Automated differentiation of pre-diagnosis Huntington's disease from healthy control individuals based on quadratic discriminant analysis of the basal ganglia: The IMAGE-HD study

The effect of multidisciplinary rehabilitation on brain structure and cognition in Huntington's disease: an exploratory study

BACKGROUND

There is a wealth of evidence detailing gray matter degeneration and loss of cognitive function over time in individuals with Huntington's disease (HD). Efforts to attenuate disease-related brain and cognitive changes have been unsuccessful to date. Multidisciplinary rehabilitation, comprising motor and cognitive intervention, has been shown to positively impact on functional capacity, depression, quality of life and some aspects of cognition in individuals with HD. This exploratory study aimed to evaluate, for the first time, whether multidisciplinary rehabilitation can slow further deterioration of disease-related brain changes and related cognitive deficits in individuals with manifest HD.

METHODS

Fifteen participants who manifest HD undertook a multidisciplinary rehabilitation intervention spanning 9 months. The intervention consisted of once-weekly supervised clinical exercise, thrice-weekly self-directed home based exercise and fortnightly occupational therapy. Participants were assessed using MR imaging and validated cognitive measures at baseline and after 9 months.

RESULTS

Participants displayed significantly increased gray matter volume in the right caudate and bilaterally in the dorsolateral prefrontal cortex after 9 months of multidisciplinary rehabilitation. Volumetric increases in gray matter were accompanied by significant improvements in verbal learning and memory (Hopkins Verbal Learning-Test). A significant association was found between gray matter volume increases in the dorsolateral prefrontal cortex and performance on verbal learning and memory.

CONCLUSIONS

This study provides preliminary evidence that multidisciplinary rehabilitation positively impacts on gray matter changes and cognitive functions relating to verbal learning and memory in individuals with manifest HD. Larger controlled trials are required to confirm these preliminary findings.

Basal ganglia-cortical structural connectivity in Huntington's disease

Huntington's disease is an incurable neurodegenerative disease caused by inheritance of an expanded cytosine-adenine-guanine (CAG) trinucleotide repeat within the Huntingtin gene. Extensive volume loss and altered diffusion metrics in the basal ganglia, cortex and white matter are seen when patients with Huntington's disease (HD) undergo structural imaging, suggesting that changes in basal ganglia-cortical structural connectivity occur. The aims of this study were to characterise altered patterns of basal ganglia-cortical structural connectivity with high anatomical precision in premanifest and early manifest HD, and to identify associations between structural connectivity and genetic or clinical markers of HD. 3-Tesla diffusion tensor magnetic resonance images were acquired from 14 early manifest HD subjects, 17 premanifest HD subjects and 18 controls. Voxel-based analyses of probabilistic tractography were used to quantify basal ganglia-cortical structural connections. Canonical variate analysis was used to demonstrate disease-associated patterns of altered connectivity and to test for associations between connectivity and genetic and clinical markers of HD; this is the first study in which such analyses have been used. Widespread changes were seen in basal ganglia-cortical structural connectivity in early manifest HD subjects; this has relevance for development of therapies targeting the striatum. Premanifest HD subjects had a pattern of connectivity more similar to that of controls, suggesting progressive change in connections over time. Associations between structural connectivity patterns and motor and cognitive markers of disease severity were present in early manifest subjects. Our data suggest the clinical phenotype in manifest HD may be at least partly a result of altered connectivity.

Hidden in plain view: degeneracy in complex systems

Degeneracy is a word with two meanings. The popular usage of the word denotes deviance and decay. In scientific discourse, degeneracy refers to the idea that different pathways can lead to the same output. In the biological sciences, the concept of degeneracy has been ignored for a few key reasons. Firstly, the word "degenerate" in popular culture has negative, emotionally powerful associations that do not inspire scientists to consider its technical meaning. Secondly, the tendency of searching for single causes of natural and social phenomena means that scientists can overlook the multi-stranded relationships between cause and effect. Thirdly, degeneracy and redundancy are often confused with each other. Degeneracy refers to dissimilar structures that are functionally similar while redundancy refers to identical structures. Degeneracy can give rise to novelty in ways that redundancy cannot. From genetic codes to immunology, vaccinology and brain development, degeneracy is a crucial part of how complex systems maintain their functional integrity. This review article discusses how the scientific concept of degeneracy was imported into genetics from physics and was later introduced to immunology and neuroscience. Using examples of degeneracy in immunology, neuroscience and linguistics, we demonstrate that degeneracy is a useful way of understanding how complex systems function. Reviewing the history and theoretical scope of degeneracy allows its usefulness to be better appreciated, its coherency to be further developed, and its application to be more quickly realized.

Longitudinal change in white matter microstructure in Huntington's disease: The IMAGE-HD study

OBJECTIVE

To quantify 18-month changes in white matter microstructure in premanifest (pre-HD) and symptomatic Huntington's disease (symp-HD). To investigate baseline clinical, cognitive and motor symptoms that are predictive of white matter microstructural change over 18months.

METHOD

Diffusion tensor imaging (DTI) data were analyzed for 28 pre-HD, 25 symp-HD, and 27 controls scanned at baseline and after 18months. Unbiased tract-based spatial statistics (TBSS) methods were used to identify longitudinal changes in fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD) of white matter. Stepwise linear regression models were used to identify baseline clinical, cognitive, and motor measures that are predictive of longitudinal diffusion changes.

RESULTS

Symp-HD compared to controls showed 18-month reductions in FA in the corpus callosum and cingulum white matter. Symp-HD compared to pre-HD showed increased RD in the corpus callosum and striatal projection pathways. FA in the body, genu, and splenium of the corpus callosum was significantly associated with a baseline clinical motor measure (Unified Huntington's Disease Rating Scale: total motor scores: UHDRS-TMS) across both HD groups. This measure was also the only independent predictor of longitudinal decline in FA in all parts of the corpus callosum across both HD groups.

CONCLUSIONS

We provide direct evidence of longitudinal decline in white matter microstructure in symp-HD. Although pre-HD did not show longitudinal change, clinical symptoms and motor function predicted white matter microstructural changes for all gene positive subjects. These findings suggest that loss of axonal integrity is an early hallmark of neurodegenerative changes which are clinically relevant.

JF, Carron SP, Ando A, Churchyard A, Chua P, Bohanna I, Dymowski AR, Poudel G, Egan GF. Functional magnetic resonance imaging of working memory in Huntington's disease: cross-sectional data from the IMAGE-HD study

We used functional magnetic resonance imaging (fMRI) to investigate spatial working memory (WM) in an N-BACK task (0, 1, and 2-BACK) in premanifest Huntington's disease (pre-HD, n = 35), early symptomatic Huntington's disease (symp-HD, n = 23), and control (n = 32) individuals. Overall, both WM conditions (1-BACK and 2-BACK) activated a large network of regions throughout the brain, common to all groups. However, voxel-wise and time-course analyses revealed significant functional group differences, despite no significant behavioral performance differences. During 1-BACK, voxel-wise blood-oxygen-level-dependent (BOLD) signal activity was significantly reduced in a number of regions from the WM network (inferior frontal gyrus, anterior insula, caudate, putamen, and cerebellum) in pre-HD and symp-HD groups, compared with controls; however, time-course analysis of the BOLD response in the dorsolateral prefrontal cortex (DLPFC) showed increased activation in symp-HD, compared with pre-HD and controls. The pattern of reduced voxel-wise BOLD activity in pre-HD and symp-HD, relative to controls, became more pervasive during 2-BACK affecting the same structures as in 1-BACK, but also incorporated further WM regions (anterior cingulate gyrus, parietal lobe and thalamus). The DLPFC BOLD time-course for 2-BACK showed a reversed pattern to that observed in 1-BACK, with a significantly diminished signal in symp-HD, relative to pre-HD and controls. Our findings provide support for functional brain reorganisation in cortical and subcortical regions in both pre-HD and symp-HD, which are modulated by task difficulty. Moreover, the lack of a robust striatal BOLD signal in pre-HD may represent a very early signature of change observed up to 15 years prior to clinical diagnosis.

The multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) high performance computing infrastructure: applications in neuroscience and neuroinformatics research

The Multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) is a national imaging and visualization facility established by Monash University, the Australian Synchrotron, the Commonwealth Scientific Industrial Research Organization (CSIRO), and the Victorian Partnership for Advanced Computing (VPAC), with funding from the National Computational Infrastructure and the Victorian Government. The MASSIVE facility provides hardware, software, and expertise to drive research in the biomedical sciences, particularly advanced brain imaging research using synchrotron x-ray and infrared imaging, functional and structural magnetic resonance imaging (MRI), x-ray computer tomography (CT), electron microscopy and optical microscopy. The development of MASSIVE has been based on best practice in system integration methodologies, frameworks, and architectures. The facility has: (i) integrated multiple different neuroimaging analysis software components, (ii) enabled cross-platform and cross-modality integration of neuroinformatics tools, and (iii) brought together neuroimaging databases and analysis workflows. MASSIVE is now operational as a nationally distributed and integrated facility for neuroinfomatics and brain imaging research.

Abnormal synchrony of resting state networks in premanifest and symptomatic Huntington disease: the IMAGE-HD study

BACKGROUND

Functional neural impairments have been documented in people with symptomatic Huntington disease (symp-HD) and in premanifest gene carriers (pre-HD). This study aimed to characterize synchrony in resting state cerebral networks in both pre-HD and symp-HD populations and to determine its association with disease burden and neurocognitive functions.

METHODS

We acquired functional magnetic resonance imaging (fMRI) data from pre-HD, symp-HD and healthy control participants. The fMRI data were analyzed using multisubject independent component analysis and dual regression. We compared networks of interest among the groups using a nonparametric permutation method and correcting for multiple comparisons.

RESULTS

Our study included 25 people in the pre-HD, 23 in the symp-HD and 18 in the healthy control groups. Compared with the control group, the pre-HD group showed decreased synchrony in the sensorimotor and dorsal attention networks; decreased level of synchrony in the sensorimotor network was associated with poorer motor performance. Compared with the control group, the symp-HD group showed widespread reduction in synchrony in the dorsal attention network, which was associated with poorer cognitive performance. The posterior putamen and superior parietal cortex were functionally disconnected from the frontal executive network in the symp-HD compared with control and pre-HD groups. Furthermore, the left frontoparietal network showed areas of increased synchrony in the symp-HD compared with the pre-HD group.

LIMITATIONS

We could not directly correct for influence of autonomic changes (e.g., heart rate) and respiration on resting state synchronization.

CONCLUSION

Our findings suggest that aberrant synchrony in the sensorimotor and dorsal attention networks may serve as an early signature of neural change in pre-HD individuals. The altered synchrony in dorsal attention, frontoparietal and corticostriatal networks may contribute to the development of clinical symptoms in people with Huntington disease.

Comparison of different EHG feature selection methods for the detection of preterm labor

Numerous types of linear and nonlinear features have been extracted from the electrohysterogram (EHG) in order to classify labor and pregnancy contractions. As a result, the number of available features is now very large. The goal of this study is to reduce the number of features by selecting only the relevant ones which are useful for solving the classification problem. This paper presents three methods for feature subset selection that can be applied to choose the best subsets for classifying labor and pregnancy contractions: an algorithm using the Jeffrey divergence (JD) distance, a sequential forward selection (SFS) algorithm, and a binary particle swarm optimization (BPSO) algorithm. The two last methods are based on a classifier and were tested with three types of classifiers. These methods have allowed us to identify common features which are relevant for contraction classification.

The evolving role of diffusion magnetic resonance imaging in movement disorders

Significant advances have allowed diffusion magnetic resonance imaging (MRI) to evolve into a powerful tool in the field of movement disorders that can be used to study disease states and connectivity between brain regions. Diffusion MRI is a promising potential biomarker for Parkinson's disease and other forms of parkinsonism, and may allow the distinction of different forms of parkinsonism. Techniques such as tractography have contributed to our current thinking regarding the pathophysiology of dystonia and possible mechanisms of penetrance. Diffusion MRI measures could potentially assist in monitoring disease progression in Huntington's disease, and in uncovering the nature of the processes and structures involved the development of essential tremor. The ability to represent structural connectivity in vivo also makes diffusion MRI an ideal adjunctive tool for the surgical treatment of movement disorders. We review recent studies using diffusion MRI in movement disorders research and present the current state of the science as well as future directions.

Multi-modal neuroimaging in premanifest and early Huntington's disease: 18 month longitudinal data from the IMAGE-HD study

IMAGE-HD is an Australian based multi-modal longitudinal magnetic resonance imaging (MRI) study in premanifest and early symptomatic Huntington's disease (pre-HD and symp-HD, respectively). In this investigation we sought to determine the sensitivity of imaging methods to detect macrostructural (volume) and microstructural (diffusivity) longitudinal change in HD. We used a 3T MRI scanner to acquire T1 and diffusion weighted images at baseline and 18 months in 31 pre-HD, 31 symp-HD and 29 controls. Volume was measured across the whole brain, and volume and diffusion measures were ascertained for caudate and putamen. We observed a range of significant volumetric and, for the first time, diffusion changes over 18 months in both pre-HD and symp-HD, relative to controls, detectable at the brain-wide level (volume change in grey and white matter) and in caudate and putamen (volume and diffusivity change). Importantly, longitudinal volume change in the caudate was the only measure that discriminated between groups across all stages of disease: far from diagnosis (>15 years), close to diagnosis (<15 years) and after diagnosis. Of the two diffusion metrics (mean diffusivity, MD; fractional anisotropy, FA), only longitudinal FA change was sensitive to group differences, but only after diagnosis. These findings further confirm caudate atrophy as one of the most sensitive and early biomarkers of neurodegeneration in HD. They also highlight that different tissue properties have varying schedules in their ability to discriminate between groups along disease progression and may therefore inform biomarker selection for future therapeutic interventions.

Longitudinal analysis of the electroencephalogram and sleep phenotype in the R6/2 mouse model of Huntington's disease

Deficits in sleep and circadian organization have been identified as common early features in patients with Huntington's disease that correlate with symptom severity and may be instrumental in disease progression. Studies in Huntington's disease gene carriers suggest that alterations in the electroencephalogram may reflect underlying neuronal dysfunction that is present in the premanifest stage. We conducted a longitudinal characterization of sleep/wake and electroencephalographic activity in the R6/2 mouse model of Huntington's disease to determine whether analogous electroencephalographic 'signatures' could be identified early in disease progression. R6/2 and wild-type mice were implanted for electroencephalographic recordings along with telemetry for the continuous recording of activity and body temperature. Diurnal patterns of activity and core body temperature were progressively disrupted in R6/2 mice, with a large reduction in the amplitude of these rhythms apparent by 13 weeks of age. The diurnal variation in sleep/wake states was gradually attenuated as sleep became more fragmented and total sleep time was reduced relative to wild-type mice. These genotypic differences were augmented at 17 weeks and evident across the entire 24-h period. Quantitative electroencephalogram analysis revealed anomalous increases in high beta and gamma activity (25-60 Hz) in all sleep/wake states in R6/2 mice, along with increases in theta activity during both non-rapid eye movement and rapid eye movement sleep and a reduction of delta power in non-rapid eye movement sleep. These dramatic alterations in quantitative electroencephalographic measures were apparent from our earliest recording (9 weeks), before any major differences in diurnal physiology or sleep/wake behaviour occurred. In addition, the homeostatic response to sleep deprivation was greatly attenuated with disease progression. These findings demonstrate the sensitivity of quantitative electroencephalographic analysis to identify early pathophysiological alterations in the R6/2 model of Huntington's disease and suggest longitudinal studies in other preclinical Huntington's disease models are needed to determine the generality of these observations as a potential adjunct in therapeutic development.

Structural MRI in Huntington's disease and recommendations for its potential use in clinical trials

Huntington's disease (HD) results in progressive impairment of motor and cognitive function and neuropsychiatric disturbance. There are no disease-modifying treatments available, but HD research is entering a critical phase where promising disease-specific therapies are on the horizon. Thus, a pressing need exists for biomarkers capable of monitoring progression and ultimately determining drug efficacy. Neuroimaging provides a powerful tool for assessing disease progression. However, in order to be accepted as biomarkers for clinical trials, imaging measures must be reproducible, robust to scanner differences, sensitive to disease-related change and demonstrate a relationship to clinically meaningful measures. We provide a review of the current structural imaging literature in HD and highlight inconsistencies between studies. We make recommendations for the standardisation of reporting for future studies, such as appropriate cohort characterisation and documentation of methodologies to facilitate comparisons and inform trial design. We also argue for an intensified effort to consider issues highlighted here so that we have the best chance of assessing the efficacy of the therapeutic benefit in forestalling this devastating disease.