Brain structure and function in Huntington's disease gene carriers far from predicted disease onset

Whilst there are currently no available disease modifying therapies for Huntington’s Disease (HD), recent progress in huntingtin-lowering strategies hold great promise. Initiating therapies early in the disease course will be important and a complete characterisation of the premanifest period will help inform when to initiate disease modifying therapies and the biomarkers that may be useful in such trials. Previous research has characterised the premanifest period up to approximately 15 years from predicted onset, but even at this early stage the disease process is already underway as evidenced by striatal and white matter atrophy, reductions in structural connectivity within brain networks, rising biofluid biomarkers of neuronal dysfunction, elevations in psychiatric symptoms and emerging subtle cognitive impairments. In order to understand how early neurodegeneration can be detected and which measures are most sensitive to the early disease processes, we need to look even earlier in the disease course. This thesis documents the recruitment and analysis of the HD Young Adult Study: a premanifest cohort further from predicted clinical onset than previously studied with an average of 24 years prior to predicted onset. Differences between gene carriers and controls were examined across a range of imaging, cognitive, neuropsychiatric and biofluid measures. The structural and functional brain connectivity in this cohort is then investigated in further detail. By providing a detailed characterisation of brain structure and function in the early premanifest period along with the most sensitive biomarkers at this stage, this work will inform future treatment strategies that may seek to delay the onset of functional impairments in HD

Dynamic Changes in White Matter Abnormalities Correlate With Late Improvement and Deterioration Following TBI: A Diffusion Tensor Imaging Study.

OBJECTIVE: Traumatic brain injury (TBI) is not a single insult with monophasic resolution, but a chronic disease, with dynamic processes that remain active for years. We aimed to assess patient trajectories over the entire disease narrative, from ictus to late outcome. METHODS: Twelve patients with moderate-to-severe TBI underwent magnetic resonance imaging in the acute phase (within 1 week of injury) and twice in the chronic phase of injury (median 7 and 21 months), with some undergoing imaging at up to 2 additional time points. Longitudinal imaging changes were assessed using structural volumetry, deterministic tractography, voxel-based diffusion tensor analysis, and region of interest analyses (including corpus callosum, parasagittal white matter, and thalamus). Imaging changes were related to behavior. RESULTS: Changes in structural volumes, fractional anisotropy, and mean diffusivity continued for months to years postictus. Changes in diffusion tensor imaging were driven by increases in both axial and radial diffusivity except for the earliest time point, and were associated with changes in reaction time and performance in a visual memory and learning task (paired associates learning). Dynamic structural changes after TBI can be detected using diffusion tensor imaging and could explain changes in behavior. CONCLUSIONS: These data can provide further insight into early and late pathophysiology, and begin to provide a framework that allows magnetic resonance imaging to be used as an imaging biomarker of therapy response. Knowledge of the temporal pattern of changes in TBI patient populations also provides a contextual framework for assessing imaging changes in individuals at any given time point

Peripheral Blood and Salivary Biomarkers of Blood-Brain Barrier Permeability and Neuronal Damage:Clinical and Applied Concepts

International audienceWithin the neurovascular unit (NVU), the blood-brain barrier (BBB) operates as a key cerebrovascular interface, dynamically insulating the brain parenchyma from peripheral blood and compartments. Increased BBB permeability is clinically relevant for at least two reasons: it actively participates to the etiology of central nervous system (CNS) diseases, and it enables the diagnosis of neurological disorders based on the detection of CNS molecules in peripheral body fluids. In pathological conditions, a suite of glial, neuronal, and pericyte biomarkers can exit the brain reaching the peripheral blood and, after a process of filtration, may also appear in saliva or urine according to varying temporal trajectories. Here, we specifically examine the evidence in favor of or against the use of protein biomarkers of NVU damage and BBB permeability in traumatic head injury, including sport (sub)concussive impacts, seizure disorders, and neurodegenerative processes such as Alzheimer's disease. We further extend this analysis by focusing on the correlates of human extreme physiology applied to the NVU and its biomarkers. To this end, we report NVU changes after prolonged exercise, freediving, and gravitational stress, focusing on the presence of peripheral biomarkers in these conditions. The development of a biomarker toolkit will enable minimally invasive routines for the assessment of brain health in a broad spectrum of clinical, emergency, and sport settings

A critical review of white matter changes in Huntington’s disease

Huntington’s disease is a genetic neurodegenerative disorder. White matter alterations have recently been identified as a relevant pathophysiological feature of Huntington’s disease, but their etiology and role in disease pathogenesis and progression remain unclear. Increasing evidence suggests that white matter changes in this disorder are due to alterations in myelin-associated biological processes. This review first discusses evidence from neurochemical studies lending support to the ‘De-myelination hypothesis’ of Huntington’s disease, and demonstrating aberrant myelination and changes in oligodendrocytes in the Huntington’s brain. Next, evidence from neuroimaging studies is reviewed, the limitations of the described methodologies are discussed, and suggested interpretations of findings from published studies are challenged. Although our understanding of Huntington’s associated pathological changes in the brain will increasingly rely on neuroimaging techniques, the shortcomings of these methodologies must not be forgotten. Advances in MRI techniques and tissue modeling will enable a better in vivo, longitudinal characterization of the biological properties of white matter microstructure. This, in turn, will facilitate identification of disease-related biomarkers and the specification of outcome measures in clinical trials

One-year changes in brain microstructure differentiate preclinical Huntington's disease stages.

OBJECTIVE: To determine whether brain imaging markers of tissue microstructure can detect the effect of disease progression across the preclinical stages of Huntington's disease. METHODS: Longitudinal microstructural changes in diffusion imaging metrics (mean diffusivity and fractional anisotropy) were investigated in participants with presymptomatic Huntington's disease (N = 35) stratified into three preclinical subgroups according to their estimated time until onset of symptoms, compared with age- and gender-matched healthy controls (N = 19) over a 1y period. RESULTS: Significant differences were found over the four groups in change of mean diffusivity in the posterior basal ganglia and the splenium of the corpus callosum. This overall effect was driven by significant differences between the group far-from-onset (FAR) of symptoms and the groups midway- (MID) and near-the-onset (NEAR) of symptoms. In particular, an initial decrease of mean diffusivity in the FAR group was followed by a subsequent increase in groups closer to onset of symptoms. The seemingly counter-intuitive decrease of mean diffusivity in the group furthest from onset of symptoms might be an early indicator of neuroinflammatory process preceding the neurodegenerative phase. In contrast, the only clinical measure that was able to capture a difference in 1y changes between the preclinical stages was the UHDRS confidence in motor score. CONCLUSIONS: With sensitivity to longitudinal changes in brain microstructure within and between preclinical stages, and potential differential response to distinct pathophysiological mechanisms, diffusion imaging is a promising state marker for monitoring treatment response and identifying the optimal therapeutic window of opportunity in preclinical Huntington's disease

Analytic Tools for Post-traumatic Epileptogenesis Biomarker Search in Multimodal Dataset of an Animal Model and Human Patients

Epilepsy is among the most common serious disabling disorders of the brain, and the global burden of epilepsy exerts a tremendous cost to society. Most people with epilepsy have acquired forms of the disorder, and the development of antiepileptogenic interventions could potentially prevent or cure epilepsy in many of them. However, the discovery of potential antiepileptogenic treatments and clinical validation would require a means to identify populations of patients at very high risk for epilepsy after a potential epileptogenic insult, to know when to treat and to document prevention or cure. A fundamental challenge in discovering biomarkers of epileptogenesis is that this process is likely multifactorial and crosses multiple modalities. Investigators must have access to a large number of high quality, well-curated data points and study subjects for biomarker signals to be detectable above the noise inherent in complex phenomena, such as epileptogenesis, traumatic brain injury (TBI), and conditions of data collection. Additionally, data generating and collecting sites are spread worldwide among different laboratories, clinical sites, heterogeneous data types, formats, and across multi-center preclinical trials. Before the data can even be analyzed, these data must be standardized. The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) is a multi-center project with the overarching goal that epileptogenesis after TBI can be prevented with specific treatments. The identification of relevant biomarkers and performance of rigorous preclinical trials will permit the future design and performance of economically feasible full-scale clinical trials of antiepileptogenic therapies. We have been analyzing human data collected from UCLA and rat data collected from the University of Eastern Finland, both centers collecting data for EpiBioS4Rx, to identify biomarkers of epileptogenesis. Big data techniques and rigorous analysis are brought to longitudinal data collected from humans and an animal model of TBI, epilepsy, and their interaction. The prolonged continuous data streams of intracranial, cortical surface, and scalp EEG from humans and an animal model of epilepsy span months. By applying our innovative mathematical tools via supervised and unsupervised learning methods, we are able to subject a robust dataset to recently pioneered data analysis tools and visualize multivariable interactions with novel graphical methods

Macroscale imaging: a potential biomarker for post stroke functional outcome?

To determine whether long-term functional outcomes in stroke patients can be predicted by the amount of acutely damaged white matter tracts. We collected acute behavioral and neuroimaging data from a group of first-time stroke patients and add those from the other(s) databases. (n=114 + n) within one week (check with the other DBs) post-stroke. Functional outcome was telephonically evaluated using the Stroke Impact Scale 3.0 at 12 months post-stroke. For each patient, we calculated the absolute number of white matter tracts affected by the ischemic lesion from our anatomical scans. We measured a numerical index that considers white matter tract density (WMTD index). We compared the ability of the WMTD index, considered individually, or within a series of prediction models including demographics and behavioral data), to predict chronic outcomes. Multiple linear regression was used to assess the quality of prediction of the most informative model.To determine whether long-term functional outcomes in stroke patients can be predicted by the amount of acutely damaged white matter tracts. We collected acute behavioral and neuroimaging data from a group of first-time stroke patients and add those from the other(s) databases. (n=114 + n) within one week (check with the other DBs) post-stroke. Functional outcome was telephonically evaluated using the Stroke Impact Scale 3.0 at 12 months post-stroke. For each patient, we calculated the absolute number of white matter tracts affected by the ischemic lesion from our anatomical scans. We measured a numerical index that considers white matter tract density (WMTD index). We compared the ability of the WMTD index, considered individually, or within a series of prediction models including demographics and behavioral data), to predict chronic outcome. Multiple linear regression was used to assess the quality of prediction of the most informative model

Imaging Pain And Brain Plasticity: A Longitudinal Structural Imaging Study

Chronic musculoskeletal pain is a leading cause of disability worldwide yet the mechanisms of chronification and neural responses to effective treatment remain elusive. Non-invasive imaging techniques are useful for investigating brain alterations associated with health and disease. Thus the overall goal of this dissertation was to investigate the white (WM) and grey matter (GM) structural differences in patients with musculoskeletal pain before and after psychotherapeutic intervention: cognitive behavioral therapy (CBT). To aid in the interpretation of clinical findings, we used a novel porcine model of low back pain-like pathophysiology and developed a post-mortem, in situ, neuroimaging approach to facilitate translational investigation. The first objective of this dissertation (Chapter 2) was to identify structural brain alterations in chronic pain patients compared to healthy controls. To achieve this, we examined GM volume and diffusivity as well as WM metrics of complexity, density, and connectivity. Consistent with the literature, we observed robust differences in GM volume across a number of brain regions in chronic pain patients, however, findings of increased GM volume in several regions are in contrast to previous reports. We also identified WM changes, with pain patients exhibiting reduced WM density in tracts that project to descending pain modulatory regions as well as increased connectivity to default mode network structures, and bidirectional alterations in complexity. These findings may reflect network level dysfunction in patients with chronic pain. The second aim (Chapter 3) was to investigate reversibility or neuroplasticity of structural alterations in the chronic pain brain following CBT compared to an active control group. Longitudinal evaluation was carried out at baseline, following 11-week intervention, and a four-month follow-up. Similarly, we conducted structural brain assessments including GM morphometry and WM complexity and connectivity. We did not observe GM volumetric or WM connectivity changes, but we did discover differences in WM complexity after therapy and at follow-up visits. To facilitate mechanistic investigation of pain related brain changes, we used a novel porcine model of low back pain-like pathophysiology (Chapter 6). This model replicates hallmarks of chronic pain, such as soft tissue injury and movement alteration. We also developed a novel protocol to perform translational post-mortem, in situ, neuroimaging in our porcine model to reproduce WM and GM findings observed in humans, followed by a unique perfusion and immersion fixation protocol to enable histological assessment (Chapter 4). In conclusion, our clinical data suggest robust structural brain alterations in patients with chronic pain as compared to healthy individuals and in response to therapeutic intervention. However, the mechanism of these brain changes remains unknown. Therefore, we propose to use a porcine model of musculoskeletal pain with a novel neuroimaging protocol to promote mechanistic investigation and expand our interpretation of clinical findings

Consensus Paper: Radiological Biomarkers of Cerebellar Diseases

Hereditary and sporadic cerebellar ataxias represent a vast and still growing group of diseases whose diagnosis and differentiation cannot only rely on clinical evaluation. Brain imaging including magnetic resonance (MR) and nuclear medicine techniques allows for characterization of structural and functional abnormalities underlying symptomatic ataxias. These methods thus constitute a potential source of radiological biomarkers, which could be used to identify these diseases and differentiate subgroups of them, and to assess their severity and their evolution. Such biomarkers mainly comprise qualitative and quantitative data obtained from MR including proton spectroscopy, diffusion imaging, tractography, voxel-based morphometry, functional imaging during task execution or in a resting state, and from SPETC and PET with several radiotracers. In the current article, we aim to illustrate briefly some applications of these neuroimaging tools to evaluation of cerebellar disorders such as inherited cerebellar ataxia, fetal developmental malformations, and immune-mediated cerebellar diseases and of neurodegenerative or early-developing diseases, such as dementia and autism in which cerebellar involvement is an emerging feature. Although these radiological biomarkers appear promising and helpful to better understand ataxia-related anatomical and physiological impairments, to date, very few of them have turned out to be specific for a given ataxia with atrophy of the cerebellar system being the main and the most usual alteration being observed. Consequently, much remains to be done to establish sensitivity, specificity, and reproducibility of available MR and nuclear medicine features as diagnostic, progression and surrogate biomarkers in clinical routine

Diffusion Tensor Imaging of the Central Nervous System Following an Injury to the Spinal Cord and Cell Transplant

The purpose of this dissertation research was to characterize the use of magnetic resonance diffusion tensor imaging (DTI) as a diagnostic and prognostic tool in understanding the changes that occur throughout the spinal cord and brain following a spinal cord injury (SCI) and following stem cell transplant. The diffusion of water inside the nervous system is dramatically altered around the lesion site following a traumatic SCI. However, following damage to the spinal cord, little is known about the diffusion characteristics away from an injury and even less is understood about DTI\u27s sensitivity to structural changes that occur following regenerative transplant therapies. The non-invasive nature of DTI could potentially allow for diagnostic and prognostic indicators of an SCI remote from injury and could provide physicians a method for tracking and monitoring the effectiveness of injected stem cells. To evaluate the sensitivity of DTI to structural changes in the central nervous system (CNS) following a traumatic SCI, diffusion metrics in the brain and cervical spinal cord were compared for four different injury severities in a thoracic contusion model of a rat SCI. Structural changes in the cervical region of the spinal cord after transplantation of C17.2 neuronal stem cells were also examined with the use of DTI. The findings from this dissertation suggest that diffusion tensor imaging is sensitive to changes in tissue structure in regions remote from injury and for cellular environments that increased astrocytic sprouting as a result of stem cell transplant. Mean water diffusion in the distal locations of the spinal cord and in the brain decreased following SCI. Neuronal stem cells that are known to elicit astrocytic proliferation produced mean increases in water diffusion. These results further clarify the potential for DTI to provide physicians a method to non-invasively monitor how the CNS changes following SCI and detec