Synaptic Mechanisms of Psychotic Disorders

2017 ◽  
Author(s):  
Seth G. N. Grant
Keyword(s):  
Mental Illness ◽  
Psychotic Disorders ◽  
Common Mental Disorders ◽  
Cell Activity ◽  
Molecular Machines ◽  
Synaptic Proteins ◽  
Brain Diseases ◽  
Molecular Anatomy ◽  
The Brain ◽  
Synaptic Mechanisms

Synapses are the hallmark of the neuroanatomy of the brain. The million billion synapses of the human brain connect the nerve cells into the networks that underpin all behavior. The molecular anatomy of synapses is also remarkably complicated with ~2000 proteins in the synapse proteome. The proteins are physically organized into a hierarchy of molecular machines that control synapse biology. These proteins integrate and compute the information in patterns of nerve cell activity. Mutations in hundreds of genes that encode synaptic proteins contribute to over one hundred brain diseases, including common mental disorders. The synapse proteome is of fundamental importance to mental illness.

scholarly journals ON MENTAL ILLNESS AND BROKEN BRAINS

Think ◽  
2021 ◽  
Vol 20 (58) ◽  
pp. 103-112
Author(s):  
Anneli Jefferson
Keyword(s):  
Mental Illness ◽  
Mental Disorders ◽  
Brain Cancer ◽  
World View ◽  
Brain Diseases ◽  
Brain Disorders ◽  
Empirical Question ◽  
The Brain

ABSTRACTWe often hear that certain mental disorders are disorders of the brain, but it is not clear what this claim amounts to. Does it mean that they are like classic brain diseases such as brain cancer? I argue that this is not the case for most mental disorders. Neither does the claim that all mental disorders are brain disorders follow from a materialist world-view. The only plausible way of understanding mental disorders as brain disorders is a fairly modest one, where we label brain differences we find in mental illness as pathological based on their link to mental dysfunction. How many mental disorders will turn out to be brain disorders on this understanding is an empirical question.

scholarly journals Hidden proteome of synaptic vesicles in the mammalian brain

2020 ◽  
Vol 117 (52) ◽  
pp. 33586-33596
Author(s):  
Zacharie Taoufiq ◽  
Momchil Ninov ◽  
Alejandro Villar-Briones ◽  
Han-Ying Wang ◽  
Toshio Sasaki ◽  
...  
Keyword(s):  
Synaptic Vesicles ◽  
Copy Number ◽  
Synaptic Proteins ◽  
Brain Diseases ◽  
Mammalian Brain ◽  
Functional Studies ◽  
Health And Disease ◽  
Vesicular Transporters ◽  
Average Copy ◽  
The Brain

Current proteomic studies clarified canonical synaptic proteins that are common to many types of synapses. However, proteins of diversified functions in a subset of synapses are largely hidden because of their low abundance or structural similarities to abundant proteins. To overcome this limitation, we have developed an “ultra-definition” (UD) subcellular proteomic workflow. Using purified synaptic vesicle (SV) fraction from rat brain, we identified 1,466 proteins, three times more than reported previously. This refined proteome includes all canonical SV proteins, as well as numerous proteins of low abundance, many of which were hitherto undetected. Comparison of UD quantifications between SV and synaptosomal fractions has enabled us to distinguish SV-resident proteins from potential SV-visitor proteins. We found 134 SV residents, of which 86 are present in an average copy number per SV of less than one, including vesicular transporters of nonubiquitous neurotransmitters in the brain. We provide a fully annotated resource of all categorized SV-resident and potential SV-visitor proteins, which can be utilized to drive novel functional studies, as we characterized here Aak1 as a regulator of synaptic transmission. Moreover, proteins in the SV fraction are associated with more than 200 distinct brain diseases. Remarkably, a majority of these proteins was found in the low-abundance proteome range, highlighting its pathological significance. Our deep SV proteome will provide a fundamental resource for a variety of future investigations on the function of synapses in health and disease.

A new method to predict anomaly in brain network based on graph deep learning

2020 ◽  
Vol 31 (6) ◽  
pp. 681-689
Author(s):  
Jalal Mirakhorli ◽  
Hamidreza Amindavar ◽  
Mojgan Mirakhorli
Keyword(s):  
Deep Learning ◽  
Large Scale ◽  
Brain Plasticity ◽  
Brain Network ◽  
High Order ◽  
Brain Diseases ◽  
Simultaneous Occurrence ◽  
Generative Adversarial Network ◽  
The Brain ◽  
Brain Connections

AbstractFunctional magnetic resonance imaging a neuroimaging technique which is used in brain disorders and dysfunction studies, has been improved in recent years by mapping the topology of the brain connections, named connectopic mapping. Based on the fact that healthy and unhealthy brain regions and functions differ slightly, studying the complex topology of the functional and structural networks in the human brain is too complicated considering the growth of evaluation measures. One of the applications of irregular graph deep learning is to analyze the human cognitive functions related to the gene expression and related distributed spatial patterns. Since a variety of brain solutions can be dynamically held in the neuronal networks of the brain with different activity patterns and functional connectivity, both node-centric and graph-centric tasks are involved in this application. In this study, we used an individual generative model and high order graph analysis for the region of interest recognition areas of the brain with abnormal connection during performing certain tasks and resting-state or decompose irregular observations. Accordingly, a high order framework of Variational Graph Autoencoder with a Gaussian distributer was proposed in the paper to analyze the functional data in brain imaging studies in which Generative Adversarial Network is employed for optimizing the latent space in the process of learning strong non-rigid graphs among large scale data. Furthermore, the possible modes of correlations were distinguished in abnormal brain connections. Our goal was to find the degree of correlation between the affected regions and their simultaneous occurrence over time. We can take advantage of this to diagnose brain diseases or show the ability of the nervous system to modify brain topology at all angles and brain plasticity according to input stimuli. In this study, we particularly focused on Alzheimer’s disease.

scholarly journals Genomic Mosaicism Formed by Somatic Variation in the Aging and Diseased Brain

Genes ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 1071
Author(s):  
Isabel Costantino ◽  
Juliet Nicodemus ◽  
Jerold Chun
Keyword(s):  
Dna Sequence ◽  
Technology Development ◽  
Copy Number Variations ◽  
Brain Cell ◽  
Brain Diseases ◽  
Multiple Forms ◽  
Somatic Variation ◽  
Dna Content Variation ◽  
Effects Of Aging ◽  
The Brain

Over the past 20 years, analyses of single brain cell genomes have revealed that the brain is composed of cells with myriad distinct genomes: the brain is a genomic mosaic, generated by a host of DNA sequence-altering processes that occur somatically and do not affect the germline. As such, these sequence changes are not heritable. Some processes appear to occur during neurogenesis, when cells are mitotic, whereas others may also function in post-mitotic cells. Here, we review multiple forms of DNA sequence alterations that have now been documented: aneuploidies and aneusomies, smaller copy number variations (CNVs), somatic repeat expansions, retrotransposons, genomic cDNAs (gencDNAs) associated with somatic gene recombination (SGR), and single nucleotide variations (SNVs). A catch-all term of DNA content variation (DCV) has also been used to describe the overall phenomenon, which can include multiple forms within a single cell’s genome. A requisite step in the analyses of genomic mosaicism is ongoing technology development, which is also discussed. Genomic mosaicism alters one of the most stable biological molecules, DNA, which may have many repercussions, ranging from normal functions including effects of aging, to creating dysfunction that occurs in neurodegenerative and other brain diseases, most of which show sporadic presentation, unlinked to causal, heritable genes.

scholarly journals The brain timewise: how timing shapes and supports brain function

2015 ◽  
Vol 370 (1668) ◽  
pp. 20140170 ◽  
Author(s):  
Riitta Hari ◽  
Lauri Parkkonen
Keyword(s):  
Human Brain ◽  
Brain Imaging ◽  
Brain Function ◽  
Temporal Dynamics ◽  
Generative Models ◽  
Network Activity ◽  
Brain Diseases ◽  
Specific Information ◽  
Non Invasive ◽  
The Brain

We discuss the importance of timing in brain function: how temporal dynamics of the world has left its traces in the brain during evolution and how we can monitor the dynamics of the human brain with non-invasive measurements. Accurate timing is important for the interplay of neurons, neuronal circuitries, brain areas and human individuals. In the human brain, multiple temporal integration windows are hierarchically organized, with temporal scales ranging from microseconds to tens and hundreds of milliseconds for perceptual, motor and cognitive functions, and up to minutes, hours and even months for hormonal and mood changes. Accurate timing is impaired in several brain diseases. From the current repertoire of non-invasive brain imaging methods, only magnetoencephalography (MEG) and scalp electroencephalography (EEG) provide millisecond time-resolution; our focus in this paper is on MEG. Since the introduction of high-density whole-scalp MEG/EEG coverage in the 1990s, the instrumentation has not changed drastically; yet, novel data analyses are advancing the field rapidly by shifting the focus from the mere pinpointing of activity hotspots to seeking stimulus- or task-specific information and to characterizing functional networks. During the next decades, we can expect increased spatial resolution and accuracy of the time-resolved brain imaging and better understanding of brain function, especially its temporal constraints, with the development of novel instrumentation and finer-grained, physiologically inspired generative models of local and network activity. Merging both spatial and temporal information with increasing accuracy and carrying out recordings in naturalistic conditions, including social interaction, will bring much new information about human brain function.

GROUP 6 year outcome data in relation to antipsychotic medication

2016 ◽  
Vol 33 (S1) ◽  
pp. S50-S50
Author(s):  
W. Cahn ◽  
Keyword(s):  
Metabolic Syndrome ◽  
Cohort Study ◽  
Psychotic Disorders ◽  
Medication Use ◽  
Mood Stabilizer ◽  
Outcome Data ◽  
Longitudinal Cohort Study ◽  
Longitudinal Cohort ◽  
The Brain ◽  
Over Time

ObjectiveGenetic risk and outcome of psychoses (GROUP) is a 6 year longitudinal cohort study that focus on gene–environment vulnerability and resilience in patients with psychotic disorders, their unaffected family members and non-related controls. Its main aim is to elucidate etiological and pathogenetic factors that influence the onset and course of psychotic disorders. In this substudy, we will examine medication use over time, its relation with (the change in) metabolic syndrome status and effects on the brain.MethodsA consortium of four university psychiatric centers and their affiliated mental health care institutions, conducted the GROUP study. At baseline, 1120 patients, 1057 siblings, 919 parents and 590 healthy controls were included. After inclusion, participants, except parents, were evaluated again after three and six years of follow-up. Extensive assessment of genetic factors, environmental factors, medication use, metabolic parameters and outcome were performed. Moreover, brain imaging was performed in a subset of participants, using a 1.5 Tesla MRI scanner.ResultsAt baseline 65% of patients used atypical antipsychotics, 16% used conventional antipsychotics and 19% used clozapine. Siblings and controls used no antipsychotics. Forty-three percent of patients, 21.3% of siblings and 9.1% of controls used antidepressants; 43.9% of patients, 2.1% of siblings and none of the controls used a mood stabilizer. We are currently analyzing the medication data over time in relation to (change in) metabolic syndrome status and the effects on the brain.ConclusionGROUP is a longitudinal cohort study in patients with psychotic disorders, their healthy siblings and controls without psychosis. This naturalistic substudy examines medication use, its association with (change of) metabolic status and effects on the brain in subjects with (high risk of) psychosis.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Learning disability and the Scottish Mental Health Act

2017 ◽  
Vol 11 (2) ◽  
pp. 74-82
Author(s):  
Heather Welsh ◽  
Gary Morrison
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Learning Disabilities ◽  
Mental Disorder ◽  
Learning Disability ◽  
Psychotic Disorders ◽  
Content Type ◽  
Mental Health Legislation ◽  
Scottish Government ◽  
Health Legislation

Purpose The purpose of this paper is to investigate the use of the Mental Health (Care and Treatment) (Scotland) Act 2003 for people with learning disabilities in Scotland, in the context of the recent commitment by the Scottish Government to review the place of learning disability (LD) within the Act. Design/methodology/approach All current compulsory treatment orders (CTO) including LD as a type of mental disorder were identified and reviewed. Data was collected on duration and type of detention (hospital or community based) for all orders. For those with additional mental illness and/or personality disorder, diagnoses were recorded. For those with LD only, symptoms, severity of LD and treatment were recorded. Findings In total, 11 per cent of CTOs included LD as a type of mental disorder. The majority of these also included mental illness. The duration of detention for people with LD only was almost double that for those without LD. A variety of mental illness diagnoses were represented, psychotic disorders being the most common (54 per cent). Treatment was broad and multidisciplinary. In all, 87 per cent of people with LD only were prescribed psychotropic medication authorised by CTO. Originality/value There has been limited research on the use of mental health legislation for people with learning disabilities. This project aids understanding of current practice and will be of interest to readers both in Scotland and further afield. It will inform the review of LD as a type of mental disorder under Scottish mental health law, including consideration of the need for specific legislation.

scholarly journals Transient Receptor Potential Vanilloid in the Brain Gliovascular Unit: Prospective Targets in Therapy

Pharmaceutics ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 334
Author(s):  
Huilong Luo ◽  
Xavier Declèves ◽  
Salvatore Cisternino
Keyword(s):  
Transient Receptor Potential ◽  
Receptor Potential ◽  
Brain Diseases ◽  
Transient Receptor Potential Vanilloid ◽  
Main Role ◽  
Trpv Channels ◽  
Gliovascular Unit ◽  
Transient Receptor ◽  
The Brain

The gliovascular unit (GVU) is composed of the brain microvascular endothelial cells forming blood–brain barrier and the neighboring surrounding “mural” cells (e.g., pericytes) and astrocytes. Modulation of the GVU/BBB features could be observed in a variety of vascular, immunologic, neuro-psychiatric diseases, and cancers, which can disrupt the brain homeostasis. Ca2+ dynamics have been regarded as a major factor in determining BBB/GVU properties, and previous studies have demonstrated the role of transient receptor potential vanilloid (TRPV) channels in modulating Ca2+ and BBB/GVU properties. The physiological role of thermosensitive TRPV channels in the BBB/GVU, as well as their possible therapeutic potential as targets in treating brain diseases via preserving the BBB are reviewed. TRPV2 and TRPV4 are the most abundant isoforms in the human BBB, and TRPV2 was evidenced to play a main role in regulating human BBB integrity. Interspecies differences in TRPV2 and TRPV4 BBB expression complicate further preclinical validation. More studies are still needed to better establish the physiopathological TRPV roles such as in astrocytes, vascular smooth muscle cells, and pericytes. The effect of the chronic TRPV modulation should also deserve further studies to evaluate their benefit and innocuity in vivo.

Striatal dopamine mediates hallucination-like perception in mice

Science ◽  
2021 ◽  
Vol 372 (6537) ◽  
pp. eabf4740
Author(s):  
K. Schmack ◽  
M. Bosc ◽  
T. Ott ◽  
J. F. Sturgill ◽  
A. Kepecs
Keyword(s):  
Psychotic Disorders ◽  
Neural Circuit ◽  
Dopamine Neurons ◽  
Striatal Dopamine ◽  
Model Organisms ◽  
High Confidence ◽  
Optogenetic Stimulation ◽  
The Brain ◽  
Central Symptom ◽  
Stimulation Of

Hallucinations, a central symptom of psychotic disorders, are attributed to excessive dopamine in the brain. However, the neural circuit mechanisms by which dopamine produces hallucinations remain elusive, largely because hallucinations have been challenging to study in model organisms. We developed a task to quantify hallucination-like perception in mice. Hallucination-like percepts, defined as high-confidence false detections, increased after hallucination-related manipulations in mice and correlated with self-reported hallucinations in humans. Hallucination-like percepts were preceded by elevated striatal dopamine levels, could be induced by optogenetic stimulation of mesostriatal dopamine neurons, and could be reversed by the antipsychotic drug haloperidol. These findings reveal a causal role for dopamine-dependent striatal circuits in hallucination-like perception and open new avenues to develop circuit-based treatments for psychotic disorders.

scholarly journals Associations between common mental disorders and the Mental Illness Needs Index in community settings

2007 ◽  
Vol 191 (2) ◽  
pp. 158-163 ◽  
Author(s):  
David L. Fone ◽  
Frank Dunstan ◽  
Ann John ◽  
Keith Lloyd
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Mental Disorders ◽  
Mental Disorder ◽  
Small Area ◽  
Common Mental Disorders ◽  
Common Mental Disorder ◽  
Service Planning ◽  
Individual Risk ◽  
Community Settings

BackgroundThe relationship between the Mental Illness Needs Index (MINI) and the common mental disorders is not known.AimsTo investigate associations between the small-area MINI score and common mental disorder at individual level.MethodMental health status was measured using the Mental Health Inventory of the Short Form 36 instrument (SF-36). Data from the Caerphilly Health and Social Needs population survey were analysed in multilevel models of 10 653 individuals aged 18–74 years nested within the 2001 UK census geographies of 110 lower super output areas and 33 wards.ResultsThe MINI score was significantly associated with common mental disorder after adjusting for individual risk factors. This association was stronger at the smaller spatial scale of the lower super output area and for individuals who were permanently sick or disabled.ConclusionsThe MINI is potentially useful for small-area needs assessment and service planning for common mental disorder in community settings.

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