Genetic topography and cortical cell loss in Huntington's disease link development and neurodegeneration

Cortical cell loss is a core feature of Huntington's disease (HD), beginning many years before clinical motor diagnosis, during the premanifest stage. However, it is unclear how genetic topography relates to cortical cell loss. Here, we explore the biological processes and cell types underlying this relationship and validate these using cell-specific post-mortem data. Eighty premanifest participants on average 15 years from disease onset and 71 controls were included. Using volumetric and diffusion MRI we extracted HD-specific whole brain maps where lower grey matter volume and higher grey matter mean diffusivity, relative to controls, were used as proxies of cortical cell loss. These maps were combined with gene expression data from the Allen Human Brain Atlas (AHBA) to investigate the biological processes relating genetic topography and cortical cell loss. Cortical cell loss was positively correlated with the expression of developmental genes (i.e. higher expression correlated with greater atrophy and increased diffusivity) and negatively correlated with the expression of synaptic and metabolic genes that have been implicated in neurodegeneration. These findings were consistent for diffusion MRI and volumetric HD-specific brain maps. As wild-type huntingtin is known to play a role in neurodevelopment, we explored the association between wild-type huntingtin (HTT) expression and developmental gene expression across the AHBA. Co-expression network analyses in 134 human brains free of neurodegenerative disorders were also performed. HTT expression was correlated with the expression of genes involved in neurodevelopment while co-expression network analyses also revealed that HTT expression was associated with developmental biological processes. Expression weighted cell-type enrichment (EWCE) analyses were used to explore which specific cell types were associated with HD cortical cell loss and these associations were validated using cell specific single nucleus RNAseq (snRNAseq) data from post-mortem HD brains. The developmental transcriptomic profile of cortical cell loss in preHD was enriched in astrocytes and endothelial cells, while the neurodegenerative transcriptomic profile was enriched for neuronal and microglial cells. Astrocyte-specific genes differentially expressed in HD post-mortem brains relative to controls using snRNAseq were enriched in the developmental transcriptomic profile, while neuronal and microglial-specific genes were enriched in the neurodegenerative transcriptomic profile. Our findings suggest that cortical cell loss in preHD may arise from dual pathological processes, emerging as a consequence of neurodevelopmental changes, at the beginning of life, followed by neurodegeneration in adulthood, targeting areas with reduced expression of synaptic and metabolic genes. These events result in age-related cell death across multiple brain cell types.

Quantitative MRI maps of human neocortex explored using cell type-specific gene expression analysis

Quantitative magnetic resonance imaging (qMRI) allows extraction of reproducible and robust parameter maps. However, the connection to underlying biological substrates remains murky, especially in the complex, densely packed cortex. We investigated associations in human neocortex between qMRI parameters and neocortical cell types by comparing the spatial distribution of the qMRI parameters longitudinal relaxation rate (${R_{1}}$), effective transverse relaxation rate (${R_{2}}^{\ast }$), and magnetization transfer saturation (MTsat) to gene expression from the Allen Human Brain Atlas, then combining this with lists of genes enriched in specific cell types found in the human brain. As qMRI parameters are magnetic field strength-dependent, the analysis was performed on MRI data at 3T and 7T. All qMRI parameters significantly covaried with genes enriched in GABA- and glutamatergic neurons, i.e. they were associated with cytoarchitecture. The qMRI parameters also significantly covaried with the distribution of genes enriched in astrocytes (${R_{2}}^{\ast }$ at 3T, ${R_{1}}$ at 7T), endothelial cells (${R_{1}}$ and MTsat at 3T), microglia (${R_{1}}$ and MTsat at 3T, ${R_{1}}$ at 7T), and oligodendrocytes and oligodendrocyte precursor cells (${R_{1}}$ at 7T). These results advance the potential use of qMRI parameters as biomarkers for specific cell types.

Neurofilament light-associated connectivity in young-adult Huntington's disease is related to neuronal genes

Upregulation of functional network connectivity in the presence of structural degeneration is seen in the premanifest stages of Huntington's disease (preHD) 10-15 years from clinical diagnosis. However, whether widespread network connectivity changes are seen in gene carriers much further from onset has yet to be explored. We characterized functional network connectivity throughout the brain and related it to a measure of disease pathology burden (CSF neurofilament light, NfL) and measures of structural connectivity in asymptomatic gene carriers, on average 24 years from onset. We related these measurements to estimates of cortical and subcortical gene expression. We found no overall differences in functional (or structural) connectivity anywhere in the brain comparing control and preHD participants. However, increased functional connectivity, particularly between posterior cortical areas, correlated with increasing CSF NfL level in preHD participants. Using the Allen Human Brain Atlas and expression-weighted cell-type enrichment analysis, we demonstrated that this functional connectivity upregulation occurred in cortical regions associated with regional expression of genes specific to neuronal cells. This relationship was validated using single-nucleus RNAseq data from post-mortem Huntington's disease and control brains showing enrichment of neuronal-specific genes that are differentially expressed in Huntington's disease. Functional brain networks in asymptomatic preHD gene carriers very far from disease onset show evidence of upregulated connectivity correlating with increased disease burden. These changes occur among brain areas that show regional expression of genes specific to neuronal GABAergic and glutamatergic cells.

Changes in dynamic transitions between integrated and segregated states underlie visual hallucinations in Parkinson's disease

Hallucinations are a core feature of psychosis and common in Parkinson's. Their transient, unexpected nature suggests a change in dynamic brain states, but underlying causes are unknown. Here, we examine temporal dynamics and underlying structural connectivity in Parkinson's-hallucinations using a combination of functional and structural MRI, network control theory, neurotransmitter density and genetic analyses. We show that Parkinson's-hallucinators spent more time in a predominantly Segregated functional state with fewer between-state transitions. The transition from integrated-to-segregated state had lower energy cost in Parkinson's-hallucinators; and was therefore potentially preferable. The regional energy needed for this transition was correlated with regional neurotransmitter density and gene expression for serotoninergic, GABAergic, noradrenergic and cholinergic, but not dopaminergic, receptors. We show how the combination of neurochemistry and brain structure jointly shape functional brain dynamics leading to hallucinations and highlight potential therapeutic targets by linking these changes to neurotransmitter systems involved in early sensory and complex visual processing.

128 White matter fibre loss in Parkinson’s disease hallucinations

References

Weil,et al. Visual dysfunction in Parkinson’s disease.Brain2016 Jul 13.

Raffelt,et al. Investigating white matter fibre density and morphology using fixel-based analysis.Neu- roimage2017;144:58–73.

a.zarkali@ucl.ac.uk

129 Network controllability and regional gene expression explain visual hallucinations in Parkinson’s

Reference

Shine,et al. The role of dysfunctional attentional control networks in visual misperceptions in Parkinson’s disease. HumBrainMapp;2014.

a.zarkali@ucl.ac.uk

Visual dysfunction predicts cognitive impairment and white matter degenera- tion in Parkinson’s disease

Introduction

Visual dysfunction predicts Parkinson’s dementia but whether this translates to structural change is not known. We aimed to identify longitudinal white matter changes in Parkinson’s with low visual function and those who developed mild cognitive impairment(MCI).

Methods

We used fixel-based analysis to examine longitudinal white matter change in Parkinson’s. Diffusion MRI and clinical assessments were performed in 77 patients (22 low/55 high visual performers; and 13 MCI/51 normal cognition) and 25 controls at baseline and after 18 months. We compared micro-structural changes in fibre density, macro-structural changes in fibre cross-section and combined fibre density and cross-section across white matter, adjusting for age, gender and intracranial volume.

Results

Parkinson’s with low visual performance showed worse cognition at follow-up (r=-0.386, p-0.024) and were more likely to develop MCI than those with normal vision (p=0.008). Parkinson’s with poor visual function showed diffuse micro-structural and macro-structural changes at baseline, whereas those with MCI showed fewer baseline changes. At follow-up, Parkinson’s with low visual function showed wide- spread macrostructural changes with up to 22% further reductions in fibre cross-section, involving the fronto-occipital fasciculi, external capsules, and middle cerebellar peduncles bilaterally. No longitudinal change was seen in baseline MCI or in MCI converters, even when combining the two groups.

Conclusions

Parkinson’s with poor visual function show increased white matter damage over time, providing further evidence for visual function as a marker of imminent cognitive decline.

a.zarkali@ucl.ac.uk

Timing of selective basal ganglia white matter loss in premanifest Huntington's disease

OBJECTIVES

To investigate the timeframe prior to symptom onset when cortico-basal ganglia white matter (white matter) loss begins in premanifest Huntington's disease (preHD), and which striatal and thalamic sub-region white matter tracts are most vulnerable.

METHODS

We performed fixel-based analysis, which allows resolution of crossing white matter fibres at the voxel level, on diffusion tractography derived white matter tracts of striatal and thalamic sub-regions in two independent cohorts; TrackON-HD, which included 72 preHD (approx. 11 years before disease onset) and 85 controls imaged at three time points over two years; and the HD young adult study (HD-YAS), which included 54 preHD (approx. 25 years before disease onset) and 53 controls, imaged at one time point. Group differences in fibre density and cross section (FDC) were investigated.

RESULTS

We found no significant group differences in cortico-basal ganglia sub-region FDC in preHD gene carriers 25 years before onset. In gene carriers 11 years before onset, there were reductions in striatal (limbic and caudal motor) and thalamic (premotor, motor and sensory) FDC at baseline, with no significant change over 2 years. Caudal motor-striatal, pre-motor-thalamic, and primary motor-thalamic FDC at baseline, showed significant correlations with the Unified Huntington's disease rating scale (UHDRS) total motor score (TMS). Limbic cortico-striatal FDC and apathy were also significantly correlated.

CONCLUSIONS

Our findings suggest that limbic and motor white matter tracts to the striatum and thalamus are most susceptible to early degeneration in HD but that approximately 25 years from onset, these tracts appear preserved. These findings may have importance in determining the optimum time to initiate future disease modifying therapies in HD.

Longitudinal thalamic white and grey matter changes associated with visual hallucinations in Parkinson's disease

OBJECTIVE

Visual hallucinations are common in Parkinson's disease (PD) and associated with worse outcomes. Large-scale network imbalance is seen in PD-associated hallucinations, but mechanisms remain unclear. As the thalamus is critical in controlling cortical networks, structural thalamic changes could underlie network dysfunction in PD hallucinations.

METHODS

We used whole-brain fixel-based analysis and cortical thickness measures to examine longitudinal white and grey matter changes in 76 patients with PD (15 hallucinators, 61 non-hallucinators) and 26 controls at baseline, and after 18 months. We compared white matter and cortical thickness, adjusting for age, gender, time-between-scans and intracranial volume. To assess thalamic changes, we extracted volumes for 50 thalamic subnuclei (25 each hemisphere) and mean fibre cross-section (FC) for white matter tracts originating in each subnucleus and examined longitudinal change in PD-hallucinators versus non-hallucinators.

RESULTS

PD hallucinators showed white matter changes within the corpus callosum at baseline and extensive posterior tract involvement over time. Less extensive cortical thickness changes were only seen after follow-up. White matter connections from the right medial mediodorsal magnocellular thalamic nucleus showed reduced FC in PD hallucinators at baseline followed by volume reductions longitudinally. After follow-up, almost all thalamic subnuclei showed tract losses in PD hallucinators compared with non-hallucinators.

INTERPRETATION

PD hallucinators show white matter loss particularly in posterior connections and in thalamic nuclei, over time with relatively preserved cortical thickness. The right medial mediodorsal thalamic nucleus shows both connectivity and volume loss in PD hallucinations. Our findings provide mechanistic insights into the drivers of network imbalance in PD hallucinations and potential therapeutic targets.

Relating quantitative 7T MRI across cortical depths to cytoarchitectonics, gene expression and connectomics

Ultra-high field MRI across the depth of the cortex has the potential to provide anatomically precise biomarkers and mechanistic insights into neurodegenerative disease like Huntington's disease that show layer-selective vulnerability. Here we compare multi-parametric mapping (MPM) measures across cortical depths for a 7T 500 μm whole brain acquisition to (a) layer-specific cell measures from the von Economo histology atlas, (b) layer-specific gene expression, using the Allen Human Brain atlas and (c) white matter connections using high-fidelity diffusion tractography, at a 1.3 mm isotropic voxel resolution, from a 300mT/m Connectom MRI system. We show that R2*, but not R1, across cortical depths is highly correlated with layer-specific cell number and layer-specific gene expression. R1- and R2*-weighted connectivity strength of cortico-striatal and intra-hemispheric cortical white matter connections was highly correlated with grey matter R1 and R2* across cortical depths. Limitations of the layer-specific relationships demonstrated are at least in part related to the high cross-correlations of von Economo atlas cell counts and layer-specific gene expression across cortical layers. These findings demonstrate the potential and limitations of combining 7T MPMs, gene expression and white matter connections to provide an anatomically precise framework for tracking neurodegenerative disease.

Regional brain iron and gene expression provide insights into neurodegeneration in Parkinson's disease

The mechanisms responsible for the selective vulnerability of specific neuronal populations in Parkinson's disease are poorly understood. Oxidative stress secondary to brain iron accumulation is one postulated mechanism. We measured iron deposition in 180 cortical regions of 96 patients with Parkinson's disease and 35 control subjects using quantitative susceptibility mapping. We estimated the expression of 15 745 genes in the same regions using transcriptomic data from the Allen Human Brain Atlas. Using partial least squares regression, we then identified the profile of gene transcription in the healthy brain that underlies increased cortical iron in patients with Parkinson's disease relative to controls. Applying gene ontological tools, we investigated the biological processes and cell types associated with this transcriptomic profile and identified the sets of genes with spatial expression profiles in control brains that correlated significantly with the spatial pattern of cortical iron deposition in Parkinson's disease. Gene ontological analyses revealed that these genes were enriched for biological processes relating to heavy metal detoxification, synaptic function and nervous system development and were predominantly expressed in astrocytes and glutamatergic neurons. Furthermore, we demonstrated that the genes differentially expressed in Parkinson's disease are associated with the pattern of cortical expression identified in this study. Our findings provide mechanistic insights into regional selective vulnerabilities in Parkinson's disease, particularly the processes involving iron accumulation.

Visual Dysfunction Predicts Cognitive Impairment and White Matter Degeneration in Parkinson's Disease

BACKGROUND

Visual dysfunction predicts dementia in Parkinson's disease (PD), but whether this translates to structural change is not known. The objectives of this study were to identify longitudinal white matter changes in patients with Parkinson's disease and low visual function and also in those who developed mild cognitive impairment.

METHODS

We used fixel-based analysis to examine longitudinal white matter change in PD. Diffusion MRI and clinical assessments were performed in 77 patients at baseline (22 low visual function/55 intact vision and 13 PD-mild cognitive impairment/51 normal cognition) and 25 controls and again after 18 months. We compared microstructural changes in fiber density, macrostructural changes in fiber bundle cross-section and combined fiber density and cross-section, across white matter, adjusting for age, sex, and intracranial volume.

RESULTS

Patients with PD and visual dysfunction showed worse cognitive performance at follow-up and were more likely to develop mild cognitive impairment compared with those with normal vision (P = 0.008). Parkinson's with poor visual function showed diffuse microstructural and macrostructural changes at baseline, whereas those with mild cognitive impairment showed fewer baseline changes. At follow-up, Parkinson's with low visual function showed widespread macrostructural changes, involving the fronto-occipital fasciculi, external capsules, and middle cerebellar peduncles bilaterally. No longitudinal change was seen in those with mild cognitive impairment at baseline or converters, even when the 2 groups were combined.

CONCLUSION

Parkinson's patients with poor visual function show increased white matter damage over time, providing further evidence for visual function as a marker of imminent cognitive decline. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Organisational and neuromodulatory underpinnings of structural-functional connectivity decoupling in patients with Parkinson's disease

Parkinson's dementia is characterised by changes in perception and thought, and preceded by visual dysfunction, making this a useful surrogate for dementia risk. Structural and functional connectivity changes are seen in humans with Parkinson's disease, but the organisational principles are not known. We used resting-state fMRI and diffusion-weighted imaging to examine changes in structural-functional connectivity coupling in patients with Parkinson's disease, and those at risk of dementia. We identified two organisational gradients to structural-functional connectivity decoupling: anterior-to-posterior and unimodal-to-transmodal, with stronger structural-functional connectivity coupling in anterior, unimodal areas and weakened towards posterior, transmodal regions. Next, we related spatial patterns of decoupling to expression of neurotransmitter receptors. We found that dopaminergic and serotonergic transmission relates to decoupling in Parkinson's overall, but instead, serotonergic, cholinergic and noradrenergic transmission relates to decoupling in patients with visual dysfunction. Our findings provide a framework to explain the specific disorders of consciousness in Parkinson's dementia, and the neurotransmitter systems that underlie these.

Differences in network controllability and regional gene expression underlie hallucinations in Parkinson's disease

Visual hallucinations are common in Parkinson's disease and are associated with poorer prognosis. Imaging studies show white matter loss and functional connectivity changes with Parkinson's visual hallucinations, but the biological factors underlying selective vulnerability of affected parts of the brain network are unknown. Recent models for Parkinson's disease hallucinations suggest they arise due to a shift in the relative effects of different networks. Understanding how structural connectivity affects the interplay between networks will provide important mechanistic insights. To address this, we investigated the structural connectivity changes that accompany visual hallucinations in Parkinson's disease and the organizational and gene expression characteristics of the preferentially affected areas of the network. We performed diffusion-weighted imaging in 100 patients with Parkinson's disease (81 without hallucinations, 19 with visual hallucinations) and 34 healthy age-matched controls. We used network-based statistics to identify changes in structural connectivity in Parkinson's disease patients with hallucinations and performed an analysis of controllability, an emerging technique that allows quantification of the influence a brain region has across the rest of the network. Using these techniques, we identified a subnetwork of reduced connectivity in Parkinson's disease hallucinations. We then used the Allen Institute for Brain Sciences human transcriptome atlas to identify regional gene expression patterns associated with affected areas of the network. Within this network, Parkinson's disease patients with hallucinations showed reduced controllability (less influence over other brain regions), than Parkinson's disease patients without hallucinations and controls. This subnetwork appears to be critical for overall brain integration, as even in controls, nodes with high controllability were more likely to be within the subnetwork. Gene expression analysis of gene modules related to the affected subnetwork revealed that down-weighted genes were most significantly enriched in genes related to mRNA and chromosome metabolic processes (with enrichment in oligodendrocytes) and upweighted genes to protein localization (with enrichment in neuronal cells). Our findings provide insights into how hallucinations are generated, with breakdown of a key structural subnetwork that exerts control across distributed brain regions. Expression of genes related to mRNA metabolism and membrane localization may be implicated, providing potential therapeutic targets.

Dementia risk in Parkinson's disease is associated with interhemispheric connectivity loss and determined by regional gene expression

Parkinson's dementia is a common and devastating part of Parkinson's disease. Whilst timing and severity vary, dementia in Parkinson's is often preceded by visual dysfunction. White matter changes, representing axonal loss, occur early in the disease process. Clarifying which white matter connections are affected in Parkinson's with visual dysfunction and why specific connections are vulnerable will provide important mechanistic insights. Here, we use diffusion tractography in 100 Parkinson's patients (33 low visual performers) and 34 controls to identify patterns of connectivity loss in Parkinson's with visual dysfunction. We examine the relationship between regional transcription and connectivity loss, using the Allen Institute for Brain Science transcriptome atlas. We show that interhemispheric connections are preferentially affected in Parkinson's low visual performers. Interhemispheric connection loss was associated with downweighted genes related to the smoothened signalling pathway (enriched in glutamatergic neurons) and upweighted metabolic genes. Risk genes for Parkinson's but not Alzheimer's or Dementia with Lewy bodies were over-represented in upweighted genes associated with interhemispheric connection loss. Our findings suggest selective vulnerability in Parkinson's patients at highest risk of dementia (those with visual dysfunction), where differences in gene expression and metabolic dysfunction, affecting longer connections with higher metabolic burden, drive connectivity loss.

The human motor cortex microcircuit: insights for neurodegenerative disease

The human motor cortex comprises a microcircuit of five interconnected layers with different cell types. In this Review, we use a layer-specific and cell-specific approach to integrate physiological accounts of this motor cortex microcircuit with the pathophysiology of neurodegenerative diseases affecting motor functions. In doing so we can begin to link motor microcircuit pathology to specific disease stages and clinical phenotypes. Based on microcircuit physiology, we can make future predictions of axonal loss and microcircuit dysfunction. With recent advances in high-resolution neuroimaging we can then test these predictions in humans in vivo, providing mechanistic insights into neurodegenerative disease.

Biological and clinical characteristics of gene carriers far from predicted onset in the Huntington's disease Young Adult Study (HD-YAS): a cross-sectional analysis

BACKGROUND

Disease-modifying treatments are in development for Huntington's disease; crucial to their success is to identify a timepoint in a patient's life when there is a measurable biomarker of early neurodegeneration while clinical function is still intact. We aimed to identify this timepoint in a novel cohort of young adult premanifest Huntington's disease gene carriers (preHD) far from predicted clinical symptom onset.

METHODS

We did the Huntington's disease Young Adult Study (HD-YAS) in the UK. We recruited young adults with preHD and controls matched for age, education, and sex to ensure each group had at least 60 participants with imaging data, accounting for scan fails. Controls either had a family history of Huntington's disease but a negative genetic test, or no known family history of Huntington's disease. All participants underwent detailed neuropsychiatric and cognitive assessments, including tests from the Cambridge Neuropsychological Test Automated Battery and a battery assessing emotion, motivation, impulsivity and social cognition (EMOTICOM). Imaging (done for all participants without contraindications) included volumetric MRI, diffusion imaging, and multiparametric mapping. Biofluid markers of neuronal health were examined using blood and CSF collection. We did a cross-sectional analysis using general least-squares linear models to assess group differences and associations with age and CAG length, relating to predicted years to clinical onset. Results were corrected for multiple comparisons using the false discovery rate (FDR), with FDR <0·05 deemed a significant result.

FINDINGS

Data were obtained between Aug 2, 2017, and April 25, 2019. We recruited 64 young adults with preHD and 67 controls. Mean ages of participants were 29·0 years (SD 5·6) and 29·1 years (5·7) in the preHD and control groups, respectively. We noted no significant evidence of cognitive or psychiatric impairment in preHD participants 23·6 years (SD 5·8) from predicted onset (FDR 0·22-0·87 for cognitive measures, 0·31-0·91 for neuropsychiatric measures). The preHD cohort had slightly smaller putamen volumes (FDR=0·03), but this did not appear to be closely related to predicted years to onset (FDR=0·54). There were no group differences in other brain imaging measures (FDR >0·16). CSF neurofilament light protein (NfL), plasma NfL, and CSF YKL-40 were elevated in this far-from-onset preHD cohort compared with controls (FDR<0·0001, =0·01, and =0·03, respectively). CSF NfL elevations were more likely in individuals closer to expected clinical onset (FDR <0·0001).

INTERPRETATION

We report normal brain function yet a rise in sensitive measures of neurodegeneration in a preHD cohort approximately 24 years from predicted clinical onset. CSF NfL appears to be a more sensitive measure than plasma NfL to monitor disease progression. This preHD cohort is one of the earliest yet studied, and our findings could be used to inform decisions about when to initiate a potential future intervention to delay or prevent further neurodegeneration while function is intact.

FUNDING

Wellcome Trust, CHDI Foundation.

Fiber-specific white matter reductions in Parkinson hallucinations and visual dysfunction

OBJECTIVE

To investigate the microstructural and macrostructural white matter changes that accompany visual hallucinations and low visual performance in Parkinson disease, a risk factor for Parkinson dementia.

METHODS

We performed fixel-based analysis, a novel technique that provides metrics of specific fiber-bundle populations within a voxel (or fixel). Diffusion MRI data were acquired from patients with Parkinson disease (n = 105, of whom 34 were low visual performers and 19 were hallucinators) and age-matched controls (n = 35). We used whole-brain fixel-based analysis to compare microstructural differences in fiber density (FD), macrostructural differences in fiber bundle cross section (FC), and the combined FD and FC (FDC) metric across all white matter fixels. We then performed a tract-of-interest analysis comparing the most sensitive FDC metric across 11 tracts within the visual system.

RESULTS

Patients with Parkinson disease hallucinations exhibited macrostructural changes (reduced FC) within the splenium of the corpus callosum and the left posterior thalamic radiation compared to patients without hallucinations. While there were no significant changes in FD, we found large reductions in the combined FDC metric in Parkinson hallucinators within the splenium (>50% reduction compared to nonhallucinators). Patients with Parkinson disease and low visual performance showed widespread microstructural and macrostructural changes within the genu and splenium of the corpus callosum, bilateral posterior thalamic radiations, and left inferior fronto-occipital fasciculus.

CONCLUSIONS

We demonstrate specific white matter tract degeneration affecting posterior thalamic tracts in patients with Parkinson disease with hallucinations and low visual performance, providing direct mechanistic support for attentional models of visual hallucinations.

Identifying disease-associated biomarker network features through conditional graphical model

Biomarkers are often organized into networks, in which the strengths of network connections vary across subjects depending on subject-specific covariates (eg, genetic variants). Variation of network connections, as subject-specific feature variables, has been found to predict disease clinical outcome. In this work, we develop a two-stage method to estimate biomarker networks that account for heterogeneity among subjects and evaluate network's association with disease clinical outcome. In the first stage, we propose a conditional Gaussian graphical model with mean and precision matrix depending on covariates to obtain covariate-dependent networks with connection strengths varying across subjects while assuming homogeneous network structure. In the second stage, we evaluate clinical utility of network measures (connection strengths) estimated from the first stage. The second-stage analysis provides the relative predictive power of between-region network measures on clinical impairment in the context of regional biomarkers and existing disease risk factors. We assess the performance of proposed method by extensive simulation studies and application to a Huntington's disease (HD) study to investigate the effect of HD causal gene on the rate of change in motor symptom through affecting brain subcortical and cortical gray matter atrophy connections. We show that cortical network connections and subcortical volumes, but not subcortical connections are identified to be predictive of clinical motor function deterioration. We validate these findings in an independent HD study. Lastly, highly similar patterns seen in the gray matter connections and a previous white matter connectivity study suggest a shared biological mechanism for HD and support the hypothesis that white matter loss is a direct result of neuronal loss as opposed to the loss of myelin or dysmyelination.

Learning Subject-Specific Directed Acyclic Graphs With Mixed Effects Structural Equation Models From Observational Data

The identification of causal relationships between random variables from large-scale observational data using directed acyclic graphs (DAG) is highly challenging. We propose a new mixed-effects structural equation model (mSEM) framework to estimate subject-specific DAGs, where we represent joint distribution of random variables in the DAG as a set of structural causal equations with mixed effects. The directed edges between nodes depend on observed exogenous covariates on each of the individual and unobserved latent variables. The strength of the connection is decomposed into a fixed-effect term representing the average causal effect given the covariates and a random effect term representing the latent causal effect due to unobserved pathways. The advantage of such decomposition is to capture essential asymmetric structural information and heterogeneity between DAGs in order to allow for the identification of causal structure with observational data. In addition, by pooling information across subject-specific DAGs, we can identify causal structure with a high probability and estimate subject-specific networks with a high precision. We propose a penalized likelihood-based approach to handle multi-dimensionality of the DAG model. We propose a fast, iterative computational algorithm, DAG-MM, to estimate parameters in mSEM and achieve desirable sparsity by hard-thresholding the edges. We theoretically prove the identifiability of mSEM. Using simulations and an application to protein signaling data, we show substantially improved performances when compared to existing methods and consistent results with a network estimated from interventional data. Lastly, we identify gray matter atrophy networks in regions of brain from patients with Huntington's disease and corroborate our findings using white matter connectivity data collected from an independent study.

Can neuroimaging predict dementia in Parkinson's disease?

Dementia in Parkinson's disease affects 50% of patients within 10 years of diagnosis but there is wide variation in severity and timing. Thus, robust neuroimaging prediction of cognitive involvement in Parkinson's disease is important: (i) to identify at-risk individuals for clinical trials of potential new treatments; (ii) to provide reliable prognostic information for individuals and populations; and (iii) to shed light on the pathophysiological processes underpinning Parkinson's disease dementia. To date, neuroimaging has not made major contributions to predicting cognitive involvement in Parkinson's disease. This is perhaps unsurprising considering conventional methods rely on macroscopic measures of topographically distributed neurodegeneration, a relatively late event in Parkinson's dementia. However, new technologies are now emerging that could provide important insights through detection of other potentially relevant processes. For example, novel MRI approaches can quantify magnetic susceptibility as a surrogate for tissue iron content, and increasingly powerful mathematical approaches can characterize the topology of brain networks at the systems level. Here, we present an up-to-date overview of the growing role of neuroimaging in predicting dementia in Parkinson's disease. We discuss the most relevant findings to date, and consider the potential of emerging technologies to detect the earliest signs of cognitive involvement in Parkinson's disease.

Brain Regions Showing White Matter Loss in Huntington's Disease Are Enriched for Synaptic and Metabolic Genes

BACKGROUND

The earliest white matter changes in Huntington's disease are seen before disease onset in the premanifest stage around the striatum, within the corpus callosum, and in posterior white matter tracts. While experimental evidence suggests that these changes may be related to abnormal gene transcription, we lack an understanding of the biological processes driving this regional vulnerability.

METHODS

Here, we investigate the relationship between regional transcription in the healthy brain, using the Allen Institute for Brain Science transcriptome atlas, and regional white matter connectivity loss at three time points over 24 months in subjects with premanifest Huntington's disease relative to control participants. The baseline cohort included 72 premanifest Huntington's disease participants and 85 healthy control participants.

RESULTS

We show that loss of corticostriatal, interhemispheric, and intrahemispheric white matter connections at baseline and over 24 months in premanifest Huntington's disease is associated with gene expression profiles enriched for synaptic genes and metabolic genes. Corticostriatal gene expression profiles are predominately associated with motor, parietal, and occipital regions, while interhemispheric expression profiles are associated with frontotemporal regions. We also show that genes with known abnormal transcription in human Huntington's disease and animal models are overrepresented in synaptic gene expression profiles, but not in metabolic gene expression profiles.

CONCLUSIONS

These findings suggest a dual mechanism of white matter vulnerability in Huntington's disease, in which abnormal transcription of synaptic genes and metabolic disturbance not related to transcription may drive white matter loss.

Large-scale DCMs for resting-state fMRI

This paper considers the identification of large directed graphs for resting-state brain networks based on biophysical models of distributed neuronal activity, that is, effective connectivity. This identification can be contrasted with functional connectivity methods based on symmetric correlations that are ubiquitous in resting-state functional MRI (fMRI). We use spectral dynamic causal modeling (DCM) to invert large graphs comprising dozens of nodes or regions. The ensuing graphs are directed and weighted, hence providing a neurobiologically plausible characterization of connectivity in terms of excitatory and inhibitory coupling. Furthermore, we show that the use of Bayesian model reduction to discover the most likely sparse graph (or model) from a parent (e.g., fully connected) graph eschews the arbitrary thresholding often applied to large symmetric (functional connectivity) graphs. Using empirical fMRI data, we show that spectral DCM furnishes connectivity estimates on large graphs that correlate strongly with the estimates provided by stochastic DCM. Furthermore, we increase the efficiency of model inversion using functional connectivity modes to place prior constraints on effective connectivity. In other words, we use a small number of modes to finesse the potentially redundant parameterization of large DCMs. We show that spectral DCM—with functional connectivity priors—is ideally suited for directed graph theoretic analyses of resting-state fMRI. We envision that directed graphs will prove useful in understanding the psychopathology and pathophysiology of neurodegenerative and neurodevelopmental disorders. We will demonstrate the utility of large directed graphs in clinical populations in subsequent reports, using the procedures described in this paper.

Structural and functional brain network correlates of depressive symptoms in premanifest Huntington's disease

Depression is common in premanifest Huntington's disease (preHD) and results in significant morbidity. We sought to examine how variations in structural and functional brain networks relate to depressive symptoms in premanifest HD and healthy controls. Brain networks were constructed using diffusion tractography (70 preHD and 81 controls) and resting state fMRI (92 preHD and 94 controls) data. A sub-network associated with depression was identified in a data-driven fashion and network-based statistics was used to investigate which specific connections correlated with depression scores. A replication analysis was then performed using data from a separate study. Correlations between depressive symptoms with increased functional connectivity and decreased structural connectivity were seen for connections in the default mode network (DMN) and basal ganglia in preHD. This study reveals specific connections in the DMN and basal ganglia that are associated with depressive symptoms in preHD. Hum Brain Mapp 38:2819-2829, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Topological length of white matter connections predicts their rate of atrophy in premanifest Huntington's disease

We lack a mechanistic explanation for the stereotyped pattern of white matter loss seen in Huntington’s disease (HD). While the earliest white matter changes are seen around the striatum, within the corpus callosum, and in the posterior white matter tracts, the order in which these changes occur and why these white matter connections are specifically vulnerable is unclear. Here, we use diffusion tractography in a longitudinal cohort of individuals yet to develop clinical symptoms of HD to identify a hierarchy of vulnerability, where the topological length of white matter connections between a brain area and its neighbors predicts the rate of atrophy over 24 months. This demonstrates a new principle underlying neurodegeneration in HD, whereby brain connections with the greatest topological length are the first to suffer damage that can account for the stereotyped pattern of white matter loss observed in premanifest HD.

Diffusion tractography in a longitudinal cohort demonstrates that topological length of white matter connections can account for white matter loss patterns in premanifest Huntington’s disease.

White matter predicts functional connectivity in premanifest Huntington's disease

Objectives

The distribution of pathology in neurodegenerative disease can be predicted by the organizational characteristics of white matter in healthy brains. However, we have very little evidence for the impact these pathological changes have on brain function. Understanding any such link between structure and function is critical for understanding how underlying brain pathology influences the progressive behavioral changes associated with neurodegeneration. Here, we demonstrate such a link between structure and function in individuals with premanifest Huntington's.

Methods

Using diffusion tractography and resting state functional magnetic resonance imaging to characterize white matter organization and functional connectivity, we investigate whether characteristic patterns of white matter organization in the healthy human brain shape the changes in functional coupling between brain regions in premanifest Huntington's disease.

Results

We find changes in functional connectivity in premanifest Huntington's disease that link directly to underlying patterns of white matter organization in healthy brains. Specifically, brain areas with strong structural connectivity show decreases in functional connectivity in premanifest Huntington's disease relative to controls, while regions with weak structural connectivity show increases in functional connectivity. Furthermore, we identify a pattern of dissociation in the strongest functional connections between anterior and posterior brain regions such that anterior functional connectivity increases in strength in premanifest Huntington's disease, while posterior functional connectivity decreases.

Interpretation

Our findings demonstrate that organizational principles of white matter underlie changes in functional connectivity in premanifest Huntington's disease. Furthermore, we demonstrate functional antero–posterior dissociation that is in keeping with the caudo–rostral gradient of striatal pathology in HD.

Longitudinal changes in functional connectivity of cortico-basal ganglia networks in manifests and premanifest huntington's disease

Huntington's disease (HD) is a genetic neurological disorder resulting in cognitive and motor impairments. We evaluated the longitudinal changes of functional connectivity in sensorimotor, associative and limbic cortico-basal ganglia networks. We acquired structural MRI and resting-state fMRI in three visits one year apart, in 18 adult HD patients, 24 asymptomatic mutation carriers (preHD) and 18 gender- and age-matched healthy volunteers from the TRACK-HD study. We inferred topological changes in functional connectivity between 182 regions within cortico-basal ganglia networks using graph theory measures. We found significant differences for global graph theory measures in HD but not in preHD. The average shortest path length (L) decreased, which indicated a change toward the random network topology. HD patients also demonstrated increases in degree k, reduced betweeness centrality bc and reduced clustering C. Changes predominated in the sensorimotor network for bc and C and were observed in all circuits for k. Hubs were reduced in preHD and no longer detectable in HD in the sensorimotor and associative networks. Changes in graph theory metrics (L, k, C and bc) correlated with four clinical and cognitive measures (symbol digit modalities test, Stroop, Burden and UHDRS). There were no changes in graph theory metrics across sessions, which suggests that these measures are not reliable biomarkers of longitudinal changes in HD. preHD is characterized by progressive decreasing hub organization, and these changes aggravate in HD patients with changes in local metrics. HD is characterized by progressive changes in global network interconnectivity, whose network topology becomes more random over time. Hum Brain Mapp 37:4112-4128, 2016. © 2016 Wiley Periodicals, Inc.

Cerebrospinal fluid total tau concentration predicts clinical phenotype in Huntington's disease

Huntington's disease (HD) is a hereditary neurodegenerative condition with no therapeutic intervention known to alter disease progression, but several trials are ongoing and biomarkers of disease progression are needed. Tau is an axonal protein, often altered in neurodegeneration, and recent studies pointed out its role on HD neuropathology. Our goal was to study whether cerebrospinal fluid (CSF) tau is a biomarker of disease progression in HD. After informed consent, healthy controls, pre-symptomatic and symptomatic gene expansion carriers were recruited from two HD clinics. All participants underwent assessment with the Unified HD Rating Scale '99 (UHDRS). CSF was obtained according to a standardized lumbar puncture protocol. CSF tau was quantified using enzyme-linked immunosorbent assay. Comparisons between two groups were tested using ancova. Pearson's correlation coefficients were calculated for disease progression. Significance level was defined as p < 0.05. Seventy-six participants were included in this cross-sectional multicenter international pilot study. Age-adjusted CSF tau was significantly elevated in gene expansion carriers compared with healthy controls (p = 0.002). UHDRS total functional capacity was significantly correlated with CSF tau (r = -0.29, p = 0.004) after adjustment for age, and UHDRS total motor score was significantly correlated with CSF tau after adjustment for age (r = 0.32, p = 0.002). Several UHDRS cognitive tasks were also significantly correlated with CST total tau after age-adjustment. This study confirms that CSF tau concentrations in HD gene mutation carriers are increased compared with healthy controls and reports for the first time that CSF tau concentration is associated with phenotypic variability in HD. These conclusions strengthen the case for CSF tau as a biomarker in HD. In the era of novel targeted approaches to Huntington's disease, reliable biomarkers are needed. We quantified Tau protein, a marker of neuronal death, in cerebrospinal fluid and found it was increased in patients with Huntington's disease and predicted motor, cognitive, and functional disability in patients. It is therefore likely to be a biomarker of disease progression, and possibly of therapeutic response. Read the Editorial Highlight for this article on page 9.

Cerebrospinal Fluid Inflammatory Biomarkers Reflect Clinical Severity in Huntington's Disease

INTRODUCTION

Immune system activation is involved in Huntington's disease (HD) pathogenesis and biomarkers for this process could be relevant to study the disease and characterise the therapeutic response to specific interventions. We aimed to study inflammatory cytokines and microglial markers in the CSF of HD patients.

METHODS

CSF TNF-α, IL-1β, IL-6, IL-8, YKL-40, chitotriosidase, total tau and neurofilament light chain (NFL) from 23 mutation carriers and 14 healthy controls were assayed.

RESULTS

CSF TNF-α and IL-1β were below the limit of detection. Mutation carriers had higher YKL-40 (p = 0.003), chitotriosidase (p = 0.015) and IL-6 (p = 0.041) than controls. YKL-40 significantly correlated with disease stage (p = 0.007), UHDRS total functional capacity score (r = -0.46, p = 0.016), and UHDRS total motor score (r = 0.59, p = 4.5*10-4) after adjustment for age.

CONCLUSION

YKL-40 levels in CSF may, after further study, come to have a role as biomarkers for some aspects of HD. Further investigation is needed to support our exploratory findings.

Selective vulnerability of Rich Club brain regions is an organizational principle of structural connectivity loss in Huntington's disease

Huntington's disease can be predicted many years before symptom onset, and thus makes an ideal model for studying the earliest mechanisms of neurodegeneration. Diffuse patterns of structural connectivity loss occur in the basal ganglia and cortex early in the disease. However, the organizational principles that underlie these changes are unclear. By understanding such principles we can gain insight into the link between the cellular pathology caused by mutant huntingtin and its downstream effect at the macroscopic level. The 'rich club' is a pattern of organization established in healthy human brains, where specific hub 'rich club' brain regions are more highly connected to each other than other brain regions. We hypothesized that selective loss of rich club connectivity might represent an organizing principle underlying the distributed pattern of structural connectivity loss seen in Huntington's disease. To test this hypothesis we performed diffusion tractography and graph theoretical analysis in a pseudo-longitudinal study of 50 premanifest and 38 manifest Huntington's disease participants compared with 47 healthy controls. Consistent with our hypothesis we found that structural connectivity loss selectively affected rich club brain regions in premanifest and manifest Huntington's disease participants compared with controls. We found progressive network changes across controls, premanifest Huntington's disease and manifest Huntington's disease characterized by increased network segregation in the premanifest stage and loss of network integration in manifest disease. These regional and whole brain network differences were highly correlated with cognitive and motor deficits suggesting they have pathophysiological relevance. We also observed greater reductions in the connectivity of brain regions that have higher network traffic and lower clustering of neighbouring regions. This provides a potential mechanism that results in a characteristic pattern of structural connectivity loss targeting highly connected brain regions with high network traffic and low clustering of neighbouring regions. Our findings highlight the role of the rich club as a substrate for the structural connectivity loss seen in Huntington's disease and have broader implications for understanding the connection between molecular and systems level pathology in neurodegenerative disease.

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.

Oculoleptomeningeal Amyloidosis associated with transthyretin Leu12Pro in an African patient

Oculoleptomeningeal amyloidosis is a rare manifestation of hereditary transthyretin (TTR) amyloidosis. Here, we present the first case of leptomeningeal amyloidosis associated with the TTR variant Leu12Pro mutation in an African patient. A 43-year-old right-handed Nigerian man was referred to our centre with rapidly progressive neurological decline. He presented initially with weight loss, confusion, fatigue, and urinary and erectile dysfunction. He then suffered recurrent episodes of slurred speech with right-sided weakness. He went on to develop hearing difficulties and painless paraesthesia. Neurological examination revealed horizontal gaze-evoked nystagmus, brisk jaw jerk, increased tone, brisk reflexes throughout and bilateral heel-shin ataxia. Magnetic resonance imaging showed extensive leptomeningeal enhancement. Cerebrospinal fluid analysis showed a raised protein of 6.4 g/dl. Nerve conduction studies showed an axonal neuropathy. Echocardiography was characteristic of cardiac amyloid. TTR gene sequencing showed that he was heterozygous for the leucine 12 proline mutation. Meningeal and brain biopsy confirmed widespread amyloid angiopathy. TTR amyloidosis is a rare cause of leptomeningeal enhancement, but should be considered if there is evidence of peripheral or autonomic neuropathy with cardiac or ocular involvement. The relationship between different TTR mutations and clinical phenotype, disease course, and response to treatment remains unclear.

C9orf72 expansions are the most common genetic cause of Huntington disease phenocopies

OBJECTIVE

In many cases where Huntington disease (HD) is suspected, the genetic test for HD is negative: these are known as HD phenocopies. A repeat expansion in the C9orf72 gene has recently been identified as a major cause of familial and sporadic frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Our objective was to determine whether this mutation causes HD phenocopies.

METHODS

A cohort of 514 HD phenocopy patients were analyzed for the C9orf72 expansion using repeat primed PCR. In cases where the expansion was found, Southern hybridization was performed to determine expansion size. Clinical case notes were reviewed to determine the phenotype of expansion-positive cases.

RESULTS

Ten subjects (1.95%) had the expansion, making it the most common identified genetic cause of HD phenocopy presentations. The size of expansion was not significantly different from that associated with other clinical presentations of C9orf72 expanded cases. The C9orf72 expansion-positive subjects were characterized by the presence of movement disorders, including dystonia, chorea, myoclonus, tremor, and rigidity. Furthermore, the age at onset in this cohort was lower than previously reported for subjects with the C9orf72 expansion and included one case with pediatric onset.

DISCUSSION

This study extends the known phenotype of the C9orf72 expansion in both age at onset and movement disorder symptoms. We propose a revised clinico-genetic algorithm for the investigation of HD phenocopy patients based on these data.

Luminescence of oxygen atoms stimulated by metastable helium at cryogenic temperatures

We present investigations of the afterglow of oxygen-helium gas mixtures at cryogenic temperatures. The cooling of a helium jet containing trace amounts of oxygen after passing through a radio frequency discharge zone led to the observation of strong emissions from atomic oxygen. The effect results from the increasing efficiency of energy transfer from metastable helium atoms and molecules to oxygen impurities in the cold dense helium vapor. This effect might find an application for the detection of small quantities of the impurities in helium gas.

The Addenbrooke's Cognitive Examination for the differential diagnosis and longitudinal assessment of patients with parkinsonian disorders

OBJECTIVE

Differentiating idiopathic Parkinson's disease from atypical parkinsonian syndromes is challenging, especially in the early stages. We assessed whether the Revised Addenbrooke's Cognitive Examination (ACE-R) could differentiate between parkinsonian syndromes and reflect longitudinal changes in cognition in these disorders.

METHODS

The ACE-R was administered at baseline and after approximately 18 months to 135 patients with parkinsonian disorders: 86 with idiopathic Parkinson's disease (PD), 30 with progressive supranuclear palsy (PSP), 19 with corticobasal degeneration (CBD). We assessed differences between groups for ACE-R, ACE-R subscores and Mini Mental State Examination (MMSE) scores at baseline (analyses of variance, receiver operating characteristics curves), and the interaction between diagnosis and change in ACE-R scores between visits (analyses of variance).

RESULTS

The ACE-R verbal fluency subscore distinguished between PSP and PD with a high sensitivity (0.92) and specificity (0.87); total ACE-R score and the visuospatial subscore were less specific (0.87 and 0.84 respectively) and sensitive (0.70 and 0.73). Significant group level differences were found between PD and PSP for MMSE and ACE-R (total score and subscores for attention and concentration, fluency, language, and visuospatial function), and between PD and CBD for the ACE-R visuospatial subscore. Performance worsened between visits for ACE-R score in PD (p=0.001) and CBD (p=0.001); visuospatial subscore in PD (p=0.003), PSP (p=0.022) and CBD (p=0.0002); and MMSE in CBD (p=0.004).

CONCLUSIONS

We propose the ACE-R, particularly the verbal fluency subscore, as a valuable contributor to the differential diagnosis of parkinsonian syndromes in the correct clinical context. The ACE-R may reflect disease progression in PD and CBD.