Multimodal longitudinal study of structural brain involvement in amyotrophic lateral sclerosis

Longitudinal Image Data for Outcome Modeling

In oncology, medical imaging is crucial for diagnosis, treatment planning and therapy execution. Treatment responses can be complex and varied and are known to involve factors of treatment, patient characteristics and tumor microenvironment. Longitudinal image analysis is able to track temporal changes, aiding in disease monitoring, treatment evaluation, and outcome prediction. This allows for the enhancement of personalized medicine. However, analyzing longitudinal 2D and 3D images presents unique challenges, including image registration, reliable segmentation, dealing with variable imaging intervals, and sparse data. This review presents an overview of techniques and methodologies in longitudinal image analysis, with a primary focus on outcome modeling in radiation oncology.

Functional network dynamics revealed by EEG microstates reflect cognitive decline in amyotrophic lateral sclerosis

Recent electroencephalography (EEG) studies have shown that patterns of brain activity can be used to differentiate amyotrophic lateral sclerosis (ALS) and control groups. These differences can be interrogated by examining EEG microstates, which are distinct, reoccurring topographies of the scalp's electrical potentials. Quantifying the temporal properties of the four canonical microstates can elucidate how the dynamics of functional brain networks are altered in neurological conditions. Here we have analysed the properties of microstates to detect and quantify signal-based abnormality in ALS. High-density resting-state EEG data from 129 people with ALS and 78 HC were recorded longitudinally over a 24-month period. EEG topographies were extracted at instances of peak global field power to identify four microstate classes (labelled A-D) using K-means clustering. Each EEG topography was retrospectively associated with a microstate class based on global map dissimilarity. Changes in microstate properties over the course of the disease were assessed in people with ALS and compared with changes in clinical scores. The topographies of microstate classes remained consistent across participants and conditions. Differences were observed in coverage, occurrence, duration, and transition probabilities between ALS and control groups. The duration of microstate class B and coverage of microstate class C correlated with lower limb functional decline. The transition probabilities A to D, C to B and C to B also correlated with cognitive decline (total ECAS) in those with cognitive and behavioural impairments. Microstate characteristics also significantly changed over the course of the disease. Examining the temporal dependencies in the sequences of microstates revealed that the symmetry and stationarity of transition matrices were increased in people with late-stage ALS. These alterations in the properties of EEG microstates in ALS may reflect abnormalities within the sensory network and higher-order networks. Microstate properties could also prospectively predict symptom progression in those with cognitive impairments.

Differential Expression of miRNAs in Amyotrophic Lateral Sclerosis Patients

Amyotrophic lateral sclerosis (ALS) is a progressive motor neuron disease that affects nerve cells in the brain and spinal cord, causing loss of muscle control, muscle atrophy and in later stages, death. Diagnosis has an average delay of 1 year after symptoms onset, which impairs early management. The identification of a specific disease biomarker could help decrease the diagnostic delay. MicroRNA (miRNA) expression levels have been proposed as ALS biomarkers, and altered function has been reported in ALS pathogenesis. The aim of this study was to assess the differential expression of plasma miRNAs in ALS patients and two control populations (healthy controls and ALS-mimic disorders). For that, 16 samples from each group were pooled, and then 1008 miRNAs were assessed through reverse transcription-quantitative polymerase chain reaction (RT-qPCR). From these, ten candidate miRNAs were selected and validated in 35 ALS patients, 16 ALS-mimic disorders controls and 15 healthy controls. We also assessed the same miRNAs in two different time points of disease progression. Although we were unable to determine a miRNA signature to use as disease or condition marker, we found that miR-7-2-3p, miR-26a-1-3p, miR-224-5p and miR-206 are good study candidates to understand the pathophysiology of ALS.

Structural and microstructural neuroimaging signature of C9orf72-associated ALS: A multiparametric MRI study

BACKGROUND

ALS patients with hexanucleotide expansion in C9orf72 are characterized by a specific clinical phenotype, including more aggressive disease course and cognitive decline. Computerized multiparametric MRI with gray matter volumetry and diffusion tensor imaging (DTI) to analyze white matter structural connectivity is a potential in vivo biomarker.

OBJECTIVE

The objective of this study was to develop a multiparametric MRI signature in a large cohort of ALS patients with C9orf72 mutations. The aim was to investigate how morphological features of C9orf72-associated ALS differ in structural MRI and DTI compared to healthy controls and ALS patients without C9orf72 mutations.

METHODS

Atlas-based volumetry (ABV) and whole brain-based DTI-based analyses were performed in a cohort of n = 51 ALS patients with C9orf72 mutations and compared with both n = 51 matched healthy controls and n = 51 C9orf72 negative ALS patients, respectively. Subsequently, Spearman correlation analysis of C9orf72 ALS patients' data with clinical parameters (age of onset, sex, ALS-FRS-R, progression rate, survival) as well as ECAS and p-NfH in CSF was performed.

RESULTS

The whole brain voxel-by-voxel comparison of fractional anisotropy (FA) maps between C9orf72 ALS patients and controls showed significant bilateral alterations in axonal structures of the white matter at group level, primarily along the corticospinal tracts and in fibers projecting to the frontal lobes. For the frontal lobes, these alterations were also significant between C9orf72 positive and C9orf72 negative ALS patients. In ABV, patients with C9orf72 mutations showed lower volumes of the frontal, temporal, and parietal lobe, with the lowest values in the gray matter of the superior frontal and the precentral gyrus, but also in hippocampi and amygdala. Compared to C9orf72 negative ALS, the differences were shown to be significant for cerebral gray matter (p = 0.04), especially in the frontal (p = 0.01) and parietal lobe (p = 0.01), and in the thalamus (p = 0.004). A correlation analysis between ECAS and averaged regional FA values revealed significant correlations between cognitive performance in ECAS and frontal association fibers. Lower FA values in the frontal lobes were associated with worse performance in all cognitive domains measured (language, verbal fluency, executive functions, memory and spatial perception). In addition, there were significant negative correlations between age of onset and atlas-based volumetry results for gray matter.

CONCLUSIONS

This study demonstrates a distinct pattern of DTI alterations of the white matter and ubiquitous volume reductions of the gray matter early in the disease course of C9orf72-associated ALS. Alterations were closely linked to a more aggressive cognitive phenotype. These results are in line with an expected pTDP43 propagation pattern of cortical affection and thus strengthen the hypothesis that an underlying developmental disorder is present in ALS with C9orf72 expansions. Thus, multiparametric MRI could contribute to the assessment of the disease as an in vivo biomarker even in the early phase of the disease.

Presymptomatic grey matter alterations in ALS kindreds: a computational neuroimaging study of asymptomatic C9orf72 and SOD1 mutation carriers

BACKGROUND

The characterisation of presymptomatic disease-burden patterns in asymptomatic mutation carriers has a dual academic and clinical relevance. The understanding of disease propagation mechanisms is of considerable conceptual interests, and defining the optimal time of pharmacological intervention is essential for improved clinical trial outcomes.

METHODS

In a prospective, multimodal neuroimaging study, 22 asymptomatic C9orf72 GGGGCC hexanucleotide repeat carriers, 13 asymptomatic subjects with SOD1, and 54 "gene-negative" ALS kindreds were enrolled. Cortical and subcortical grey matter alterations were systematically appraised using volumetric, morphometric, vertex, and cortical thickness analyses. Using a Bayesian approach, the thalamus and amygdala were further parcellated into specific nuclei and the hippocampus was segmented into anatomically defined subfields.

RESULTS

Asymptomatic GGGGCC hexanucleotide repeat carriers in C9orf72 exhibited early subcortical changes with the preferential involvement of the pulvinar and mediodorsal regions of the thalamus, as well as the lateral aspect of the hippocampus. Volumetric approaches, morphometric methods, and vertex analyses were anatomically consistent in capturing focal subcortical changes in asymptomatic C9orf72 hexanucleotide repeat expansion carriers. SOD1 mutation carriers did not exhibit significant subcortical grey matter alterations. In our study, none of the two asymptomatic cohorts exhibited cortical grey matter alterations on either cortical thickness or morphometric analyses.

DISCUSSION

The presymptomatic radiological signature of C9orf72 is associated with selective thalamic and focal hippocampal degeneration which may be readily detectable before cortical grey matter changes ensue. Our findings confirm selective subcortical grey matter involvement early in the course of C9orf72-associated neurodegeneration.

Sleep disorders and white matter integrity in patients with sporadic amyotrophic lateral sclerosis

This study aimed to explore the characteristics of sleep disorders and their relationship with abnormal white-matter integrity in patients with sporadic amyotrophic lateral sclerosis. One hundred and thirty-six patients and 80 healthy controls were screened consecutively, and 56 patients and 43 healthy controls were ultimately analyzed. Sleep disorders were confirmed using the Pittsburgh sleep quality index, the Epworth sleepiness scale, and polysomnography; patients were classified into those with poor and good sleep quality. White-matter integrity was assessed using diffusion tensor imaging and compared between groups to identify the white-matter tracts associated with sleep disorders. The relationship between scores on the Pittsburgh sleep quality index and impaired white-matter tracts was analyzed using multiple regression. Poor sleep quality was more common in patients (adjusted odds ratio, 4.26; p = 0.005). Compared to patients with good sleep quality (n = 30), patients with poor sleep quality (n = 26; 46.4%) showed decreased fractional anisotropy, increased mean diffusivity, and increased radial diffusivity of projection and commissural fibers, and increased radial diffusivity of the right thalamus. The Pittsburgh score showed the best fit with the mean fractional anisotropy of the right anterior limb of the internal capsule (r = - 0.355, p = 0.011) and the mean radial diffusivity of the right thalamus (r = 0.309, p = 0.028). We conclude that sleep disorders are common in patients with sporadic amyotrophic lateral sclerosis and are associated with reduced white-matter integrity. The pathophysiology of amyotrophic lateral sclerosis may contribute directly to sleep disorders.

Multimodal MRI improves diagnostic accuracy and sensitivity to longitudinal change in amyotrophic lateral sclerosis

BACKGROUND

Recent advances in MRI acquisitions and image analysis have increased the utility of neuroimaging in understanding disease-related changes. In this work, we aim to demonstrate increased sensitivity to disease progression as well as improved diagnostic accuracy in Amyotrophic lateral sclerosis (ALS) with multimodal MRI of the brain and cervical spinal cord.

METHODS

We acquired diffusion MRI data from the brain and cervical cord, and T1 data from the brain, of 20 participants with ALS and 20 healthy control participants. Ten ALS and 14 control participants, and 11 ALS and 13 control participants were re-scanned at 6-month and 12-month follow-ups respectively. We estimated cross-sectional differences and longitudinal changes in diffusion metrics, cortical thickness, and fixel-based microstructure measures, i.e. fiber density and fiber cross-section.

RESULTS

We demonstrate improved disease diagnostic accuracy and sensitivity through multimodal analysis of brain and spinal cord metrics. The brain metrics also distinguished lower motor neuron-predominant ALS participants from control participants. Fiber density and cross-section provided the greatest sensitivity to longitudinal change. We demonstrate evidence of progression in a cohort of 11 participants with slowly progressive ALS, including in participants with very slow change in ALSFRS-R. More importantly, we demonstrate that longitudinal change is detectable at a six-month follow-up visit. We also report correlations between ALSFRS-R and the fiber density and cross-section metrics.

CONCLUSIONS

Our findings suggest that multimodal MRI is useful in improving disease diagnosis, and fixel-based measures may serve as potential biomarkers of disease progression in ALS clinical trials.

FDG-PET shows weak correlation between focal motor weakness and brain metabolic alterations in ALS

Objective: Amyotrophic lateral sclerosis (ALS) is a clinically heterogenous disease, typically presenting with focal motor weakness that eventually generalizes. Weather there is a correlation between focal motor weakness and metabolic alterations in specific areas of the brain has not been thoroughly explored. This study aims to systematically investigate this by using fluorodeoxyglucose-positron emission tomography (FDG-PET), including longitudinal imaging. Methods: This observational imaging study included 131 ALS patients diagnosed and examined with FDG-PET at the ALS Clinical Research Center at the Karolinska University Hospital in Stockholm, Sweden. Thirteen ALS patients had a second scan and were analyzed longitudinally. The findings were compared to 39 healthy controls examined at the University Medical Center of Gröningen, the Netherlands. Results: There was a general pattern of brain metabolic alterations consistent with previously reported findings in ALS, namely hypometabolism in frontal regions and hypermetabolism in posterior regions. A higher symptom burden was associated with increased hypometabolism and decreased hypermetabolism. However, there was no clear correlation between focal motor weakness and specific metabolic alterations, neither when analyzing focal motor weakness with concomitant upper motor neuron signs or when including all focal motor weakness. Longitudinal FDG-PET imaging showed inconsistent results with little correlation between progression of motor weakness and metabolic alterations. Conclusion: Our results support the disease model of ALS as a diffuse process since no clear correlation was seen between focal motor weakness and specific metabolic alterations. However, there is need for further research on a larger number of patients, particularly including longitudinal imaging.

Thalamic pathology in frontotemporal dementia: Predilection for specific nuclei, phenotype-specific signatures, clinical correlates, and practical relevance

BACKGROUND

Frontotemporal dementia (FTD) phenotypes are classically associated with distinctive cortical atrophy patterns and regional hypometabolism. However, the spectrum of cognitive and behavioral manifestations in FTD arises from multisynaptic network dysfunction. The thalamus is a key hub of several corticobasal and corticocortical circuits. The main circuits relayed via the thalamic nuclei include the dorsolateral prefrontal circuit, the anterior cingulate circuit, and the orbitofrontal circuit.

METHODS

In this paper, we have reviewed evidence for thalamic pathology in FTD based on radiological and postmortem studies. Original research papers were systematically reviewed for preferential involvement of specific thalamic regions, for phenotype-associated thalamic disease burden patterns, characteristic longitudinal changes, and genotype-associated thalamic signatures. Moreover, evidence for presymptomatic thalamic pathology was also reviewed. Identified papers were systematically scrutinized for imaging methods, cohort sizes, clinical profiles, clinicoradiological associations, and main anatomical findings. The findings of individual research papers were amalgamated for consensus observations and their study designs further evaluated for stereotyped shortcomings. Based on the limitations of existing studies and conflicting reports in low-incidence FTD variants, we sought to outline future research directions and pressing research priorities.

RESULTS

FTD is associated with focal thalamic degeneration. Phenotype-specific thalamic traits mirror established cortical vulnerability patterns. Thalamic nuclei mediating behavioral and language functions are preferentially involved. Given the compelling evidence for considerable thalamic disease burden early in the course of most FTD subtypes, we also reflect on the practical relevance, diagnostic role, prognostic significance, and monitoring potential of thalamic metrics in FTD.

CONCLUSIONS

Cardinal manifestations of FTD phenotypes are likely to stem from thalamocortical circuitry dysfunction and are not exclusively driven by focal cortical changes.

Cognition in the course of ALS-a meta-analysis

Objective: The goal of this meta-analysis is to improve insight into the development of cognition over the course of ALS and to assess predictors of cognitive performance.Method: A literature search was conducted in Pubmed and Web of Science on 29 July 2019 and 16 March 2021. Data were screened in Endnote^® Version X9 (London, UK). Meta-analyses and meta-regressions were calculated for cross-sectional data using Rstudio^®. Studies were assigned to temporal and physical categories and Hedges' g was calculated for the respective categories to provide an estimate of a cognitive course based on cross-sectional data. Due to low numbers and heterogeneity in reporting, longitudinal studies were analyzed descriptively.Results: A total of N = 45 cross-sectional and N = 13 longitudinal studies were included. Impairments in all cognitive domains, except verbal IQ, were found in ALS patients (PALS). PALS showed stable cognitive performances in cross-sectional and in most longitudinal studies. PALS with symptoms for 18-24 months and PALS who had an ALSFRS-R score of 40-36 were the most frequently reported subgroup regarding neuropsychology. Age was related to visuospatial functioning, and depressiveness to attention. In longitudinal studies, impact of site of onset and cognitive status at baseline on cognitive course was found.Conclusion: Despite vast evidence for cognitive impairment at disease onset in different domains, evidence for evolution of these deficits is rather limited, suggesting that PALS present with cognitive impairment early in the course possibly in a sense of disease trait.

Iron quantitative analysis of motor combined with bulbar region in M1 cortex may improve diagnosis performance in ALS

OBJECTIVES

To explore whether the combined analysis of motor and bulbar region of M1 on susceptibility-weighted imaging (SWI) can be a valid biomarker for amyotrophic lateral sclerosis (ALS).

METHODS

Thirty-two non-demented ALS patients and 35 age- and gender-matched healthy controls (HC) were retrospectively recruited. SWI and 3D-T1-MPRAGE images were obtained from all individuals using a 3.0-T MRI scan. The bilateral posterior band of M1 was manually delineated by three neuroradiologists on phase images and subdivided into the motor and bulbar regions. We compared the phase values in two groups and performed a stratification analysis (ALSFRS-R score, duration, disease progression rate, and onset). Receiver operating characteristic (ROC) curves were also constructed.

RESULTS

ALS group showed significantly increased phase values in M1 and the two subregions than the HC group, on the all and elderly level (p < 0.001, respectively). On all-age level comparison, negative correlations were found between phase values of M1 and clinical score and duration (p < 0.05, respectively). Similar associations were found in the motor region (p < 0.05, respectively). On both the total (p < 0.01) and elderly (p < 0.05) levels, there were positive relationships between disease progression rate and M1 phase values. In comparing ROC curves, the entire M1 showed the best diagnostic performance.

CONCLUSIONS

Combining motor and bulbar analyses as an integral M1 region on SWI can improve ALS diagnosis performance, especially in the elderly. The phase value could be a valuable biomarker for ALS evaluation.

KEY POINTS

• Integrated analysis of the motor and bulbar as an entire M1 region on SWI can improve the diagnosis performance in ALS. • Quantitative analysis of iron deposition by SWI measurement helps the clinical evaluation, especially for the elderly patients. • Phase value, when combined with the disease progression rate, could be a valuable biomarker for ALS.

Longitudinal Effects of Asymptomatic C9orf72 Carriership on Brain Morphology

OBJECTIVE

We investigated effects of C9orf72 repeat expansion and gene expression on longitudinal cerebral changes before symptom onset.

METHODS

We enrolled 79 asymptomatic family members (AFMs) from 9 families with C9orf72 repeat expansion. Twenty-eight AFMs carried the mutation (C9+). Participants had up to 3 magnetic resonance imaging (MRI) scans, after which we compared motor cortex and motor tracts between C9+ and C9- AFMs using mixed effects models, incorporating kinship to correct for familial relations and lessen effects of other genetic factors. We also compared cortical, subcortical, cerebellar, and connectome structural measurements in a hypothesis-free analysis. We correlated regional C9orf72 expression in donor brains with the pattern of cortical thinning in C9+ AFMs using meta-regression. For comparison, we included 42 C9+ and 439 C9- patients with amyotrophic lateral sclerosis (ALS) in this analysis.

RESULTS

C9+ AFM motor cortex had less gyrification and was thinner than in C9- AFMs, without differences in motor tracts. Whole brain analysis revealed thinner cortex and less gyrification in parietal, occipital, and temporal regions, smaller thalami and right hippocampus, and affected frontotemporal connections. Thinning of bilateral precentral, precuneus, and left superior parietal cortex was faster in C9+ than in C9- AFMs. Higher C9orf72 expression correlated with thinner cortex in both C9+ AFMs and C9+ ALS patients.

INTERPRETATION

In asymptomatic C9orf72 repeat expansion carriers, brain MRI reveals widespread features suggestive of impaired neurodevelopment, along with faster decline of motor and parietal cortex than found in normal aging. C9orf72 expression might play a role in cortical development, and consequently explain the specific brain abnormalities of mutation carriers. ANN NEUROL 2022.

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.

Cortical and subcortical grey matter atrophy in Amyotrophic Lateral Sclerosis correlates with measures of disease accumulation independent of disease aggressiveness

There is a growing demand for reliable biomarkers to monitor disease progression in Amyotrophic Lateral Sclerosis (ALS) that also take the heterogeneity of ALS into account. In this study, we explored the association between Magnetic Resonance Imaging (MRI)-derived measures of cortical thickness (CT) and subcortical grey matter (GM) volume with D50 model parameters. T1-weighted MRI images of 72 Healthy Controls (HC) and 100 patients with ALS were analyzed using Surface-based Morphometry for cortical structures and Voxel-based Morphometry for subcortical Region-Of-Interest analyses using the Computational Anatomy Toolbox (CAT12). In Inter-group contrasts, these parameters were compared between patients and HC. Further, the D50 model was used to conduct subgroup-analyses, dividing patients by a) Phase of disease covered at the time of MRI-scan and b) individual overall disease aggressiveness. Finally, correlations between GM and D50 model-derived parameters were examined. Inter-group analyses revealed ALS-related cortical thinning compared to HC located mainly in frontotemporal regions and a decrease in GM volume in the left hippocampus and amygdala. A comparison of patients in different phases showed further cortical and subcortical GM atrophy along with disease progression. Correspondingly, regression analyses identified negative correlations between cortical thickness and individual disease covered. However, there were no differences in CT and subcortical GM between patients with low and high disease aggressiveness. By application of the D50 model, we identified correlations between cortical and subcortical GM atrophy and ALS-related functional disability, but not with disease aggressiveness. This qualifies CT and subcortical GM volume as biomarkers representing individual disease covered to monitor therapeutic interventions in ALS.

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.

Cognitive reserve protects ALS-typical cognitive domains: A longitudinal study

Background and Objectives

To determine whether cognitive reserve (CR) as measured by verbal intelligence quotient, educational length, and achievement protects amyotrophic lateral sclerosis (ALS) patients' verbal fluency, executive functioning, and memory against brain volume loss over a period of 12 months.

Methods

This cohort study was completed between 2013 and 2016 with a follow‐up duration of 12 months. ALS patients were recruited from two specialist out‐patient clinics in Rostock and Magdeburg in Germany. Participants underwent cognitive testing and magnetic resonance imaging both at baseline and again after 12 months. The cognitive domains assessed included verbal memory in addition to executive functions such as verbal fluency, working memory, shifting and selective attention.

Results

Thirty‐eight ALS patients took part; 25 patients had no cognitive impairment (ALSni), and 13 were cognitively impaired (ALSci). On average, patients lost 294 mm³ in their superior frontal gyri, 225 mm³ in their orbitofrontal gyri, and 15.97 mm³ in their hippocampi over 12 months. There was strong evidence that CR protected letter fluency from further decline (Bayes factor [BF] >10) and moderate evidence that it supported learning effects in letter flexibility (BF >3). However, there is a lack of evidence supporting the notion that working memory, shifting, selective attention or verbal memory (BF = 1) are protected.

Discussion

As CR is easily determined and protects ALS‐specific cognitive domains over time, it should be regarded as a valuable predictive marker.

Cortical and subcortical changes in resting-state neuronal activity and connectivity in early symptomatic ALS and advanced frontotemporal dementia

The objective of this study was to examine if patterns of resting-state brain activity and functional connectivity in cortical and subcortical regions in patients with early symptomatic amyotrophic lateral sclerosis (ALS) resemble those of behavioural variant frontotemporal dementia (bvFTD). In a cross-sectional design, eyes-closed resting-state magnetoencephalography (MEG) data of 34 ALS patients, 18 bvFTD patients and 18 age- and gender-matched healthy controls (HCs) were projected to source-space using an atlas-based beamformer. Group differences in peak frequency, band-specific oscillatory activity and functional connectivity (corrected amplitude envelope correlation) in 78 cortical regions and 12 subcortical regions were determined. False discovery rate was used to correct for multiple comparisons. BvFTD patients, as compared to ALS and HCs, showed lower relative beta power in parietal, occipital, temporal and nearly all subcortical regions. Compared to HCs, patients with ALS and patients with bvFTD had a higher delta (0.5-4 Hz) and gamma (30-48 Hz) band resting-state functional connectivity in a high number of overlapping regions in the frontal lobe and in limbic and subcortical regions. Higher delta band connectivity was widespread in the bvFTD patients compared to HCs. ALS showed a more widespread higher gamma band functional connectivity compared to bvFTD. In conclusion, MEG in early symptomatic ALS patients shows resting-state functional connectivity changes in frontal, limbic and subcortical regions that overlap considerably with bvFTD. The findings show the potential of MEG to detect brain changes in early symptomatic phases of ALS and contribute to our understanding of the disease spectrum, with ALS and bvFTD at the two extreme ends.

Longitudinal surface-based spatial Bayesian GLM reveals complex trajectories of motor neurodegeneration in ALS

Longitudinal fMRI studies hold great promise for the study of neurodegenerative diseases, development and aging, but realizing their full potential depends on extracting accurate fMRI-based measures of brain function and organization in individual subjects over time. This is especially true for studies of rare, heterogeneous and/or rapidly progressing neurodegenerative diseases. These often involve small samples with heterogeneous functional features, making traditional group-difference analyses of limited utility. One such disease is amyotrophic lateral sclerosis (ALS), a severe disease resulting in extreme loss of motor function and eventual death. Here, we use an advanced individualized task fMRI analysis approach to analyze a rich longitudinal dataset containing 190 hand clench fMRI scans from 16 ALS patients (78 scans) and 22 age-matched healthy controls (112 scans) Specifically, we adopt our cortical surface-based spatial Bayesian general linear model (GLM), which has high power and precision to detect activations in individual subjects, and propose a novel longitudinal extension to leverage information shared across visits. We perform all analyses in native surface space to preserve individua anatomical and functional features. Using mixed-effects models to subsequently study the relationship between size of activation and ALS disease progression, we observe for the first time an inverted U-shaped trajectory o motor activations: at relatively mild motor disability we observe enlarging activations, while at higher levels of motor disability we observe severely diminished activation, reflecting progression toward complete loss of motor function. We further observe distinct trajectories depending on clinical progression rate, with faster progressors exhibiting more extreme changes at an earlier stage of disability. These differential trajectories suggest that initial hyper-activation is likely attributable to loss of inhibitory neurons, rather than functional compensation as earlier assumed. These findings substantially advance scientific understanding of the ALS disease process. This study also provides the first real-world example of how surface-based spatial Bayesian analysis of task fMRI can further scientific understanding of neurodegenerative disease and other phenomena. The surface-based spatial Bayesian GLM is implemented in the BayesfMRI R package

Thalamic and Cerebellar Regional Involvement across the ALS-FTD Spectrum and the Effect of C9orf72

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are part of the same disease spectrum. While thalamic−cerebellar degeneration has been observed in C9orf72 expansion carriers, the exact subregions involved across the clinical phenotypes of the ALS−FTD spectrum remain unclear. Using MRIs from 58 bvFTD, 41 ALS−FTD and 52 ALS patients compared to 57 controls, we aimed to delineate thalamic and cerebellar subregional changes across the ALS−FTD spectrum and to contrast these profiles between cases with and without C9orf72 expansions. Thalamic involvement was evident across all ALS−FTD clinical phenotypes, with the laterodorsal nucleus commonly affected across all groups (values below the 2.5th control percentile). The mediodorsal nucleus was disproportionately affected in bvFTD and ALS−FTD but not in ALS. Cerebellar changes were only observed in bvFTD and ALS−FTD predominantly in the superior−posterior region. Comparison of genetic versus sporadic cases revealed significantly lower volumes exclusively in the pulvinar in C9orf72 expansion carriers compared to non-carriers, irrespective of clinical syndrome. Overall, bvFTD showed significant correlations between thalamic subregions, level of cognitive dysfunction and severity of behavioural symptoms. Notably, strong associations were evident between mediodorsal nucleus atrophy and severity of behavioural changes in C9orf72-bvFTD (r = −0.9, p < 0.0005). Our findings reveal distinct thalamic and cerebellar atrophy profiles across the ALS−FTD spectrum, with differential impacts on behaviour and cognition, and point to a unique contribution of C9orf72 expansions in the clinical profiles of these patients.

Brain Connectivity and Network Analysis in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with no effective treatment or cure. ALS is characterized by the death of lower motor neurons (LMNs) in the spinal cord and upper motor neurons (UMNs) in the brain and their networks. Since the lower motor neurons are under the control of UMN and the networks, cortical degeneration may play a vital role in the pathophysiology of ALS. These changes that are not apparent on routine imaging with CT scans or MRI brain can be identified using modalities such as diffusion tensor imaging, functional MRI, arterial spin labelling (ASL), electroencephalogram (EEG), magnetoencephalogram (MEG), functional near-infrared spectroscopy (fNIRS), and positron emission tomography (PET) scan. They can help us generate a representation of brain networks and connectivity that can be visualized and parsed out to characterize and quantify the underlying pathophysiology in ALS. In addition, network analysis using graph measures provides a novel way of understanding the complex network changes occurring in the brain. These have the potential to become biomarker for the diagnosis and treatment of ALS. This article is a systematic review and overview of the various connectivity and network-based studies in ALS.

Classification of amyotrophic lateral sclerosis by brain volume, connectivity, and network dynamics

Emerging studies corroborate the importance of neuroimaging biomarkers and machine learning to improve diagnostic classification of amyotrophic lateral sclerosis (ALS). While most studies focus on structural data, recent studies assessing functional connectivity between brain regions by linear methods highlight the role of brain function. These studies have yet to be combined with brain structure and nonlinear functional features. We investigate the role of linear and nonlinear functional brain features, and the benefit of combining brain structure and function for ALS classification. ALS patients (N = 97) and healthy controls (N = 59) underwent structural and functional resting state magnetic resonance imaging. Based on key hubs of resting state networks, we defined three feature sets comprising brain volume, resting state functional connectivity (rsFC), as well as (nonlinear) resting state dynamics assessed via recurrent neural networks. Unimodal and multimodal random forest classifiers were built to classify ALS. Out-of-sample prediction errors were assessed via five-fold cross-validation. Unimodal classifiers achieved a classification accuracy of 56.35-61.66%. Multimodal classifiers outperformed unimodal classifiers achieving accuracies of 62.85-66.82%. Evaluating the ranking of individual features' importance scores across all classifiers revealed that rsFC features were most dominant in classification. While univariate analyses revealed reduced rsFC in ALS patients, functional features more generally indicated deficits in information integration across resting state brain networks in ALS. The present work undermines that combining brain structure and function provides an additional benefit to diagnostic classification, as indicated by multimodal classifiers, while emphasizing the importance of capturing both linear and nonlinear functional brain properties to identify discriminative biomarkers of ALS.

Amyotrophic Lateral Sclerosis-Frontotemporal Dementia: Shared and Divergent Neural Correlates Across the Clinical Spectrum

BACKGROUND AND OBJECTIVES

A significant overlap between amyotrophic lateral sclerosis (ALS) and behavioral variant of frontotemporal dementia (bvFTD) has been observed at clinical, genetic, and pathologic levels. Within this continuum of presentations, the presence of mild cognitive or behavioral symptoms in patients with ALS has been consistently reported, although it is unclear whether this is to be considered a distinct phenotype or rather a natural evolution of ALS. Here, we used mathematical modeling of MRI connectomic data to decipher common and divergent neural correlates across the ALS-frontotemporal dementia (FTD) spectrum.

METHODS

We included 83 patients with ALS, 35 patients with bvFTD, and 61 healthy controls, who underwent clinical, cognitive, and MRI assessments. Patients with ALS were classified according to the revised Strong criteria into 54 ALS with only motor deficits (ALS-cn), 21 ALS with cognitive or behavioral involvement (ALS-ci/bi), and 8 ALS with bvFTD (ALS-FTD). First, we assessed the functional and structural connectivity patterns across the ALS-FTD spectrum. Second, we investigated whether and where MRI connectivity alterations of patients with ALS with any degree of cognitive impairment (i.e., ALS-ci/bi and ALS-FTD) resembled more the pattern of damage of one (ALS-cn) or the other end (bvFTD) of the spectrum, moving from group-level to single-subject analysis.

RESULTS

As compared with controls, extensive structural and functional disruption of the frontotemporal and parietal networks characterized bvFTD (bvFTD-like pattern), while a more focal structural damage within the sensorimotor-basal ganglia areas characterized ALS-cn (ALS-cn-like pattern). ALS-ci/bi patients demonstrated an ALS-cn-like pattern of structural damage, diverging from ALS-cn with similar motor impairment for the presence of enhanced functional connectivity within sensorimotor areas and decreased functional connectivity within the bvFTD-like pattern. On the other hand, patients with ALS-FTD resembled both structurally and functionally the bvFTD-like pattern of damage with, in addition, the structural ALS-cn-like damage in the motor areas.

DISCUSSION

Our findings suggest a maladaptive role of functional rearrangements in ALS-ci/bi concomitantly with similar structural alterations compared to ALS-cn, supporting the hypothesis that ALS-ci/bi might be considered as a phenotypic variant of ALS, rather than a consequence of disease worsening.

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.

Distinct patterns of progressive gray and white matter degeneration in amyotrophic lateral sclerosis

Progressive cerebral degeneration in amyotrophic lateral sclerosis (ALS) remains poorly understood. Here, three-dimensional (3D) texture analysis was used to study longitudinal gray and white matter cerebral degeneration in ALS from routine T1-weighted magnetic resonance imaging (MRI). Participants were included from the Canadian ALS Neuroimaging Consortium (CALSNIC) who underwent up to three clinical assessments and MRI at four-month intervals, up to 8 months after baseline (T₀ ). Three-dimensional maps of the texture feature autocorrelation were computed from T1-weighted images. One hundred and nineteen controls and 137 ALS patients were included, with 81 controls and 84 ALS patients returning for at least one follow-up. At baseline, texture changes in ALS patients were detected in the motor cortex, corticospinal tract, insular cortex, and bilateral frontal and temporal white matter compared to controls. Longitudinal comparison of texture maps between T₀ and T_max (last follow-up visit) within ALS patients showed progressive texture alterations in the temporal white matter, insula, and internal capsule. Additionally, when compared to controls, ALS patients had greater texture changes in the frontal and temporal structures at T_max than at T₀ . In subgroup analysis, slow progressing ALS patients had greater progressive texture change in the internal capsule than the fast progressing patients. Contrastingly, fast progressing patients had greater progressive texture changes in the precentral gyrus. These findings suggest that the characteristic longitudinal gray matter pathology in ALS is the progressive involvement of frontotemporal regions rather than a worsening pathology within the motor cortex, and that phenotypic variability is associated with distinct progressive spatial pathology.

Biomarkers for C9orf7-ALS in Symptomatic and Pre-symptomatic Patients: State-of-the-art in the New Era of Clinical Trials

The development of new possible treatments for C9orf72-related ALS and the possibility of early identification of subjects genetically at risk of developing the disease is creating a critical need for biomarkers to track neurodegeneration that could be used as outcome measures in clinical trials. Current candidate biomarkers in C9orf72-ALS include neuropsychology tests, imaging, electrophysiology as well as different circulating biomarkers. Neuropsychology tests show early executive and verbal function involvement both in symptomatic and asymptomatic mutation carriers. At brain MRI, C9orf72-ALS patients present diffuse white and grey matter degeneration, which are already identified up to 20 years before symptom onset and that seem to be slowly progressive over time, while regions of altered connectivity at fMRI and of hypometabolism at [¹⁸F]FDG PET have been described as well. At the same time, spinal cord MRI has also shown progressive decrease of FA in the cortico-spinal tract over time. On the side of wet biomarkers, neurofilament proteins are increased both in the CSF and serum just before symptom onset and tend to slowly increase over time, while poly(GP) protein can be detected in the CSF and probably used as target engagement marker in clinical trials.

Time-course of decline in different cognitive domains in Parkinson's disease: a retrospective study

Cognitive impairment and dementia are common non-motor symptoms in Parkinson's disease (PD). To elucidate the potentially typical progression of cognitive decline in PD and its variation, we retrospectively surveyed neuropsychological data obtained at the Parkinson-Klinik Ortenau, Germany in the years 1996-2015. Many of the patients in the surveyed period were repeatedly admitted to our clinic and we were thus able to compile neuropsychological re-test data for 252 patients obtained at varying time intervals. Neuropsychological testing was conducted with the NAI (Nürnberger Alters-Inventar). This battery provides sub-tests that examine cognitive processing speed, executive function, working memory, and verbal/visual memory functions. The re-test time span varied across patients from below 1 year up to about 12 years. Most patients were seen twice, but some patients were tested up to eight times. The steepest rates of cognitive decline were observed for the NAI sub-tests Trail-Making, Maze Test, and Stroop-Word Reading/Color Naming. Intermediate rates of decline were found for Digit Span, Word List-Immediate Recall, and Picture Test. Stroop Test-Interference, Word List-Delayed Recognition, and Figure Test exhibited the slowest decline rates. We did not observe a significant effect of age at diagnosis or gender on the rate of decline. In sum, this study retrospectively evaluated cognitive decline in a sample of patients with PD. Our data suggest a broad cognitive decline that particularly affects the cognitive capacities for processing speed, executive functions, and immediate memory functions.

Tackling clinical heterogeneity across the amyotrophic lateral sclerosis-frontotemporal dementia spectrum using a transdiagnostic approach

The disease syndromes of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) display considerable clinical, genetic and pathological overlap, yet mounting evidence indicates substantial differences in progression and survival. To date, there has been limited examination of how profiles of brain atrophy might differ between clinical phenotypes. Here, we address this longstanding gap in the literature by assessing cortical and subcortical grey and white matter volumes on structural MRI in a large cohort of 209 participants. Cognitive and behavioural changes were assessed using the Addenbrooke’s Cognitive Examination and the Cambridge Behavioural Inventory. Relative to 58 controls, behavioural variant FTD (n = 58) and ALS–FTD (n = 41) patients displayed extensive atrophy of frontoinsular, cingulate, temporal and motor cortices, with marked subcortical atrophy targeting the hippocampus, amygdala, thalamus and striatum, with atrophy further extended to the brainstem, pons and cerebellum in the latter group. At the other end of the spectrum, pure-ALS patients (n = 52) displayed considerable frontoparietal atrophy, including right insular and motor cortices and pons and brainstem regions. Subcortical regions included the bilateral pallidum and putamen, but to a lesser degree than in the ALS–FTD and behavioural variant FTD groups. Across the spectrum the most affected region in all three groups was the insula, and specifically the anterior part (76–90% lower than controls). Direct comparison of the patient groups revealed disproportionate temporal atrophy and widespread subcortical involvement in ALS–FTD relative to pure-ALS. In contrast, pure-ALS displayed significantly greater parietal atrophy. Both behavioural variant FTD and ALS–FTD were characterized by volume decrease in the frontal lobes relative to pure-ALS. The motor cortex and insula emerged as differentiating structures between clinical syndromes, with bilateral motor cortex atrophy more pronounced in ALS–FTD compared with pure-ALS, and greater left motor cortex and insula atrophy relative to behavioural variant FTD. Taking a transdiagnostic approach, we found significant associations between abnormal behaviour and volume loss in a predominantly frontoinsular network involving the amygdala, striatum and thalamus. Our findings demonstrate the presence of distinct atrophy profiles across the ALS–FTD spectrum, with key structures including the motor cortex and insula. Notably, our results point to subcortical involvement in the origin of behavioural disturbances, potentially accounting for the marked phenotypic variability typically observed across the spectrum.

Resting-state EEG reveals four subphenotypes of amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis is a devastating disease characterized primarily by motor system degeneration, with clinical evidence of cognitive and behavioural change in up to 50% of cases. Amyotrophic lateral sclerosis is both clinically and biologically heterogeneous. Subgrouping is currently undertaken using clinical parameters, such as site of symptom onset (bulbar or spinal), burden of disease (based on the modified El Escorial Research Criteria) and genomics in those with familial disease. However, with the exception of genomics, these subcategories do not take into account underlying disease pathobiology, and are not fully predictive of disease course or prognosis.

Recently, we have shown that resting-state EEG can reliably and quantitatively capture abnormal patterns of motor and cognitive network disruption in amyotrophic lateral sclerosis. These network disruptions have been identified across multiple frequency bands, and using measures of neural activity (spectral power) and connectivity (comodulation of activity by amplitude envelope correlation and synchrony by imaginary coherence) on source-localized brain oscillations from high-density EEG. Using data-driven methods (similarity network fusion and spectral clustering), we have now undertaken a clustering analysis to identify disease subphenotypes and to determine whether different patterns of disruption are predictive of disease outcome.

We show that amyotrophic lateral sclerosis patients (n = 95) can be subgrouped into four phenotypes with distinct neurophysiological profiles. These clusters are characterized by varying degrees of disruption in the somatomotor (α-band synchrony), frontotemporal (β-band neural activity and γ_l-band synchrony) and frontoparietal (γ_l-band comodulation) networks, which reliably correlate with distinct clinical profiles and different disease trajectories. Using an in-depth stability analysis, we show that these clusters are statistically reproducible and robust, remain stable after reassessment using a follow-up EEG session, and continue to predict the clinical trajectory and disease outcome.

Our data demonstrate that novel phenotyping using neuroelectric signal analysis can distinguish disease subtypes based exclusively on different patterns of network disturbances. These patterns may reflect underlying disease neurobiology. The identification of amyotrophic lateral sclerosis subtypes based on profiles of differential impairment in neuronal networks has clear potential in future stratification for clinical trials. Advanced network profiling in amyotrophic lateral sclerosis can also underpin new therapeutic strategies that are based on principles of neurobiology and designed to modulate network disruption.

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.

Progressive Neurochemical Abnormalities in Cognitive and Motor Subgroups of Amyotrophic Lateral Sclerosis: A Prospective Multicenter Study

OBJECTIVE

To evaluate progressive cerebral degeneration in amyotrophic lateral sclerosis (ALS) by assessing alterations in N-acetylaspartate (NAA) ratios in the motor and prefrontal cortex within clinical subgroups of ALS.

METHODS

Seventy-six patients with ALS and 59 healthy controls were enrolled in a prospective, longitudinal, multicenter study in the Canadian ALS Neuroimaging Consortium. Participants underwent serial clinical evaluations and magnetic resonance spectroscopy at baseline and 4 and 8 months using a harmonized protocol across 5 centers. NAA ratios were quantified in the motor cortex and prefrontal cortex. Patients were stratified into subgroups based on disease progression rate, upper motor neuron (UMN) signs, and cognitive status. Linear mixed models were used for baseline and longitudinal comparisons of NAA metabolite ratios.

RESULTS

Patients with ALS had reduced NAA ratios in the motor cortex at baseline (p < 0.001). Ratios were lower in those with more rapid disease progression and greater UMN signs (p < 0.05). A longitudinal decline in NAA ratios was observed in the motor cortex in the rapidly progressing (p < 0.01) and high UMN burden (p < 0.01) cohorts. The severity of UMN signs did not change significantly over time. NAA ratios were reduced in the prefrontal cortex only in cognitively impaired patients (p < 0.05); prefrontal cortex metabolites did not change over time.

CONCLUSIONS

Progressive degeneration of the motor cortex in ALS is associated with more aggressive clinical presentations. These findings provide biological evidence of variable spatial and temporal cerebral degeneration linked to the disease heterogeneity of ALS. The use of standardized imaging protocols may have a role in clinical trials for patient selection or subgrouping.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that MRS NAA metabolite ratios of the motor cortex are associated with more rapid disease progression and greater UMN signs in patients with ALS.

TRIAL REGISTRATION INFORMATION

ClinicalTrials.gov Identifier: NCT02405182.

Case Report: Cognitive Conversion in a Non-brazilian VAPB Mutation Carrier (ALS8)

Amyotrophic lateral sclerosis 8 (ALS8) is a predominantly lower motor neuron syndrome originally described in a Portuguese–Brazilian family, which originated from a common founder. ALS8 is caused by a VAPB mutation and extremely rare in Central Europe. We present a 51-year-old German man with ALS8 who had the P56S VAPB mutation independently of the founder effect. In the final 4 years of his life (disease duration 10 years), the patient had five MRI scans and four in-depth neuropsychological assessments. This paper addresses the course of the patient's cognitive status and relates cognitive performance to structural brain changes in order to determine whether this ALS8 case showed a different pattern of cognitive decline compared with sporadic ALS. The executive functions, verbal fluency, and memory of the patient and 17 age-, sex-, and education-matched controls were assessed on four different occasions. His cognitive performance and decline were investigated for abnormality using cross-sectional and longitudinal matched case–control analysis. We obtained five T1-weighted MRI, which we analyzed using voxel-wise non-parametric analysis with statistical non-parametric mapping in Matlab. Moreover, we conducted a single-subject correlation between cognitive performance and brain atrophy. The cognitive profile of the index patient featured executive dysfunction. Notably, his working memory and shifting ability declined from a healthy baseline to an impaired performance, leading to a transition from cognitively non-impaired (ALSni) to cognitively impaired (ALSci). The correlations we observed between cerebellar atrophy and verbal fluency in addition to fusiform gyrus atrophy and shifting are novel findings. We found that the conversion from ALSni to ALSci was associated with widespread cerebral atrophy, which extended beyond the primary motor and premotor cortex and affected, among others, the cerebellum and left fusiform gyrus. The index patients' cognitive profile resembles that of other ALS phenotypes, but the extensive atrophy beyond extra-motor areas has not yet been described.

Cognitive and behavioural impairment in amyotrophic lateral sclerosis: A landmark of the disease? A mini review of longitudinal studies

Amyotrophic lateral sclerosis (ALS) is a heterogeneous neurodegenerative disease marked by progressive loss of motor abilities. Approximately half of patents with ALS experience cognitive (ALSci) or behavioural impairment (ALSbi) during the course of the disease, with a small percentage developing overt frontotemporal dementia (FTD). ALSci and/or ALSbi can occur simultaneously with motor neuron degeneration or develop in advanced stages of the disease, but it can even precede motor involvement in some cases, namely in ALS patients meeting criteria for FTD. Despite clear evidence that cognitive/behavioural impairment may appear early in the course of ALS, no prominent deterioration seems to occur with disease progression. Longitudinal studies have failed to reach conclusive results on the progression of cognitive and behavioural involvement in ALS. This may be due to some structural limitations of the studies, such as attrition rate, practice effect, short-time interval between neuropsychological assessments, but it can also be due to the heterogeneity of ALS phenotypes. The objective of this review is to provide a comprehensive and critical analysis of results of longitudinal studies highlighting cognitive and behavioural domains mainly affected by neurodegeneration pointing out the determinants that might be associate with the development and worsening of frontotemporal symptoms in ALS. At this regard, older age, rapidly progressing ALS, bulbar-onset, advanced disease stages are among factors mainly associated with cognitive and behavioural involvement. Moreover, the progression of cognitive and behavioural deficits seems to be not directly related to the slope of motor disability, thus suggesting the independence of neuropsychological and motor functional decline in ALS. Cognitive and motor involvement may indeed present with distinct trajectories suggesting a differential vulnerability of motor and non-motor cortical networks. In this scenario, determining the progression of extra-motor involvement in ALS may help refine understanding of the clinical implications of cognitive and behavioural abnormalities, and provide clues to the aetiology of the disease.

Patterns of grey and white matter changes differ between bulbar and limb onset amyotrophic lateral sclerosis

Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disease that is characterized by a high heterogeneity in patients' disease course. Patients with bulbar onset of symptoms (b-ALS) have a poorer prognosis than patients with limb onset (l-ALS). However, neuroimaging correlates of the assumed biological difference between b-ALS and l-ALS may have been obfuscated by patients' diversity in the disease course. We conducted Voxel-Based-Morphometry (VBM) and Tract-Based-Spatial-Statistics (TBSS) in a group of 76 ALS patients without clinically relevant cognitive deficits. The subgroups of 26 b-ALS and 52 l-ALS patients did not differ in terms of disease Phase or disease aggressiveness according to the D50 progression model. VBM analyses showed widespread ALS-related changes in grey and white matter, that were more pronounced for b-ALS. TBSS analyses revealed that b-ALS was predominantly characterized by frontal fractional anisotropy decreases. This demonstrates a higher degree of neurodegenerative burden for the group of b-ALS patients in comparison to l-ALS. Correspondingly, higher bulbar symptom burden was associated with right-temporal and inferior-frontal grey matter density decreases as well as fractional anisotropy decreases in inter-hemispheric and long association tracts. Contrasts between patients in Phase I and Phase II further revealed that b-ALS was characterized by an early cortical pathology and showed a spread only outside primary motor regions to frontal and temporal areas. In contrast, l-ALS showed ongoing structural integrity loss within primary motor-regions until Phase II. We therefore provide a strong rationale to treat both onset types of disease separately in ALS studies.

Cognitive reserve and regional brain volume in amyotrophic lateral sclerosis

OBJECTIVE

We investigated whether cognitive reserve measured by education and premorbid IQ allows amyotrophic lateral sclerosis patients to compensate for regional brain volume loss.

METHODS

This was a cross-sectional study. We recruited sixty patients with amyotrophic lateral sclerosis from two specialist out-patient clinics. All participants underwent neuropsychological assessment; the outcomes were standardized z-scores reflecting verbal fluency, executive functions (shifting, planning, working memory), verbal memory and visuo-constructive ability. The predictor was regional brain volume. The moderating proxies of cognitive reserve were premorbid IQ (estimated by vocabulary) and educational years. We hypothesized that higher cognitive reserve would correlate with better performance on a cognitive test battery, and tested this hypothesis with Bayesian analysis of covariance.

RESULTS

The analyses provided moderate to very strong evidence in favor of our hypothesis with regard to verbal fluency functions, working memory, verbal learning and recognition, and visuo-constructive ability (all BF₀₁ > 3): higher cognitive reserve was associated with a mild increase in performance. For shifting and planning ability, the evidence was anecdotal.

CONCLUSIONS

These results indicate that cognitive reserve moderates the effect of brain morphology on cognition in ALS. Patients draw small but meaningful benefits from higher reserve, preserving fluency, memory and visuo-constructive functions. Executive functions presented a dissociation: verbally assessed functions benefitted from cognitive reserve, non-verbally assessed functions did not. This motivates future research into cognitive reserve in ALS and practical implications, such as strengthening reserve to delay decline.

Brain Damage and Gene Expression Across Hereditary Spastic Paraplegia Subtypes

BACKGROUND

Spinal cord has been considered the main target of damage in hereditary spastic paraplegias (HSPs), but mounting evidence indicates that the brain is also affected. Despite this, little is known about the brain signature of HSPs, in particular regarding stratification for specific genetic subtypes.

OBJECTIVE

We aimed to characterize cerebral and cerebellar damage in five HSP subtypes (9 SPG3A, 27 SPG4, 10 SPG7, 9 SPG8, and 29 SPG11) and to uncover the clinical and gene expression correlates.

METHODS

We obtained high-resolution brain T1 and diffusion tensor image (DTI) datasets in this cross-sectional case-control study (n = 84). The MRICloud, FreeSurfer, and CERES-SUIT pipelines were employed to assess cerebral gray (GM) and white matter (WM) as well as the cerebellum.

RESULTS

Brain abnormalities were found in all but one HSP group (SPG3A), but the patterns were gene-specific: basal ganglia, thalamic, and posterior WM involvement in SPG4; diffuse WM and cerebellar involvement in SPG7; cortical thinning at the motor cortices and pallidal atrophy in SPG8; and widespread GM, WM, and deep cerebellar nuclei damage in SPG11. Abnormal regions in SPG4 and SPG8 matched those with higher SPAST and WASHC5 expression, whereas in SPG7 and SPG11 this concordance was only noticed in the cerebellum.

CONCLUSIONS

Brain damage is a conspicuous feature of HSPs (even for pure subtypes), but the pattern of abnormalities is genotype-specific. Correlation between brain structural damage and gene expression maps is different for autosomal dominant and recessive HSPs, pointing to distinct pathophysiological mechanisms underlying brain damage in these subgroups of the disease. © 2021 International Parkinson and Movement Disorder Society.

Cortical progression patterns in individual ALS patients across multiple timepoints: a mosaic-based approach for clinical use

INTRODUCTION

The majority of imaging studies in ALS infer group-level imaging signatures from group comparisons, as opposed to estimating disease burden in individual patients. In a condition with considerable clinical heterogeneity, the characterisation of individual patterns of pathology is hugely relevant. In this study, we evaluate a strategy to track progressive cortical involvement in single patients by using subject-specific reference cohorts.

METHODS

We have interrogated a multi-timepoint longitudinal dataset of 61 ALS patients to demonstrate the utility of estimating cortical disease burden and the expansion of cerebral atrophy over time. We contrast our strategy to the gold-standard approach to gauge the advantages and drawbacks of our method. We modelled the evolution of cortical integrity in a conditional growth model, in which we accounted for age, gender, disability, symptom duration, education and handedness. We hypothesised that the variance associated with demographic variables will be successfully eliminated in our approach.

RESULTS

In our model, the only covariate which modulated the expansion of atrophy was motor disability as measured by the ALSFRS-r (t(153) = - 2.533, p = 0.0123). Using the standard approach, age also significantly influenced progression of CT change (t(153) = - 2.151, p = 0.033) demonstrating the validity and potential clinical utility of our approach.

CONCLUSION

Our strategy of estimating the extent of cortical atrophy in individual patients with ALS successfully corrects for demographic factors and captures relevant cortical changes associated with clinical disability. Our approach provides a framework to interpret single T1-weighted images in ALS and offers an opportunity to track cortical propagation patterns both at individual subject level and at cohort level.

The imaging signature of C9orf72 hexanucleotide repeat expansions: implications for clinical trials and therapy development

While C9orf72-specific imaging signatures have been proposed by both ALS and FTD research groups and considerable presymptomatic alterations have also been confirmed in young mutation carriers, considerable inconsistencies exist in the literature. Accordingly, a systematic review of C9orf72-imaging studies has been performed to identify consensus findings, stereotyped shortcomings, and unique contributions to outline future directions. A formal literature review was conducted according to the STROBE guidelines. All identified papers were individually reviewed for sample size, choice of controls, study design, imaging modalities, statistical models, clinical profiling, and identified genotype-associated pathological patterns. A total of 74 imaging papers were systematically reviewed. ALS patients with GGGGCC repeat expansions exhibit relatively limited motor cortex involvement and widespread extra-motor pathology. C9orf72 positive FTD patients often show preferential posterior involvement. Reports of thalamic involvement are relatively consistent across the various phenotypes. Asymptomatic hexanucleotide repeat carriers often exhibit structural and functional changes decades prior to symptom onset. Common shortcomings included sample size limitations, lack of disease-controls, limited clinical profiling, lack of genetic testing in healthy controls, and absence of post mortem validation. There is a striking paucity of longitudinal studies and existing presymptomatic studies have not evaluated the predictive value of radiological changes with regard to age of onset and phenoconversion. With the advent of antisense oligonucleotide therapies, the meticulous characterisation of C9orf72-associated changes has gained practical relevance. Neuroimaging offers non-invasive biomarkers for future clinical trials, presymptomatic ascertainment, diagnostic and prognostic applications.

Longitudinal clinical and neuroanatomical correlates of memory impairment in motor neuron disease

Memory impairment in motor neuron disease (MND) is still an underrecognized feature and has traditionally been attributed to executive dysfunction. Here, we investigate the rate of memory impairment in a longitudinal cohort of MND patients, its relationship to other cognitive functions and the underlying neuroanatomical correlates. 142 patients with MND and 99 healthy controls (HC) underwent comprehensive neuropsychological testing and structural MRI at 3T up to four times over a period of 18 months. Linear-mixed effects models were fitted to identify changes at baseline and over time in episodic memory function (learning, immediate and delayed recall, recognition), composed cognitive scores (memory, verbal fluency, executive function), and memory-related structural brain regions (hippocampus, entorhinal cortex, parahippocampal gyrus). Associations between episodic memory performance and volumetric or cortical thickness changes of these regions were computed using Pearson's r. Learning, immediate and delayed recall, as well as recognition performance were significantly reduced in MND when compared to controls at baseline. Performances in these subtests improved over time although MND showed less improvement than controls. This relationship did not change when only "classical" ALS patients were considered. Patients with MND showed thinning of the right parahippocampal gyrus (PhG) in comparison to controls that was progressing over time. Bilateral hippocampal atrophy was observed in MND patients with memory impairment after splitting the group according to their overall episodic memory performance, with the right hippocampus shrinking over time. In MND patients, the bilateral hippocampal atrophy was associated with impairment in learning, recall, and recognition at baseline. In contrast, left PhG thinning was associated with a poorer learning performance. These results show that episodic memory impairment in MND is a frequent cognitive dysfunction. Since deficits are not clearly declining with disease course, an early involvement of this cognitive domain in the disease seems probable. The memory performance-dependent atrophy of the hippocampus and PhG provide evidence for a widespread involvement of these non-motor cortical areas in disease pathology.

Neuroimaging in genetic frontotemporal dementia and amyotrophic lateral sclerosis

Frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) have a strong clinical, genetic and pathological overlap. This review focuses on the current understanding of structural, functional and molecular neuroimaging signatures of genetic FTD and ALS. We overview quantitative neuroimaging studies on the most common genes associated with FTD (MAPT, GRN), ALS (SOD1), and both (C9orf72), and summarize visual observations of images reported in the rarer genes (CHMP2B, TARDBP, FUS, OPTN, VCP, UBQLN2, SQSTM1, TREM2, CHCHD10, TBK1).

A Systematic Review of Genotype-Phenotype Correlation across Cohorts Having Causal Mutations of Different Genes in ALS

Amyotrophic lateral sclerosis is a rare and fatal neurodegenerative disease characterised by progressive deterioration of upper and lower motor neurons that eventually culminates in severe muscle atrophy, respiratory failure and death. There is a concerning lack of understanding regarding the mechanisms that lead to the onset of ALS and as a result there are no reliable biomarkers that aid in the early detection of the disease nor is there an effective treatment. This review first considers the clinical phenotypes associated with ALS, and discusses the broad categorisation of ALS and ALS-mimic diseases into upper and lower motor neuron diseases, before focusing on the genetic aetiology of ALS and considering the potential relationship of mutations of different genes to variations in phenotype. For this purpose, a systematic review is conducted collating data from 107 original published clinical studies on monogenic forms of the disease, surveying the age and site of onset, disease duration and motor neuron involvement. The collected data highlight the complexity of the disease's genotype-phenotype relationship, and thus the need for a nuanced approach to the development of clinical assays and therapeutics.