct current stimulation as an intervention for depression and had BM as an outcome measure. The search was limited to human studies written in English.

RESULTS

Of 1234 potential articles, 52 articles were included. Only studies using TMS were found. Biological markers included immune and endocrine serum markers, neuroimaging techniques, and electrophysiological outcomes. In 12 articles (21.4%), end point BM measurements were not significantly associated with clinical outcomes. All studies reached significant results in the main clinical rating scales. Biological marker outcomes were used as predictors of response, to understand mechanisms of TMS, and as a surrogate of safety.

CONCLUSIONS

Functional magnetic resonance imaging, single-photon emission computed tomography, positron emission tomography, magnetic resonance spectroscopy, cortical excitability, and brain-derived neurotrophic factor consistently showed positive results. Brain-derived neurotrophic factor was the best predictor of patients' likeliness to respond. These initial results are promising; however, all studies investigating BMs are small, used heterogeneous samples, and did not take into account confounders such as age, sex, or family history. Based on our findings, we recommend further studies to validate BMs in noninvasive brain stimulation trials in MDD.

Circuit dynamics of adaptive and maladaptive behaviour

The recent development of technologies for investigating specific components of intact biological systems has allowed elucidation of the neural circuitry underlying adaptive and maladaptive behaviours. Investigators are now able to observe and control, with high spatio-temporal resolution, structurally defined intact pathways along which electrical activity flows during and after the performance of complex behaviours. These investigations have revealed that control of projection-specific dynamics is well suited to modulating behavioural patterns that are relevant to a broad range of psychiatric diseases. Structural dynamics principles have emerged to provide diverse, unexpected and causal insights into the operation of intact and diseased nervous systems, linking form and function in the brain.

Chiropractic management using a brain-based model of care for a 15-year-old adolescent boy with migraine headaches and behavioral and learning difficulties: a case report

OBJECTIVE

The purpose of this report is to describe chiropractic management, using a brain-based model of care, of a teen who had migraine headaches and several social and learning difficulties.

CLINICAL FEATURES

A 15-year-old adolescent boy with a chronic history of migraines and more than 10 years of learning and behavioral difficulties, including attention-deficit/hyperactivity disorder, obsessive compulsive disorder, and Tourette syndrome, presented for chiropractic care.

INTERVENTION AND OUTCOME

The patient received spinal manipulation and was given home physical coordination activities that were contralateral to the side of the involved basal ganglia and ipsilateral to the involved cerebellum, along with interactive metronome training. Quantitative changes were noted in neurological soft signs, tests of variables of attention Conners' Parent Rating Scale, the California Achievement Test, grade point, and reduction of medications. The patient reported qualitative improvements in tics, attention, reading, vision, health, relationships with his peers and his family, and self-esteem.

CONCLUSION

The patient with migraine headaches and learning difficulties responded well to the course of chiropractic care. This study suggests that there may be value in a brain-based model of care in the chiropractic management of conditions that are beyond musculoskeletal in nature.

Novel directions for psychiatric diagnosis: from psychopathology to motor function to monitoring technology

In the light of the recent publication of the DSM-5, there is renewed debate about the relative merit of categorical diagnosis, as laid down in Diagnostic and Statistical Manual of Mental Disorders (DSM) and International Classification of Diseases (ICD) diagnostic manuals. Issues such as validity, usefulness and acceptability of the diagnoses in this manual are increasingly debated. Several alternative possibilities have been suggested including: (i) the introduction of truly cross-cutting dimensional measures, that would facilitate dynamic multidimensional formulations of psychopathology, (ii) the Research Domain Criteria, that may facilitate biological research but move away from clinical symptoms, (iii) a system of personalized diagnosis based on psychopathology as a network of symptoms and contexts, and (iv) enhanced focus on motor alterations, other than catatonia, as a possible additional informative dimension of diagnosis in psychiatry, particularly as a possible marker of underlying neurodevelopmental alterations. We suggest that novel systems of diagnosis are likely to rely more on continuous monitoring of diagnostically relevant information in daily life, complementing retrospective symptom criteria in DSM and ICD. Patients and their families are likely to benefit from these projects, as novel models of diagnosis based on daily life information may be linked more strongly to treatment needs and prognosis.

Spatial and temporal mapping of de novo mutations in schizophrenia to a fetal prefrontal cortical network

Genes disrupted in schizophrenia may be revealed by de novo mutations in affected persons from otherwise healthy families. Furthermore, during normal brain development, genes are expressed in patterns specific to developmental stage and neuroanatomical structure. We identified de novo mutations in persons with schizophrenia and then mapped the responsible genes onto transcriptome profiles of normal human brain tissues from age 13 weeks gestation to adulthood. In the dorsolateral and ventrolateral prefrontal cortex during fetal development, genes harboring damaging de novo mutations in schizophrenia formed a network significantly enriched for transcriptional coexpression and protein interaction. The 50 genes in the network function in neuronal migration, synaptic transmission, signaling, transcriptional regulation, and transport. These results suggest that disruptions of fetal prefrontal cortical neurogenesis are critical to the pathophysiology of schizophrenia. These results also support the feasibility of integrating genomic and transcriptome analyses to map critical neurodevelopmental processes in time and space in the brain.

Genetics of Childhood Onset Schizophrenia

Schizophrenia is a heritable disorder. The genetic architecture of schizophrenia is complex and heterogeneous. This article discusses genetic studies of childhood-onset schizophrenia (COS) and compares findings in familial aggregation, common allele, and rare allele studies of COS with those for adult-onset schizophrenia (AOS). COS seems to be a rare variant of AOS with greater familial aggregation of schizophrenia spectrum disorders and higher occurrence of rare allelic variants. The usefulness of genetic screening for diagnosis and individualized treatment is limited; however, identifying common pathways through which multiple genes adversely affect neural systems offers great promise toward developing novel pharmacologic interventions.

Normative preconditions for the assessment of mental disorder

The debate about the relevance of values for the concept of a mental disorder has quite a long history. In the light of newer insights into neuroscience and molecular biology it is necessary to re-evaluate this issue. Since the medical model in previous decades was more of a confession rather than evidence based, one could assume that it is—due to scientific progress—currently becoming the one and only bedrock of psychiatry. This article argues that this would be a misapprehension of the normative constitution of the assessment of human behavior. The claim made here is twofold: First, whether something is a mental disease can only be determined on the mental level. This is so because we can only call behavior deviant by comparing it to non-deviant behavior, i.e., by using norms regarding behavior. Second, from this it follows that psychiatric disorders cannot be completely reduced to the physical level even if mental processes and states as such might be completely reducible to brain functions.

The 'missing heritability' of common disorders: should health researchers care?

This article critiques the "missing heritability" position, which calls for greater efforts and funding to identify the genetic architecture of common disorders, even if this endeavor has yet to translate into tangible prevention, diagnosis, or treatment interventions. Supporters of the position contend that genetic variants "for" common disorders, which they argue must exist based on heritability estimates (hence their "missing heritability" position), have not been found because the current state of science and technology is not adequate to the task, yet they insist that this search warrants significant societal investments. We argue, instead, that these variants have not been found because they do not exist. The thrust of the problem with the "missing heritability" position, we propose, lies in its proponents' use of faulty concepts and research methods, including reliance on twin studies, plagued with environmental confounds; on the concept of heritability, a breeding statistic and not a measure of the importance of genetic influences on phenotypes; and on the belief that genetic variations are relevant to understanding, preventing, or treating common disorders, a belief that we argue is false. We elaborate on these problems, discuss their public health implications, and suggest future directions for a critical analysis of human genetics.

Cortical-amygdalar circuit dysfunction in a genetic mouse model of serotonin deficiency

Although the majority of first-line antidepressants increase brain serotonin and rare polymorphisms in tryptophan hydroxlase-2 (Tph2), the rate-limiting enzyme in the brain serotonin synthesis pathway, have been identified in cohorts of subjects with major depressive disorder, the circuit level alterations that results from serotonergic hypofunction remain poorly understood. Here we use chronic multicircuit neurophysiological recordings to characterize functional interactions across cortical and limbic circuits in mice engineered to express a human loss-of-function depression allele Tph2-(R441H) [Tph2 knockin (Tph2KI)]. Our results show that Tph2KI mice exhibit increased intra-network synchrony within medial prefrontal cortex (mPFC) and basal amygdala (AMY) and increased inter-network synchrony between these two brain networks. Moreover, we demonstrate that chronic treatment with fluoxetine reverses several of the circuit alterations observed within Tph2KI mice. Together, our findings establish a functional link between functional hyposerotonergia and altered mPFC-AMY network dynamics.

Cortical control of affective networks

Transcranial magnetic stimulation and deep brain stimulation have emerged as therapeutic modalities for treatment refractory depression; however, little remains known regarding the circuitry that mediates the therapeutic effect of these approaches. Here we show that direct optogenetic stimulation of prefrontal cortex (PFC) descending projection neurons in mice engineered to express Chr2 in layer V pyramidal neurons (Thy1-Chr2 mice) models an antidepressant-like effect in mice subjected to a forced-swim test. Furthermore, we show that this PFC stimulation induces a long-lasting suppression of anxiety-like behavior (but not conditioned social avoidance) in socially stressed Thy1-Chr2 mice: an effect that is observed >10 d after the last stimulation. Finally, we use optogenetic stimulation and multicircuit recording techniques concurrently in Thy1-Chr2 mice to demonstrate that activation of cortical projection neurons entrains neural oscillatory activity and drives synchrony across limbic brain areas that regulate affect. Importantly, these neural oscillatory changes directly correlate with the temporally precise activation and suppression of limbic unit activity. Together, our findings show that the direct activation of cortical projection systems is sufficient to modulate activity across networks underlying affective regulation. They also suggest that optogenetic stimulation of cortical projection systems may serve as a viable therapeutic strategy for treating affective disorders.

Metastatic breast cancer in patients with schizophrenia

Breast cancer is a major health problem worldwide. The median survival duration for patients with metastatic breast cancer is two to three years. Approximately 1% of populations worldwide have schizophrenia. The manner in which schizophrenic patients fare when diagnosed with metastatic breast carcinoma (MBC) was evaluated. We queried the National Department of Veterans Affairs (DVA) datasets using computer codes for a pre-existing diagnosis of schizophrenia and a later diagnosis of breast carcinoma. Chart-based data concerning the identified subjects were then requested. Previously determined inclusion and exclusion criteria were applied to select evaluable patients from the medical records, prior to extracting demographic details and data concerning the treatment course in each subject. Ten patients had distant metastases at initial diagnosis, while seven developed MBC following prior curative-intent treatment. Two patients refused therapy. Ten did not comply with recommended management. Five harmed or threatened physicians, other caregivers or themselves. Schizophrenic patients with MBC often fail to understand the nature of their illnesses. Often they do not accept palliative treatment, while a number of them do not comply with therapy, once initiated. They often exhibit behaviors that are detrimental to themselves or others. Formal psychiatric consultation is therefore necessary in patients. Several detrimental behaviors may be predicted reliably by history alone.

Single neuron capture and axonal development in three-dimensional microscale hydrogels

Autapse is an unusual type of synapse generated by a neuron on itself. The ability to monitor axonal growth of single neurons and autapse formation in three-dimensions (3D) may provide fundamental information relating to many cellular processes, such as axonal development, synaptic plasticity and neural signal transmission. However, monitoring such growth is technically challenging due to the requirement for precise capture and long-term analysis of single neurons in 3D. Herein, we present a simple two-step photolithography method to efficiently capture single cells in microscale gelatin methacrylate hydrogel rings. We applied this method to capture and culture single neurons. The results demonstrated that neural axons grew and consequently formed axonal circles, indicating that our method could be an enabling tool to analyze axonal development and autapse formation. This method holds great potential for impact in multiple areas, such as neuroscience, cancer biology, and stem cell biology.

Increasing power for voxel-wise genome-wide association studies: the random field theory, least square kernel machines and fast permutation procedures

Imaging traits are thought to have more direct links to genetic variation than diagnostic measures based on cognitive or clinical assessments and provide a powerful substrate to examine the influence of genetics on human brains. Although imaging genetics has attracted growing attention and interest, most brain-wide genome-wide association studies focus on voxel-wise single-locus approaches, without taking advantage of the spatial information in images or combining the effect of multiple genetic variants. In this paper we present a fast implementation of voxel- and cluster-wise inferences based on the random field theory to fully use the spatial information in images. The approach is combined with a multi-locus model based on least square kernel machines to associate the joint effect of several single nucleotide polymorphisms (SNP) with imaging traits. A fast permutation procedure is also proposed which significantly reduces the number of permutations needed relative to the standard empirical method and provides accurate small p-value estimates based on parametric tail approximation. We explored the relation between 448,294 single nucleotide polymorphisms and 18,043 genes in 31,662 voxels of the entire brain across 740 elderly subjects from the Alzheimer's disease neuroimaging initiative (ADNI). Structural MRI scans were analyzed using tensor-based morphometry (TBM) to compute 3D maps of regional brain volume differences compared to an average template image based on healthy elderly subjects. We find method to be more sensitive compared with voxel-wise single-locus approaches. A number of genes were identified as having significant associations with volumetric changes. The most associated gene was GRIN2B, which encodes the N-methyl-d-aspartate (NMDA) glutamate receptor NR2B subunit and affects both the parietal and temporal lobes in human brains. Its role in Alzheimer's disease has been widely acknowledged and studied, suggesting the validity of the approach. The various advantages over existing approaches indicate a great potential offered by this novel framework to detect genetic influences on human brains.

Phenotypic overlap in the contribution of individual genes to CNV pathogenicity revealed by cross-species computational analysis of single-gene mutations in humans, mice and zebrafish

Numerous disease syndromes are associated with regions of copy number variation (CNV) in the human genome and, in most cases, the pathogenicity of the CNV is thought to be related to altered dosage of the genes contained within the affected segment. However, establishing the contribution of individual genes to the overall pathogenicity of CNV syndromes is difficult and often relies on the identification of potential candidates through manual searches of the literature and online resources. We describe here the development of a computational framework to comprehensively search phenotypic information from model organisms and single-gene human hereditary disorders, and thus speed the interpretation of the complex phenotypes of CNV disorders. There are currently more than 5000 human genes about which nothing is known phenotypically but for which detailed phenotypic information for the mouse and/or zebrafish orthologs is available. Here, we present an ontology-based approach to identify similarities between human disease manifestations and the mutational phenotypes in characterized model organism genes; this approach can therefore be used even in cases where there is little or no information about the function of the human genes. We applied this algorithm to detect candidate genes for 27 recurrent CNV disorders and identified 802 gene-phenotype associations, approximately half of which involved genes that were previously reported to be associated with individual phenotypic features and half of which were novel candidates. A total of 431 associations were made solely on the basis of model organism phenotype data. Additionally, we observed a striking, statistically significant tendency for individual disease phenotypes to be associated with multiple genes located within a single CNV region, a phenomenon that we denote as pheno-clustering. Many of the clusters also display statistically significant similarities in protein function or vicinity within the protein-protein interaction network. Our results provide a basis for understanding previously un-interpretable genotype-phenotype correlations in pathogenic CNVs and for mobilizing the large amount of model organism phenotype data to provide insights into human genetic disorders.

Alzheimer's disease risk gene, GAB2, is associated with regional brain volume differences in 755 young healthy twins

The development of late-onset Alzheimer's disease (LOAD) is under strong genetic control and there is great interest in the genetic variants that confer increased risk. The Alzheimer's disease risk gene, growth factor receptor bound protein 2-associated protein (GAB2), has been shown to provide a 1.27-1.51 increased odds of developing LOAD for rs7101429 major allele carriers, in case-control analysis. GAB2 is expressed across the brain throughout life, and its role in LOAD pathology is well understood. Recent studies have begun to examine the effect of genetic variation in the GAB2 gene on differences in the brain. However, the effect of GAB2 on the young adult brain has yet to be considered. Here we found a significant association between the GAB2 gene and morphological brain differences in 755 young adult twins (469 females) (M = 23.1, SD = 3.1 years), using a gene-based test with principal components regression (PCReg). Detectable differences in brain morphology are therefore associated with variation in the GAB2 gene, even in young adults, long before the typical age of onset of Alzheimer's disease.

Increasing the validity of experimental models for depression

Major depressive disorder (MDD) is a central nervous system disorder characterized by the culmination of profound disturbances in mood and affective regulation. Animal models serve as a powerful tool for investigating the neurobiological mechanisms underlying this disorder; however, little standardization exists across the wide range of available modeling approaches most often employed. This review will illustrate some of the most challenging obstacles faced by investigators attempting to associate depressive-like behaviors in rodents with symptoms expressed in MDD. Furthermore, a novel series of depressive-like criteria based on correlating behavioral endophenotypes, novel in vivo neurophysiological measurements, and molecular/cellular analyses within multiple brain are proposed as a potential solution to overcoming this barrier. Ultimately, linking the neurophysiological and cellular/biochemical actions that contribute to the expression of a defined MDD-like syndrome will dramatically extend the translational value of the most valid animal models of MDD.

Evolutionary molecular medicine

Evolution has long provided a foundation for population genetics, but some major advances in evolutionary biology from the twentieth century that provide foundations for evolutionary medicine are only now being applied in molecular medicine. They include the need for both proximate and evolutionary explanations, kin selection, evolutionary models for cooperation, competition between alleles, co-evolution, and new strategies for tracing phylogenies and identifying signals of selection. Recent advances in genomics are transforming evolutionary biology in ways that create even more opportunities for progress at its interfaces with genetics, medicine, and public health. This article reviews 15 evolutionary principles and their applications in molecular medicine in hopes that readers will use them and related principles to speed the development of evolutionary molecular medicine.

α7-Nicotinic acetylcholine receptor: role in early odor learning preference in mice

Recently, we have shown that mice with decreased expression of α7-nicotinic acetylcholine receptors (α7) in the olfactory bulb were associated with a deficit in odor discrimination compared to wild-type mice. However, it is unknown if mice with decreased α7-receptor expression also show a deficit in early odor learning preference (ELP), an enhanced behavioral response to odors with attractive value observed in rats. In this study, we modified ELP methods performed in rats and implemented similar conditions in mice. From post-natal days 5–18, wild-type mice were stroked simultaneously with an odor presentation (conditioned odor) for 90 s daily. Control mice were only stroked, exposed to odor, or neither. On the day of testing (P21), mice that were stroked in concert with a conditioned odor significantly investigated the conditioned odor compared to a novel odor, as observed similarly in rats. However, mice with a decrease in α7-receptor expression that were stroked during a conditioned odor did not show a behavioral response to that odorant. These results suggest that decreased α7-receptor expression has a role in associative learning, olfactory preference, and/or sensory processing deficits.

Serotonergic transcriptional networks and potential importance to mental health

Transcription regulatory networks governing the genesis, maturation and maintenance of vertebrate brain serotonin (5-HT) neurons determine the level of serotonergic gene expression and signaling throughout an animal's lifespan. Recent studies suggest that alterations in these networks can cause behavioral and physiological pathogenesis in mice. Here, we synthesize findings from vertebrate loss-of-function and gain-of-function studies to build a new model of the transcriptional regulatory networks that specify 5-HT neurons during fetal life, integrate them into CNS circuitry in early postnatal life and maintain them in adulthood. We then describe findings from animal and human genetic studies that support possible alterations in the activity of serotonergic regulatory networks in the etiology of mental illness. We conclude with a discussion of the potential utility of our model, as an experimentally well-defined molecular pathway, to predict and interpret the biological effect of genetic variation that may be discovered in the orthologous human network.

Towards a genuinely medical model for psychiatric nosology

Psychiatric nosology is widely criticized, but solutions are proving elusive. Planned revisions of diagnostic criteria will not resolve heterogeneity, comorbidity, fuzzy boundaries between normal and pathological, and lack of specific biomarkers. Concern about these difficulties reflects a narrow model that assumes most mental disorders should be defined by their etiologies. A more genuinely medical model uses understanding of normal function to categorize pathologies. For instance, understanding the function of a cough guides the search for problems causing it, and decisions about when it is expressed abnormally. Understanding the functions of emotions is a foundation missing from decisions about emotional disorders. The broader medical model used by the rest of medicine also recognizes syndromes defined by failures of functional systems or failures of feedback control. Such medical syndromes are similar to many mental diagnoses in their multiple causes, blurry boundaries, and nonspecific biomarkers. Dissatisfaction with psychiatric nosology may best be alleviated, not by new diagnostic criteria and categories, but by more realistic acknowledgment of the untidy landscape of mental and other medical disorders.

Two patients walk into a clinic...a genomics perspective on the future of schizophrenia

Progress is being made in schizophrenia genomics, suggesting that this complex brain disorder involves rare, moderate to high-risk mutations and the cumulative impact of small genetic effects, coupled with environmental factors. The genetic heterogeneity underlying schizophrenia and the overlap with other neurodevelopmental disorders suggest that it will not continue to be viewed as a single disease. This has radical implications for clinical practice, as diagnosis and treatment will be guided by molecular etiology rather than clinical diagnostic criteria.

The conundrums of understanding genetic risks for autism spectrum disorders

Recent advances in the genetics of autism spectrum disorders (ASDs) are offering new valuable insights into molecular and cellular mechanisms of pathology. At the same time, the emerging data challenge long-standing diagnostic conventions and the notion of phenotypic specificity. This review addresses the particular issues that attend gene discovery in neuropsychiatric and neurodevelopmental disorders and ASDs in particular, summarizes recent findings in human genetics broadly that are driving the reevaluation of the conventional wisdom regarding the allelic architecture of common psychiatric conditions, reviews selected discoveries in ASDs and their relevance to models of pathology, highlights the conceptual and practical issues raised by the observation of a convergence of ASD genetic risks with distinct psychiatric disorders, and considers the important interplay of studies of neurobiology and genetics in clarifying and extending our understanding of social disability syndromes.

Multilocus genetic analysis of brain images

The quest to identify genes that influence disease is now being extended to find genes that affect biological markers of disease, or endophenotypes. Brain images, in particular, provide exquisitely detailed measures of anatomy, function, and connectivity in the living brain, and have identified characteristic features for many neurological and psychiatric disorders. The emerging field of imaging genomics is discovering important genetic variants associated with brain structure and function, which in turn influence disease risk and fundamental cognitive processes. Statistical approaches for testing genetic associations are not straightforward to apply to brain images because the data in brain images is spatially complex and generally high dimensional. Neuroimaging phenotypes typically include 3D maps across many points in the brain, fiber tracts, shape-based analyses, and connectivity matrices, or networks. These complex data types require new methods for data reduction and joint consideration of the image and the genome. Image-wide, genome-wide searches are now feasible, but they can be greatly empowered by sparse regression or hierarchical clustering methods that isolate promising features, boosting statistical power. Here we review the evolution of statistical approaches to assess genetic influences on the brain. We outline the current state of multivariate statistics in imaging genomics, and future directions, including meta-analysis. We emphasize the power of novel multivariate approaches to discover reliable genetic influences with small effect sizes.

From genes to therapeutic targets for psychiatric disorders - what to expect?

Neuropsychiatric disorders as schizophrenia, autism and mood disorders represent one of the leading causes of disability. The cost of bringing a drug to the market is increasing and becoming more risky. Pharmaceutical investments in neuroscience are decreasing. At the same time we are facing an unprecedented rate of discovery in human genetics. Genes predisposing for common diseases including psychiatric disorders are being identified. The knowledge derived from the identification of genes relevant for psychiatric disorders holds the promise of providing truly innovative therapeutic interventions. The process of approving new psychiatric drugs, is however complex, lengthy and requires a well orchestrated and funded effort of multiple disciplines. In this article a brief overview of the key learning obtained from the conduction genome-wide association studies, thus far, is given in an attempt to provide a realistic view on the potential contribution of human genetics to drug discovery in psychiatry.

Translational epidemiology in psychiatry: linking population to clinical and basic sciences

Translational research generally refers to the application of knowledge generated by advances in basic sciences research translated into new approaches for diagnosis, prevention, and treatment of disease. This direction is called bench-to-bedside. Psychiatry has similarly emphasized the basic sciences as the starting point of translational research. This article introduces the term translational epidemiology for psychiatry research as a bidirectional concept in which the knowledge generated from the bedside or the population can also be translated to the benches of laboratory science. Epidemiologic studies are primarily observational but can generate representative samples, novel designs, and hypotheses that can be translated into more tractable experimental approaches in the clinical and basic sciences. This bedside-to-bench concept has not been explicated in psychiatry, although there are an increasing number of examples in the research literature. This article describes selected epidemiologic designs, providing examples and opportunities for translational research from community surveys and prospective, birth cohort, and family-based designs. Rapid developments in informatics, emphases on large sample collection for genetic and biomarker studies, and interest in personalized medicine--which requires information on relative and absolute risk factors--make this topic timely. The approach described has implications for providing fresh metaphors to communicate complex issues in interdisciplinary collaborations and for training in epidemiology and other sciences in psychiatry.

Neural correlates of local contextual processing deficits in schizophrenic patients

Deficits in processing contextual information are one of the main features of cognitive dysfunction in schizophrenia, but the neurophysiologic substrate underlying this dysfunction is poorly understood. We used ERPs to investigate local contextual processing in schizophrenic patients. Local context was defined as the occurrence of a short predictive series of stimuli occurring before delivery of a target event. Response times of predicted targets were faster in controls compared to patients. Schizophrenia patients failed to generate the P3b latency shift between predicted and random targets that was observed in controls and demonstrated a prominent reduction of the peak of an early latency context dependent positivity. The current study provides evidence of contextual processing deficits in schizophrenia patients by demonstrating alteration in the behavioral and neural correlates of local contextual processing.

Prospects for neurodegenerative and psychiatric disorder drug discovery

The discovery of CNS-active drugs has, to a major extent, resulted from clinical serendipity. Once targets for such compounds were identified, conventional mechanism-based approaches were used to identify new chemical entities for the treatment of neurological and psychiatric disorders. Most of these have, however, failed to display any greater efficacy than existing psychotherapeutics and may, in fact, be less efficacious because of side effect liabilities. Among the reasons for this lack of success in drug discovery include a lack of fundamental knowledge regarding the causes of CNS disorders, the absence of biomarkers for diagnosing and monitoring these conditions, a paucity of animal models that are congruent with the human disease state and the increasing likelihood that CNS conditions are multifactorial in their etiology. These challenges force the inclusion of a Phase IIa proof of concept trial as a component of the drug discovery program. Unlike other therapeutic areas, serendipity is a major factor in the CNS translational medicine interface requiring a close collaboration between preclinical and clinical scientists trained to appreciate unusual behavioral phenotypes. When combined with conventional target-based drug discovery technologies, this increases the likelihood of identifying truly novel drugs for the treatment of CNS disorders.

Psychiatric molecular genetics and the ethics of social promises

A recent literature review of commentaries and 'state of the art' articles from researchers in psychiatric genetics (PMG) offers a consensus about progress in the science of genetics, disappointments in the discovery of new and effective treatments, and a general optimism about the future of the field. I argue that optimism for the field of psychiatric molecular genetics (PMG) is overwrought, and consider progress in the field in reference to a sample estimate of US National Institute of Mental Health funding for this paradigm for the years 2008 and 2009. I conclude that the amounts of financial investment in PMG is questionable from an ethical perspective, given other research and clinical needs in the USA.

Gamma synchrony: towards a translational biomarker for the treatment-resistant symptoms of schizophrenia

The lack of efficacy for antipsychotics with respect to negative symptoms and cognitive deficits is a significant obstacle for the treatment of schizophrenia. Developing new drugs to target these symptoms requires appropriate neural biomarkers that can be investigated in model organisms, be used to track treatment response, and provide insight into pathophysiological disease mechanisms. A growing body of evidence indicates that neural oscillations in the gamma frequency range (30-80 Hz) are disturbed in schizophrenia. Gamma synchrony has been shown to mediate a host of sensory and cognitive functions, including perceptual encoding, selective attention, salience, and working memory - neurocognitive processes that are dysfunctional in schizophrenia and largely refractory to treatment. This review summarizes the current state of clinical literature with respect to gamma-band responses (GBRs) in schizophrenia, focusing on resting and auditory paradigms. Next, preclinical studies of schizophrenia that have investigated gamma-band activity are reviewed to gain insight into neural mechanisms associated with these deficits. We conclude that abnormalities in gamma synchrony are ubiquitous in schizophrenia and likely reflect an elevation in baseline cortical gamma synchrony ('noise') coupled with reduced stimulus-evoked GBRs ('signal'). Such a model likely reflects hippocampal and cortical dysfunction, as well as reduced glutamatergic signaling with downstream GABAergic deficits, but is probably less influenced by dopaminergic abnormalities implicated in schizophrenia. Finally, we propose that analogous signal-to-noise deficits in the flow of cortical information in preclinical models are useful targets for the development of new drugs that target the treatment-resistant symptoms of schizophrenia.

Challenges and opportunities in mining neuroscience data

Understanding the brain requires a broad range of approaches and methods from the domains of biology, psychology, chemistry, physics, and mathematics. The fundamental challenge is to decipher the "neural choreography" associated with complex behaviors and functions, including thoughts, memories, actions, and emotions. This demands the acquisition and integration of vast amounts of data of many types, at multiple scales in time and in space. Here we discuss the need for neuroinformatics approaches to accelerate progress, using several illustrative examples. The nascent field of "connectomics" aims to comprehensively describe neuronal connectivity at either a macroscopic level (in long-distance pathways for the entire brain) or a microscopic level (among axons, dendrites, and synapses in a small brain region). The Neuroscience Information Framework (NIF) encompasses all of neuroscience and facilitates the integration of existing knowledge and databases of many types. These examples illustrate the opportunities and challenges of data mining across multiple tiers of neuroscience information and underscore the need for cultural and infrastructure changes if neuroinformatics is to fulfill its potential to advance our understanding of the brain.