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| 4. |
- Thomas, HS, et al.
(författare)
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- 2019
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swepub:Mat__t
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| 8. |
- Fuchsberger, Christian, et al.
(författare)
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The genetic architecture of type 2 diabetes
- 2016
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 536:7614, s. 41-47
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Tidskriftsartikel (refereegranskat)abstract
- The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.
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| 9. |
- Flannick, Jason, et al.
(författare)
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Data Descriptor : Sequence data and association statistics from 12,940 type 2 diabetes cases and controls
- 2017
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Ingår i: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 4
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Tidskriftsartikel (refereegranskat)abstract
- To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (> 80% of low-frequency coding variants in similar to ~82 K Europeans via the exome chip, and similar to ~90% of low-frequency non-coding variants in similar to ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.
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| 11. |
- Lindskog, Maria, et al.
(författare)
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Transient calcium and dopamine increase PKA activity and DARPP-32 phosphorylation
- 2006
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Ingår i: PloS Computational Biology. - : Public Library of Science (PLoS). - 1553-734X .- 1553-7358. ; 2:9, s. 1045-1060
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Forskningsöversikt (refereegranskat)abstract
- Reinforcement learning theorizes that strengthening of synaptic connections in medium spiny neurons of the striatum occurs when glutamatergic input (from cortex) and dopaminergic input (from substantia nigra) are received simultaneously. Subsequent to learning, medium spiny neurons with strengthened synapses are more likely to fire in response to cortical input alone. This synaptic plasticity is produced by phosphorylation of AMPA receptors, caused by phosphorylation of various signalling molecules. A key signalling molecule is the phosphoprotein DARPP-32, highly expressed in striatal medium spiny neurons. DARPP-32 is regulated by several neurotransmitters through a complex network of intracellular signalling pathways involving cAMP (increased through dopamine stimulation) and calcium (increased through glutamate stimulation). Since DARPP-32 controls several kinases and phosphatases involved in striatal synaptic plasticity, understanding the interactions between cAMP and calcium, in particular the effect of transient stimuli on DARPP-32 phosphorylation, has major implications for understanding reinforcement learning. We developed a computer model of the biochemical reaction pathways involved in the phosphorylation of DARPP-32 on Thr34 and Thr75. Ordinary differential equations describing the biochemical reactions were implemented in a single compartment model using the software XPPAUT. Reaction rate constants were obtained from the biochemical literature. The first set of simulations using sustained elevations of dopamine and calcium produced phosphorylation levels of DARPP-32 similar to that measured experimentally, thereby validating the model. The second set of simulations, using the validated model, showed that transient dopamine elevations increased the phosphorylation of Thr34 as expected, but transient calcium elevations also increased the phosphorylation of Thr34, contrary to what is believed. When transient calcium and dopamine stimuli were paired, PKA activation and Thr34 phosphorylation increased compared with dopamine alone. This result, which is robust to variation in model parameters, supports reinforcement learning theories in which activity-dependent long-term synaptic plasticity requires paired glutamate and dopamine inputs.
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| 12. |
- Blackwell, Kim T., et al.
(författare)
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Molecular mechanisms underlying striatal synaptic plasticity : relevance chronic alcohol consumption and seeking
- 2019
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Ingår i: European Journal of Neuroscience. - : Wiley. - 0953-816X .- 1460-9568. ; 49:6, s. 768-783
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Tidskriftsartikel (refereegranskat)abstract
- The striatum, the input structure of the basal ganglia, is a major site learning and memory for goal-directed actions and habit formation. iny projection neurons of the striatum integrate cortical, thalamic, d nigral inputs to learn associations, with cortico-striatal synaptic asticity as a learning mechanism. Signaling molecules implicated in naptic plasticity are altered in alcohol withdrawal, which may ntribute to overly strong learning and increased alcohol seeking and nsumption. To understand how interactions among signaling molecules oduce synaptic plasticity, we implemented a mechanistic model of gnaling pathways activated by dopamine D1 receptors, acetylcholine ceptors, and glutamate. We use our novel, computationally efficient mulator, NeuroRD, to simulate stochastic interactions both within and tween dendritic spines. Dopamine release during theta burst and 20-Hz imulation was extrapolated from fast-scan cyclic voltammetry data llected in mouse striatal slices. Our results show that the combined tivity of several key plasticity molecules correctly predicts the currence of either LTP, LTD, or no plasticity for numerous perimental protocols. To investigate spatial interactions, we imulate two spines, either adjacent or separated on a 20-mu m ndritic segment. Our results show that molecules underlying LTP hibit spatial specificity, whereas 2-arachidonoylglycerol exhibits a atially diffuse elevation. We also implement changes in NMDA ceptors, adenylyl cyclase, and G protein signaling that have been asured following chronic alcohol treatment. Simulations under these nditions suggest that the molecular changes can predict changes in naptic plasticity, thereby accounting for some aspects of alcohol use sorder.
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| 13. |
- Eriksson, Olivia, PhD, 1971-, et al.
(författare)
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Combining hypothesis- and data-driven neuroscience modeling in FAIR workflows
- 2022
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Ingår i: eLIFE. - : eLife Sciences Publications, Ltd. - 2050-084X. ; 11
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Forskningsöversikt (refereegranskat)abstract
- Modeling in neuroscience occurs at the intersection of different points of view and approaches. Typically, hypothesis-driven modeling brings a question into focus so that a model is constructed to investigate a specific hypothesis about how the system works or why certain phenomena are observed. Data-driven modeling, on the other hand, follows a more unbiased approach, with model construction informed by the computationally intensive use of data. At the same time, researchers employ models at different biological scales and at different levels of abstraction. Combining these models while validating them against experimental data increases understanding of the multiscale brain. However, a lack of interoperability, transparency, and reusability of both models and the workflows used to construct them creates barriers for the integration of models representing different biological scales and built using different modeling philosophies. We argue that the same imperatives that drive resources and policy for data - such as the FAIR (Findable, Accessible, Interoperable, Reusable) principles - also support the integration of different modeling approaches. The FAIR principles require that data be shared in formats that are Findable, Accessible, Interoperable, and Reusable. Applying these principles to models and modeling workflows, as well as the data used to constrain and validate them, would allow researchers to find, reuse, question, validate, and extend published models, regardless of whether they are implemented phenomenologically or mechanistically, as a few equations or as a multiscale, hierarchical system. To illustrate these ideas, we use a classical synaptic plasticity model, the Bienenstock-Cooper-Munro rule, as an example due to its long history, different levels of abstraction, and implementation at many scales.
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| 14. |
- Hjorth, Johannes, et al.
(författare)
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GABAergic control of backpropagating action potentials in striatal medium spiny neurons
- 2008
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Konferensbidrag (refereegranskat)abstract
- Experiments have demonstrated the ability of action potentials to actively backpropagate in striatal medium spiny (MS) neurons, affecting the calcium levels in the dendrites[1-3]. Increased calcium levels trigger changes in plasticity[4,5], which is important for learning and other functions[6]. Studies in the hippocampus have shown that GABAergic input can modulate the backpropagation of action potentials from the soma to the distal dendrites[7]. The MS neurons receive both proximal feedforward GABAergic inhibition from fast spiking interneurons (FS), and distal feedback inhibition from other neighbouring MS neurons. In the present study the effect of these GABAergic inputs on the dendritic calcium dynamics is investigated.
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| 15. |
- Hjorth, Johannes, et al.
(författare)
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GABAergic control of dendritic calcium dynamics in striatal medium spiny neurons
- 2008
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Ingår i: Frontiers in Neuroinformatics. - : Frontiers Media SA. - 1662-5196.
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Konferensbidrag (refereegranskat)abstract
- Experiments have demonstrated the ability of action potentials to actively backpropagate in striatal medium spiny (MS) neurons, affecting the calcium levels in the dendrites [1, 2, 3]. Increased calcium levels trigger changes in plasticity [4, 5], which is important for learning and other functions [6]. Studies in the hippocampus have shown that GABAergic input can modulate the backpropagation of action potentials from the soma to the distal dendrites [7]. The MS neurons receive both proximal feedforward GABAergic inhibition from fast spiking interneurons (FS), and distal feedback inhibition from other neighbouring MS neurons. In the present study the effect of GABAergic inputs on the dendritic calcium dynamics is investigated.
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| 16. |
- Hjorth, Johannes, et al.
(författare)
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Gap Junctions between Striatal Fast-Spiking Interneurons Regulate Spiking Activity and Synchronization as a Function of Cortical Activity
- 2009
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Ingår i: Journal of Neuroscience. - 0270-6474 .- 1529-2401. ; 29:16, s. 5276-5286
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Tidskriftsartikel (refereegranskat)abstract
- Striatal fast-spiking (FS) interneurons are interconnected by gap junctions into sparsely connected networks. As demonstrated for cortical FS interneurons, these gap junctions in the striatum may cause synchronized spiking, which would increase the influence that FS neurons have on spiking by the striatal medium spiny (MS) neurons. Dysfunction of the basal ganglia is characterized by changes in synchrony or periodicity, thus gap junctions between FS interneurons may modulate synchrony and thereby influence behavior such as reward learning and motor control. To explore the roles of gap junctions on activity and spike synchronization in a striatal FS population, we built a network model of FS interneurons. Each FS connects to 30-40% of its neighbors, as found experimentally, and each FS interneuron in the network is activated by simulated corticostriatal synaptic inputs. Our simulations show that the proportion of synchronous spikes in FS networks with gap junctions increases with increased conductance of the electrical synapse; however, the synchronization effects are moderate for experimentally estimated conductances. Instead, the main tendency is that the presence of gap junctions reduces the total number of spikes generated in response to synaptic inputs in the network. The reduction in spike firing is due to shunting through the gap junctions; which is minimized or absent when the neurons receive coincident inputs. Together these findings suggest that a population of electrically coupled FS interneurons may function collectively as input detectors that are especially sensitive to synchronized synaptic inputs received from the cortex.
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| 17. |
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| 18. |
- Hjorth, Johannes, et al.
(författare)
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Synchronization Effects in Networks of Striatal Fast Spiking Interneurons - Role of Gap Junctions
- 2008
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Ingår i: ADVANCES IN COGNITIVE NEURODYNAMICS, PROCEEDINGS. - TOTOWA : HUMANA PRESS INC. - 9781402083860 ; , s. 63-66
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Konferensbidrag (refereegranskat)abstract
- Recent studies have found gap junctions between striatal fast spiking interneurons (FSN). Gap junctions between neocortical FSNs cause increased synchrony of firing in response to current injection, but the effect of gap junctions in response to synaptic input is unknown. To explore this issue, we built a network model of FSNs. Each FSN connects to 30-40% of its neighbours, as found experimentally, and each FSN in the network is activated by simulated up-state synaptic inputs. Simulation experiments show that the proportion of synchronous spikes in coupled FSNs increases with gap junction conductance. Proximal gap junctions increase the synchronization more than distal gap junctions. During up-states the synchronization effects in FSNs coupled pairwise with proximal gap junctions are small for experimentally estimated gap junction conductances; however, higher order correlations are significantly increased in larger FSN networks.
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| 19. |
- Hällgren Kotaleski, Jeanette, et al.
(författare)
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Modelling the molecular mechanisms of synaptic plasticity using systems biology approaches
- 2010
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Ingår i: Nature Reviews Neuroscience. - : Springer Science and Business Media LLC. - 1471-003X .- 1471-0048. ; 11:4, s. 239-251
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Forskningsöversikt (refereegranskat)abstract
- Synaptic plasticity is thought to underlie learning and memory, but the complexity of the interactions between the ion channels, enzymes and genes that are involved in synaptic plasticity impedes a deep understanding of this phenomenon. Computer modelling has been used to investigate the information processing that is performed by the signalling pathways involved in synaptic plasticity in principal neurons of the hippocampus, striatum and cerebellum. In the past few years, new software developments that combine computational neuroscience techniques with systems biology techniques have allowed large-scale, kinetic models of the molecular mechanisms underlying long-term potentiation and long-term depression. We highlight important advancements produced by these quantitative modelling efforts and introduce promising approaches that use advancements in live-cell imaging.
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| 20. |
- Manninen, Tiina, et al.
(författare)
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Postsynaptic signal transduction models for long-term potentiation and depression
- 2010
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Ingår i: Frontiers in Computational Neuroscience. - : Frontiers Media SA. - 1662-5188. ; 4, s. 152-
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Forskningsöversikt (refereegranskat)abstract
- More than a hundred biochemical species, activated by neurotransmitters binding to transmembrane receptors, are important in long-term potentiation (LTP) and long-term depression (LTD). To investigate which species and interactions are critical for synaptic plasticity, many computational postsynaptic signal transduction models have been developed. The models range from simple models with a single reversible reaction to detailed models with several hundred kinetic reactions. In this study, more than a hundred models are reviewed, and their features are compared and contrasted so that similarities and differences are more readily apparent. The models are classified according to the type of synaptic plasticity that is modeled (LTP or LTD) and whether they include diffusion or electrophysiological phenomena. Other characteristics that discriminate the models include the phase of synaptic plasticity modeled (induction, expression, or maintenance) and the simulation method used (deterministic or stochastic). We find that models are becoming increasingly sophisticated, by including stochastic properties, integrating with electrophysiological properties of entire neurons, or incorporating diffusion of signaling molecules. Simpler models continue to be developed because they are computationally efficient and allow theoretical analysis. The more complex models permit investigation of mechanisms underlying specific properties and experimental verification of model predictions. Nonetheless, it is difficult to fully comprehend the evolution of these models because (1) several models are not described in detail in the publications, (2) only a few models are provided in existing model databases, and (3) comparison to previous models is lacking. We conclude that the value of these models for understanding molecular mechanisms of synaptic plasticity is increasing and will be enhanced further with more complete descriptions and sharing of the published models.
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| 21. |
- Nair, Anu G., et al.
(författare)
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Modeling Intracellular Signaling Underlying Striatal Function in Health and Disease
- 2014
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Ingår i: Computational Neuroscience. - Amsterdam : Elsevier. - 9780123978974 ; 123, s. 277-304
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Bokkapitel (refereegranskat)abstract
- Striatum, which is the input nucleus of the basal ganglia, integrates cortical and thalamic glutamatergic inputs with dopaminergic afferents from the substantia nigra pars cornpacta. The combination of dopamine and glutamate strongly modulates molecular and cellular properties of striatal neurons and the strength of corticostriatal synapses. These actions are performed via intracellular signaling networks, containing several intertwined feedback loops. Understanding the role of dopamine and other neuromodulators requires the development of quantitative dynamical models for describing the intracellular signaling, in order to provide precise unambiguous descriptions and quantitative predictions. Building such models requires integration of data from multiple data sources containing information regarding the molecular interactions, the strength of these interactions, and the subcellular localization of the molecules. Due to the uncertainty, variability, and sparseness of these data, parameter estimation techniques are critical for inferring or constraining the unknown parameters, and sensitivity analysis evaluates which parameters are most critical for a given observed macroscopic behavior. Here, we briefly review the modeling approaches and tools that have been used to investigate biochemical signaling in the striatum, along with some of the models built around striatum. We also suggest a future direction for the development of such models from the, now becoming abundant, high-throughput data.
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| 22. |
- Sawcer, Stephen, et al.
(författare)
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Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis
- 2011
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 476:7359, s. 214-219
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Tidskriftsartikel (refereegranskat)abstract
- Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis.
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