Unsuspected Involvement of Spinal Cord in Alzheimer Disease

Neurodegenerative Diseases: Molecular Mechanisms and Therapies

Neurodegenerative diseases are characterized by the progressive degeneration or death of neurons in the central or peripheral nervous system [...].

Virtual brain simulations reveal network-specific parameters in neurodegenerative dementias

Introduction

Neural circuit alterations lay at the core of brain physiopathology, and yet are hard to unveil in living subjects. The Virtual Brain (TVB) modeling, by exploiting structural and functional magnetic resonance imaging (MRI), yields mesoscopic parameters of connectivity and synaptic transmission.

Methods

We used TVB to simulate brain networks, which are key for human brain function, in Alzheimer's disease (AD) and frontotemporal dementia (FTD) patients, whose connectivity and synaptic parameters remain largely unknown; we then compared them to healthy controls, to reveal novel in vivo pathological hallmarks.

Results

The pattern of simulated parameter differed between AD and FTD, shedding light on disease-specific alterations in brain networks. Individual subjects displayed subtle differences in network parameter patterns that significantly correlated with their individual neuropsychological, clinical, and pharmacological profiles.

Discussion

These TVB simulations, by informing about a new personalized set of networks parameters, open new perspectives for understanding dementias mechanisms and design personalized therapeutic approaches.

The confound of hemodynamic response function variability in human resting-state functional MRI studies

Functional magnetic resonance imaging (fMRI) is an indirect measure of neural activity with the hemodynamic response function (HRF) coupling it with unmeasured neural activity. The HRF, modulated by several non-neural factors, is variable across brain regions, individuals and populations. Yet, a majority of human resting-state fMRI connectivity studies continue to assume a non-variable HRF. In this article, with supportive prior evidence, we argue that HRF variability cannot be ignored as it substantially confounds within-subject connectivity estimates and between-subjects connectivity group differences. We also discuss its clinical relevance with connectivity impairments confounded by HRF aberrations in several disorders. We present limited data on HRF differences between women and men, which resulted in a 15.4% median error in functional connectivity estimates in a group-level comparison. We also discuss the implications of HRF variability for fMRI studies in the spinal cord. There is a need for more dialogue within the community on the HRF confound, and we hope that our article is a catalyst in the process.

Central nervous system sulfatide deficiency as a causal factor for bladder disorder in Alzheimer's disease

BACKGROUND

Despite being a brain disorder, Alzheimer's disease (AD) is often accompanied by peripheral organ dysregulations (e.g., loss of bladder control in late-stage AD), which highly rely on spinal cord coordination. However, the causal factor(s) for peripheral organ dysregulation in AD remain elusive.

METHODS

The central nervous system (CNS) is enriched in lipids. We applied quantitative shotgun lipidomics to determine lipid profiles of human AD spinal cord tissues. Additionally, a CNS sulfatide (ST)-deficient mouse model was used to study the lipidome, transcriptome and peripheral organ phenotypes of ST loss.

RESULTS

We observed marked myelin lipid reduction in the spinal cord of AD subjects versus cognitively normal individuals. Among which, levels of ST, a myelin-enriched lipid class, were strongly and negatively associated with the severity of AD. A CNS myelin-specific ST-deficient mouse model was used to further identify the causes and consequences of spinal cord lipidome changes. Interestingly, ST deficiency led to spinal cord lipidome and transcriptome profiles highly resembling those observed in AD, characterized by decline of multiple myelin-enriched lipid classes and enhanced inflammatory responses, respectively. These changes significantly disrupted spinal cord function and led to substantial enlargement of urinary bladder in ST-deficient mice.

CONCLUSIONS

Our study identified CNS ST deficiency as a causal factor for AD-like lipid dysregulation, inflammation response and ultimately the development of bladder disorders. Targeting to maintain ST levels may serve as a promising strategy for the prevention and treatment of AD-related peripheral disorders.

Diagnostic performance of magnetic resonance imaging-based machine learning in Alzheimer's disease detection: a meta-analysis

PURPOSE

Advanced machine learning (ML) algorithms can assist rapid medical image recognition and realize automatic, efficient, noninvasive, and convenient diagnosis. We aim to further evaluate the diagnostic performance of ML to distinguish patients with probable Alzheimer's disease (AD) from normal older adults based on structural magnetic resonance imaging (MRI).

METHODS

The Medline, Embase, and Cochrane Library databases were searched for relevant literature published up until July 2021. We used the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool and Checklist for Artificial Intelligence in Medical Imaging (CLAIM) to evaluate all included studies' quality and potential bias. Random-effects models were used to calculate pooled sensitivity and specificity, and the Deeks' test was used to assess publication bias.

RESULTS

We included 24 models based on different brain features extracted by ML algorithms in 19 papers. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and area under the summary receiver operating characteristic curve for ML in detecting AD were 0.85 (95%CI 0.81-0.89), 0.88 (95%CI 0.84-0.91), 7.15 (95%CI 5.40-9.47), 0.17 (95%CI 0.12-0.22), 43.34 (95%CI 26.89-69.84), and 0.93 (95%CI 0.91-0.95).

CONCLUSION

ML using structural MRI data performed well in diagnosing probable AD patients and normal elderly. However, more high-quality, large-scale prospective studies are needed to further enhance the reliability and generalizability of ML for clinical applications before it can be introduced into clinical practice.

Increased Heat Pain Tolerance but Hyperalgesia to Tonic Inflammatory Pain in the CRND8 Mouse Model of Alzheimer's Disease

BACKGROUND

The effects of Alzheimer's disease (AD) pathology on the experience of pain are poorly understood.

OBJECTIVE

To understand the pathophysiological mechanisms underlying pain sensory transmission in the transgenic mouse model of AD, CRND8.

METHODS

We explored AD-related pathology in the spinal cord and dorsal root ganglia of 18-week-old female CRND8 mice. We assessed nociceptive responses to both acute heat stimuli and persistent inflammatory pain in CRND8 mice and non-transgenic (non-Tg) littermates. In addition, we searched for differences in biochemical correlates of inflammatory pain between CRND8 and non-Tg mice. Finally, we investigated the excitability of dorsal horn noc iceptive neurons in spinal cord slices from CRND8 and non-Tg mice.

RESULTS

We demonstrated the presence of intracellular AD-like pathology in the spinal cord and in the dorsal root ganglia nociceptive sensory neurons of CRND8 mice. We found that CRND8 mice had a reduced susceptibility to acute noxious heat stimuli and an increased sensitivity to tonic inflammatory pain. Tonic inflammatory pain correlated with a lack of induction of pro-opiomelanocortin in the spinal cord of CRND8 mice as compared to non-Tg mice. Electrophysiological recording in acute spinal cord slice preparations indicated an increased probability of glutamate release at the membrane of dorsal horn nociceptive neurons in CRND8 mice.

CONCLUSION

This study suggests that an increased thermal tolerance and a facilitation of nociception by peripheral inflammation can coexist in AD.

Glial Gap Junction Pathology in the Spinal Cord of the 5xFAD Mouse Model of Early-Onset Alzheimer's Disease

Gap junctions (GJs) are specialized transmembrane channels assembled by two hemi-channels of six connexin (Cx) proteins that facilitate neuroglial crosstalk in the central nervous system (CNS). Previous studies confirmed the crucial role of glial GJs in neurodegenerative disorders with dementia or motor dysfunction including Alzheimer's disease (AD). The aim of this study was to examine the alterations in astrocyte and related oligodendrocyte GJs in association with Aβ plaques in the spinal cord of the 5xFAD mouse model of AD. Our analysis revealed abundant Aβ plaque deposition, activated microglia, and astrogliosis in 12-month-old (12M) 5xFAD mice, with significant impairment of motor performance starting from 3-months (3M) of age. Additionally, 12M 5xFAD mice displayed increased immunoreactivity of astroglial Cx43 and Cx30 surrounding Aβ plaques and higher protein levels, indicating upregulated astrocyte-to-astrocyte GJ connectivity. In addition, they demonstrated increased numbers of mature CC1-positive and precursor oligodendrocytes (OPCs) with higher immunoreactivity of Cx47-positive GJs in individual cells. Moreover, total Cx47 protein levels were significantly elevated in 12M 5xFAD, reflecting increased oligodendrocyte-to-oligodendrocyte Cx47-Cx47 GJ connectivity. In contrast, we observed a marked reduction in Cx32 protein levels in 12M 5xFAD spinal cords compared with controls, while qRT-PCR analysis revealed a significant upregulation in Cx32 mRNA levels. Finally, myelin deficits were found focally in the areas occupied by Aβ plaques, whereas axons themselves remained preserved. Overall, our data provide novel insights into the altered glial GJ expression in the spinal cord of the 5xFAD model of AD and the implicated role of GJ pathology in neurodegeneration. Further investigation to understand the functional consequences of these extensive alterations in oligodendrocyte-astrocyte (O/A) GJ connectivity is warranted.

Subject-specific features of excitation/inhibition profiles in neurodegenerative diseases

Brain pathologies are characterized by microscopic changes in neurons and synapses that reverberate into large scale networks altering brain dynamics and functional states. An important yet unresolved issue concerns the impact of patients' excitation/inhibition profiles on neurodegenerative diseases including Alzheimer's Disease, Frontotemporal Dementia, and Amyotrophic Lateral Sclerosis. In this work, we used The Virtual Brain (TVB) simulation platform to simulate brain dynamics in healthy and neurodegenerative conditions and to extract information about the excitatory/inhibitory balance in single subjects. The brain structural and functional connectomes were extracted from 3T-MRI (Magnetic Resonance Imaging) scans and TVB nodes were represented by a Wong-Wang neural mass model endowing an explicit representation of the excitatory/inhibitory balance. Simulations were performed including both cerebral and cerebellar nodes and their structural connections to explore cerebellar impact on brain dynamics generation. The potential for clinical translation of TVB derived biophysical parameters was assessed by exploring their association with patients' cognitive performance and testing their discriminative power between clinical conditions. Our results showed that TVB biophysical parameters differed between clinical phenotypes, predicting higher global coupling and inhibition in Alzheimer's Disease and stronger N-methyl-D-aspartate (NMDA) receptor-dependent excitation in Amyotrophic Lateral Sclerosis. These physio-pathological parameters allowed us to perform an advanced analysis of patients' conditions. In backward regressions, TVB-derived parameters significantly contributed to explain the variation of neuropsychological scores and, in discriminant analysis, the combination of TVB parameters and neuropsychological scores significantly improved the discriminative power between clinical conditions. Moreover, cluster analysis provided a unique description of the excitatory/inhibitory balance in individual patients. Importantly, the integration of cerebro-cerebellar loops in simulations improved TVB predictive power, i.e., the correlation between experimental and simulated functional connectivity in all pathological conditions supporting the cerebellar role in brain function disrupted by neurodegeneration. Overall, TVB simulations reveal differences in the excitatory/inhibitory balance of individual patients that, combined with cognitive assessment, can promote the personalized diagnosis and therapy of neurodegenerative diseases.

Imaging of Common Spinal Cord Diseases

Spinal cord evaluation is an integral part of spine assessment, and its reliable imaging work-up is mandatory because even localized lesions may produce serious effects with potentially irreversible sequelae. Spinal cord alterations are found both incidentally during spine evaluation in otherwise neurologically asymptomatic patients or during neurologic/neuroradiologic assessment in myelopathic patients. Myelopathy (an umbrella term for any neurologic deficit that refers to spinal cord impairment) can be caused by intrinsic lesions or extrinsic mechanical compression, and its etiology may be both traumatic and/or nontraumatic. The symptoms largely depend on the size/extension of lesions, ranging from incontinence to ataxia, from spasticity to hyperreflexia, from numbness to weakness. Magnetic resonance imaging is the reference imaging modality in spinal cord evaluation, ensuring the best signal and spatial resolution. We provide an overview of the most common spinal cord disorders encountered by radiologists and describe the technical measures that offer optimal spinal cord visualization.

A Method for Bridging Population-Specific Genotypes to Detect Gene Modules Associated with Alzheimer's Disease

BACKGROUND

Genome-wide association studies have successfully identified variants associated with multiple conditions. However, generalizing discoveries across diverse populations remains challenging due to large variations in genetic composition. Methods that perform gene expression imputation have attempted to address the transferability of gene discoveries across populations, but with limited success.

METHODS

Here, we introduce a pipeline that combines gene expression imputation with gene module discovery, including a dense gene module search and a gene set variation analysis, to address the transferability issue. Our method feeds association probabilities of imputed gene expression with a selected phenotype into tissue-specific gene-module discovery over protein interaction networks to create higher-level gene modules.

RESULTS

We demonstrate our method's utility in three case-control studies of Alzheimer's disease (AD) for three different race/ethnic populations (Whites, African descent and Hispanics). We discovered 182 AD-associated genes from gene modules shared between these populations, highlighting new gene modules associated with AD.

CONCLUSIONS

Our innovative framework has the potential to identify robust discoveries across populations based on gene modules, as demonstrated in AD.

Structural MRI Reveals Cervical Spinal Cord Atrophy in the P301L Mouse Model of Tauopathy: Gender and Transgene-Dosing Effects

In primary tauopathies, the deposition of tau neurofibrillary tangles and threads as well as neurodegenerative changes have been found within the brain and spinal cord. While degenerative changes have been intensively studied in the brain using structural magnetic resonance imaging (MRI), MRI studies investigating the spinal cord are still scarce. In the present study, we acquired ex vivo high resolution structural MRI of the cervical spinal cord of 8.5–9 month old hemizygous and homozygous P301L mice and non-transgenic littermates of both genders. We assessed the total cross-sectional area, and the gray and white matter anterior-posterior width and left-right width that are established imaging marker of spinal cord degeneration. We observed significant tissue-specific reductions in these parameters in female P301L mice that were stronger in homozygous than in hemizygous P301L mice, indicating both an effect of gender and transgene expression on cervical spinal cord atrophy. Moreover, atrophy was stronger in the gray matter than in the white matter. Immunohistochemical analysis revealed neurodegenerative and neuroinflammatory changes in the cervical spinal cord in both the gray and white matter of P301L mice. Collectively, our results provide evidence for cervical spinal cord atrophy that may directly contribute to the motor signs associated with tauopathy.

Neurodegenerative disorders and gut-brain interactions

Neurodegenerative disorders (NDs) affect essential functions not only in the CNS, but also cause persistent gut dysfunctions, suggesting that they have an impact on both CNS and gut-innervating neurons. Although the CNS biology of NDs continues to be well studied, how gut-innervating neurons, including those that connect the gut to the brain, are affected by or involved in the etiology of these debilitating and progressive disorders has been understudied. Studies in recent years have shown how CNS and gut biology, aided by the gut-brain connecting neurons, modulate each other's functions. These studies underscore the importance of exploring the gut-innervating and gut-brain connecting neurons of the CNS and gut function in health, as well as the etiology and progression of dysfunction in NDs. In this Review, we discuss our current understanding of how the various gut-innervating neurons and gut physiology are involved in the etiology of NDs, including Parkinson's disease, Alzheimer's disease, Huntington's disease, and amyotrophic lateral sclerosis, to cause progressive CNS and persistent gut dysfunction.

Use of Zebrafish Genetic Models to Study Etiology of the Amyloid-Beta and Neurofibrillary Tangle Pathways in Alzheimer's Disease

The prevalence of neurodegenerative diseases is increasing globally, with an imperative need to identify and expand the availability of pharmaceutical treatment strategies. Alzheimer's disease is the most common neurodegenerative disease for which there is no cure or has limited treatments. Rodent models are primarily used in Alzheimer's disease research to investigate causes, pathology, molecular mechanisms, and pharmaceutical therapies. However, there is a lack of a comprehensive understanding of Alzheimer's disease causes, pathogenesis, and optimal treatments due in part to some limitations of using rodents, including higher economic cost, which can influence sample size and ultimately statistical power. It is necessary to expand our animal model toolbox to provide alternative strategies in Alzheimer's disease research. The zebrafish application in neurodegenerative disease research and neuropharmacology is greatly expanding due to several vital strengths spanning lower economic costs, the smaller size of the organism, a sequenced characterized genome, and well described anatomical structures. These characteristics are coupled to the conserved molecular function and disease pathways in humans. The existence of orthologs for genes associated with Alzheimer's disease in zebrafish is also confirmed. While wild-type zebrafish appear to lack some of the neuropathological features of Alzheimer's disease, the advent of genetic editing technologies has expanded evaluation of the amyloid and neurofibrillary tangle hypotheses using the zebrafish and exploration of pharmaceutical molecular targets. An overview of how genetic editing technologies are being used with the zebrafish to create models to investigate the causes, pathology, molecular mechanisms, and pharmaceutical targets of Alzheimer's disease is detailed.

Cortical volume reductions as a sign of secondary cerebral and cerebellar impairment in patients with degenerative cervical myelopathy

•

Degenerative cervical myelopathy is the most common cause of chronic impairment of the spinal cord.

•

MRI-based anatomical assessment of cerebral and cerebellar areas revealed significant tissue volume reduction in DCM patients compared to healthy controls.

•

Disease severity correlated with cerebral and cerebellar atrophy in the primary motor cortex, primary somatosensory cortex and cerebellar areas.

•

Chronic injury to the spinal cord seems to have impact on remote anatomical structures in the brain.

This study investigated supra- and infratentorial structural gray and white matter (GM, WM) alterations in patients with degenerative cervical myelopathy (DCM) as an indicator of secondary harm due to chronic cervical cord compression and micro trauma. With MRI-based anatomical assessment and subsequent voxel-based morphometry analyses, pre- and postoperative volume alterations in the primary motor cortex (MI), the primary somatosensory cortex (SI), the supplementary motor area (SMA), and the cerebellum were analyzed in 43 DCM patients and 20 controls. We assessed disease-related symptom severity by the modified Japanese Orthopaedic Association scale (mJOA). The study also explored symptom severity-based brain volume alterations as well as their association with clinical status. Patients had lower mJOA scores (p = .000) and lower GM volume than controls in SI (p = .016) and cerebellar regions (p = .001). Symptom severity-based subgroup analyses revealed volume reductions in almost all investigated GM ROIs (MI: p = .001; CB: p = .040; SMA: p = .007) in patients with severe clinical symptoms as well as atrophy already present in patients with moderate symptom severity. Clinical symptoms in DCM were associated with cortical and cerebellar volume reduction. GM volume alterations may serve as an indicator of both disease severity and ongoing disease progression in DCM, and should be considered in further patient care and treatment monitoring.

Minimum detectable spinal cord atrophy with automatic segmentation: Investigations using an open-access dataset of healthy participants

•

Evaluate the robustness of an automated analysis pipeline for detecting SC atrophy.

•

Simulate spinal cord atrophy and scan-rescan variability.

•

Fully automated analysis method available on an open access database.

•

Evaluation of sample size and inter/intra-subject variability for T1w and T2w images.

Spinal cord atrophy is a well-known biomarker in multiple sclerosis (MS) and other diseases. It is measured by segmenting the spinal cord on an MRI image and computing the average cross-sectional area (CSA) over a few slices. Introduced about 25 years ago, this procedure is highly sensitive to the quality of the segmentation and is prone to rater-bias. Recently, fully-automated spinal cord segmentation methods, which remove the rater-bias and enable the automated analysis of large populations, have been introduced. A lingering question related to these automated methods is: How reliable are they at detecting atrophy? In this study, we evaluated the precision and accuracy of automated atrophy measurements by simulating scan-rescan experiments.

Spinal cord MRI data from the open-access spine-generic project were used. The dataset aggregates 42 sites worldwide and consists of 260 healthy subjects and includes T1w and T2w contrasts. To simulate atrophy, each volume was globally rescaled at various scaling factors. Moreover, to simulate patient repositioning, random rigid transformations were applied. Using the DeepSeg algorithm from the Spinal Cord Toolbox, the spinal cord was segmented and vertebral levels were identified. Then, the average CSA between C3-C5 vertebral levels was computed for each Monte Carlo sample, allowing us to derive measures of atrophy, intra/inter-subject variability, and sample-size calculations.

The minimum sample size required to detect an atrophy of 2% between unpaired study arms, commonly seen in MS studies, was 467 +/− 13.9 using T1w and 467 +/− 3.2 using T2w images. The minimum sample size to detect a longitudinal atrophy (between paired study arms) of 0.8% was 60 +/− 25.1 using T1w and 10 +/− 1.2 using T2w images. At the intra-subject level, the estimated CSA, observed in this study, showed good precision compared to other studies with COVs (across Monte Carlo transformations) of 0.8% for T1w and 0.6% for T2w images.

While these sample sizes seem small, we would like to stress that these results correspond to a “best case” scenario, in that the dataset used here was of particularly good quality and the model for simulating atrophy does not encompass all the variability met in real-life datasets. The simulated atrophy and scan-rescan variability may over-simplify the biological reality. The proposed framework is open-source and available at https://csa-atrophy.readthedocs.io/.

Multi-parametric quantitative in vivo spinal cord MRI with unified signal readout and image denoising

Multi-parametric quantitative MRI (qMRI) of the spinal cord is a promising non-invasive tool to probe early microstructural damage in neurological disorders. It is usually performed in vivo by combining acquisitions with multiple signal readouts, which exhibit different thermal noise levels, geometrical distortions and susceptibility to physiological noise. This ultimately hinders joint multi-contrast modelling and makes the geometric correspondence of parametric maps challenging. We propose an approach to overcome these limitations, by implementing state-of-the-art microstructural MRI of the spinal cord with a unified signal readout in vivo (i.e. with matched spatial encoding parameters across a range of imaging contrasts). We base our acquisition on single-shot echo planar imaging with reduced field-of-view, and obtain data from two different vendors (vendor 1: Philips Achieva; vendor 2: Siemens Prisma). Importantly, the unified acquisition allows us to compare signal and noise across contrasts, thus enabling overall quality enhancement via multi-contrast image denoising methods. As a proof-of-concept, here we provide a demonstration with one such method, known as Marchenko-Pastur (MP) Principal Component Analysis (PCA) denoising. MP-PCA is a singular value (SV) decomposition truncation approach that relies on redundant acquisitions, i.e. such that the number of measurements is large compared to the number of components that are maintained in the truncated SV decomposition. Here we used in vivo and synthetic data to test whether a unified readout enables more efficient MP-PCA denoising of less redundant acquisitions, since these can be denoised jointly with more redundant ones. We demonstrate that a unified readout provides robust multi-parametric maps, including diffusion and kurtosis tensors from diffusion MRI, myelin metrics from two-pool magnetisation transfer, and T1 and T2 from relaxometry. Moreover, we show that MP-PCA improves the quality of our multi-contrast acquisitions, since it reduces the coefficient of variation (i.e. variability) by up to 17% for mean kurtosis, 8% for bound pool fraction (myelin-sensitive), and 13% for T1, while enabling more efficient denoising of modalities limited in redundancy (e.g. relaxometry). In conclusion, multi-parametric spinal cord qMRI with unified readout is feasible and provides robust microstructural metrics with matched resolution and distortions, whose quality benefits from multi-contrast denoising methods such as MP-PCA.