Cerebral atrophy in amyotrophic lateral sclerosis parallels the pathological distribution of TDP43

Mapping motor and extra-motor gray and white matter changes in ALS: a comprehensive review of MRI insights

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease primarily affecting motor neurons, yet with substantial clinical variability. Furthermore, beyond motor symptoms, ALS patients also show non-motor features, reflecting its classification as a multi-system disorder. The identification of reliable biomarkers is a critical challenge for improving diagnosis, tracking disease progression, and predicting patient outcomes. This review explores macro- and microstructural alterations in ALS, focusing on gray matter (GM) and white matter (WM) as observed through Magnetic Resonance Imaging (MRI). This approach synthesizes not only the expected involvement of motor areas but also highlights emerging evidence that these changes extend to extra-motor areas, such as the frontal and temporal lobes, underscoring the complex pathophysiology of ALS. The review emphasizes the potential of MRI as a non-invasive tool to provide new biomarkers by assessing both GM and WM integrity, a key advancement in ALS research. Additionally, it addresses existing discrepancies in findings and stresses the need for standardized imaging protocols. It also highlights the role of multi-modal MRI approaches in deepening our understanding of ALS pathology, emphasizing the importance of combining structural and diffusion MRI techniques to offer more comprehensive insights into ALS progression, ultimately advancing the potential for personalized treatment strategies and improving patient outcomes.

A comprehensive update on neuroimaging endpoints in amyotrophic lateral sclerosis

INTRODUCTION

There are currently few treatments approved for amyotrophic lateral sclerosis (ALS). Additionally, there remains a significant unmet need for reliable, standardized biomarkers to assess endpoints in clinical trials. Magnetic resonance imaging (MRI)- and positron emission tomography (PET)-derived metrics could help in patient selection and stratification, shortening trial duration and reducing costs.

AREAS COVERED

This review focuses on the potential use of neuroimaging endpoints in the context of ALS therapeutic trials, providing insights on structural and functional neuroimaging, plexus and muscle alterations, glial involvement and neuroinflammation, envisioning how these surrogates of disease progression could be implemented in clinical trials. A PubMed search covering the past 15 years was performed.

EXPERT OPINION

Neuroimaging is essential in understanding ALS pathophysiology, aiding in disease progression tracking and evaluating therapeutic interventions. High costs, limited accessibility, lack of standardization, and patient tolerability limit their use in routine ALS care. Addressing these obstacles is essential for fully harnessing neuroimaging potential in improving diagnostics and treatment in ALS.

Regional Cerebral Atrophy Contributes to Personalized Survival Prediction in Amyotrophic Lateral Sclerosis: A Multicentre, Machine Learning, Deformation-Based Morphometry Study

OBJECTIVE

Accurate personalized survival prediction in amyotrophic lateral sclerosis is essential for effective patient care planning. This study investigates whether grey and white matter changes measured by magnetic resonance imaging can improve individual survival predictions.

METHODS

We analyzed data from 178 patients with amyotrophic lateral sclerosis and 166 healthy controls in the Canadian Amyotrophic Lateral Sclerosis Neuroimaging Consortium study. A voxel-wise linear mixed-effects model assessed disease-related and survival-related atrophy detected through deformation-based morphometry, controlling for age, sex, and scanner variations. Additional linear mixed-effects models explored associations between regional imaging and clinical measurements, and their associations with time to the composite outcome of death, tracheostomy, or permanent assisted ventilation. We evaluated whether incorporating imaging features alongside clinical data could improve the performance of an individual survival distribution model.

RESULTS

Deformation-based morphometry uncovered distinct voxel-wise atrophy patterns linked to disease progression and survival, with many of these regional atrophies significantly associated with clinical manifestations of the disease. By integrating regional imaging features with clinical data, we observed a substantial enhancement in the performance of survival models across key metrics. Our analysis identified specific brain regions, such as the corpus callosum, rostral middle frontal gyrus, and thalamus, where atrophy predicted an increased risk of mortality.

INTERPRETATION

This study suggests that brain atrophy patterns measured by deformation-based morphometry provide valuable insights beyond clinical assessments for prognosis. It offers a more comprehensive approach to prognosis and highlights brain regions involved in disease progression and survival, potentially leading to a better understanding of amyotrophic lateral sclerosis. ANN NEUROL 2025.

Disentangling the effect of sex from brain size on brain organization and cognitive functioning

Neuroanatomical sex differences estimated in neuroimaging studies are confounded by total intracranial volume (TIV) as a major biological factor. Employing a matching approach widely used for causal modeling, we disentangled the effect of TIV from sex to study sex-differentiated brain aging trajectories, their relation to functional networks and cytoarchitectonic classes, brain allometry, and cognition. Using data from the UK Biobank, we created subsamples that removed, maintained, or exaggerated the TIV differences in the original sample. We compared regional and vertex-level sex estimates across subsamples. The overall sex-related differences diminished in head size-matched subsamples, suggesting that most of the observed variability results from TIV differences. Furthermore, bidirectional sex differences in brain neuroanatomy emerged that were previously masked by the effect of TIV. Allometry remained fairly consistent across lifespan and was not sex-differentiated. Finally, the matching process changed the direction of the estimated sex differences in "verbal and numerical reasoning" and "working memory", suggesting that behavioral sex difference investigations can benefit from additional biological analysis to uncover the underlying factors contributing to cognition. Taken together, we provide new evidence disentangling sex differences from TIV as a relevant biological confound.

Cortical thickness correlated with peripheral inflammatory cytokines in amyotrophic lateral sclerosis

Introduction

Amyotrophic lateral sclerosis (ALS) is a rare, devastating neurodegenerative disease that affects upper and lower motor neurons, resulting in muscle atrophy, spasticity, hyperreflexia, and paralysis. Inflammation plays an important role in the development of ALS, and associated with rapid disease progression. Current observational studies indicate the thinning of cortical thickness in patients with ALS is associated with rapid disease progression and cognitive changes. However, the effects of inflammatory cytokines on cortical thickness in patients with ALS are unclear. Here, we investigated the relationship between inflammatory cytokines and cortical thickness in patients with ALS.

Methods

We evaluated 51 patients with ALS for inflammatory cytokines including interleukin (IL)-4, interferon (IFN)-α, IL-1β, IL-2, IL-5, IL-12, tumor necrosis factor (TNF)-α, IL-6, IL-10, IL-8, IL-17, and IFN-γ and analyzed the correlation between these indicators and the ALS functional rating scale-revised (ALSFRS-R) score or disease progression rate (ΔFS score). Twenty-six patients with ALS and 26 controls were studied using whole-cortex analysis, and post-hoc analyses were performed to examine the correlation between brain cortical thickness and ALSFRS-R or ΔFS scores.

Results

IL-4, IFN-α, IL-1β, and IL-2 levels were significantly correlated with ALSFRS-R scores, and the IL-2 level was significantly correlated with ΔFS scores. After controlling for age and sex, the ALS group had thinner cortexes in multiple clusters across the brain than the control group. Further analyses revealed that cortical thickness in the right superior temporal and lingual gyrus regions was inversely correlated with ΔFS scores. There was a significant positive correlation between the clusters in the right lingual cortex and IL-2 level.

Conclusion

These results suggest cortical thickness was reduced in patients with ALS in motor and non-motor cortical areas. Inflammatory factors (especially IL-2) were correlated with cortical thickness, and both were related to the disease progression rate, suggesting IL-2 plays an important role in ALS.

Longevity of a Brain-Computer Interface for Amyotrophic Lateral Sclerosis

The durability of communication with the use of brain-computer interfaces in persons with progressive neurodegenerative disease has not been extensively examined. We report on 7 years of independent at-home use of an implanted brain-computer interface for communication by a person with advanced amyotrophic lateral sclerosis (ALS), the inception of which was reported in 2016. The frequency of at-home use increased over time to compensate for gradual loss of control of an eye-gaze-tracking device, followed by a progressive decrease in use starting 6 years after implantation. At-home use ended when control of the brain-computer interface became unreliable. No signs of technical malfunction were found. Instead, the amplitude of neural signals declined, and computed tomographic imaging revealed progressive atrophy, which suggested that ALS-related neurodegeneration ultimately rendered the brain-computer interface ineffective after years of successful use, although alternative explanations are plausible. (Funded by the National Institute on Deafness and Other Communication Disorders and others; ClinicalTrials.gov number, NCT02224469.).

Neuronal Circuit Dysfunction in Amyotrophic Lateral Sclerosis

The primary neural circuit affected in Amyotrophic Lateral Sclerosis (ALS) patients is the corticospinal motor circuit, originating in upper motor neurons (UMNs) in the cerebral motor cortex which descend to synapse with the lower motor neurons (LMNs) in the spinal cord to ultimately innervate the skeletal muscle. Perturbation of these neural circuits and consequent loss of both UMNs and LMNs, leading to muscle wastage and impaired movement, is the key pathophysiology observed. Despite decades of research, we are still lacking in ALS disease-modifying treatments. In this review, we document the current research from patient studies, rodent models, and human stem cell models in understanding the mechanisms of corticomotor circuit dysfunction and its implication in ALS. We summarize the current knowledge about cortical UMN dysfunction and degeneration, altered excitability in LMNs, neuromuscular junction degeneration, and the non-cell autonomous role of glial cells in motor circuit dysfunction in relation to ALS. We further highlight the advances in human stem cell technology to model the complex neural circuitry and how these can aid in future studies to better understand the mechanisms of neural circuit dysfunction underpinning ALS.

Distinctive whole-brain cell types predict tissue damage patterns in thirteen neurodegenerative conditions

For over a century, brain research narrative has mainly centered on neuron cells. Accordingly, most neurodegenerative studies focus on neuronal dysfunction and their selective vulnerability, while we lack comprehensive analyses of other major cell types' contribution. By unifying spatial gene expression, structural MRI, and cell deconvolution, here we describe how the human brain distribution of canonical cell types extensively predicts tissue damage in 13 neurodegenerative conditions, including early- and late-onset Alzheimer's disease, Parkinson's disease, dementia with Lewy bodies, amyotrophic lateral sclerosis, mutations in presenilin-1, and 3 clinical variants of frontotemporal lobar degeneration (behavioral variant, semantic and non-fluent primary progressive aphasia) along with associated three-repeat and four-repeat tauopathies and TDP43 proteinopathies types A and C. We reconstructed comprehensive whole-brain reference maps of cellular abundance for six major cell types and identified characteristic axes of spatial overlapping with atrophy. Our results support the strong mediating role of non-neuronal cells, primarily microglia and astrocytes, in spatial vulnerability to tissue loss in neurodegeneration, with distinct and shared across-disorder pathomechanisms. These observations provide critical insights into the multicellular pathophysiology underlying spatiotemporal advance in neurodegeneration. Notably, they also emphasize the need to exceed the current neuro-centric view of brain diseases, supporting the imperative for cell-specific therapeutic targets in neurodegeneration.

Evidence based on Mendelian randomization and colocalization analysis strengthens causal relationships between structural changes in specific brain regions and risk of amyotrophic lateral sclerosis

Background

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by the degeneration of motor neurons in the brain and spinal cord with a poor prognosis. Previous studies have observed cognitive decline and changes in brain morphometry in ALS patients. However, it remains unclear whether the brain structural alterations contribute to the risk of ALS. In this study, we conducted a bidirectional two-sample Mendelian randomization (MR) and colocalization analysis to investigate this causal relationship.

Methods

Summary data of genome-wide association study were obtained for ALS and the brain structures, including surface area (SA), thickness and volume of subcortical structures. Inverse-variance weighted (IVW) method was used as the main estimate approach. Sensitivity analysis was conducted detect heterogeneity and pleiotropy. Colocalization analysis was performed to calculate the posterior probability of causal variation and identify the common genes.

Results

In the forward MR analysis, we found positive associations between the SA in four cortical regions (lingual, parahippocampal, pericalcarine, and middle temporal) and the risk of ALS. Additionally, decreased thickness in nine cortical regions (caudal anterior cingulate, frontal pole, fusiform, inferior temporal, lateral occipital, lateral orbitofrontal, pars orbitalis, pars triangularis, and pericalcarine) was significantly associated with a higher risk of ALS. In the reverse MR analysis, genetically predicted ALS was associated with reduced thickness in the bankssts and increased thickness in the caudal middle frontal, inferior parietal, medial orbitofrontal, and superior temporal regions. Colocalization analysis revealed the presence of shared causal variants between the two traits.

Conclusion

Our results suggest that altered brain morphometry in individuals with high ALS risk may be genetically mediated. The causal associations of widespread multifocal extra-motor atrophy in frontal and temporal lobes with ALS risk support the notion of a continuum between ALS and frontotemporal dementia. These findings enhance our understanding of the cortical structural patterns in ALS and shed light on potentially viable therapeutic targets.

Cortical structure and the risk of amyotrophic lateral sclerosis: A bidirectional Mendelian randomization study

BACKGROUND

Current observational studies indicate progressive brain atrophy is closely associated with the clinical feature of amyotrophic lateral sclerosis. However, it is unclear whether the changes in cortical structure are the cause or result of ALS. Our study aimed to investigate the causal relationship between cortical structure and ALS risk using a bidirectional two-sample MR study.

METHODS

We collected publicly available genome-wide association studies' summary statistics for cortical structure from UK Biobank and ENIGMA consortium (n = 33,992) and ALS from the Project MinE (n = 138,086). We used the inverse variance weighted method (IVW) as primary analysis in order to evaluate the causal effects. In addition, the weighted median and MR Egger methods were performed to ensure the robustness and reliability of the IVW results.

RESULTS

We found the decreased surface of the paracentral lobule and thickness of the frontal pole and middle temporal lobe were suggestively associated with an increased risk of ALS as well as the increased surface of medial orbitofrontal and middle temporal lobe. In another aspect, the causalities between the susceptibility to ALS and the volume of the transverse temporal gyrus and superior temporal gyrus were negative. Besides, the susceptibility to ALS might also contribute to an increased thickness of the postcentral gyrus and superior parietal gyrus.

CONCLUSION

In this two-sample MR analysis, we observed that multiple cortical brain regions are associated with a higher ALS risk. Further research into the underlying mechanisms is required to back up our findings.

Differential cortical gray matter changes in early- and late-onset patients with amyotrophic lateral sclerosis

Age at onset may be an important feature associated with distinct subtypes of amyotrophic lateral sclerosis (ALS). Little is known about the neuropathological mechanism of early-onset ALS (EO-ALS) and late-onset ALS (LO-ALS). Ninety ALS patients were divided into EO-ALS and LO-ALS group, and 128 healthy controls were matched into young controls(YCs) and old controls (OCs). A voxel-based morphometry approach was employed to investigate differences in gray matter volume (GMV). Significant age at onset-by-diagnosis interactions were found in the left parietal operculum, left precentral gyrus, bilateral postcentral gyrus, right occipital gyrus, and right orbitofrontal cortex. Post hoc analysis revealed a significant decrease in GMV in all affected regions of EO-ALS patients compared with YCs, with increased GMV in 5 of the 6 brain regions, except for the right orbitofrontal cortex, in LO-ALS patients compared with OCs. LO-ALS patients had a significantly increased GMV than EO-ALS patients after removing the aging effect. Correspondingly, GMV of the left postcentral gyrus correlated with disease severity in the 2 ALS groups. Our findings suggested that the pathological mechanisms in ALS patients with different ages at onset might differ. These findings provide unique insight into the clinical and biological heterogeneity of the 2 ALS subtypes.

A comparative study of cognitive and behavioral profiles between sporadic and type 8 amyotrophic lateral sclerosis

INTRODUCTION/AIMS

Amyotrophic lateral sclerosis (ALS) type 8 (ALS8) is caused by VAPB gene mutations. The differences between neuropsychological and behavioral profiles of patients with sporadic ALS (sALS) and those with ALS8 are unclear. We aimed to compare cognitive performance and behavioral aspects between sALS and ALS8 patients.

METHODS

Our study included 29 symptomatic ALS8 patients (17 men; median age 49 years), 20 sALS patients (12 men; median age 55 years), and 30 healthy controls (16 men; median age 50 years), matched for sex, age, and education. Participants underwent neuropsychological assessments focused on executive functions, visual memory, and facial emotion recognition. Behavioral and psychiatric symptoms were evaluated using the Hospital Anxiety and Depression Scale and the Cambridge Behavioral Inventory.

RESULTS

Clinical groups (sALS and ALS8) exhibited lower global cognitive efficiency and impaired cognitive flexibility, processing speed, and inhibitory control compared with controls. ALS8 and sALS showed similar performance in most executive tests, except for poorer verbal (lexical) fluency in those with sALS. Apathy, anxiety, and stereotypical behaviors were frequent in both clinical groups.

DISCUSSION

sALS and ALS8 patients demonstrated similar deficits in most cognitive domains and had comparable behavioral profiles. These findings should be considered in the care of patients.

Neuroinflammatory Pathways in the ALS-FTD Continuum: A Focus on Genetic Variants

Amyotrophic Lateral Sclerosis (ALS) and Frontotemporal dementia (FDT) are progressive neurodegenerative disorders that, in several cases, overlap in clinical presentation, and genetic and pathological disease mechanisms. About 10-15% of ALS cases and up to 40% of FTD are familial, usually with dominant traits. ALS and FTD, in several cases, share common gene mutations, such as in C9ORF72, TARDBP, SQSTM-1, FUS, VCP, CHCHD10, and TBK-1. Also, several mechanisms are involved in ALS and FTD pathogenesis, such as protein misfolding, oxidative stress, and impaired axonal transport. In addition, neuroinflammation and neuroinflammatory cells, such as astrocytes, oligodendrocytes, microglia, and lymphocytes and, overall, the cellular microenvironment, have been proposed as pivotal players in the pathogenesis the ALS-FTD spectrum disorders. This review overviews the current evidence regarding neuroinflammatory markers in the ALS/FTD continuum, focusing on the neuroinflammatory pathways involved in the genetic cases, moving from post-mortem reports to in vivo biofluid and neuroimaging data. We further discuss the potential link between genetic and autoimmune disorders and potential therapeutic implications.

Brain imaging signatures in amyotrophic lateral sclerosis: Correlation with peripheral motor degeneration

OBJECTIVE

This study aimed to explore the clinical significance of brain imaging signatures in the context of clinical neurological deficits in association with upper and lower motor neuron degeneration in amyotrophic lateral sclerosis (ALS).

METHODS

We performed brain MRI examinations to quantitatively evaluate (1) gray matter volume and (2) white matter tract fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD). Image-derived indices were correlated with (1) global neurological deficits of MRC muscle strength sum score, revised amyotrophic lateral sclerosis functional rating scale (ALSFRS-R), and forced vital capacity (FVC), and (2) focal scores of University of Pennsylvania Upper motor neuron score (Penn score) and the summation of compound muscle action potential Z scores (CMAP Z sum score).

RESULTS

There were 39 ALS patients and 32 control subjects matched for age and gender. Compared to controls, ALS patients had a lower gray matter volume in the precentral gyrus of the primary motor cortex, which was correlated with FA of corticofugal tracts. The gray matter volume of the precentral gyrus was correlated with FVC, MRC sum score, and CMAP Z sum score, while the FA of the corticospinal tract was linearly associated with CMAP Z sum score and Penn score on multivariate linear regression model.

INTERPRETATION

This study indicated that clinical assessment of muscle strength and routine measurements on nerve conduction studies provided surrogate markers of brain structural changes for ALS. Furthermore, these findings suggested parallel involvement of both upper and lower motor neurons in ALS.

Investigating neurological symptoms of infectious diseases like COVID-19 leading to a deeper understanding of neurodegenerative disorders such as Parkinson's disease

Apart from common respiratory symptoms, neurological symptoms are prevalent among patients with COVID-19. Research has shown that infection with SARS-CoV-2 accelerated alpha-synuclein aggregation, induced Lewy-body-like pathology, caused dopaminergic neuron senescence, and worsened symptoms in patients with Parkinson's disease (PD). In addition, SARS-CoV-2 infection can induce neuroinflammation and facilitate subsequent neurodegeneration in long COVID, and increase individual vulnerability to PD or parkinsonism. These findings suggest that a post-COVID-19 parkinsonism might follow the COVID-19 pandemic. In order to prevent a possible post-COVID-19 parkinsonism, this paper reviewed neurological symptoms and related findings of COVID-19 and related infectious diseases (influenza and prion disease) and neurodegenerative disorders (Alzheimer's disease, PD and amyotrophic lateral sclerosis), and discussed potential mechanisms underlying the neurological symptoms and the relationship between the infectious diseases and the neurodegenerative disorders, as well as the therapeutic and preventive implications in the neurodegenerative disorders. Infections with a relay of microbes (SARS-CoV-2, influenza A viruses, gut bacteria, etc.) and prion-like alpha-synuclein proteins over time may synergize to induce PD. Therefore, a systematic approach that targets these pathogens and the pathogen-induced neuroinflammation and neurodegeneration may provide cures for neurodegenerative disorders. Further, antiviral/antimicrobial drugs, vaccines, immunotherapies and new therapies (e.g., stem cell therapy) need to work together to treat, manage or prevent these disorders. As medical science and technology advances, it is anticipated that better vaccines for SARS-CoV-2 variants, new antiviral/antimicrobial drugs, effective immunotherapies (alpha-synuclein antibodies, vaccines for PD or parkinsonism, etc.), as well as new therapies will be developed and made available in the near future, which will help prevent a possible post-COVID-19 parkinsonism in the 21st century.

MRI Clustering Reveals Three ALS Subtypes With Unique Neurodegeneration Patterns

OBJECTIVE

The purpose of this study was to identify subtypes of amyotrophic lateral sclerosis (ALS) by comparing patterns of neurodegeneration using brain magnetic resonance imaging (MRI) and explore their phenotypes.

METHODS

We performed T1-weighted and diffusion tensor imaging in 488 clinically well-characterized patients with ALS and 338 control subjects. Measurements of whole-brain cortical thickness and white matter connectome fractional anisotropy were adjusted for disease-unrelated variation. A probabilistic network-based clustering algorithm was used to divide patients into subgroups of similar neurodegeneration patterns. Clinical characteristics and cognitive profiles were assessed for each subgroup. In total, 512 follow-up scans were used to validate clustering results longitudinally.

RESULTS

The clustering algorithm divided patients with ALS into 3 subgroups of 187, 163, and 138 patients. All subgroups displayed involvement of the precentral gyrus and are characterized, respectively, by (1) pure motor involvement (pure motor cluster [PM]), (2) orbitofrontal and temporal involvement (frontotemporal cluster [FT]), and (3) involvement of the posterior cingulate cortex, parietal white matter, temporal operculum, and cerebellum (cingulate-parietal-temporal cluster [CPT]). These subgroups had significantly distinct clinical profiles regarding male-to-female ratio, age at symptom onset, and frequency of bulbar symptom onset. FT and CPT revealed higher rates of cognitive impairment on the Edinburgh cognitive and behavioral ALS screen (ECAS). Longitudinally, clustering remained stable: at 90.4% of their follow-up visits, patients clustered in the same subgroup as their baseline visit.

INTERPRETATION

ALS can manifest itself in 3 main patterns of cerebral neurodegeneration, each associated with distinct clinical characteristics and cognitive profiles. Besides the pure motor and frontotemporal dementia (FTD)-like variants of ALS, a new neuroimaging phenotype has emerged, characterized by posterior cingulate, parietal, temporal, and cerebellar involvement. ANN NEUROL 2022;92:1030-1045.

Longitudinal grey matter and metabolic contributions to cognitive changes in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis is characterized by rapidly evolving cognitive and brain impairments. While previous work revealed structural and functional alterations associated with cognitive decline in patients suffering from amyotrophic lateral sclerosis, the relationships between anatomo-functional changes and both disease's progression and the evolution of cognitive performance remain largely unexplored. Here, we took advantage of repeated multi-modal acquisitions in patients with amyotrophic lateral sclerosis over 1 year to assess the longitudinal sequence of grey matter atrophy, glucose metabolism and cognitive changes. Results revealed metabolic and structural changes over frontal, thalamic and temporal regions. Both cortical hypermetabolism and hypometabolism (right temporal gyrus and right angular gyrus, respectively) were associated with cognitive performance and thalamic hypometabolism during the follow-up testing session. Furthermore, the inferior frontal gyrus atrophy mediated the relation between early hypometabolism in this region and the subsequent decline of the theory of mind abilities. Marked volume loss was associated with larger hypometabolism and impaired cognitive performance. To our knowledge, this is the first study to longitudinally examine both grey matter volume and metabolic alteration patterns in patients with amyotrophic lateral sclerosis, over a mean follow-up time of 1 year. We identify how changes of the inferior frontal gyrus critically underly later cognitive performance, shedding new light on its high prognostic significance for amyotrophic lateral sclerosis-related changes. These results have important implications for our understanding of structural and functional changes associated with amyotrophic lateral sclerosis and how they underly cognitive impairments.

Frequency and Longitudinal Course of Motor Signs in Genetic Frontotemporal Dementia

BACKGROUND AND OBJECTIVES

Frontotemporal dementia (FTD) is a highly heritable disorder. The majority of genetic cases are caused by autosomal dominant pathogenic variants in the chromosome 9 open reading frame 72 (c9orf72), progranulin (GRN), and microtubule-associated protein tau (MAPT) gene. As motor disorders are increasingly recognized as part of the clinical spectrum, the current study aimed to describe motor phenotypes caused by genetic FTD, quantify their temporal association, and investigate their regional association with brain atrophy.

METHODS

We analyzed baseline visit data of known carriers of a pathogenic variant in the c9orf72, GRN, or MAPT gene from the Genetic Frontotemporal Dementia Initiative cohort study. Principal component analysis with varimax rotation was performed to identify motor sign clusters that were compared with respect to frequency and severity between groups. Associations with cross-sectional atrophy patterns were determined using voxel-wise regression. We applied linear mixed effects models to assess whether groups differed in the association between motor signs and estimated time to symptom onset.

RESULTS

A total of 322 pathogenic variant carriers were included in the analysis: 122 c9orf72 (79 presymptomatic), 143 GRN (112 presymptomatic), and 57 MAPT (43 presymptomatic) pathogenic variant carriers. Principal component analysis revealed 5 motor clusters, which we call progressive supranuclear palsy (PSP)-like, bulbar amyotrophic lateral sclerosis (ALS)-like, mixed/ALS-like, Parkinson disease (PD) like, and corticobasal syndrome-like motor phenotypes. There was no significant group difference in the frequency of signs of different motor phenotypes. However, mixed/ALS-like motor signs were most frequent, followed by PD-like motor signs. Although the PSP-like phenotype was associated with mesencephalic atrophy, the mixed/ALS-like phenotype was associated with motor cortex and corticospinal tract atrophy. The PD-like phenotype was associated with widespread cortical and subcortical atrophy. Estimated time to onset, genetic group and their interaction influenced motor signs. In c9orf72 pathogenic variant carriers, motor signs could be detected up to 25 years before expected symptom onset.

DISCUSSION

These results indicate the presence of multiple natural clusters of motor signs in genetic FTD, each correlated with specific atrophy patterns. Their motor severity depends on time and the affected gene. These clinicogenetic associations can guide diagnostic evaluations and the design of clinical trials for new disease-modifying and preventive treatments.

Simultaneous PET/MRI: The future gold standard for characterizing motor neuron disease-A clinico-radiological and neuroscientific perspective

Neuroimaging assessment of motor neuron disease has turned into a cornerstone of its clinical workup. Amyotrophic lateral sclerosis (ALS), as a paradigmatic motor neuron disease, has been extensively studied by advanced neuroimaging methods, including molecular imaging by MRI and PET, furthering finer and more specific details of the cascade of ALS neurodegeneration and symptoms, facilitated by multicentric studies implementing novel methodologies. With an increase in multimodal neuroimaging data on ALS and an exponential improvement in neuroimaging technology, the need for harmonization of protocols and integration of their respective findings into a consistent model becomes mandatory. Integration of multimodal data into a model of a continuing cascade of functional loss also calls for the best attempt to correlate the different molecular imaging measurements as performed at the shortest inter-modality time intervals possible. As outlined in this perspective article, simultaneous PET/MRI, nowadays available at many neuroimaging research sites, offers the perspective of a one-stop shop for reproducible imaging biomarkers on neuronal damage and has the potential to become the new gold standard for characterizing motor neuron disease from the clinico-radiological and neuroscientific perspectives.

Mills’ syndrome is a unique entity of upper motor neuron disease with N-shaped progression: Three case reports

BACKGROUND

Mills’ syndrome is an extremely rare degenerative motor neuron disorder first described by Mills in 1900, but its nosological status is still not clear. We aimed to analyze the clinical features of Mills’ syndrome.

CASE SUMMARY

Herein, we present 3 cases with similar features as those described in Mills’ original paper and review the related literature. Our patients showed middle- and older-age onset, with only upper motor neuron symptoms evident throughout the course of the disease. Spastic hemiplegia began in the lower extremity with a unique progressive pattern.

CONCLUSION

We consider that Mills’ syndrome is a unique entity of motor neuron disorder with an N-shaped progression. Clinicians should maintain a high index of suspicion for the diagnosis of Mills’ syndrome when the onset involves lower extremity paralysis without evidence of lower motor neuron or sensory involvement.

Impact of Weight Loss on Brain Age: Improved Brain Health Following Bariatric Surgery

Individuals living with obesity tend to have increased brain age, reflecting poorer brain health likely due to grey and white matter atrophy related to obesity. However, it is unclear if older brain age associated with obesity can be reversed following weight loss and cardiometabolic health improvement. The aim of this study was to assess the impact of weight loss and cardiometabolic improvement following bariatric surgery on brain health, as measured by change in brain age estimated based on voxel-based morphometry (VBM) measurements. We used three distinct datasets to perform this study: 1) CamCAN dataset to train the brain age prediction model, 2) Human Connectome Project (HCP) dataset to investigate whether individuals with obesity have greater brain age than individuals with normal weight, and 3) pre-surgery, as well as 4, 12, and 24 month post-surgery data from participants (n=87, age: 44.0±9.2 years, BMI: 43.9±4.2 kg/m2) who underwent a bariatric surgery to investigate whether weight loss and cardiometabolic improvement as a result of bariatric surgery lowers the brain age. As expected, our results from the HCP dataset showed a higher brain age for individuals with obesity compared to individuals with normal weight (T-value = 7.08, p-value < 0.0001). We also found significant improvement in brain health, indicated by a decrease of 2.9 and 5.6 years in adjusted delta age at 12 and 24 months following bariatric surgery compared to baseline (p-value < 0.0005 for both). While the overall effect seemed to be driven by a global change across all brain regions and not from a specific region, our exploratory analysis showed lower delta age in certain brain regions (mainly in somatomotor, visual, and ventral attention networks) at 24 months. This reduced age was also associated with post-surgery improvements in BMI, systolic/diastolic blood pressure, and HOMA-IR (T-value_BMI=4.29, T-value_SBP=4.67, T-value_DBP=4.12, T-value_HOMA-IR=3.16, all p-values < 0.05). In conclusion, these results suggest that obesity-related brain health abnormalities (as measured by delta age) might be reversed by bariatric surgery-induced weight loss and widespread improvements in cardiometabolic alterations.

Pathophysiological Underpinnings of Extra-Motor Neurodegeneration in Amyotrophic Lateral Sclerosis: New Insights From Biomarker Studies

Amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) lie at opposing ends of a clinical, genetic, and neuropathological continuum. In the last decade, it has become clear that cognitive and behavioral changes in patients with ALS are more frequent than previously recognized. Significantly, these non-motor features can impact the diagnosis, prognosis, and management of ALS. Partially overlapping neuropathological staging systems have been proposed to describe the distribution of TAR DNA-binding protein 43 (TDP-43) aggregates outside the corticospinal tract. However, the relationship between TDP-43 inclusions and neurodegeneration is not absolute and other pathophysiological processes, such as neuroinflammation (with a prominent role of microglia), cortical hyperexcitability, and synaptic dysfunction also play a central role in ALS pathophysiology. In the last decade, imaging and biofluid biomarker studies have revealed important insights into the pathophysiological underpinnings of extra-motor neurodegeneration in the ALS-FTLD continuum. In this review, we first summarize the clinical and pathophysiological correlates of extra-motor neurodegeneration in ALS. Next, we discuss the diagnostic and prognostic value of biomarkers in ALS and their potential to characterize extra-motor neurodegeneration. Finally, we debate about how biomarkers could improve the diagnosis and classification of ALS. Emerging imaging biomarkers of extra-motor neurodegeneration that enable the monitoring of disease progression are particularly promising. In addition, a growing arsenal of biofluid biomarkers linked to neurodegeneration and neuroinflammation are improving the diagnostic accuracy and identification of patients with a faster progression rate. The development and validation of biomarkers that detect the pathological aggregates of TDP-43 in vivo are notably expected to further elucidate the pathophysiological underpinnings of extra-motor neurodegeneration in ALS. Novel biomarkers tracking the different aspects of ALS pathophysiology are paving the way to precision medicine approaches in the ALS-FTLD continuum. These are essential steps to improve the diagnosis and staging of ALS and the design of clinical trials testing novel disease-modifying treatments.

Decreased Brain Ventricular Volume in Psychiatric Inpatients with Serotonin Reuptake Inhibitor Treatment

Background

Brain ventricles have been reported to be enlarged in several neuropsychiatric disorders and in aging. Whether human cerebral ventricular volume can decrease over time with psychiatric treatment is not well-studied. The aim of this study was to examine whether inpatients taking serotonin reuptake inhibitors (SRI) exhibited reductions in cerebral ventricular volume.

Methods

Psychiatric inpatients, diagnosed mainly with depression, substance use, anxiety, and personality disorders, underwent two imaging sessions (Time 1 and Time 2, approximately 4 weeks apart). FreeSurfer was used to quantify volumetric features of the brain, and ANOVA was used to analyze ventricular volume differences between Time 1 and Time 2. Inpatients' brain ventricle volumes were normalized by dividing by estimated total intracranial volume (eTIV). Clinical features such as depression and anxiety levels were collected at Time 1, Time 1.5 (approximately 2 weeks apart), and Time 2.

Results

Inpatients consistently taking SRIs (SRI + , n = 44) showed statistically significant reductions of brain ventricular volumes particularly for their left and right lateral ventricular volumes. Reductions in their third ventricular volume were close to significance (p = .068). The inpatients that did not take SRIs (SRI-, n = 25) showed no statistically significant changes in brain ventricular volumes. The SRI + group also exhibited similar brain structural features to the healthy control group based on the 90% confidence interval comparsions on brain ventricular volume parameters, whereas the SRI- group still exhibited relatively enlarged brain ventricular volumes after treatment.

Conclusions

SRI treatment was associated with decreased brain ventricle volume over treatment.

White matter hyperintensities are associated with grey matter atrophy and cognitive decline in Alzheimer's disease and frontotemporal dementia

White matter hyperintensities (WMHs) are commonly assumed to represent non-specific cerebrovascular disease comorbid to neurodegenerative processes, rather than playing a synergistic role. We compared the impact of WMHs on grey matter (GM) atrophy and cognition in normal aging (n = 571), mild cognitive impairment (MCI, n = 551), Alzheimer's dementia (AD, n = 212), fronto-temporal dementia (FTD, n = 125), and Parkinson's disease (PD, n = 271). Longitudinal data were obtained from ADNI, FTLDNI, and PPMI datasets. Mixed-effects models were used to compare WMHs and GM atrophy between patients and controls and assess the impact of WMHs on GM atrophy and cognition. MCI, AD, and FTD patients had significantly higher WMH loads than controls. WMHs were related to GM atrophy in insular and parieto-occipital regions in MCI/AD, and frontal regions and basal ganglia in FTD. In addition, WMHs contributed to more severe cognitive deficits in AD and FTD compared to controls, whereas their impact in MCI and PD was not significantly different from controls. These results suggest potential synergistic effects between WMHs and proteinopathies in the neurodegenerative process in MCI, AD and FTD.

Feature selection from magnetic resonance imaging data in ALS: a systematic review

Background:

With the advances in neuroimaging in amyotrophic lateral sclerosis (ALS), it has been speculated that multiparametric magnetic resonance imaging (MRI) is capable to contribute to early diagnosis. Machine learning (ML) can be regarded as the missing piece that allows for the useful integration of multiparametric MRI data into a diagnostic classifier. The major challenges in developing ML classifiers for ALS are limited data quantity and a suboptimal sample to feature ratio which can be addressed by sound feature selection.

Methods:

We conducted a systematic review to collect MRI biomarkers that could be used as features by searching the online database PubMed for entries in the recent 4 years that contained cross-sectional neuroimaging data of subjects with ALS and an adequate control group. In addition to the qualitative synthesis, a semi-quantitative analysis was conducted for each MRI modality that indicated which brain regions were most commonly reported.

Results:

Our search resulted in 151 studies with a total of 221 datasets. In summary, our findings highly resembled generally accepted neuropathological patterns of ALS, with degeneration of the motor cortex and the corticospinal tract, but also in frontal, temporal, and subcortical structures, consistent with the neuropathological four-stage model of the propagation of pTDP-43 in ALS.

Conclusions:

These insights are discussed with respect to their potential for MRI feature selection for future ML-based neuroimaging classifiers in ALS. The integration of multiparametric MRI including DTI, volumetric, and texture data using ML may be the best approach to generate a diagnostic neuroimaging tool for ALS.

Splicing factor proline and glutamine rich intron retention, reduced expression and aggregate formation are pathological features of amyotrophic lateral sclerosis

AIM

Splicing factor proline and glutamine rich (SFPQ) is an RNA-DNA binding protein that is dysregulated in Alzheimer's disease and frontotemporal dementia. Dysregulation of SFPQ, specifically increased intron retention and nuclear depletion, has been linked to several genetic subtypes of amyotrophic lateral sclerosis (ALS), suggesting that SFPQ pathology may be a common feature of this heterogeneous disease. Our study aimed to investigate this hypothesis by providing the first comprehensive assessment of SFPQ pathology in large ALS case-control cohorts.

METHODS

We examined SFPQ at the RNA, protein and DNA levels. SFPQ RNA expression and intron retention were examined using RNA-sequencing and quantitative PCR. SFPQ protein expression was assessed by immunoblotting and immunofluorescent staining. At the DNA level, SFPQ was examined for genetic variation novel to ALS patients.

RESULTS

At the RNA level, retention of SFPQ intron nine was significantly increased in ALS patients' motor cortex. In addition, SFPQ RNA expression was significantly reduced in the central nervous system, but not blood, of patients. At the protein level, neither nuclear depletion nor reduced expression of SFPQ was found to be a consistent feature of spinal motor neurons. However, SFPQ-positive ubiquitinated protein aggregates were observed in patients' spinal motor neurons. At the DNA level, our genetic screen identified two novel and two rare SFPQ sequence variants not previously reported in the literature.

CONCLUSIONS

Our findings confirm dysregulation of SFPQ as a pathological feature of the central nervous system of ALS patients and indicate that investigation of the functional consequences of this pathology will provide insight into ALS biology.

Computer-aided identification of degenerative neuromuscular diseases based on gait dynamics and ensemble decision tree classifiers

This study proposes a reliable computer-aided framework to identify gait fluctuations associated with a wide range of degenerative neuromuscular disease (DNDs) and health conditions. Investigated DNDs included amyotrophic lateral sclerosis (ALS), Parkinson's disease (PD), and Huntington's disease (HD). We further performed a statistical and classification comparison elucidating the discriminative capability of different gait signals, including vertical ground reaction force (VGRF), stride duration, stance duration, and swing duration. Feature representation of these gait signals was based on statistical amplitude quantification using the root mean square (RMS), variance, kurtosis, and skewness metrics. We investigated various decision tree (DT) based ensemble methods such as bagging, adaptive boosting (AdaBoost), random under-sampling boosting (RUSBoost), and random subspace to tackle the challenge of multi-class classification. Experimental results showed that AdaBoost ensembling provided a 6.49%, 0.78%, 2.31%, and 2.72% prediction rate improvement for the VGRF, stride, stance, and swing signals, respectively. The proposed approach achieved the highest classification accuracy of 99.17%, sensitivity of 98.23%, and specificity of 99.43%, using the VGRF-based features and the adaptive boosting classification model. This work demonstrates the effective capability of using simple gait fluctuation analysis and machine learning approaches to detect DNDs. Computer-aided analysis of gait fluctuations provides a promising advent to enhance clinical diagnosis of DNDs.