2,459 research outputs found
Increased mortality in schizophrenia due to cardiovascular disease - a non-systematic review of epidemiology, possible causes and interventions
Background: Schizophrenia is among the major causes of disability worldwide and the mortality from cardiovascular disease (CVD) is significantly elevated. There is a growing concern that this health challenge is not fully understood and efficiently addressed.
Methods: Non-systematic review using searches in PubMed on relevant topics as well as selection of references based on the authors’ experience from clinical work and research in the field.
Results: In most countries, the standardized mortality rate in schizophrenia is about 2.5, leading to a reduction in life expectancy between 15 and 20 years. A major contributor of the increased mortality is due to CVD, with CVD mortality ranging from 40 to 50% in most studies. Important causal factors are related to lifestyle, including poor diet, lack of physical activity, smoking, and substance abuse. Recent findings suggest that there are overlapping pathophysiology and genetics between schizophrenia and CVD-risk factors, further increasing the liability to CVD in schizophrenia. Many pharmacological agents used for treating psychotic disorders have side effects augmenting CVD risk. Although several CVD-risk factors can be effectively prevented and treated, the provision of somatic health services to people with schizophrenia seems inadequate. Further, there is a sparseness of studies investigating the effects of lifestyle interventions in schizophrenia, and there is little knowledge about effective programs targeting physical health in this population.
Discussion: The risk for CVD and CVD-related deaths in people with schizophrenia is increased, but the underlying mechanisms are not fully known. Coordinated interventions in different health care settings could probably reduce the risk. There is an urgent need to develop and implement effective programs to increase life expectancy in schizophrenia, and we argue that mental health workers should be more involved in this important task
Functional effects of schizophrenia-linked genetic variants on intrinsic single-neuron excitability: A modeling study
Background: Recent genome-wide association studies (GWAS) have identified a
large number of genetic risk factors for schizophrenia (SCZ) featuring ion
channels and calcium transporters. For some of these risk factors, independent
prior investigations have examined the effects of genetic alterations on the
cellular electrical excitability and calcium homeostasis. In the present
proof-of-concept study, we harnessed these experimental results for modeling of
computational properties on layer V cortical pyramidal cell and identify
possible common alterations in behavior across SCZ-related genes.
Methods: We applied a biophysically detailed multi-compartmental model to
study the excitability of a layer V pyramidal cell. We reviewed the literature
on functional genomics for variants of genes associated with SCZ, and used
changes in neuron model parameters to represent the effects of these variants.
Results: We present and apply a framework for examining the effects of subtle
single nucleotide polymorphisms in ion channel and Ca2+ transporter-encoding
genes on neuron excitability. Our analysis indicates that most of the
considered SCZ- related genetic variants affect the spiking behavior and
intracellular calcium dynamics resulting from summation of inputs across the
dendritic tree.
Conclusions: Our results suggest that alteration in the ability of a single
neuron to integrate the inputs and scale its excitability may constitute a
fundamental mechanistic contributor to mental disease, alongside with the
previously proposed deficits in synaptic communication and network behavior
Psychiatric genetics and the structure of psychopathology
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
Bears are simply voles writ large: social structure determines the mechanisms of intrinsic population regulation in mammals
The literature reveals opposing views regarding the importance of intrinsic population regulation in mammals. Different models have been proposed; adding importance to contrasting life histories, body sizes and social interactions. Here we evaluate current theory based on results from two Scandinavian projects studying two ecologically different mammal species with contrasting body sizes and life history traits: the root vole Microtus oeconomus and the brown bear Ursus arctos. We emphasize four inter-linked behavioral aspects—territoriality, dispersal, social inhibition of breeding, and infanticide—that together form a density-dependent syndrome with potentially regulatory effects on population growth. We show that the two species are similar in all four behaviors and thus the overall regulatory syndrome. Females form matrilineal assemblages, female natal dispersal is negatively density dependent and breeding is suppressed in philopatric young females. In both species, male turnover due to extrinsic mortality agents cause infanticide with negative effects on population growth. The sex-biased and density-dependent dispersal patterns promote the formation of matrilineal clusters which, in turn, leads to reproductive suppression with potentially regulatory effects. Hence, we show that intrinsic population regulation interacting with extrinsic mortality agents may occur irrespective of taxon, life history and body size. Our review stresses the significance of a mechanistic approach to understanding population ecology. We also show that experimental model populations are useful to elucidate natural populations of other species with similar social systems. In particular, such experiments should be combined with methodical innovations that may unravel the effects of cryptic intrinsic mechanisms such as infanticid
Patterns of childhood adverse events are associated with clinical characteristics of bipolar disorder
Background
Previous studies in bipolar disorder investigating childhood trauma and clinical presentations of the illness have mainly focused on physical and sexual abuse. Our aim was to explore further the relationship between childhood trauma and disease characteristics in bipolar disorder to determine which clinical characteristics were most strongly associated with childhood trauma total score, as well as subtypes of adverse childhood events, including physical, sexual, emotional abuse and neglect.
Methods
141 Patients with bipolar disorder were consecutively recruited, and disease history and clinical characteristics were assessed. History of childhood abuse was obtained using the Childhood Trauma Questionnaire (CTQ). Statistical methods used were factor analysis, Poisson and linear regression, and generalized additive modeling (GAM).
Results
The factor analysis of CTQ identified three factors: emotional abuse/neglect, sexual abuse and physical abuse. There were significant associations between CTQ total score and earlier onset of illness, reduced level of psychosocial functioning (GAF; Global Assessment of Functioning) and decreased number of hospitalization, which mainly were due to the factor emotional abuse/neglect. Physical abuse was significantly associated with lower GAF scores, and increased number of mood episodes, as well as self-harm. Sexual abuse was significantly associated with increased number of mood episodes. For mood episodes and self-harm the associations were characterized by great variance and fluctuations.
Conclusions
Our results suggest that childhood trauma is associated with a more severe course of bipolar illness. Further, childhood abuse (physical and sexual), as well as emotional abuse and neglect were significantly associated with accelerating staging process of bipolar disorder. By using specific trauma factors (physical abuse, sexual abuse and emotional abuse/neglect) the associations become both more precise, and diverse
Bivariate causal mixture model quantifies polygenic overlap between complex traits beyond genetic correlation.
Accumulating evidence from genome wide association studies (GWAS) suggests an abundance of shared genetic influences among complex human traits and disorders, such as mental disorders. Here we introduce a statistical tool, MiXeR, which quantifies polygenic overlap irrespective of genetic correlation, using GWAS summary statistics. MiXeR results are presented as a Venn diagram of unique and shared polygenic components across traits. At 90% of SNP-heritability explained for each phenotype, MiXeR estimates that 8.3 K variants causally influence schizophrenia and 6.4 K influence bipolar disorder. Among these variants, 6.2 K are shared between the disorders, which have a high genetic correlation. Further, MiXeR uncovers polygenic overlap between schizophrenia and educational attainment. Despite a genetic correlation close to zero, the phenotypes share 8.3 K causal variants, while 2.5 K additional variants influence only educational attainment. By considering the polygenicity, discoverability and heritability of complex phenotypes, MiXeR analysis may improve our understanding of cross-trait genetic architectures
A stepwise neuron model fitting procedure designed for recordings with high spatial resolution : Application to layer 5 pyramidal cells
© 2017 The Author(s). Published by Elsevier B. V. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.Background Recent progress in electrophysiological and optical methods for neuronal recordings provides vast amounts of high-resolution data. In parallel, the development of computer technology has allowed simulation of ever-larger neuronal circuits. A challenge in taking advantage of these developments is the construction of single-cell and network models in a way that faithfully reproduces neuronal biophysics with subcellular level of details while keeping the simulation costs at an acceptable level. New method In this work, we develop and apply an automated, stepwise method for fitting a neuron model to data with fine spatial resolution, such as that achievable with voltage sensitive dyes (VSDs) and Ca2+ imaging. Result We apply our method to simulated data from layer 5 pyramidal cells (L5PCs) and construct a model with reduced neuronal morphology. We connect the reduced-morphology neurons into a network and validate against simulated data from a high-resolution L5PC network model. Comparison with existing methods Our approach combines features from several previously applied model-fitting strategies. The reduced-morphology neuron model obtained using our approach reliably reproduces the membrane-potential dynamics across the dendrites as predicted by the full-morphology model. Conclusions The network models produced using our method are cost-efficient and predict that interconnected L5PCs are able to amplify delta-range oscillatory inputs across a large range of network sizes and topologies, largely due to the medium after hyperpolarization mediated by the Ca2+-activated SK current.Peer reviewedFinal Published versio
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