Advanced patient-specific microglia cell models for pre-clinical studies in Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is an incurable neurodegenerative disorder with a rapidly increasing prevalence worldwide. Current approaches targeting hallmark pathological features of AD have had no consistent clinical benefit. Neuroinflammation is a major contributor to neurodegeneration and hence, microglia, the brain's resident immune cells, are an attractive target for potentially more effective therapeutic strategies. However, there is no current in vitro model system that captures AD patient-specific microglial characteristics using physiologically relevant and experimentally flexible culture conditions. METHODS: To address this shortcoming, we developed novel 3D Matrigel-based monocyte-derived microglia-like cell (MDMi) mono-cultures and co-cultures with neuro-glial cells (ReNcell VM). We used single-cell RNA sequencing (scRNAseq) analysis to compare the transcriptomic signatures of MDMi between model systems (2D, 3D and 3D co-culture) and against published human microglia datasets. To demonstrate the potential of MDMi for use in personalized pre-clinical strategies, we generated and characterized MDMi models from sixteen AD patients and matched healthy controls, and profiled cytokine responses upon treatment with anti-inflammatory drugs (dasatinib and spiperone). RESULTS: MDMi in 3D exhibited a more branched morphology and longer survival in culture compared to 2D. scRNAseq uncovered distinct MDMi subpopulations that exhibit higher functional heterogeneity and best resemble human microglia in 3D co-culture. AD MDMi in 3D co-culture showed altered cell-to-cell interactions, growth factor and cytokine secretion profiles and responses to amyloid-ß. Drug testing assays revealed patient- and model-specific cytokine responses. CONCLUSION: Our study presents a novel, physiologically relevant and AD patient-specific 3D microglia cell model that opens avenues towards improving personalized drug development strategies in AD.

Functional re-organization of hippocampal-cortical gradients during naturalistic memory processes.

The functional organization of the hippocampus mirrors that of the cortex, changing smoothly along connectivity gradients and abruptly at inter-areal boundaries. Hippocampal-dependent cognitive processes require flexible integration of these hippocampal gradients into functionally related cortical networks. To understand the cognitive relevance of this functional embedding, we acquired fMRI data while participants viewed brief news clips, either containing or lacking recently familiarized cues. Participants were 188 healthy mid-life adults and 31 adults with mild cognitive impairment (MCI) or Alzheimer's disease (AD). We employed a recently developed technique - connectivity gradientography - to study gradually changing patterns of voxel to whole brain functional connectivity and their sudden transitions. We observed that functional connectivity gradients of the anterior hippocampus map onto connectivity gradients across the default mode network during these naturalistic stimuli. The presence of familiar cues in the news clips accentuates a stepwise transition across the boundary from the anterior to the posterior hippocampus. This functional transition is shifted in the posterior direction in the left hippocampus of individuals with MCI or AD. These findings shed new light on the functional integration of hippocampal connectivity gradients into large-scale cortical networks, how these adapt with memory context and how these change in the presence of neurodegenerative disease.

Lower hypothalamic volume with lower body mass index is associated with shorter survival in patients with amyotrophic lateral sclerosis.

BACKGROUND AND PURPOSE: Weight loss in patients with amyotrophic lateral sclerosis (ALS) is associated with faster disease progression and shorter survival. Decreased hypothalamic volume is proposed to contribute to weight loss due to loss of appetite and/or hypermetabolism. We aimed to investigate the relationship between hypothalamic volume and body mass index (BMI) in ALS and Alzheimer's disease (AD), and the associations of hypothalamic volume with weight loss, appetite, metabolism and survival in patients with ALS. METHODS: We compared hypothalamic volumes from magnetic resonance imaging scans with BMI for patients with ALS (n = 42), patients with AD (n = 167) and non-neurodegenerative disease controls (n = 527). Hypothalamic volumes from patients with ALS were correlated with measures of appetite and metabolism, and change in anthropomorphic measures and disease outcomes. RESULTS: Lower hypothalamic volume was associated with lower and higher BMI in ALS (quadratic association; probability of direction = 0.96). This was not observed in AD patients or controls. Hypothalamic volume was not associated with loss of appetite (p = 0.58) or hypermetabolism (p = 0.49). Patients with lower BMI and lower hypothalamic volume tended to lose weight (p = 0.08) and fat mass (p = 0.06) over the course of their disease, and presented with an increased risk of earlier death (hazard ratio [HR] 3.16, p = 0.03). Lower hypothalamic volume alone trended for greater risk of earlier death (HR 2.61, p = 0.07). CONCLUSION: These observations suggest that lower hypothalamic volume in ALS contributes to positive and negative energy balance, and  is not universally associated with loss of appetite or hypermetabolism. Critically, lower hypothalamic volume with lower BMI was associated with weight loss and earlier death.

ALS monocyte-derived microglia-like cells reveal cytoplasmic TDP-43 accumulation, DNA damage, and cell-specific impairment of phagocytosis associated with disease progression.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a multifactorial neurodegenerative disease characterised by the loss of upper and lower motor neurons. Increasing evidence indicates that neuroinflammation mediated by microglia contributes to ALS pathogenesis. This microglial activation is evident in post-mortem brain tissues and neuroimaging data from patients with ALS. However, the role of microglia in the pathogenesis and progression of amyotrophic lateral sclerosis remains unclear, partly due to the lack of a model system that is able to faithfully recapitulate the clinical pathology of ALS. To address this shortcoming, we describe an approach that generates monocyte-derived microglia-like cells that are capable of expressing molecular markers, and functional characteristics similar to in vivo human brain microglia. METHODS: In this study, we have established monocyte-derived microglia-like cells from 30 sporadic patients with ALS, including 15 patients with slow disease progression, 6 with intermediate progression, and 9 with rapid progression, together with 20 non-affected healthy controls. RESULTS: We demonstrate that patient monocyte-derived microglia-like cells recapitulate canonical pathological features of ALS including non-phosphorylated and phosphorylated-TDP-43-positive inclusions. Moreover, ALS microglia-like cells showed significantly impaired phagocytosis, altered cytokine profiles, and abnormal morphologies consistent with a neuroinflammatory phenotype. Interestingly, all ALS microglia-like cells showed abnormal phagocytosis consistent with the progression of the disease. In-depth analysis of ALS microglia-like cells from the rapid disease progression cohort revealed significantly altered cell-specific variation in phagocytic function. In addition, DNA damage and NOD-leucine rich repeat and pyrin containing protein 3 (NLRP3) inflammasome activity were also elevated in ALS patient monocyte-derived microglia-like cells, indicating a potential new pathway involved in driving disease progression. CONCLUSIONS: Taken together, our work demonstrates that the monocyte-derived microglia-like cell model recapitulates disease-specific hallmarks and characteristics that substantiate patient heterogeneity associated with disease subgroups. Thus, monocyte-derived microglia-like cells are highly applicable to monitor disease progression and can be applied as a functional readout in clinical trials for anti-neuroinflammatory agents, providing a basis for personalised treatment for patients with ALS.

Digital Devices for Assessing Motor Functions in Mobility-Impaired and Healthy Populations: Systematic Literature Review.

BACKGROUND: With the advent of smart sensing technology, mobile and wearable devices can provide continuous and objective monitoring and assessment of motor function outcomes. OBJECTIVE: We aimed to describe the existing scientific literature on wearable and mobile technologies that are being used or tested for assessing motor functions in mobility-impaired and healthy adults and to evaluate the degree to which these devices provide clinically valid measures of motor function in these populations. METHODS: A systematic literature review was conducted by searching Embase, MEDLINE, CENTRAL (January 1, 2015, to June 24, 2020), the United States and European Union clinical trial registries, and the United States Food and Drug Administration website using predefined study selection criteria. Study selection, data extraction, and quality assessment were performed by 2 independent reviewers. RESULTS: A total of 91 publications representing 87 unique studies were included. The most represented clinical conditions were Parkinson disease (n=51 studies), followed by stroke (n=5), Huntington disease (n=5), and multiple sclerosis (n=2). A total of 42 motion-detecting devices were identified, and the majority (n=27, 64%) were created for the purpose of health care-related data collection, although approximately 25% were personal electronic devices (eg, smartphones and watches) and 11% were entertainment consoles (eg, Microsoft Kinect or Xbox and Nintendo Wii). The primary motion outcomes were related to gait (n=30), gross motor movements (n=25), and fine motor movements (n=23). As a group, sensor-derived motion data showed a mean sensitivity of 0.83 (SD 7.27), a mean specificity of 0.84 (SD 15.40), a mean accuracy of 0.90 (SD 5.87) in discriminating between diseased individuals and healthy controls, and a mean Pearson r validity coefficient of 0.52 (SD 0.22) relative to clinical measures. We did not find significant differences in the degree of validity between in-laboratory and at-home sensor-based assessments nor between device class (ie, health care-related device, personal electronic devices, and entertainment consoles). CONCLUSIONS: Sensor-derived motion data can be leveraged to classify and quantify disease status for a variety of neurological conditions. However, most of the recent research on digital clinical measures is derived from proof-of-concept studies with considerable variation in methodological approaches, and much of the reviewed literature has focused on clinical validation, with less than one-quarter of the studies performing analytical validation. Overall, future research is crucially needed to further consolidate that sensor-derived motion data may lead to the development of robust and transformative digital measurements intended to predict, diagnose, and quantify neurological disease state and its longitudinal change.

Non-linear realignment improves hippocampus subfield segmentation reliability.

Participant movement can deleteriously affect MR image quality. Further, for the visualization and segmentation of small anatomical structures, there is a need to improve image quality, specifically signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), by acquiring multiple anatomical scans consecutively. We aimed to ameliorate movement artefacts and increase SNR in a high-resolution turbo spin-echo (TSE) sequence acquired thrice using non-linear realignment in order to improve segmentation consistency of the hippocampus subfields. We assessed the method in 29 young healthy participants, 11 Motor Neuron Disease patients, and 11 age matched controls at 7T, and 24 healthy adolescents at 3T. Results show improved image segmentation of the hippocampus subfields when comparing template-based segmentations with individual segmentations with Dice overlaps N = 75; ps < 0.001 (Friedman's test) and higher sharpness ps < 0.001 in non-linearly realigned scans as compared to linearly, and arithmetically averaged scans.

Dominant hemisphere lateralization of cortical parasympathetic control as revealed by frontotemporal dementia.

The brain continuously influences and perceives the physiological condition of the body. Related cortical representations have been proposed to shape emotional experience and guide behavior. Although previous studies have identified brain regions recruited during autonomic processing, neurological lesion studies have yet to delineate the regions critical for maintaining autonomic outflow. Even greater controversy surrounds hemispheric lateralization along the parasympathetic-sympathetic axis. The behavioral variant of frontotemporal dementia (bvFTD), featuring progressive and often asymmetric degeneration that includes the frontoinsular and cingulate cortices, provides a unique lesion model for elucidating brain structures that control autonomic tone. Here, we show that bvFTD is associated with reduced baseline cardiac vagal tone and that this reduction correlates with left-lateralized functional and structural frontoinsular and cingulate cortex deficits and with reduced agreeableness. Our results suggest that networked brain regions in the dominant hemisphere are critical for maintaining an adaptive level of baseline parasympathetic outflow.

Latent source mining in FMRI via restricted Boltzmann machine.

Blind source separation (BSS) is commonly used in functional magnetic resonance imaging (fMRI) data analysis. Recently, BSS models based on restricted Boltzmann machine (RBM), one of the building blocks of deep learning models, have been shown to improve brain network identification compared to conventional single matrix factorization models such as independent component analysis (ICA). These models, however, trained RBM on fMRI volumes, and are hence challenged by model complexity and limited training set. In this article, we propose to apply RBM to fMRI time courses instead of volumes for BSS. The proposed method not only interprets fMRI time courses explicitly to take advantages of deep learning models in latent feature learning but also substantially reduces model complexity and increases the scale of training set to improve training efficiency. Our experimental results based on Human Connectome Project (HCP) datasets demonstrated the superiority of the proposed method over ICA and the one that applied RBM to fMRI volumes in identifying task-related components, resulted in more accurate and specific representations of task-related activations. Moreover, our method separated out components representing intermixed effects between task events, which could reflect inherent interactions among functionally connected brain regions. Our study demonstrates the value of RBM in mining complex structures embedded in large-scale fMRI data and its potential as a building block for deeper models in fMRI data analysis.

Distinct Cerebellar Contributions to Cognitive-Perceptual Dynamics During Natural Viewing.

The crucial role of the cerebellum in motor learning and coordination is very well known. Considerable interest has recently shifted toward its contribution to nonmotor tasks, such as working memory, emotion, and language. However, the cognitive role and functional subdivisions of the cerebellum, particularly in dynamic, ecologically realistic contexts, are not yet established. By analyzing functional neuroimaging data acquired while participants viewed a short dramatic movie, we found that posterior and inferior cerebellar regions are reliably engaged in dynamic perceptual and affective processes with no explicit motor component. These cerebellar regions show significant relevance to visual salience and unexpected turning points of the movie. Our results demonstrate that distinct functional subdivisions of the cerebellum are robustly engaged in real-life cognitive processes, playing specific roles through a dynamic interaction with higher order regions in the cerebral cortex.

Test-retest reliability of functional connectivity networks during naturalistic fMRI paradigms.

Functional connectivity analysis has become a powerful tool for probing the human brain function and its breakdown in neuropsychiatry disorders. So far, most studies adopted resting-state paradigm to examine functional connectivity networks in the brain, thanks to its low demand and high tolerance that are essential for clinical studies. However, the test-retest reliability of resting-state connectivity measures is moderate, potentially due to its low behavioral constraint. On the other hand, naturalistic neuroimaging paradigms, an emerging approach for cognitive neuroscience with high ecological validity, could potentially improve the reliability of functional connectivity measures. To test this hypothesis, we characterized the test-retest reliability of functional connectivity measures during a natural viewing condition, and benchmarked it against resting-state connectivity measures acquired within the same functional magnetic resonance imaging (fMRI) session. We found that the reliability of connectivity and graph theoretical measures of brain networks is significantly improved during natural viewing conditions over resting-state conditions, with an average increase of almost 50% across various connectivity measures. Not only sensory networks for audio-visual processing become more reliable, higher order brain networks, such as default mode and attention networks, but also appear to show higher reliability during natural viewing. Our results support the use of natural viewing paradigms in estimating functional connectivity of brain networks, and have important implications for clinical application of fMRI. Hum Brain Mapp 38:2226-2241, 2017. © 2017 Wiley Periodicals, Inc.

Cerebellar atrophy in neurodegeneration-a meta-analysis.

INTRODUCTION: The cerebellum has strong cortical and subcortical connectivity, but is rarely taken into account for clinical diagnosis in many neurodegenerative conditions, particularly in the absence of clinical ataxia. The current meta-analysis aims to assess patterns of cerebellar grey matter atrophy in seven neurodegenerative conditions (Alzheimer's disease (AD), Parkinson's disease (PD) and Huntington's disease (HD), frontotemporal dementia (FTD), amyotrophic lateral sclerosis (ALS), multiple system atrophy (MSA), progressive supranuclear palsy (MSP)). METHODS: We carried out a systematic search in PubMed (any date: 14 July 2016) and a hand search of references from pertinent articles according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The authors were contacted to provide missing coordinate data. Peer-reviewed studies with direct comparison of patient and control groups, and availability of coordinate data of grey matter cerebellar atrophy in patients were included. These coordinates were used in an anatomical likelihood estimation meta-analysis. RESULTS: Across 54 studies, clusters of cerebellar atrophy were found for AD, ALS, FTD, MSA, and PSP. Atrophy patterns were largely disease-specific, with overlap in certain areas of the cerebellar hemisphere, which showed marked atrophy in AD, ALS, FTD and PSP (Crus I/II), and MSA and PSP (lobules I-IV), respectively. Atrophy colocated with cerebellar areas implicated for motor (PSP, MSA) or cognitive symptoms (FTD, ALS, PSP) in the diseases. DISCUSSION: Our findings suggest that cerebellar changes are largely disease-specific and correspond to cortical or subcortical changes in neurodegenerative conditions. High clinical variability in PD and HD samples may explain the absence of findings for consistent grey matter loss across studies. Our results have clinical implications for diagnosis and cerebellar neuroimaging referencing approaches.

Network-selective vulnerability of the human cerebellum to Alzheimer's disease and frontotemporal dementia.

SEE SCHMAHMANN DOI101093/BRAIN/AWW064 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Neurodegenerative diseases are associated with distinct and distributed patterns of atrophy in the cerebral cortex. Emerging evidence suggests that these atrophy patterns resemble intrinsic connectivity networks in the healthy brain, supporting the network-based degeneration framework where neuropathology spreads across connectivity networks. An intriguing yet untested possibility is that the cerebellar circuits, which share extensive connections with the cerebral cortex, could be selectively targeted by major neurodegenerative diseases. Here we examined the structural atrophy in the cerebellum across common types of neurodegenerative diseases, and characterized the functional connectivity patterns of these cerebellar atrophy regions. Our results showed that Alzheimer's disease and frontotemporal dementia are associated with distinct and circumscribed atrophy in the cerebellum. These cerebellar atrophied regions share robust and selective intrinsic connectivity with the atrophied regions in the cerebral cortex. These findings for the first time demonstrated the selective vulnerability of the cerebellum to common neurodegenerative disease, extending the network-based degeneration framework to the cerebellum. Our work also has direct implications on the cerebellar contribution to the cognitive and affective processes that are compromised in neurodegeneration as well as the practice of using the cerebellum as reference region for ligand neuroimaging studies.

The integration of the internal and external milieu in the insula during dynamic emotional experiences.

Whilst external events trigger emotional responses, interoception (the perception of internal physiological states) is fundamental to core emotional experience. By combining high resolution functional neuroimaging with concurrent physiological recordings, we investigated the neural mechanisms of interoceptive integration during free listening to an emotionally salient audio film. We found that cardiac activity, a key interoceptive signal, was robustly synchronised across participants and centrally represented in the posterior insula. Effective connectivity analysis revealed that the anterior insula, specifically tuned to the emotionally salient moments of the audio stream, serves as an integration hub of interoceptive processing: interoceptive states represented in the posterior insula are integrated with exteroceptive representations by the anterior insula to highlight these emotionally salient moments. Our study for the first time demonstrates the insular hierarchy for interoceptive processing during natural emotional experience. These findings provide an ecologically-valid framework for elucidating the neural underpinnings of emotional deficits in neuropsychiatric disorders.

Cerebellar encoding of multiple candidate error cues in the service of motor learning.

For learning to occur through trial and error, the nervous system must effectively detect and encode performance errors. To examine this process, we designed a set of oculomotor learning tasks with more than one visual object providing potential error cues, as would occur in a natural visual scene. A task-relevant visual target and a task-irrelevant visual background both influenced vestibulo-ocular reflex learning in rhesus monkeys. Thus, motor learning does not identify a single error cue based on behavioral relevance, but can be simultaneously influenced by more than one cue. Moreover, the relative weighting of the different cues could vary. If the speed of the visual target's motion on the retina was low (≪1°/s), background motion dominated learning, but if target speed was high, the effects of the background were suppressed. The target and background motion had similar, nonlinear effects on the putative neural instructive signals carried by cerebellar climbing fibers, but with a stronger influence of the background on the climbing fibers than on learning. In contrast, putative neural instructive signals carried by the simple spikes of Purkinje cells were influenced solely by the motion of the visual target. Because they are influenced by different cues during training, joint control of learning by the climbing fibers and Purkinje cells may expand the learning capacity of the cerebellar circuit.

Altered network connectivity in frontotemporal dementia with C9orf72 hexanucleotide repeat expansion.

Hexanucleotide repeat expansion in C9orf72 represents the most common genetic cause of familial and sporadic behavioural variant frontotemporal dementia. Previous studies show that some C9orf72 carriers with behavioural variant frontotemporal dementia exhibit distinctive atrophy patterns whereas others show mild or undetectable atrophy despite severe behavioural impairment. To explore this observation, we examined intrinsic connectivity network integrity in patients with or without the C9orf72 expansion. We studied 28 patients with behavioural variant frontotemporal dementia, including 14 C9orf72 mutation carriers (age 58.3 ± 7.7 years, four females) and 14 non-carriers (age 60.8 ± 6.9 years, four females), and 14 age- and sex-matched healthy controls. Both patient groups included five patients with comorbid motor neuron disease. Neuropsychological data, structural brain magnetic resonance imaging, and task-free functional magnetic resonance imaging were obtained. Voxel-based morphometry delineated atrophy patterns, and seed-based intrinsic connectivity analyses enabled group comparisons of the salience, sensorimotor, and default mode networks. Single-patient analyses were used to explore network imaging as a potential biomarker. Despite contrasting atrophy patterns in C9orf72 carriers versus non-carriers, patient groups showed topographically similar connectivity reductions in the salience and sensorimotor networks. Patients without C9orf72 expansions exhibited increases in default mode network connectivity compared to controls and mutation carriers. Across all patients, behavioural symptom severity correlated with diminished salience network connectivity and heightened default mode network connectivity. In C9orf72 carriers, salience network connectivity reduction correlated with atrophy in the left medial pulvinar thalamic nucleus, and this region further showed diminished connectivity with key salience network hubs. Single-patient analyses revealed salience network disruption and default mode network connectivity enhancement in C9orf72 carriers with early-stage or slowly progressive symptoms. The findings suggest that patients with behavioural variant frontotemporal dementia with or without the C9orf72 expansion show convergent large-scale network breakdowns despite distinctive atrophy patterns. Medial pulvinar degeneration may contribute to the behavioural variant frontotemporal dementia syndrome in C9orf72 carriers by disrupting salience network connectivity. Task-free functional magnetic resonance imaging shows promise in detecting early-stage disease in C9orf72 carriers and may provide a unifying biomarker across diverse anatomical variants.

Intrinsic connectivity network disruption in progressive supranuclear palsy.

OBJECTIVE: Progressive supranuclear palsy (PSP) has been conceptualized as a large-scale network disruption, but the specific network targeted has not been fully characterized. We sought to delineate the affected network in patients with clinical PSP. METHODS: Using task-free functional magnetic resonance imaging, we mapped intrinsic connectivity to the dorsal midbrain tegmentum (dMT), a region that shows focal atrophy in PSP. Two healthy control groups (1 young, 1 older) were used to define and replicate the normal connectivity pattern, and patients with PSP were compared to an independent matched healthy control group on measures of network connectivity. RESULTS: Healthy young and older subjects showed a convergent pattern of connectivity to the dMT, including brainstem, cerebellar, diencephalic, basal ganglia, and cortical regions involved in skeletomotor, oculomotor, and executive control. Patients with PSP showed significant connectivity disruptions within this network, particularly within corticosubcortical and cortico-brainstem interactions. Patients with more severe functional impairment showed lower mean dMT network connectivity scores. INTERPRETATION: This study defines a PSP-related intrinsic connectivity network in the healthy brain and demonstrates the sensitivity of network-based imaging methods to PSP-related physiological and clinical changes.

Anterior temporal lobe degeneration produces widespread network-driven dysfunction.

The neural organization of semantic memory remains much debated. A 'distributed-only' view contends that semantic knowledge is represented within spatially distant, modality-selective primary and association cortices. Observations in semantic variant primary progressive aphasia have inspired an alternative model featuring the anterior temporal lobe as an amodal hub that supports semantic knowledge by linking distributed modality-selective regions. Direct evidence has been lacking, however, to support intrinsic functional interactions between an anterior temporal lobe hub and upstream sensory regions in humans. Here, we examined the neural networks supporting semantic knowledge by performing a multimodal brain imaging study in healthy subjects and patients with semantic variant primary progressive aphasia. In healthy subjects, the anterior temporal lobe showed intrinsic connectivity to an array of modality-selective primary and association cortices. Patients showed focal anterior temporal lobe degeneration but also reduced physiological integrity throughout distributed modality-selective regions connected with the anterior temporal lobe in healthy controls. Physiological deficits outside the anterior temporal lobe correlated with scores on semantic tasks and with anterior temporal subregion atrophy, following domain-specific and connectivity-based predictions. The findings provide a neurophysiological basis for the theory that semantic processing is orchestrated through interactions between a critical anterior temporal lobe hub and modality-selective processing nodes.