A Multi-Study Model-Based Evaluation of the Sequence of Imaging and Clinical Biomarker Changes in Huntington's Disease.
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ABSTRACT:
SUBMITTER: Wijeratne PA
PROVIDER: S-EPMC8374237 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveDetermining the sequence in which Huntington's disease biomarkers become abnormal can provide important insights into the disease progression and a quantitative tool for patient stratification. Here, we construct and present a uniquely fine-grained model of temporal progression of Huntington's disease from premanifest through to manifest stages.MethodsWe employ a probabilistic event-based model to determine the sequence of appearance of atrophy in brain volumes, learned from structural MRI in the Track-HD study, as well as to estimate the uncertainty in the ordering. We use longitudinal and phenotypic data to demonstrate the utility of the patient staging system that the resulting model provides.ResultsThe model recovers the following order of detectable changes in brain region volumes: putamen, caudate, pallidum, insula white matter, nonventricular cerebrospinal fluid, amygdala, optic chiasm, third ventricle, posterior insula, and basal forebrain. This ordering is mostly preserved even under cross-validation of the uncertainty in the event sequence. Longitudinal analysis performed using 6 years of follow-up data from baseline confirms efficacy of the model, as subjects consistently move to later stages with time, and significant correlations are observed between the estimated stages and nonimaging phenotypic markers.InterpretationWe used a data-driven method to provide new insight into Huntington's disease progression as well as new power to stage and predict conversion. Our results highlight the potential of disease progression models, such as the event-based model, to provide new insight into Huntington's disease progression and to support fine-grained patient stratification for future precision medicine in Huntington's disease.
| S-EPMC5945962 | biostudies-literature
Project description:BackgroundDimebon is an antihistamine compound with a long history of clinical use in Russia. Recently, Dimebon has been proposed to be useful for treating neurodegenerative disorders. It has demonstrated efficacy in phase II Alzheimer's disease (AD) and Huntington's disease (HD) clinical trials. The mechanisms responsible for the beneficial actions of Dimebon in AD and HD remain unclear. It has been suggested that Dimebon may act by blocking NMDA receptors or voltage-gated Ca2+ channels and by preventing mitochondrial permeability pore transition.ResultsWe evaluated the effects of Dimebon in experiments with primary striatal neuronal cultures (MSN) from wild type (WT) mice and YAC128 HD transgenic mice. We found that Dimebon acts as an inhibitor of NMDA receptors (IC50 = 10 muM) and voltage-gated calcium channels (IC50 = 50 muM) in WT and YAC128 MSN. We further found that application of 50 muM Dimebon stabilized glutamate-induced Ca2+ signals in YAC128 MSN and protected cultured YAC128 MSN from glutamate-induced apoptosis. Lower concentrations of Dimebon (5 muM and 10 muM) did not stabilize glutamate-induced Ca2+ signals and did not exert neuroprotective effects in experiments with YAC128 MSN. Evaluation of Dimebon against a set of biochemical targets indicated that Dimebon inhibits alpha-Adrenergic receptors (alpha1A, alpha1B, alpha1D, and alpha2A), Histamine H1 and H2 receptors and Serotonin 5-HT2c, 5-HT5A, 5-HT6 receptors with high affinity. Dimebon also had significant effect on a number of additional receptors.ConclusionOur results suggest that Ca2+ and mitochondria stabilizing effects may, in part, be responsible for beneficial clinical effects of Dimebon. However, the high concentrations of Dimebon required to achieve Ca2+ stabilizing and neuroprotective effects in our in vitro studies (50 muM) indicate that properties of Dimebon as cognitive enhancer are most likely due to potent inhibition of H1 histamine receptors. It is also possible that Dimebon acts on novel high affinity targets not present in cultured MSN preparation. Unbiased evaluation of Dimebon against a set of biochemical targets indicated that Dimebon efficiently inhibited a number of additional receptors. Potential interactions with these receptors need to be considered in interpretation of results obtained with Dimebon in clinical trials.
| S-EPMC2577671 | biostudies-literature
Project description:BackgroundThe pathological mechanism of cellular dysfunction and death in Huntington's disease (HD) is not well defined. Our transgenic HD sheep model (OVT73) was generated to investigate these mechanisms and for therapeutic testing. One particular cohort of animals has undergone focused investigation resulting in a large interrelated multi-omic dataset, with statistically significant changes observed comparing OVT73 and control 'omic' profiles and reported in literature.ObjectiveHere we make this dataset publicly available for the advancement of HD pathogenic mechanism discovery.MethodsTo enable investigation in a user-friendly format, we integrated seven multi-omic datasets from a cohort of 5-year-old OVT73 (n = 6) and control (n = 6) sheep into a single database utilising the programming language R. It includes high-throughput transcriptomic, metabolomic and proteomic data from blood, brain, and other tissues.ResultsWe present the 'multi-omic' HD sheep database as a queryable web-based platform that can be used by the wider HD research community (https://hdsheep.cer.auckland.ac.nz/). The database is supported with a suite of simple automated statistical analysis functions for rapid exploratory analyses. We present examples of its use that validates the integrity relative to results previously reported. The data may also be downloaded for user determined analysis.ConclusionWe propose the use of this online database as a hypothesis generator and method to confirm/refute findings made from patient samples and alternate model systems, to expand our understanding of HD pathogenesis. Importantly, additional tissue samples are available for further investigation of this cohort.
| S-EPMC8673501 | biostudies-literature
Project description:BackgroundMacro- and micro-structural neuroimaging measures provide valuable information on the pathophysiology of Huntington's disease (HD) and are proposed as biomarkers. Despite theoretical advantages of microstructural measures in terms of sensitivity to pathology, there is little evidence directly comparing the two.Methods40 controls and 61 early HD subjects underwent 3 T MRI (T1- and diffusion-weighted), as part of the PADDINGTON study. Macrostructural volumetrics were obtained for the whole brain, caudate, putamen, corpus callosum (CC) and ventricles. Microstructural diffusion metrics of fractional anisotropy (FA), mean-, radial- and axial-diffusivity (MD, RD, AD) were computed for white matter (WM), CC, caudate and putamen. Group differences were examined adjusting for age, gender and site. A formal comparison of effect sizes determined which modality and metrics provided a statistically significant advantage over others.ResultsMacrostructural measures showed decreased regional and global volume in HD (p < 0.001); except the ventricles which were enlarged (p < 0.01). In HD, FA was increased in the deep grey-matter structures (p < 0.001), and decreased in the WM (CC, p = 0.035; WM, p = 0.053); diffusivity metrics (MD, RD, AD) were increased for all brain regions (p < 0.001). The largest effect sizes were for putamen volume, caudate volume and putamen diffusivity (AD, RD and MD); each was significantly larger than those for all other metrics (p < 0.05).ConclusionThe highest performing macro- and micro-structural metrics had similar sensitivity to HD pathology quantified via effect sizes. Region-of-interest may be more important than imaging modality, with deep grey-matter regions outperforming the CC and global measures, for both volume and diffusivity. FA appears to be relatively insensitive to disease effects.
| S-EPMC3777685 | biostudies-literature
Project description:The order and magnitude of pathologic processes in Alzheimer's disease are not well understood, partly because the disease develops over many years. Autosomal dominant Alzheimer's disease has a predictable age at onset and provides an opportunity to determine the sequence and magnitude of pathologic changes that culminate in symptomatic disease.In this prospective, longitudinal study, we analyzed data from 128 participants who underwent baseline clinical and cognitive assessments, brain imaging, and cerebrospinal fluid (CSF) and blood tests. We used the participant's age at baseline assessment and the parent's age at the onset of symptoms of Alzheimer's disease to calculate the estimated years from expected symptom onset (age of the participant minus parent's age at symptom onset). We conducted cross-sectional analyses of baseline data in relation to estimated years from expected symptom onset in order to determine the relative order and magnitude of pathophysiological changes.Concentrations of amyloid-beta (A?)(42) in the CSF appeared to decline 25 years before expected symptom onset. A? deposition, as measured by positron-emission tomography with the use of Pittsburgh compound B, was detected 15 years before expected symptom onset. Increased concentrations of tau protein in the CSF and an increase in brain atrophy were detected 15 years before expected symptom onset. Cerebral hypometabolism and impaired episodic memory were observed 10 years before expected symptom onset. Global cognitive impairment, as measured by the Mini-Mental State Examination and the Clinical Dementia Rating scale, was detected 5 years before expected symptom onset, and patients met diagnostic criteria for dementia at an average of 3 years after expected symptom onset.We found that autosomal dominant Alzheimer's disease was associated with a series of pathophysiological changes over decades in CSF biochemical markers of Alzheimer's disease, brain amyloid deposition, and brain metabolism as well as progressive cognitive impairment. Our results require confirmation with the use of longitudinal data and may not apply to patients with sporadic Alzheimer's disease. (Funded by the National Institute on Aging and others; DIAN ClinicalTrials.gov number, NCT00869817.).
| S-EPMC3474597 | biostudies-literature
Project description:BackgroundHuntington's disease like 2 (HDL2) is the most common Huntington's disease (HD) phenocopy in many countries and described as the phenocopy with the greatest resemblance to HD. The current clinical description of HDL2 is based on retrospective data. It is unknown whether HDL2 has clinical features that distinguish it from HD.ObjectiveTo describe the HDL2 phenotype and compare it to HD systematically.MethodsA blinded cross-sectional design was used to compare the HDL2 (n = 15) and HD (n = 13) phenotypes. African ancestry participants underwent assessments, including the Unified Huntington's Disease Rating Scale (UHDRS). The UHDRS motor component was video recorded and evaluated by blinded experts and the inter-rater reliability calculated.ResultsBoth groups were homogeneous in terms of demographics and disease characteristics. However, HDL2 patients presented three years earlier with more prominent dysarthria and dystonia. Raters could not distinguish between the two diseases with a high level of agreement. No significant differences in the TMS between HDL2 and HD were found. In both disorders, disease duration correlated with motor scores, with the exception of chorea. Psychiatric and cognitive scores were not significantly different between the groups.ConclusionsThe HDL2 phenotype is similar to HD and is initially characterized by dementia, chorea, and oculomotor abnormalities, progressing to a rigid and bradykinetic state, suggesting the UHDRS is useful to monitor disease progression in HDL2. Although HDL2 patients scored higher on some UHDRS domains, this did not differentiate between the two diseases; it may however be emerging evidence of HDL2 having a more severe clinical phenotype.
| S-EPMC6476590 | biostudies-literature
Project description:Hereditary Huntington's disease (HD) is associated with progressive motor, cognitive and psychiatric symptoms. A primary consequence of the HD mutation is the preferential loss of medium spiny projection cells with relative sparing of local interneurons in the striatum. In addition, among GABAergic striatal projection cells, indirect pathway cells expressing D2 dopamine receptors are lost earlier than direct pathway cells expressing D1 receptors. To test in vivo the functional integrity of direct and indirect pathways as well as interneurons in the striatum of male R6/1 transgenic mice, we assessed their c-Fos expression levels induced by a striatal-dependent cognitive task and compared them with age-matched wild-type littermates. We found a significant increase of c-Fos+ nuclei in the dorsomedial striatum, and this only at 2 months, when our HD mouse model is still pre-motor symptomatic, the increase disappearing with symptom manifestation. Contrary to our expectation, the indirect pathway projection neurons did not undergo any severer changes of c-Fos expression regardless of age in R6/1 mice. We also found a decreased activation of interneurons that express parvalbumin in the dorsomedial striatum at both presymptomatic and symptomatic ages. Finally, analysis of c-Fos expression in extended brain regions involved in the cognitive learning used in our study, demonstrates, throughout ages studied, changes in the functional connectivity between regions in the transgenic mice. Further analysis of the cellular and molecular changes underlying the transient striatal hyperactivity in the HD mice may help to understand the mechanisms involved in the disease onset.
| S-EPMC5608247 | biostudies-literature
Project description:Although the association between cytosine-adenine-guanine (CAG) repeat length and age at onset of Huntington's disease is well known, improved prediction of onset would be advantageous for clinical trial design and prognostic counselling. We compared various measures for tracking progression and predicting conversion to manifest Huntington's disease.In this prospective observational study, we assessed the ability of 40 measures in five domains (motor, cognitive, psychiatric, functional, and imaging) to predict time to motor diagnosis of Huntington's disease, accounting for CAG repeat length, age, and the interaction of CAG repeat length and age. Eligible participants were individuals from the PREDICT-HD study (from 33 centres in six countries [USA, Canada, Germany, Australia, Spain, UK]) with the gene mutation for Huntington's disease but without a motor diagnosis (a rating below 4 on the diagnostic confidence level from the 15-item motor assessment of the Unified Huntington's Disease Rating Scale). Participants were followed up between September, 2002, and July, 2014. We used joint modelling of longitudinal and survival data to examine the extent to which baseline and change of measures analysed separately was predictive of CAG-adjusted age at motor diagnosis.1078 individuals with a CAG expansion were included in this analysis. Participants were followed up for a mean of 5·1 years (SD 3·3, range 0·0-12·0). 225 (21%) of these participants received a motor diagnosis of Huntington's disease during the study. 37 of 40 cross-sectional and longitudinal clinical and imaging measures were significant predictors of motor diagnosis beyond CAG repeat length and age. The strongest predictors were in the motor, imaging, and cognitive domains: an increase of one SD in total motor score (motor domain) increased the risk of a motor diagnosis by 3·07 times (95% CI 2·26-4·16), a reduction of one SD in putamen volume (imaging domain) increased risk by 3·32 times (2·37-4·65), and a reduction of one SD in Stroop word score (cognitive domain) increased risk by 2·32 times (1·88-2·87).Prediction of diagnosis of Huntington's disease can be improved beyond that obtained by CAG repeat length and age alone. Such knowledge about potential predictors of manifest Huntington's disease should inform discussions about guidelines for diagnosis, prognosis, and counselling, and might be useful in guiding the selection of participants and outcome measures for clinical trials.US National Institutes of Health, US National Institute of Neurological Disorders and Stroke, and CHDI Foundation.
| S-EPMC4373455 | biostudies-literature
Project description:Huntington's disease (HD) is genetically determined but with variability in symptom onset, leading to uncertainty as to when pharmacological intervention should be initiated. Here we take a computational approach based on neurocognitive phenotyping, computational modeling, and classification, in an effort to provide quantitative predictors of HD before symptom onset. A large sample of subjects-consisting of both pre-manifest individuals carrying the HD mutation (pre-HD), and early symptomatic-as well as healthy controls performed the antisaccade conflict task, which requires executive control and response inhibition. While symptomatic HD subjects differed substantially from controls in behavioral measures [reaction time (RT) and error rates], there was no such clear behavioral differences in pre-HD. RT distributions and error rates were fit with an accumulator-based model which summarizes the computational processes involved and which are related to identified mechanisms in more detailed neural models of prefrontal cortex and basal ganglia. Classification based on fitted model parameters revealed a key parameter related to executive control differentiated pre-HD from controls, whereas the response inhibition parameter declined only after symptom onset. These findings demonstrate the utility of computational approaches for classification and prediction of brain disorders, and provide clues as to the underlying neural mechanisms.
| S-EPMC4752511 | biostudies-literature
Project description:BackgroundImpaired gait plays an important role for quality of life in patients with Huntington's disease (HD). Measuring objective gait parameters in HD might provide an unbiased assessment of motor deficits in order to determine potential beneficial effects of future treatments.ObjectiveTo objectively identify characteristic features of gait in HD patients using sensor-based gait analysis. Particularly, gait parameters were correlated to the Unified Huntington's Disease Rating Scale, total motor score (TMS), and total functional capacity (TFC).MethodsPatients with manifest HD at two German sites (n?=?43) were included and clinically assessed during their annual ENROLL-HD visit. In addition, patients with HD and a cohort of age- and gender-matched controls performed a defined gait test (4?×?10 m walk). Gait patterns were recorded by inertial sensors attached to both shoes. Machine learning algorithms were applied to calculate spatio-temporal gait parameters and gait variability expressed as coefficient of variance (CV).ResultsStride length (-?15%) and gait velocity (-?19%) were reduced, while stride (+?7%) and stance time (+?2%) were increased in patients with HD. However, parameters reflecting gait variability were substantially altered in HD patients (+?17% stride length CV up to?+?41% stride time CV with largest effect size) and showed strong correlations to TMS and TFC (0.416???rSp???0.690). Objective gait variability parameters correlated with disease stage based upon TFC.ConclusionsSensor-based gait variability parameters were identified as clinically most relevant digital biomarker for gait impairment in HD. Altered gait variability represents characteristic irregularity of gait in HD and reflects disease severity.
| S-EPMC7293689 | biostudies-literature