Operationalizing compensation over time in neurodegenerative disease

Predicting the Conversion from Mild Cognitive Impairment to Alzheimer's Disease Using Graph Frequency Bands and Functional Connectivity-Based Features

Accurate prediction of the progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) is crucial for disease management. Machine learning techniques have demonstrated success in classifying AD and MCI cases, particularly with the use of resting-state functional magnetic resonance imaging (rs-fMRI) data.This study utilized three years of rs-fMRI data from the ADNI, involving 142 patients with stable MCI (sMCI) and 136 with progressive MCI (pMCI). Graph signal processing was applied to filter rs-fMRI data into low, middle, and high frequency bands. Connectivity-based features were derived from both filtered and unfiltered data, resulting in a comprehensive set of 100 features, including global graph metrics, minimum spanning tree (MST) metrics, triadic interaction metrics, hub tendency metrics, and the number of links. Feature selection was enhanced using particle swarm optimization (PSO) and simulated annealing (SA). A support vector machine (SVM) with a radial basis function (RBF) kernel and a 10-fold cross-validation setup were employed for classification. The proposed approach demonstrated superior performance, achieving optimal accuracy with minimal feature utilization. When PSO selected five features, SVM exhibited accuracy, specificity, and sensitivity rates of 77%, 70%, and 83%, respectively. The identified features were as follows: (Mean of clustering coefficient, Mean of strength)/Radius/(Mean Eccentricity, and Modularity) from low/middle/high frequency bands of graph. The study highlights the efficacy of the proposed framework in identifying individuals at risk of AD development using a parsimonious feature set. This approach holds promise for advancing the precision of MCI to AD progression prediction, aiding in early diagnosis and intervention strategies.

Clinical severity in Parkinson's disease is determined by decline in cortical compensation

Dopaminergic dysfunction in the basal ganglia, particularly in the posterior putamen, is often viewed as the primary pathological mechanism behind motor slowing (i.e. bradykinesia) in Parkinson's disease. However, striatal dopamine loss fails to account for interindividual differences in motor phenotype and rate of decline, implying that the expression of motor symptoms depends on additional mechanisms, some of which may be compensatory in nature. Building on observations of increased motor-related activity in the parieto-premotor cortex of Parkinson patients, we tested the hypothesis that interindividual differences in clinical severity are determined by compensatory cortical mechanisms and not just by basal ganglia dysfunction. Using functional MRI, we measured variability in motor- and selection-related brain activity during a visuomotor task in 353 patients with Parkinson's disease (≤5 years disease duration) and 60 healthy controls. In this task, we manipulated action selection demand by varying the number of possible actions that individuals could choose from. Clinical variability was characterized in two ways. First, patients were categorized into three previously validated, discrete clinical subtypes that are hypothesized to reflect distinct routes of α-synuclein propagation: diffuse-malignant (n = 42), intermediate (n = 128) or mild motor-predominant (n = 150). Second, we used the scores of bradykinesia severity and cognitive performance across the entire sample as continuous measures. Patients showed motor slowing (longer response times) and reduced motor-related activity in the basal ganglia compared with controls. However, basal ganglia activity did not differ between clinical subtypes and was not associated with clinical scores. This indicates a limited role for striatal dysfunction in shaping interindividual differences in clinical severity. Consistent with our hypothesis, we observed enhanced action selection-related activity in the parieto-premotor cortex of patients with a mild-motor predominant subtype, both compared to patients with a diffuse-malignant subtype and controls. Furthermore, increased parieto-premotor activity was related to lower bradykinesia severity and better cognitive performance, which points to a compensatory role. We conclude that parieto-premotor compensation, rather than basal ganglia dysfunction, shapes interindividual variability in symptom severity in Parkinson's disease. Future interventions may focus on maintaining and enhancing compensatory cortical mechanisms, rather than only attempting to normalize basal ganglia dysfunction.

Baseline Large-Scale Network Dynamics Associated with Disease Progression in Huntington's Disease

BACKGROUND

Huntington's disease (HD) is a genetically determined disease with motor, cognitive, and neuropsychiatric disorders. However, the links between clinical progression and disruptions to dynamics in motor and cognitive large-scale networks are not well established.

OBJECTIVE

To investigate changes in dynamic and static large-scale networks using an established tool of disease progression in Huntington's disease, the composite Unified Huntington's Disease Rating Scale (cUHDRS).

METHODS

Sixty-four mutation carriers were included. Static and dynamic baseline functional connectivity as well as topological features were correlated to 2-year follow-up clinical assessments using the cUHDRS.

RESULTS

Decline in cUHDRS scores was associated with higher connectivity between frontal default-mode and motor networks, whereas higher connectivity in posterior, mainly visuospatial regions was associated with a smaller decline in cUHDRS scores.

CONCLUSIONS

Structural disruptions in HD were evident both in posterior parietal/occipital and frontal motor regions, with reciprocal increases in functional connectivity. However, although higher visuospatial network connectivity was tied to a smaller cUHDRS decline, increased motor and frontal default-mode connections were linked to a larger cUHDRS decreases. Therefore, divergent functional compensation mechanisms might be at play in the clinical evolution of HD.

Neuroimaging to Facilitate Clinical Trials in Huntington's Disease: Current Opinion from the EHDN Imaging Working Group

 Neuroimaging is increasingly being included in clinical trials of Huntington's disease (HD) for a wide range of purposes from participant selection and safety monitoring, through to demonstration of disease modification. Selection of the appropriate modality and associated analysis tools requires careful consideration. On behalf of the EHDN Imaging Working Group, we present current opinion on the utility and future prospects for inclusion of neuroimaging in HD trials. Covering the key imaging modalities of structural-, functional- and diffusion- MRI, perfusion imaging, positron emission tomography, magnetic resonance spectroscopy, and magnetoencephalography, we address how neuroimaging can be used in HD trials to: 1) Aid patient selection, enrichment, stratification, and safety monitoring; 2) Demonstrate biodistribution, target engagement, and pharmacodynamics; 3) Provide evidence for disease modification; and 4) Understand brain re-organization following therapy. We also present the challenges of translating research methodology into clinical trial settings, including equipment requirements and cost, standardization of acquisition and analysis, patient burden and invasiveness, and interpretation of results. We conclude, that with appropriate consideration of modality, study design and analysis, imaging has huge potential to facilitate effective clinical trials in HD.

Connectome-based modelling of neurodegenerative diseases: towards precision medicine and mechanistic insight

Neurodegenerative diseases are the most common cause of dementia. Although their underlying molecular pathologies have been identified, there is substantial heterogeneity in the patterns of progressive brain alterations across and within these diseases. Recent advances in neuroimaging methods have revealed that pathological proteins accumulate along specific macroscale brain networks, implicating the network architecture of the brain in the system-level pathophysiology of neurodegenerative diseases. However, the extent to which 'network-based neurodegeneration' applies across the wide range of neurodegenerative disorders remains unclear. Here, we discuss the state-of-the-art of neuroimaging-based connectomics for the mapping and prediction of neurodegenerative processes. We review findings supporting brain networks as passive conduits through which pathological proteins spread. As an alternative view, we also discuss complementary work suggesting that network alterations actively modulate the spreading of pathological proteins between connected brain regions. We conclude this Perspective by proposing an integrative framework in which connectome-based models can be advanced along three dimensions of innovation: incorporating parameters that modulate propagation behaviour on the basis of measurable biological features; building patient-tailored models that use individual-level information and allowing model parameters to interact dynamically over time. We discuss promises and pitfalls of these strategies for improving disease insights and moving towards precision medicine.

Cognition's dependence on functional network integrity with age is conditional on structural network integrity

Maintaining good cognitive function is crucial for well-being across the lifespan. We proposed that the degree of cognitive maintenance is determined by the functional interactions within and between large-scale brain networks. Such connectivity can be represented by the white matter architecture of structural brain networks that shape intrinsic neuronal activity into integrated and distributed functional networks. We explored how the function-structure connectivity convergence, and the divergence of functional connectivity from structural connectivity, contribute to the maintenance of cognitive function across the adult lifespan. Multivariate analyses were used to investigate the relationship between function-structure connectivity convergence and divergence with multivariate cognitive profiles, respectively. Cognitive function was increasingly dependent on function-structure connectivity convergence as age increased. The dependency of cognitive function on connectivity was particularly strong for high-order cortical networks and subcortical networks. The results suggest that brain functional network integrity sustains cognitive functions in old age, as a function of the integrity of the brain's structural connectivity.

Temporal dynamics predict symptom onset and cognitive decline in familial frontotemporal dementia

INTRODUCTION

We tested whether changes in functional networks predict cognitive decline and conversion from the presymptomatic prodrome to symptomatic disease in familial frontotemporal dementia (FTD).

METHODS

For hypothesis generation, 36 participants with behavioral variant FTD (bvFTD) and 34 controls were recruited from one site. For hypothesis testing, we studied 198 symptomatic FTD mutation carriers, 341 presymptomatic mutation carriers, and 329 family members without mutations. We compared functional network dynamics between groups, with clinical severity and with longitudinal clinical progression.

RESULTS

We identified a characteristic pattern of dynamic network changes in FTD, which correlated with neuropsychological impairment. Among presymptomatic mutation carriers, this pattern of network dynamics was found to a greater extent in those who subsequently converted to the symptomatic phase. Baseline network dynamic changes predicted future cognitive decline in symptomatic participants and older presymptomatic participants.

DISCUSSION

Dynamic network abnormalities in FTD predict cognitive decline and symptomatic conversion.

HIGHLIGHTS

We investigated brain network predictors of dementia symptom onset Frontotemporal dementia results in characteristic dynamic network patterns Alterations in network dynamics are associated with neuropsychological impairment Network dynamic changes predict symptomatic conversion in presymptomatic carriers Network dynamic changes are associated with longitudinal cognitive decline.

Neural compensation in manifest neurodegeneration: systems neuroscience evidence from social cognition in frontotemporal dementia

BACKGROUND

It has been argued that symptom onset in neurodegeneration reflects the overload of compensatory mechanisms. The present study aimed to investigate whether neural functional compensation can be observed in the manifest neurodegenerative disease stage, by focusing on a core deficit in frontotemporal dementia, i.e. social cognition, and by combining psychophysical assessment, structural MRI and functional MRI with multidimensional neural markers that allow quantification of neural computations.

METHODS

Nineteen patients with clinically manifest behavioral variant frontotemporal dementia (bvFTD) and 20 controls performed facial expression recognition tasks in the MRI-scanner and offline. Group differences in grey matter volume, neural response amplitude and neural patterns were assessed via a combination of voxel-wise whole-brain, searchlight, and ROI-analyses and these measures were correlated with psychophysical measures of emotion, valence and arousal ratings.

RESULTS

Significant group effects were observed only outside task-relevant regions, converging in the caudate nucleus. This area showed a diagnostic neural pattern as well as hyperactivation and stronger neural representation of facial expressions in the bvFTD sample. Furthermore, response amplitude was associated with behavioral arousal ratings.

CONCLUSIONS

The combined findings reveal converging support for compensatory processes in clinically manifest neurodegeneration, complementing accounts that clinical onset synchronizes with the breakdown of compensatory processes. Furthermore, active compensation may proceed along nodes in intrinsically connected networks, rather than along the more task-specific networks. The findings underscore the potential of distributed multidimensional functional neural characteristics that may provide a novel class of biomarkers with both diagnostic and therapeutic implications, including biomarkers for clinical trials.

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.

Moderating effect of cognitive reserve on brain integrity and cognitive performance

Background

Dementia syndrome is one of the most devastating conditions in older adults. As treatments to stop neurodegeneration become available, accurate and timely diagnosis will increase in importance. One issue is that cognitive performance sometimes does not match the corresponding level of neuropathology, affecting diagnostic accuracy. Cognitive reserve (CR), which can preserve cognitive function despite underlying neuropathology, explains at least some variability in cognitive performance. We examined the influence of CR proxies (education and occupational position) on the relationship between hippocampal or total gray matter volume and cognition.

Methods

We used data from the Czech Brain Aging Study. Participants were clinically confirmed to be without dementia (n = 457, including subjective cognitive decline and amnestic mild cognitive impairment) or with dementia syndrome (n = 113).

Results

For participants without dementia, higher education magnified the associations between (a) hippocampal volume and executive control (b = 0.09, p = 0.033), (b) total gray matter volume and language (b = 0.12, p < 0.001), and (c) total gray matter volume and memory (b = 0.08, p = 0.018). Similarly, higher occupational position magnified the association between total gray matter volume and (a) attention/working memory (b = 0.09, p = 0.009), (b) language (b = 0.13, p = 0.002), and (c) memory (b = 0.10, p = 0.013). For participants with dementia, the associations between hippocampal (b = -0.26, p = 0.024) and total gray matter (b = -0.28, p = 0.024) volume and visuospatial skills decreased in magnitude with higher education.

Conclusion

We found that the association between brain volume and cognitive performance varies based on CR, with greater CR related to a stronger link between brain volume and cognition before, and a weaker link after, dementia diagnosis.

Association of Structural Measurements of Brain Reserve With Motor Progression in Patients With Parkinson Disease

BACKGROUND AND OBJECTIVES

To investigate the relationship between baseline structural measurements of brain reserve and clinical progression in Parkinson disease (PD). To further provide a possible underlying mechanism for structural measurements of brain reserve in PD, we combined functional and transcriptional data and investigated their relationship with progression-associated patterns derived from structural measurements and longitudinal clinical scores.

METHODS

This longitudinal study collected data from June 2010 to March 2019 from 2 datasets. The Parkinson's Progression Markers Initiative (PPMI) included controls and patients with newly diagnosed PD from 24 participating sites worldwide. Results were confirmed using data from the Huashan dataset (Shanghai, China), which included controls and patients with PD. Clinical symptoms were assessed with Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) scores and Schwab & England activities of daily living (ADL). Both datasets were followed up to 5 years. Linear mixed-effects (LME) models were performed to examine whether changes in clinical scores over time differed as a function of brain structural measurements at baseline.

RESULTS

A total of 389 patients with PD (n = 346, age 61.3 ± 10.03, 35% female, PPMI dataset; n = 43, age 59.4 ± 7.3, 38.7% female, Huashan dataset) with T1-MRI and follow-up clinical assessments were included in this study. Results of LME models revealed significant interactions between baseline structural measurements of subcortical regions and time on longitudinal deterioration of clinical scores (MDS-UPDRS Part II, absolute β > 0.27; total MDS-UPDRS scores, absolute β > 1.05; postural instability-gait difficulty (PIGD) score, absolute β > 0.03; Schwab & England ADL, absolute β > 0.59; all p < 0.05, false discovery rate corrected). The interaction of baseline structural measurements of subcortical regions and time on longitudinal deterioration of the PIGD score was replicated using data from Huashan Hospital. Furthermore, the β-coefficients of these interactions recapitulated the spatial distribution of dopaminergic, metabolic, and structural changes between patients with PD and normal controls and the spatial distribution of expression of the α-synuclein gene (SNCA).

DISCUSSION

Patients with PD with greater brain resources (that is, higher deformation-based morphometry values) had greater compensatory capacity, which was associated with slower rates of clinical progression. This knowledge could be used to stratify and monitor patients for clinical trials.

Inter- and intra-individual variation in brain structural-cognition relationships in aging

The sources of inter- and intra-individual variability in age-related cognitive decline remain poorly understood. We examined the association between 20-year trajectories of cognitive decline and multimodal brain structure and morphology in older age. We used the Whitehall II Study, an extensively characterised cohort with 3T brain magnetic resonance images acquired at older age (mean age = 69.52 ± 4.9) and 5 repeated cognitive performance assessments between mid-life (mean age = 53.2 ±4.9 years) and late-life (mean age = 67.7 ± 4.9). Using non-negative matrix factorization, we identified 10 brain components integrating cortical thickness, surface area, fractional anisotropy, and mean and radial diffusivities. We observed two latent variables describing distinct brain-cognition associations. The first describes variations in 5 structural components associated with low mid-life performance across multiple cognitive domains, decline in reasoning, but maintenance of fluency abilities. The second describes variations in 6 structural components associated with low mid-life performance in fluency and memory, but retention of multiple abilities. Expression of latent variables predicts future cognition 3.2 years later (mean age = 70.87 ± 4.9). This data-driven approach highlights brain-cognition relationships wherein individuals degrees of cognitive decline and maintenance across diverse cognitive functions are both positively and negatively associated with markers of cortical structure.

Classification of early-MCI patients from healthy controls using evolutionary optimization of graph measures of resting-state fMRI, for the Alzheimer's disease neuroimaging initiative

Identifying individuals with early mild cognitive impairment (EMCI) can be an effective strategy for early diagnosis and delay the progression of Alzheimer's disease (AD). Many approaches have been devised to discriminate those with EMCI from healthy control (HC) individuals. Selection of the most effective parameters has been one of the challenging aspects of these approaches. In this study we suggest an optimization method based on five evolutionary algorithms that can be used in optimization of neuroimaging data with a large number of parameters. Resting-state functional magnetic resonance imaging (rs-fMRI) measures, which measure functional connectivity, have been shown to be useful in prediction of cognitive decline. Analysis of functional connectivity data using graph measures is a common practice that results in a great number of parameters. Using graph measures we calculated 1155 parameters from the functional connectivity data of HC (n = 72) and EMCI (n = 68) extracted from the publicly available database of the Alzheimer's disease neuroimaging initiative database (ADNI). These parameters were fed into the evolutionary algorithms to select a subset of parameters for classification of the data into two categories of EMCI and HC using a two-layer artificial neural network. All algorithms achieved classification accuracy of 94.55%, which is extremely high considering single-modality input and low number of data participants. These results highlight potential application of rs-fMRI and efficiency of such optimization methods in classification of images into HC and EMCI. This is of particular importance considering that MRI images of EMCI individuals cannot be easily identified by experts.

Listen Carefully protocol: an exploratory case-control study of the association between listening effort and cognitive function

INTRODUCTION

A growing body of evidence suggests that hearing loss is a significant and potentially modifiable risk factor for cognitive impairment. Although the mechanisms underlying the associations between cognitive decline and hearing loss are unclear, listening effort has been posited as one of the mechanisms involved with cognitive decline in older age. To date, there has been a lack of research investigating this association, particularly among adults with mild cognitive impairment (MCI).

METHODS AND ANALYSIS

15-25 cognitively healthy participants and 15-25 patients with MCI (age 40-85 years) will be recruited to participate in an exploratory study investigating the association between cognitive functioning and listening effort. Both behavioural and objective measures of listening effort will be investigated. The sentence-final word identification and recall (SWIR) test will be administered with single talker non-intelligible speech background noise while monitoring pupil dilation. Evaluation of cognitive function will be carried out in a clinical setting using a battery of neuropsychological tests. This study is considered exploratory and proof of concept, with information taken to help decide the validity of larger-scale trials.

ETHICS AND DISSEMINATION

Written approval exemption was obtained by the Scientific Ethics Committee in the central region of Denmark (De Videnskabsetiske Komiteer i Region Hovedstaden), reference 19042404, and the project is registered pre-results at clinicaltrials.gov, reference NCT04593290, Protocol ID 19042404. Study results will be disseminated in peer-reviewed journals and conferences.

Limbic Serotonergic Plasticity Contributes to the Compensation of Apathy in Early Parkinson's Disease

BACKGROUND

De novo Parkinson's disease (PD) patients with apathy exhibit prominent limbic serotonergic dysfunction and microstructural disarray. Whether this distinctive lesion profile at diagnosis entails different prognosis remains unknown.

OBJECTIVES

To investigate the progression of dopaminergic and serotonergic dysfunction and their relation to motor and nonmotor impairment in PD patients with or without apathy at diagnosis.

METHODS

Thirteen de novo apathetic and 13 nonapathetic PD patients were recruited in a longitudinal double-tracer positron emission tomography cohort study. We quantified the progression of presynaptic dopaminergic and serotonergic pathology using [¹¹ C]PE2I for dopamine transporter and [¹¹ C]DASB for serotonin transporter at baseline and 3 to 5 years later, using linear mixed-effect models and mediation analysis to compare the longitudinal evolution between groups for clinical impairment and region-of-interest-based analysis.

RESULTS

After the initiation of dopamine replacement therapy, apathy, depression, and anxiety improved at follow-up in patients with apathy at diagnosis (n = 10) to the level of patients without apathy (n = 11). Patients had similar progression of motor impairment, whereas mild impulsive behaviors developed in both groups. Striato-pallidal and mesocorticolimbic presynaptic dopaminergic loss progressed similarly in both groups, as did serotonergic pathology in the putamen, caudate nucleus, and pallidum. Contrastingly, serotonergic innervation selectively increased in the ventral striatum and anterior cingulate cortex in apathetic patients, contributing to the reversal of apathy besides dopamine replacement therapy.

CONCLUSION

Patients suffering from apathy at diagnosis exhibit compensatory changes in limbic serotonergic innervation within 5 years of diagnosis, with promising evidence that serotonergic plasticity contributes to the reversal of apathy. The relationship between serotonergic plasticity and dopaminergic treatments warrants further longitudinal investigations. © 2022 International Parkinson and Movement Disorder Society.

White Matter Microstructural Alterations in Newly Diagnosed Parkinson’s Disease: A Whole-Brain Analysis Using dMRI

Parkinson’s disease (PD) is a neurodegenerative disorder characterized by cardinal motor symptoms and other non-motor symptoms. Studies have investigated various brain areas in PD by detecting white matter alterations using diffusion magnetic resonance imaging processing techniques, which can produce diffusion metrics such as fractional anisotropy and quantitative anisotropy. In this study, we compared the quantitative anisotropy of whole brain regions throughout the subcortical and cortical areas between newly diagnosed PD patients and healthy controls. Additionally, we evaluated the correlations between the quantitative anisotropy of each region and respective neuropsychological test scores to identify the areas most affected by each neuropsychological dysfunction in PD. We found significant quantitative anisotropy differences in several subcortical structures such as the basal ganglia, limbic system, and brain stem as well as in cortical structures such as the temporal lobe, occipital lobe, and insular lobe. Additionally, we found that quantitative anisotropy of some subcortical structures such as the basal ganglia, cerebellum, and brain stem showed the highest correlations with motor dysfunction, whereas cortical structures such as the temporal lobe and occipital lobe showed the highest correlations with olfactory dysfunction in PD. Our study also showed evidence regarding potential neural compensation by revealing higher diffusion metric values in early-stage PD than in healthy controls. We anticipate that our results will improve our understanding of PD’s pathophysiology.

Monitoring Neuronal Network Disturbances of Brain Diseases: A Preclinical MRI Approach in the Rodent Brain

Functional and structural neuronal networks, as recorded by resting-state functional MRI and diffusion MRI-based tractography, gain increasing attention as data driven whole brain imaging methods not limited to the foci of the primary pathology or the known key affected regions but permitting to characterize the entire network response of the brain after disease or injury. Their connectome contents thus provide information on distal brain areas, directly or indirectly affected by and interacting with the primary pathological event or affected regions. From such information, a better understanding of the dynamics of disease progression is expected. Furthermore, observation of the brain's spontaneous or treatment-induced improvement will contribute to unravel the underlying mechanisms of plasticity and recovery across the whole-brain networks. In the present review, we discuss the values of functional and structural network information derived from systematic and controlled experimentation using clinically relevant animal models. We focus on rodent models of the cerebral diseases with high impact on social burdens, namely, neurodegeneration, and stroke.

Characteristics of Neural Network Changes in Normal Aging and Early Dementia

To understand the mechanisms underlying preserved and impaired cognitive function in healthy aging and dementia, respectively, the spatial relationships of brain networks and mechanisms of their resilience should be understood. The hub regions of the brain, such as the multisensory integration and default mode networks, are critical for within- and between-network communication, remain well-preserved during aging, and play an essential role in compensatory processes. On the other hand, these brain hubs are the preferred sites for lesions in neurodegenerative dementias, such as Alzheimer's disease. Disrupted primary information processing networks, such as the auditory, visual, and sensorimotor networks, may lead to overactivity of the multisensory integration networks and accumulation of pathological proteins that cause dementia. At the cellular level, the brain hub regions contain many synapses and require a large amount of energy. These regions are rich in ATP-related gene expression and had high glucose metabolism as demonstrated on positron emission tomography (PET). Importantly, the number and function of mitochondria, which are the center of ATP production, decline by about 8% every 10 years. Dementia patients often have dysfunction of the ubiquitin-proteasome and autophagy-lysosome systems, which require large amounts of ATP. If there is low energy supply but the demand is high, the risk of disease can be high. Imbalance between energy supply and demand may cause accumulation of pathological proteins and play an important role in the development of dementia. This energy imbalance may explain why brain hub regions are vulnerable to damage in different dementias. Here, we review (1) the characteristics of gray matter network, white matter network, and resting state functional network changes related to resilience in healthy aging, (2) the mode of resting state functional network disruption in neurodegenerative dementia, and (3) the cellular mechanisms associated with the disruption.

Positive Effects of Education on Cognitive Functioning Depend on Clinical Status and Neuropathological Severity

Background: Variability in cognitive functions in healthy and pathological aging is often explained by educational attainment. However, it remains unclear to which extent different disease states alter protective effects of education. We aimed to investigate whether protective effects of education on cognition depend on (1) clinical diagnosis severity, and (2) the neuropathological burden within a diagnosis in a memory clinic setting. Methods: In this cross-sectional study, we included 108 patients with subjective cognitive decline [SCD, median age 71, IQR (66-78), 43% men], 190 with mild cognitive impairment [MCI, median age 78, IQR (73-82), 44% men], and 245 with Alzheimer's disease dementia (AD) [median age 80, IQR (76-84), 35% men]. We combined visual ratings of hippocampal atrophy, global atrophy, and white matter hyperintensities on MRI into a single neuropathology score. To investigate whether the contribution of education to cognitive performance differed across SCD, MCI, and AD, we employed several multiple linear regression models, stratified by diagnosis and adjusted for age, sex, and neurodegeneration. We re-ran each model with an additional interaction term to investigate whether these effects were influenced by neuropathological burden for each diagnostic group separately. False discovery rate (FDR) corrections for multiple comparisons were applied. Results: We observed significant positive associations between education and performance for global cognition and executive functions (all adjusted p-values < 0.05). As diagnosis became more severe, however, the strength of these associations decreased (all adjusted p-values < 0.05). Education related to episodic memory only at relatively lower levels of neuropathology in SCD (β = -0.23, uncorrected p = 0.02), whereas education related to episodic memory in those with higher levels of neuropathology in MCI (β = 0.15, uncorrected p = 0.04). However, these interaction effects did not survive FDR-corrections. Conclusions: Altogether, our results demonstrated that positive effects of education on cognitive functioning reduce with diagnosis severity, but the role of neuropathological burden within a particular diagnosis was small and warrants further investigation. Future studies may further unravel the extent to which different dimensions of an individual's disease severity contribute to the waxing and waning of protective effects in cognitive aging.

The relationship between non-motor features and weight-loss in the premanifest stage of Huntington's disease

Weight-loss is an integral part of Huntington's disease (HD) that can start before the onset of motor symptoms. Investigating the underlying pathological processes may help in the understanding of this devastating disease as well as contribute to its management. However, the complex behavior and associations of multiple biological factors is impractical to be interpreted by the conventional statistics or human experts. For the first time, we combine a clinical dataset, expert knowledge and machine intelligence to model the multi-dimensional associations between the potentially relevant factors and weight-loss activity in HD, specifically at the premanifest stage. The HD dataset is standardized and transformed into required knowledge base with the help of clinical HD experts, which is then processed by the class rule mining and self-organising maps to identify the significant associations. Statistical results and experts' report indicate a strong association between severe weight-loss in HD at the premanifest stage and measures of certain cognitive, psychiatric functional ability factors. These results suggest that the mechanism underlying weight-loss in HD is, at least partly related to dysfunction of certain areas of the brain, a finding that may have not been apparent otherwise. These associations will aid the understanding of the pathophysiology of the disease and its progression and may in turn help in HD treatment trials.

Neural dynamics of semantic categorization in semantic variant of primary progressive aphasia

Semantic representations are processed along a posterior-to-anterior gradient reflecting a shift from perceptual (e.g., it has eight legs) to conceptual (e.g., venomous spiders are rare) information. One critical region is the anterior temporal lobe (ATL): patients with semantic variant primary progressive aphasia (svPPA), a clinical syndrome associated with ATL neurodegeneration, manifest a deep loss of semantic knowledge. We test the hypothesis that svPPA patients perform semantic tasks by over-recruiting areas implicated in perceptual processing. We compared MEG recordings of svPPA patients and healthy controls during a categorization task. While behavioral performance did not differ, svPPA patients showed indications of greater activation over bilateral occipital cortices and superior temporal gyrus, and inconsistent engagement of frontal regions. These findings suggest a pervasive reorganization of brain networks in response to ATL neurodegeneration: the loss of this critical hub leads to a dysregulated (semantic) control system, and defective semantic representations are seemingly compensated via enhanced perceptual processing.

miR-128 as a Regulator of Synaptic Properties in 5xFAD Mice Hippocampal Neurons

Alzheimer's disease (AD) is characterized by progressive synaptic dysfunction, deterioration of neuronal transmission, and consequently neuronal death. Although there is no treatment for AD, exposure to enriched environment (EE) in mice, as well as physical and mental activity in human subjects have been shown to have a protective effect by slowing the disease's progression and reducing AD-like cognitive impairment. However, the molecular mechanism of this mitigating effect is still not understood. One of the mechanisms that has recently been shown to be involved in neuronal degeneration is microRNAs (miRNAs) regulation, which act as a post-transcriptional regulators of gene expression. miR-128 has been shown to be significantly altered in individuals with AD and in mice following exposure to EE. Here, we focused on elucidating the possible role of miR-128 in AD pathology and found that miR-128 regulates the expression of two proteins essential for synaptic transmission, SNAP-25, and synaptotagmin1 (Syt1). Clinically relevant, in 5xFAD mouse model for AD, this miRNA's expression was found as downregulated, resembling the alteration found in the hippocampi of individuals with AD. Interestingly, exposing WT mice to EE also resulted in downregulation of miR-128 expression levels, although EE and AD conditions demonstrate opposing effects on neuronal functioning and synaptic plasticity. We also found that miR-128 expression downregulation in primary hippocampal cultures from 5xFAD mice results in increased neuronal network activity and neuronal excitability. Altogether, our findings place miR-128 as a synaptic player that may contribute to synaptic functioning and plasticity through regulation of synaptic protein expression and function.

Brain functional network integrity sustains cognitive function despite atrophy in presymptomatic genetic frontotemporal dementia

INTRODUCTION

The presymptomatic phase of neurodegenerative disease can last many years, with sustained cognitive function despite progressive atrophy. We investigate this phenomenon in familial frontotemporal dementia (FTD).

METHODS

We studied 121 presymptomatic FTD mutation carriers and 134 family members without mutations, using multivariate data-driven approach to link cognitive performance with both structural and functional magnetic resonance imaging. Atrophy and brain network connectivity were compared between groups, in relation to the time from expected symptom onset.

RESULTS

There were group differences in brain structure and function, in the absence of differences in cognitive performance. Specifically, we identified behaviorally relevant structural and functional network differences. Structure-function relationships were similar in both groups, but coupling between functional connectivity and cognition was stronger for carriers than for non-carriers, and increased with proximity to the expected onset of disease.

DISCUSSION

Our findings suggest that the maintenance of functional network connectivity enables carriers to maintain cognitive performance.

Stimulating aged brains with transcranial direct current stimulation: Opportunities and challenges

Ageing involves significant neurophysiological changes that are both systematic while at the same time exhibiting divergent trajectories across individuals. These changes underlie cognitive impairments in elderly while also affecting the response of aged brains to interventions like transcranial direct current stimulation (tDCS). While the cognitive benefits of tDCS are more variable in elderly, older adults also respond differently to stimulation protocols compared to young adults. The age-related neurophysiological changes influencing the responsiveness to tDCS remain to be addressed in-depth. We review and discuss the premise that, in comparison to the better calibrated brain networks present in young adults, aged systems perform further away from a homoeostatic set-point. We argue that this age-related neurophysiological deviation from the homoeostatic optimum extends the leeway for tDCS to modulate the aged brain. This promotes the potency of immediate tDCS effects to induce directional plastic changes towards the homoeostatic equilibrium despite the impaired plasticity induction in elderly. We also consider how age-related neurophysiological changes pose specific challenges for tDCS that necessitate proper adaptations of stimulation protocols. Appreciating the distinctive properties of aged brains and the accompanying adjustment of stimulation parameters can increase the potency and reliability of tDCS as a treatment avenue in older adults.

Graph Theory Analysis Reveals Resting-State Compensatory Mechanisms in Healthy Aging and Prodromal Alzheimer's Disease

Several theories of cognitive compensation have been suggested to explain sustained cognitive abilities in healthy brain aging and early neurodegenerative processes. The growing number of studies investigating various aspects of task-based compensation in these conditions is contrasted by the shortage of data about resting-state compensatory mechanisms. Using our proposed criterion-based framework for compensation, we investigated 45 participants in three groups: (i) patients with mild cognitive impairment (MCI) and positive biomarkers indicative of Alzheimer's disease (AD); (ii) cognitively normal young adults; (iii) cognitively normal older adults. To increase reliability, three sessions of resting-state functional magnetic resonance imaging for each participant were performed on different days (135 scans in total). To elucidate the dimensions and dynamics of resting-state compensatory mechanisms, we used graph theory analysis along with volumetric analysis. Graph theory analysis was applied based on the Brainnetome atlas, which provides a connectivity-based parcellation framework. Comprehensive neuropsychological examinations including the Rey Auditory Verbal Learning Test (RAVLT) and the Trail Making Test (TMT) were performed, to relate graph measures of compensatory nodes to cognition. To avoid false-positive findings, results were corrected for multiple comparisons. First, we observed an increase of degree centrality in cognition related brain regions of the middle frontal gyrus, precentral gyrus and superior parietal lobe despite local atrophy in MCI and healthy aging, indicating a resting-state connectivity increase with positive biomarkers. When relating the degree centrality measures to cognitive performance, we observed that greater connectivity led to better RAVLT and TMT scores in MCI and, hence, might constitute a compensatory mechanism. The detection and improved understanding of the compensatory dynamics in healthy aging and prodromal AD is mandatory for implementing and tailoring preventive interventions aiming at preserved overall cognitive functioning and delayed clinical onset of dementia.

Association of specific biotypes in patients with Parkinson disease and disease progression

Objective

To identify biotypes in patients with newly diagnosed Parkinson disease (PD) and to test whether these biotypes could explain interindividual differences in longitudinal progression.

Methods

In this longitudinal analysis, we use a data-driven approach clustering PD patients from the Parkinson's Progression Markers Initiative (n = 314, age 61.0 ± 9.5, years 34.1% female, 5 years of follow-up). Voxel-level neuroanatomic features were estimated with deformation-based morphometry (DBM) of T1-weighted MRI. Voxels with deformation values that were significantly correlated (p < 0.01) with clinical scores (Movement Disorder Society–sponsored revision of the Unified Parkinson’s Disease Rating Scale Parts I–III and total score, tremor score, and postural instability and gait difficulty score) at baseline were selected. Then, these neuroanatomic features were subjected to hierarchical cluster analysis. Changes in the longitudinal progression and neuroanatomic pattern were compared between different biotypes.

Results

Two neuroanatomic biotypes were identified: biotype 1 (n = 114) with subcortical brain volumes smaller than heathy controls and biotype 2 (n = 200) with subcortical brain volumes larger than heathy controls. Biotype 1 had more severe motor impairment, autonomic dysfunction, and much worse REM sleep behavior disorder than biotype 2 at baseline. Although disease durations at the initial visit and follow-up were similar between biotypes, patients with PD with smaller subcortical brain volume had poorer prognosis, with more rapid decline in several clinical domains and in dopamine functional neuroimaging over an average of 5 years.

Conclusion

Robust neuroanatomic biotypes exist in PD with distinct clinical and neuroanatomic patterns. These biotypes can be detected at diagnosis and predict the course of longitudinal progression, which should benefit trial design and evaluation.

Older, non-demented apolipoprotein ε4 carrier males show hyperactivation and structural differences in odor memory regions: a blood-oxygen-level-dependent and structural magnetic resonance imaging study

The current study sought to examine the interaction of sex and Apolipoprotein ε₄ status on olfactory recognition memory within non-demented, older individuals. We separated 39 participants into groups based on ε₄ status and sex. Each participant completed an olfactory memory recognition task during 2 functional magnetic resonance imaging scans and 1 structural scan. The ε₄ carriers had greater functional recruitment of memory regions during false positives relative to ε₄ non-carriers. During hits, the male ε₄ carriers showed greater functional recruitment compared to female ε₄ carriers. The ε₄ carriers had larger bilateral putamen volumes relative to ε₄ non-carriers. Neuroimaging data were significantly associated with Dementia Rating Scale scores solely in males. Results suggest differential olfactory memory processing in relation to sex and ε₄ status. Male ε₄ carriers in particular, demonstrated hyperactivation during recognition memory, which we suspect reflects neuronal compensation to maintain functional performance. Future studies should consider examining underlying mechanisms that contribute to these sex differences within ε₄ carriers.

Brain compensation during response inhibition in premanifest Huntington's disease

Premanifest Huntington's disease (pre-HD) individuals typically show increased task-related functional magnetic resonance imaging (fMRI), suggested to reflect compensatory strategies. Despite the evidence, no study has attempted to understand the compensatory process in light of 'formal' models of compensation. We used a quantitative model of compensation - the Compensation-Related Utilization of Neural Circuits Hypothesis (CRUNCH), to characterise compensation in pre-HD using fMRI. Pre-HD individuals (n = 15) and controls (n = 15) performed a modified stop-signal task that incremented in four levels of stop difficulty. Our results did not support the critical assumption of the CRUNCH model - controls did not show increased fMRI activity with increased level of stop difficulty; however, controls showed decreased fMRI activity with increased stop difficulty in right inferior frontal gyrus and right caudate nucleus. Relative to controls, pre-HD individuals showed increased fMRI activity in right inferior frontal gyrus and in right caudate nucleus at higher levels of stop difficulty, which is the opposite effect to that predicted by the model. Our findings suggest a compensatory process of the response inhibition network in pre-HD; however, the pattern of fMRI activity was not in the manner expected by CRUNCH.

Sex differences in Parkinson's disease: A transcranial magnetic stimulation study

BACKGROUND

Demographic and clinical studies imply that female sex may be protective for PD, but pathophysiological evidence to support these observations is missing. In early PD, functional changes may be detected in primary motor cortex using transcranial magnetic stimulation.

OBJECTIVE

We hypothesised that if pathophysiology differs between sexes in PD, this will be reflected in differences of motor cortex measurements.

METHODS

Forty-one newly diagnosed PD patients (22 males, 19 females) were clinically assessed using MDS-UPDRS part III, and various measures of cortical excitability and sensorimotor cortex plasticity were measured over both hemispheres, corresponding to the less and more affected side, using transcranial magnetic stimulation. Twenty-three healthy (10 men, 13 women) participants were studied for comparison.

RESULTS

Among patients, no significant differences between sexes were found in age, age of diagnosis, symptom duration, and total or lateralized motor score. However, male patients had disturbed interhemispheric balance of motor thresholds, caused by decreased resting and active motor thresholds in the more affected hemisphere. Short interval intracortical inhibition was more effective in female compared to male patients in both hemispheres. Female patients had a preserved physiological focal response to sensorimotor plasticity protocol, whereas male patients showed an abnormal spread of the protocol effect.

CONCLUSION

The study provides one of the first neurophysiological evidences of sex differences in early PD. Female patients have a more favorable profile of transcranial magnetic stimulation measures, possibly reflecting a more successful cortical compensation or delayed maladaptive changes in the sensorimotor cortex. © 2019 International Parkinson and Movement Disorder Society.

Evidence of parietal hyperactivation in individuals with mild cognitive impairment who progressed to dementia: A longitudinal fMRI study

Hyperactivation, which is defined as a higher level of activation in patients compared to cognitively unimpaired older adults (controls; CTL), might represent an early signature of Alzheimer's Disease (AD). The goal of this study was to assess the presence and location of hyperactivation in individuals with mild cognitive impairment (MCI) who were later diagnosed with dementia, examine how hyperactivation changes longitudinally, and whether it is related to time before dementia. Forty participants, 26 with MCI and 14 CTL were enrolled in the study. Magnetic resonance imaging was used to measure functional activation while participants encoded word-pairs as well as cortical thickness and regional brain volume at study entry (Y0) and two years later (Y2). Clinical follow-up was completed every two years following study entry to identify progressors (pMCI), that is, individuals who later received a diagnosis of dementia. Task-related activation was assessed in pMCI in both hippocampi and in regions showing greater cortical thinning from Y0 to Y2 compared to CTLs. Hyperactivation was found in pMCI individuals in the right supramarginal gyrus. Persons with pMCI also showed hypoactivation in the left hippocampus and left pars opercularis. Both hyper- and hypoactivation were present at Y0 and Y2 and did not change longitudinally. Activation was not associated with time before dementia diagnosis. Smaller volume and thinner cortical thickness were associated with shorter time to diagnosis in the left hippocampus and left pars opercularis. In conclusion, hyperactivation was found in individuals who later progressed to dementia, confirming that it might represent an early biomarker to identify individuals in the prodromal phase of AD and that its understanding could contribute to elucidate the key brain mechanisms that precede dementia.

A MEG study of the neural substrates of semantic processing in semantic variant primary progressive aphasia

Despite a well-documented pattern of semantic impairment, the patterns of brain activation during semantic processing in semantic variant primary progressive aphasia (svPPA) still remain poorly understood. In the current study, one svPPA patient (EC) and six elderly controls carried out a general-level semantic categorization task while their brain activity was recorded using magnetoencephalography (MEG). Despite similar behavioral performance, EC showed hyperactivation of the left inferior temporal gyrus (ITG) and right anterior temporal lobe (ATL) relative to controls. This suggests that periatrophic regions within the ATL region may support preserved semantic abilities in svPPA.

Huntington's disease: Brain imaging in Huntington's disease

Huntington's disease (HD) gene-carriers show prominent neuronal loss by end-stage disease, and the use of magnetic resonance imaging (MRI) has been increasingly used to quantify brain changes during earlier stages of the disease. MRI offers an in vivo method of measuring structural and functional brain change. The images collected via MRI are processed to measure different anatomical features, such as brain volume, macro- and microstructural changes within white matter and functional brain activity. Structural imaging has demonstrated significant volume loss across multiple white and gray matter regions in HD, particularly within subcortical structures. There also appears to be increasing disorganization of white matter tracts and between-region connectivity with increasing disease progression. Finally, functional changes are thought to represent changes in brain activity underlying compensatory mechanisms in HD. This chapter will provide an overview of the principles of MRI and practicalities associated with using MRI in HD studies, and summarize findings from MRI studies investigating brain structure and function in HD.

Dopamine depletion alters macroscopic network dynamics in Parkinson's disease

Parkinson's disease is primarily characterized by diminished dopaminergic function; however, the impact of these impairments on large-scale brain dynamics remains unclear. It has been difficult to disentangle the direct effects of Parkinson's disease from compensatory changes that reconfigure the functional signature of the whole brain network. To examine the causal role of dopamine depletion in network-level topology, we investigated time-varying network structure in 37 individuals with idiopathic Parkinson's disease, both ON and OFF dopamine replacement therapy, along with 50 age-matched, healthy control subjects using resting state functional MRI. By tracking dynamic network-level topology, we found that the Parkinson's disease OFF state was associated with greater network-level integration than in the ON state. The extent of integration in the OFF state inversely correlated with motor symptom severity, suggesting that a shift toward a more integrated network topology may be a compensatory mechanism associated with preserved motor function in the dopamine depleted OFF state. Furthermore, we were able to demonstrate that measures of both cognitive and brain reserve (i.e. premorbid intelligence and whole brain grey matter volume) had a positive relationship with the relative increase in network integration observed in the dopaminergic OFF state. This suggests that each of these factors plays an important role in promoting network integration in the dopaminergic OFF state. Our findings provide a mechanistic basis for understanding the Parkinson's disease OFF state and provide a further conceptual link with network-level reconfiguration. Together, our results highlight the mechanisms responsible for pathological and compensatory change in Parkinson's disease.

Translational research on reserve against neurodegenerative disease: consensus report of the International Conference on Cognitive Reserve in the Dementias and the Alzheimer's Association Reserve, Resilience and Protective Factors Professional Interest Area working groups

BACKGROUND

The concept of reserve was established to account for the observation that a given degree of neurodegenerative pathology may result in varying degrees of symptoms in different individuals. There is a large amount of evidence on epidemiological risk and protective factors for neurodegenerative diseases and dementia, yet the biological mechanisms that underpin the protective effects of certain lifestyle and physiological variables remain poorly understood, limiting the development of more effective preventive and treatment strategies. Additionally, different definitions and concepts of reserve exist, which hampers the coordination of research and comparison of results across studies.

DISCUSSION

This paper represents the consensus of a multidisciplinary group of experts from different areas of research related to reserve, including clinical, epidemiological and basic sciences. The consensus was developed during meetings of the working groups of the first International Conference on Cognitive Reserve in the Dementias (24-25 November 2017, Munich, Germany) and the Alzheimer's Association Reserve and Resilience Professional Interest Area (25 July 2018, Chicago, USA). The main objective of the present paper is to develop a translational perspective on putative mechanisms underlying reserve against neurodegenerative disease, combining evidence from epidemiological and clinical studies with knowledge from animal and basic research. The potential brain functional and structural basis of reserve in Alzheimer's disease and other brain disorders are discussed, as well as relevant lifestyle and genetic factors assessed in both humans and animal models.

CONCLUSION

There is an urgent need to advance our concept of reserve from a hypothetical model to a more concrete approach that can be used to improve the development of effective interventions aimed at preventing dementia. Our group recommends agreement on a common dictionary of terms referring to different aspects of reserve, the improvement of opportunities for data sharing across individual cohorts, harmonising research approaches across laboratories and groups to reduce heterogeneity associated with human data, global coordination of clinical trials to more effectively explore whether reducing epidemiological risk factors leads to a reduced burden of neurodegenerative diseases in the population, and an increase in our understanding of the appropriateness of animal models for reserve research.

An active cognitive lifestyle as a potential neuroprotective factor in Huntington's disease

A cognitive stimulating lifestyle has been observed to confer cognitive benefits in multiple neurodegenerative diseases. However, the underlying neurobiological basis of this phenomenon remains unclear. Huntington's disease can provide a suitable model to study the effects and neural mechanisms of cognitive engagement in neurodegeneration. In this study, we investigate the effect of lifestyle factors such as education, occupation and engagement in cognitive activities in Huntington's disease gene carriers on cognitive performance and age of onset as well as the underlying neural changes sustaining these effects, measured by magnetic resonance imaging. Specifically, we analyzed both gray matter volume and the strength of connectivity of the executive control resting-state network. High levels of cognitive engagement were significantly associated with more preserved executive functions, a delay in the appearance of symptoms, reduced volume loss of the left precuneus and the bilateral caudate and a modulation of connectivity strength of anterior cingulate cortex and left angular gyrus with the executive control network. These findings suggest that a cognitively stimulating lifestyle may promote brain maintenance by modulating the executive control resting-state network and conferring protection against neurodegeneration, which results in a delayed onset of symptoms and improved performance in executive functions.

Reduced Purkinje cell size is compatible with near normal morphology and function of the cerebellar cortex in a mouse model of spinocerebellar ataxia

Spinocerebellar ataxia type 14 (SCA14) is a dominantly inherited neurodegenerative disease caused by diverse mutations in the Protein Kinase C gamma (PKCγ) gene which is one of the crucial signaling molecules of Purkinje cells. We have previously created a mouse model of SCA14 by transgenic expression of a mutated PKCγ gene causing SCA14 with a mutation in the catalytic domain. Purkinje cells from the mutated mice have a strong reduction of their dendritic tree in organotypic slice cultures typical for increased PKC activity. There was no overt degeneration of Purkinje cells in vivo and the cerebellum appeared morphologically normal with the exception of lobule 7 where abnormal Purkinje cells were present. Besides from mild motor deficits the mice have no major phenotype. We have now done a more extensive study of cerebellar morphology in these mice and show by rapid Golgi staining that there is a marked reduction of Purkinje cell dendritic tree size throughout the cerebellum. Despite this reduction in dendritic tree size, climbing fiber innervation of Purkinje cells as visualized by immunostaining for the vesicular glutamate transporter 2 (vGlut2) appeared normal in most parts of the cerebellum. The same was true for the expression of the activity and plasticity markers pS6, c-Fos and Arc. These finding suggest that the cerebellar cortex in the transgenic mice is functioning fairly normal and that the reduction of dendritic tree size and the increased PKC activity can be compensated in most Purkinje cells. Around cerebellar lobule 7 there was high transgene expression from the L7 promotor and Purkinje cells showed abnormal morphologies. Climbing fiber innervation as well as the expression of the activity and plasticity markers was strongly disturbed in this area. Our results show that there is substantial potential for functional compensation in the cerebellar cortex. In lobule 7, an area with high transgene expression, compensation failed resulting in Purkinje cell degeneration and dysfunction.

In vivo characterization of white matter pathology in premanifest huntington's disease

OBJECTIVE

Huntington's disease (HD) is a monogenic, fully penetrant neurodegenerative disorder, providing an ideal model for understanding brain changes occurring in the years prior to disease onset. Diffusion tensor imaging (DTI) studies show widespread white matter disorganization in the early premanifest stages (pre-HD). However, although DTI has proved informative, it provides only limited information about underlying changes in tissue properties. Neurite orientation dispersion and density imaging (NODDI) is a novel magnetic resonance imaging (MRI) technique for characterizing axonal pathology more specifically, providing metrics that separately quantify axonal density and axonal organization. Here, we provide the first in vivo characterization of white matter pathology in pre-HD using NODDI.

METHODS

Diffusion-weighted MRI data that support DTI and NODDI were acquired from 38 pre-HD and 45 control participants. Using whole-brain and region-of-interest analyses, NODDI metrics were compared between groups and correlated with clinical scores of disease progression. Whole-brain changes in DTI metrics were also examined.

RESULTS

The pre-HD group displayed widespread reductions in axonal density compared with control participants; this correlated with measures of clinical disease progression in the body and genu of the corpus callosum. There was also evidence in the pre-HD group of increased coherence of axonal packing in the white matter surrounding the basal ganglia.

INTERPRETATION

Our findings suggest that reduced axonal density is one of the major factors underlying white matter pathology in pre-HD, coupled with altered local organization in areas surrounding the basal ganglia. NODDI metrics show promise in providing more specific information about the biological processes underlying HD and neurodegeneration per se. Ann Neurol 2018;84:497-504.

Investigating the relationships between hypothalamic volume and measures of circadian rhythm and habitual sleep in premanifest Huntington's disease

Objective

Pathological changes within the hypothalamus have been proposed to mediate circadian rhythm and habitual sleep disturbances in individuals with Huntington's disease (HD). However, investigations examining the relationships between hypothalamic volume and circadian rhythm and habitual sleep in individuals with HD are sparse. This study aimed to comprehensively evaluate the relationships between hypothalamic pathology and circadian rhythm and habitual sleep disturbances in individuals with premanifest HD.

Methods

Thirty-two individuals with premanifest HD and twenty-nine healthy age- and gender-matched controls participated in this dual-site, cross-sectional study. Magnetic resonance imaging scans were performed to evaluate hypothalamic volume. Circadian rhythm and habitual sleep were assessed via measurement of morning and evening cortisol and melatonin levels, wrist-worn actigraphy, the Consensus Sleep Diary and sleep questionnaires. Information on mood, physical activity levels and body composition were also collected.

Results

Compared to healthy controls, individuals with premanifest HD displayed significantly reduced grey matter volume in the hypothalamus, decreased habitual sleep efficiency and increased awakenings; however, no alterations in morning cortisol or evening melatonin release were noted in individuals with premanifest HD. While differences in the associations between hypothalamic volume and cortisol and melatonin output existed in individuals with premanifest HD compared to healthy controls, no consistent associations were observed between hypothalamic volume and circadian rhythm or habitual sleep outcomes.

Conclusion

While significant differences in associations between hypothalamic volume and cortisol and melatonin existed between individuals with premanifest HD and healthy controls, no differences in circadian markers were observed between the groups. This suggests that circadian regulation is maintained despite hypothalamic pathology, perhaps via neural compensation. Longitudinal studies are required to further understand the relationships between the hypothalamus and circadian rhythm and habitual sleep disturbances in HD as the disease course lengthens.

Testing a longitudinal compensation model in premanifest Huntington's disease

The initial stages of neurodegeneration are commonly marked by normal levels of cognitive and motor performance despite the presence of structural brain pathology. Compensation is widely assumed to account for this preserved behaviour, but despite the apparent simplicity of such a concept, it has proven incredibly difficult to demonstrate such a phenomenon and distinguish it from disease-related pathology. Recently, we developed a model of compensation whereby brain activation, behaviour and pathology, components key to understanding compensation, have specific longitudinal trajectories over three phases of progression. Here, we empirically validate our explicit mathematical model by testing for the presence of compensation over time in neurodegeneration. Huntington's disease is an ideal model for examining longitudinal compensation in neurodegeneration as it is both monogenic and fully penetrant, so disease progression and potential compensation can be monitored many years prior to diagnosis. We defined our conditions for compensation as non-linear longitudinal trajectories of brain activity and performance in the presence of linear neuronal degeneration and applied our model of compensation to a large longitudinal cohort of premanifest and early-stage Huntington's disease patients from the multisite Track-On HD study. Focusing on cognitive and motor networks, we integrated progressive volume loss, task and resting state functional MRI and cognitive and motor behaviour across three sequential phases of neurodegenerative disease progression, adjusted for genetic disease load. Multivariate linear mixed models were fitted and trajectories for each variable tested. Our conceptualization of compensation was partially realized across certain motor and cognitive networks at differing levels. We found several significant network trends that were more complex than that hypothesized in our model. These trends suggest changes to our theoretical model where the network effects are delayed relative to performance effects. There was evidence of compensation primarily in the prefrontal component of the cognitive network, with increased effective connectivity between the left and right dorsolateral prefrontal cortex. Having developed an operational model for the explicit testing of longitudinal compensation in neurodegeneration, it appears that general patterns of our framework are consistent with the empirical data. With the proposed modifications, our operational model of compensation can be used to test for both cross-sectional and longitudinal compensation in neurodegenerative disease with similar patterns to Huntington's disease.

Brain Aging and APOE ε4 Interact to Reveal Potential Neuronal Compensation in Healthy Older Adults

Compensation implies the recruitment of additional neuronal resources to prevent the detrimental effect of age-related neuronal decline on cognition. Recently suggested statistical models comprise behavioral performance, brain activation, and measures related to aging- or disease-specific pathological burden to characterize compensation. Higher chronological age as well as the APOE ε4 allele are risk factors for Alzheimer's disease. A more biological approach to characterize aging compared with chronological age is the brain age gap estimation (BrainAGE), taking into account structural brain characteristics. We utilized this estimate in an fMRI experiment together with APOE variant as measures related to pathological burden and aimed at identifying compensatory regions during working memory (WM) processing in a group of 34 healthy older adults. According to published compensation criteria, better performance along with increased brain activation would indicate successful compensation. We examined the moderating effects of BrainAGE on the relationship between task performance and brain activation in prefrontal cortex, as previous studies suggest predominantly frontal compensatory activation. Then we statistically compared them to the effects of chronological age (CA) tested in a previous study. Moreover, we examined the effects of adding APOE variant as a further moderator. Herewith, we strived to uncover neuronal compensation in healthy older adults at risk for neurodegenerative disease. Higher BrainAGE alone was not associated with an increased recruitment in prefrontal cortex. When adding APOE variant as a second moderator, we found an interaction of BrainAGE and APOE variant, such that ε4 carriers recruited right inferior frontal gyrus with higher BrainAGE to maintain WM performance, thus showing a pattern compatible with successful neuronal compensation. Exploratory analyses yielded similar patterns in left inferior and bilateral middle frontal gyrus. These results contrast those from a previous study, where we found no indication of compensation in prefrontal cortex in ε4 carriers with increasing CA. We conclude that BrainAGE together with APOE variant can help to reveal potential neuronal compensation in healthy older adults. Previous results on neuronal compensation in frontal areas corroborate our findings. Compensatory brain regions could be targeted in affected individuals by training or stimulation protocols to maintain cognitive functioning as long as possible.

Functional segregation loss over time is moderated by APOE genotype in healthy elderly

We investigated the influence of the apolipoprotein E-ɛ4 allele (APOE-ɛ4) on longitudinal age-related changes in brain functional connectivity (FC) and cognition, in view of mixed cross-sectional findings. One hundred and twenty-two healthy older adults (aged 58-79; 25 APOE-ɛ4 carriers) underwent task-free fMRI scans at baseline. Seventy-eight (16 carriers) had at least one follow-up (every 2 years). Changes in intra- and internetwork FCs among the default mode (DMN), executive control (ECN), and salience (SN) networks, as well as cognition, were quantified using linear mixed models. Cross-sectionally, APOE-ɛ4 carriers had lower functional connectivity between the ECN and SN than noncarriers. Carriers also showed a stronger age-dependent decrease in visuospatial memory performance. Longitudinally, carriers had steeper increase in inter-ECN-DMN FC, indicating loss of functional segregation. The longitudinal change in processing speed performance was not moderated by APOE-ɛ4 genotype, but the brain-cognition association was. In younger elderly, faster loss of segregation was correlated with greater decline in processing speed regardless of genotype. In older elderly, such relation remained for noncarriers but reversed for carriers. APOE-ɛ4 may alter aging by accelerating the change in segregation between high-level cognitive systems. Its modulation on the longitudinal brain-cognition relationship was age-dependent.

Measuring compensation in neurodegeneration using MRI

PURPOSE OF REVIEW

Despite signs of cortical and subcortical loss, patients with prodromal and early-stage neurodegenerative disease are able to perform at a level comparable to the normal population. It is presumed that the onset of compensatory processes, that is changes in brain activation within a function-specific network or in the recruitment of a region outside of the task-network, underlies this maintenance of normal performance. However, in most studies to date, increased brain activity is not correlated with indices of both disease and performance and what appears to be compensation could simply be a symptom of neurodegeneration.

RECENT FINDINGS

MRI studies have explored compensation in neurodegenerative disease, claiming that compensation is evident across a number of disorders, including Alzheimer's and Parkinson's disease, but generally always in early stages; after this point, compensation is generally no longer able to operate under the severe burden of disease. However, none of these studies explicitly adopted a particular model of compensation. Thus, we also discuss our recent attempts to operationalize compensation for empirical testing.

SUMMARY

There is clear evidence of compensatory processes in the early stages of neurodegenerative disease. However, for a more complete understanding, this requires more explicit empirical modelling.

Cognition in Parkinson's Disease

Cognitive decline is now recognized as a common nonmotor symptom of Parkinson's disease, and it has been the subject of increasing research in recent decades. Cognitive deficits in Parkinson's disease can be distinguished as dopaminergically mediated executive dysfunction seen in the milder stages vs a global dementia syndrome that can occur with disease progression. The neural basis of these deficits has been explored from the perspective of multimodal imaging techniques to measure the structural, functional, and metabolic correlates of cognitive decline in Parkinson's disease. Increasingly, changes in neurotransmitter systems beyond dopamine, including the noradrenergic, serotonergic, and cholinergic systems, are being recognized for their contribution to cognitive decline. The impact of certain genetic variations on cognitive function has also been established, including links between cognitive decline and polymorphisms affecting COMT, MAPT, APOE, and GBA genotypes. Although therapeutic options for cognitive decline are still far less established than for motor systems, both pharmacological and nonpharmacological strategies are continuing to develop.