Braiding Braak and Braak: Staging patterns and model selection in network neurodegeneration.
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ABSTRACT:
SUBMITTER: Putra P
PROVIDER: S-EPMC8746141 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:IntroductionAlzheimer's disease diagnosis requires postmortem visualization of amyloid and tau deposits. As brain atrophy can provide assessment of consequent neurodegeneration, our objective was to predict postmortem neurofibrillary tangles (NFT) from in vivo MRI measurements.MethodsAll participants with neuroimaging and neuropathological data from the Alzheimer's Disease Neuroimaging Initiative, the National Alzheimer's Coordinating Center and the Rush Memory and Aging Project were selected (n = 186). Two hundred and thirty two variables were extracted from last MRI before death using FreeSurfer. Nonparametric correlation analysis and multivariable support vector machine classification were performed to provide a predictive model of Braak NFT staging.ResultsWe demonstrated that 59 of our MRI variables, mostly temporal lobe structures, were significantly associated with Braak NFT stages (P < .005). We obtained a 62.4% correct classification rate for discrimination between transentorhinal, limbic, and isocortical groups.DiscussionStructural neuroimaging may therefore be considered as a potential biomarker for early detection of Alzheimer's disease-associated neurofibrillary degeneration.
| S-EPMC6731211 | biostudies-literature
Project description:The accumulation of aggregated proteins is a hallmark of neurodegenerative proteinopathies. Although multiple genetic loci have been associated with specific neurodegenerative diseases (NDs), molecular mechanisms that may have relevance for all proteinopathies remain poorly resolved. Here, we introduce a multi-layered network expansion (MLnet) model that predicts protein modifiers that are common to disease groups. When applied to the four NDs, Alzheimer's disease (AD), Huntington's disease, and Spinocerebellar ataxia types 1 and 3, MLnet identifies multiple members of the insulin pathway, including PDK1, Akt1, InR, and sgg (GSK-3β), as common modifiers. We validated these modifiers with the help of four Drosophila ND models. Further evaluations in human cell-based ND models revealed that activation of Akt1 signaling by the small molecule SC79 increased cell viability. Moreover, treatment of AD model mice with SC79 enhanced their long-term memory and ameliorated dysregulated anxiety levels. These findings validate MLnet as a valuable tool to uncover molecular pathways and proteins that may be involved in the pathophysiology of multiple diseases and have relevance cross disease boundaries.
| S-SCDT-10_15252-MSB_202311801 | biostudies-other
Project description:BackgroundTo systematically examine the clinical utility of tau-PET and Braak-staging as prognostic markers of future cognitive decline in older adults with and without cognitive impairment.MethodsIn this longitudinal study, we included 396 cognitively normal to dementia subjects with 18F-Florbetapir/18F-Florbetaben-amyloid-PET, 18F-Flortaucipir-tau-PET and ~ 2-year cognitive follow-up. Annual change rates in global cognition (i.e., MMSE, ADAS13) and episodic memory were calculated via linear-mixed models. We determined global amyloid-PET (Centiloid) plus global and Braak-stage-specific tau-PET SUVRs, which were stratified as positive(+)/negative(-) at pre-established cut-offs, classifying subjects as Braak0/BraakI+/BraakI-IV+/BraakI-VI+/Braakatypical+. In bootstrapped linear regression, we assessed the predictive accuracy of global tau-PET SUVRs vs. Centiloid on subsequent cognitive decline. To test for independent tau vs. amyloid effects, analyses were further controlled for the contrary PET-tracer. Using ANCOVAs, we tested whether more advanced Braak-stage predicted accelerated future cognitive decline. All models were controlled for age, sex, education, diagnosis, and baseline cognition. Lastly, we determined Braak-stage-specific conversion risk to mild cognitive impairment (MCI) or dementia.ResultsBaseline global tau-PET SUVRs explained more variance (partial R2) in future cognitive decline than Centiloid across all cognitive tests (Cohen's d ~ 2, all tests p < 0.001) and diagnostic groups. Associations between tau-PET and cognitive decline remained consistent when controlling for Centiloid, while associations between amyloid-PET and cognitive decline were non-significant when controlling for tau-PET. More advanced Braak-stage was associated with gradually worsening future cognitive decline, independent of Centiloid or diagnostic group (p < 0.001), and elevated conversion risk to MCI/dementia.ConclusionTau-PET and Braak-staging are highly predictive markers of future cognitive decline and may be promising single-modality estimates for prognostication of patient-specific progression risk in clinical settings.
| S-EPMC8361801 | biostudies-literature
Project description:ObjectiveEmerging evidences suggest that the trans-neural propagation of phosphorylated 43-kDa transactive response DNA-binding protein (pTDP-43) contributes to neurodegeneration in Amyotrophic Lateral Sclerosis (ALS). We investigated whether Network Diffusion Model (NDM), a biophysical model of spread of pathology via the brain connectome, could capture the severity and progression of neurodegeneration (atrophy) in ALS.MethodsWe measured degeneration in limb-onset ALS patients (n = 14 at baseline, 12 at 6-months, and 9 at 12 months) and controls (n = 12 at baseline) using FreeSurfer analysis on the structural T1-weighted Magnetic Resonance Imaging (MRI) data. The NDM was simulated on the canonical structural connectome from the IIT Human Brain Atlas. To determine whether NDM could predict the atrophy pattern in ALS, the accumulation of pathology modelled by NDM was correlated against atrophy measured using MRI. In order to investigate whether network spread on the brain connectome derived from healthy individuals were significant findings, we compared our findings against network spread simulated on random networks.ResultsThe cross-sectional analyses revealed that the network diffusion seeded from the inferior frontal gyrus (pars triangularis and pars orbitalis) significantly predicts the atrophy pattern in ALS compared to controls. Whereas, atrophy over time with-in the ALS group was best predicted by seeding the network diffusion process from the inferior temporal gyrus at 6-month and caudal middle frontal gyrus at 12-month. Network spread simulated on the random networks showed that the findings using healthy brain connectomes are significantly different from null models.InterpretationOur findings suggest the involvement of extra-motor regions in seeding the spread of pathology in ALS. Importantly, NDM was able to recapitulate the dynamics of pathological progression in ALS. Understanding the spatial shifts in the seeds of degeneration over time can potentially inform further research in the design of disease modifying therapeutic interventions in ALS.
| S-EPMC9371353 | biostudies-literature
Project description:Tracing the backbone is a critical step in protein model building, as incorrect tracing leads to poor protein models. Here, a neural network trained to identify unfavourable fragments and remove them from the model-building process in order to improve backbone tracing is presented. Moreover, a decision tree was trained to select an optimal threshold to eliminate unfavourable fragments. The neural network was tested on experimental phasing data sets from the Joint Center for Structural Genomics (JCSG), recently deposited experimental phasing data sets (from 2015 to 2021) and molecular-replacement data sets. The experimental results show that using the neural network in the Buccaneer protein-model-building software can produce significantly more complete protein models than those built using Buccaneer alone. In particular, Buccaneer with the neural network built protein models with a completeness that was at least 5% higher for 25% and 50% of the original and truncated resolution JCSG experimental phasing data sets, respectively, for 28% of the recently collected experimental phasing data sets and for 43% of the molecular-replacement data sets.
| S-EPMC10071564 | biostudies-literature
Project description:The long-term pathological effects of chronic epilepsy on normal brain ageing are unknown. Previous clinical and epidemiological studies show progressive cognitive decline in subsets of patients and an increased prevalence of Alzheimer's disease in epilepsy. In a post-mortem series of 138 patients with long-term, mainly drug-resistant epilepsy, we carried out Braak staging for Alzheimer's disease neurofibrillary pathology using tau protein immunohistochemistry. The stages were compared with clinicopathological factors, including seizure history and presence of old traumatic brain injury. Overall, 31% of cases were Braak Stage 0, 36% Stage I/II, 31% Stage III/IV and 2% Stage V/VI. The mean age at death was 56.5 years and correlated with Braak stage (P < 0.001). Analysis of Braak stages within age groups showed a significant increase in mid-Braak stages (III/IV), in middle age (40-65 years) compared with data from an ageing non-epilepsy series (P < 0.01). There was no clear relationship between seizure type (generalized or complex partial), seizure frequency, age of onset and duration of epilepsy with Braak stage although higher Braak stages were noted with focal more than with generalized epilepsy syndromes (P < 0.01). In 30% of patients, there was pathological evidence of traumatic brain injury that was significantly associated with higher Braak stages (P < 0.001). Cerebrovascular disease present in 40.3% and cortical malformations in 11.3% were not significantly associated with Braak stage. Astrocytic-tau protein correlated with the presence of both traumatic brain injury (P < 0.01) and high Braak stage (P < 0.001). Hippocampal sclerosis, identified in 40% (bilateral in 48%), was not associated with higher Braak stages, but asymmetrical patterns of tau protein accumulation within the sclerotic hippocampus were noted. In over half of patients with cognitive decline, the Braak stage was low indicating causes other than Alzheimer's disease pathology. In summary, there is evidence of accelerated brain ageing in severe chronic epilepsy although progression to high Braak stages was infrequent. Traumatic brain injury, but not seizures, was associated with tau protein accumulation in this series. It is likely that Alzheimer's disease pathology is not the sole explanation for cognitive decline associated with epilepsy.
| S-EPMC3187539 | biostudies-literature
Project description:The accumulation of misfolded and aggregated proteins is a hallmark of neurodegenerative proteinopathies. Although multiple genetic loci have been associated with specific neurodegenerative diseases (NDs), molecular mechanisms that may have a broader relevance for most or all proteinopathies remain poorly resolved. In this study, we developed a multi-layered network expansion (MLnet) model to predict protein modifiers that are common to a group of diseases and, therefore, may have broader pathophysiological relevance for that group. When applied to the four NDs Alzheimer's disease (AD), Huntington's disease, and spinocerebellar ataxia types 1 and 3, we predicted multiple members of the insulin pathway, including PDK1, Akt1, InR, and sgg (GSK-3β), as common modifiers. We validated these modifiers with the help of four Drosophila ND models. Further evaluation of Akt1 in human cell-based ND models revealed that activation of Akt1 signaling by the small molecule SC79 increased cell viability in all models. Moreover, treatment of AD model mice with SC79 enhanced their long-term memory and ameliorated dysregulated anxiety levels, which are commonly affected in AD patients. These findings validate MLnet as a valuable tool to uncover molecular pathways and proteins involved in the pathophysiology of entire disease groups and identify potential therapeutic targets that have relevance across disease boundaries. MLnet can be used for any group of diseases and is available as a web tool at http://ssbio.cau.ac.kr/software/mlnet.
| S-EPMC10698508 | biostudies-literature
Project description:Clinical and neuropathological staging of Alzheimer disease (AD) neurodegeneration and neuronal loss dynamics is the baseline for identification of treatment targets and timing. The aim of this study of 14 brain regions in 25 subjects diagnosed with AD and 13 age-matched control subjects was to establish the pattern of neurodegeneration, and the severity and rate of neuronal loss in mild cognitive impairment/mild AD (Functional Assessment Staging [FAST] test 3-4), moderate to moderately severe AD (FAST 5-6), and severe AD (FAST 7). The study revealed (1) the most severe neuronal loss in FAST 3-4; (2) the highest rate of neuronal loss in FAST 5-6, to the "critical" point limiting further increase in neuronal loss; (3) progression of neurofibrillary degeneration, but decline of neuronal loss to a floor level in FAST 7; and (4) structure-specific rate of neuronal loss caused by neurofibrillary degeneration and a large pool of neuronal loss caused by other mechanisms. This study defines a range and speed of progression of AD pathology and functional decline that might potentially be prevented by the arrest of neuronal loss, both related and unrelated to neurofibrillary degeneration, during the 9-year duration of mild cognitive impairment/mild AD.
| S-EPMC7749716 | biostudies-literature
Project description:BackgroundThe gap gene system controls the early cascade of the segmentation pathway in Drosophila melanogaster as well as other insects. Owing to its tractability and key role in embryo patterning, this system has been the focus for both computational modelers and experimentalists. The gap gene expression dynamics can be considered strictly as a one-dimensional process and modeled as a system of reaction-diffusion equations. While substantial progress has been made in modeling this phenomenon, there still remains a deficit of approaches to evaluate competing hypotheses. Most of the model development has happened in isolation and there has been little attempt to compare candidate models.ResultsThe Bayesian framework offers a means of doing formal model evaluation. Here, we demonstrate how this framework can be used to compare different models of gene expression. We focus on the Papatsenko-Levine formalism, which exploits a fractional occupancy based approach to incorporate activation of the gap genes by the maternal genes and cross-regulation by the gap genes themselves. The Bayesian approach provides insight about relationship between system parameters. In the regulatory pathway of segmentation, the parameters for number of binding sites and binding affinity have a negative correlation. The model selection analysis supports a stronger binding affinity for Bicoid compared to other regulatory edges, as shown by a larger posterior mean. The procedure doesn't show support for activation of Kruppel by Bicoid.ConclusionsWe provide an efficient solver for the general representation of the Papatsenko-Levine model. We also demonstrate the utility of Bayes factor for evaluating candidate models for spatial pattering models. In addition, by using the parallel tempering sampler, the convergence of Markov chains can be remarkably improved and robust estimates of Bayes factors obtained.
| S-EPMC6567646 | biostudies-literature
Project description:According to a basic rule of fermionic and bosonic many-body physics, known as the linked cluster theorem, physical observables are not affected by vacuum bubbles, which represent virtual particles created from vacuum and self-annihilating without interacting with real particles. Here we show that this conventional knowledge must be revised for anyons, quasiparticles that obey fractional exchange statistics intermediate between fermions and bosons. We find that a certain class of vacuum bubbles of Abelian anyons does affect physical observables. They represent virtually excited anyons that wind around real anyonic excitations. These topological bubbles result in a temperature-dependent phase shift of Fabry-Perot interference patterns in the fractional quantum Hall regime accessible in current experiments, thus providing a tool for direct and unambiguous observation of elusive fractional statistics.
| S-EPMC4821888 | biostudies-literature