The presymptomatic phase of amyotrophic lateral sclerosis: are we merely scratching the surface?

Considering the response in addition to the challenge - a narrative review in appraisal of a motor reserve framework

The remarkable increase in human life expectancy over the past century has been achieved at the expense of the risk of age-related impairment and disease. Neurodegeneration, be it part of normal aging or due to neurodegenerative disorders, is characterized by loss of specific neuronal populations, leading to increasing clinical impairment. The individual course may be described as balance between aging- or disease-related pathology and intrinsic mechanisms of adaptation. There is plenty of evidence that the human brain is provided with exhaustible resources to maintain function in the face of adverse conditions. While a reserve concept has mainly been coined in cognitive neuroscience, emerging evidence suggests similar mechanisms to underlie individual differences of adaptive capacity within the motor system. In this narrative review, we summarize what has been proposed to date about a motor reserve (mR) framework. We present current evidence from research in aging subjects and people with neurological conditions, followed by a description of what is known about potential neuronal substrates of mR so far. As there is no gold standard of mR quantification, we outline current approaches which describe various indicators of mR. We conclude by sketching out potential future directions of research. Expediting our understanding of differences in individual motor resilience towards aging and disease will eventually contribute to new, individually tailored therapeutic strategies. Provided early diagnosis, enhancing the individual mR may be suited to postpone disease onset by years and may be an efficacious contribution towards healthy aging, with an increased quality of life for the elderly.

Language deficits in primary lateral sclerosis: cortical atrophy, white matter degeneration and functional disconnection between cerebral regions

BACKGROUND

Primary lateral sclerosis (PLS) is traditionally regarded as a pure upper motor neuron disorder, but recent cases series have highlighted cognitive deficits in executive and language domains.

METHODS

A single-centre, prospective neuroimaging study was conducted with comprehensive clinical and genetic profiling. The structural and functional integrity of language-associated brain regions and networks were systematically evaluated in 40 patients with PLS in comparison to 111 healthy controls. The structural integrity of the arcuate fascicle, frontal aslant tract, inferior occipito-frontal fascicle, inferior longitudinal fascicle, superior longitudinal fascicle and uncinate fascicle was evaluated. Functional connectivity between the supplementary motor region and the inferior frontal gyrus and connectivity between Wernicke's and Broca's areas was also assessed.

RESULTS

Cortical thickness reductions were observed in both Wernicke's and Broca's areas. Fractional anisotropy reduction was noted in the aslant tract and increased radical diffusivity (RD) identified in the aslant tract, arcuate fascicle and superior longitudinal fascicle in the left hemisphere. Functional connectivity was reduced along the aslant track, i.e. between the supplementary motor region and the inferior frontal gyrus, but unaffected between Wernicke's and Broca's areas. Cortical thickness alterations, structural and functional connectivity changes were also noted in the right hemisphere.

CONCLUSIONS

Disease-burden in PLS is not confined to motor regions, but there is also a marked involvement of language-associated tracts, networks and cortical regions. Given the considerably longer survival in PLS compared to ALS, the impact of language impairment on the management of PLS needs to be carefully considered.

Biomarkers in amyotrophic lateral sclerosis: current status and future prospects

Disease heterogeneity in amyotrophic lateral sclerosis poses a substantial challenge in drug development. Categorization based on clinical features alone can help us predict the disease course and survival, but quantitative measures are also needed that can enhance the sensitivity of the clinical categorization. In this Review, we describe the emerging landscape of diagnostic, categorical and pharmacodynamic biomarkers in amyotrophic lateral sclerosis and their place in the rapidly evolving landscape of new therapeutics. Fluid-based markers from cerebrospinal fluid, blood and urine are emerging as useful diagnostic, pharmacodynamic and predictive biomarkers. Combinations of imaging measures have the potential to provide important diagnostic and prognostic information, and neurophysiological methods, including various electromyography-based measures and quantitative EEG-magnetoencephalography-evoked responses and corticomuscular coherence, are generating useful diagnostic, categorical and prognostic markers. Although none of these biomarker technologies has been fully incorporated into clinical practice or clinical trials as a primary outcome measure, strong evidence is accumulating to support their clinical utility.

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.

Aberrantly Expressed Hsa_circ_0060762 and CSE1L as Potential Peripheral Blood Biomarkers for ALS

Amyotrophic lateral sclerosis (ALS) is a rapidly progressive adult-onset neurodegenerative disease that is often diagnosed with a delay due to initial non-specific symptoms. Therefore, reliable and easy-to-obtain biomarkers are an absolute necessity for earlier and more accurate diagnostics. Circular RNAs (circRNAs) have already been proposed as potential biomarkers for several neurodegenerative diseases. In this study, we further investigated the usefulness of circRNAs as potential biomarkers for ALS. We first performed a microarray analysis of circRNAs on peripheral blood mononuclear cells of a subset of ALS patients and controls. Among the differently expressed circRNA by microarray analysis, we selected only the ones with a host gene that harbors the highest level of conservation and genetic constraints. This selection was based on the hypothesis that genes under selective pressure and genetic constraints could have a major role in determining a trait or disease. Then we performed a linear regression between ALS cases and controls using each circRNA as a predictor variable. With a False Discovery Rate (FDR) threshold of 0.1, only six circRNAs passed the filtering and only one of them remained statistically significant after Bonferroni correction: hsa_circ_0060762 and its host gene CSE1L. Finally, we observed a significant difference in expression levels between larger sets of patients and healthy controls for both hsa_circ_0060762 and CSE1L. CSE1L is a member of the importin β family and mediates inhibition of TDP-43 aggregation; the central pathogenicity in ALS and hsa_circ_0060762 has binding sites for several miRNAs that have been already proposed as biomarkers for ALS. In addition, receiver operating characteristics curve analysis showed diagnostic potential for CSE1L and hsa_circ_0060762. Hsa_circ_0060762 and CSE1L thus represent novel potential peripheral blood biomarkers and therapeutic targets for ALS.

Brainstem-cortex disconnection in amyotrophic lateral sclerosis: bulbar impairment, genotype associations, asymptomatic changes and biomarker opportunities

BACKGROUND

Bulbar dysfunction is a cardinal feature of ALS with important quality of life and management implications. The objective of this study is the longitudinal evaluation of a large panel imaging metrics pertaining to bulbar dysfunction, encompassing cortical measures, structural and functional cortico-medullary connectivity indices and brainstem metrics.

METHODS

A standardised, multimodal imaging protocol was implemented with clinical and genetic profiling to systematically appraise the biomarker potential of specific metrics. A total of 198 patients with ALS and 108 healthy controls were included.

RESULTS

Longitudinal analyses revealed progressive structural and functional disconnection between the motor cortex and the brainstem over time. Cortical thickness reduction was an early feature on cross-sectional analyses with limited further progression on longitudinal follow-up. Receiver operating characteristic analyses of the panel of MR metrics confirmed the discriminatory potential of bulbar imaging measures between patients and controls and area-under-the-curve values increased significantly on longitudinal follow-up. C9orf72 carriers exhibited lower brainstem volumes, lower cortico-medullary structural connectivity and faster cortical thinning. Sporadic patients without bulbar symptoms, already exhibit significant brainstem and cortico-medullary connectivity alterations.

DISCUSSION

Our results indicate that ALS is associated with multi-level integrity change from cortex to brainstem. The demonstration of significant corticobulbar alterations in patients without bulbar symptoms confirms considerable presymptomatic disease burden in sporadic ALS. The systematic assessment of radiological measures in a single-centre academic study helps to appraise the diagnostic and monitoring utility of specific measures for future clinical and clinical trial applications.

Extracellular Vesicles as Potential Biomarkers in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is described as a fatal and rapidly progressive neurodegenerative disorder caused by the degeneration of upper motor neurons in the primary motor cortex and lower motor neurons of the brainstem and spinal cord. Due to ALS's slowly progressive characteristic, which is often accompanied by other neurological comorbidities, its diagnosis remains challenging. Perturbations in vesicle-mediated transport and autophagy as well as cell-autonomous disease initiation in glutamatergic neurons have been revealed in ALS. The use of extracellular vesicles (EVs) may be key in accessing pathologically relevant tissues for ALS, as EVs can cross the blood-brain barrier and be isolated from the blood. The number and content of EVs may provide indications of the disease pathogenesis, its stage, and prognosis. In this review, we collected a recent study aiming at the identification of EVs as a biomarker of ALS with respect to the size, quantity, and content of EVs in the biological fluids of patients compared to controls.

miRNA extracted from extracellular vesicles is a robust biomarker of amyotrophic lateral sclerosis

BACKGROUND AND OBJECTIVES

We examined miRNA biomarkers for ALS extracted from extracellular vesicles in blood samples using a large and diverse patient and control population. Different blood collection and storage protocols by different investigators could impact repeatability of miRNA analysis. We tested the hypotheses that miRNA extracted from extracellular vesicles using immunoaffinity purification techniques are robust and repeatable across investigators, laboratories and in a broad ALS population.

METHODS

De-identified patient blood plasma samples obtained from the U.S. National ALS Biorepository were compared with plasma from non-ALS controls. Extracellular vesicles were extracted and isolated using L1CAM immunoaffinity purification. Total RNA was extracted, and miRNA quantified using qPCR following careful quality control measures. Gene fold expressions of eight miRNAs were compared using a Mann-Whitney two-tailed test.

RESULTS

One hundred blinded, blood plasma samples were analyzed. Thirty-five men and 15 women with ALS were compared with controls consisting of 30 men and 20 women. None of the ALS patient cohort reported family members with ALS suggesting sporadic ALS. Five of the eight biomarkers previously published were found to significantly discriminate ALS patient samples from control samples.

DISCUSSION

The methods used in this study provide a repeatable measure of miRNA biomarkers that statistically differentiate ALS patient samples from control samples. The broad inclusion criteria for both the ALS patient cohort and controls along with the collection of blood samples by different investigators suggest that these methods are robust and represent good candidates for further research and development aimed at clinical application.

Neuroimaging in hereditary spastic paraplegias: from qualitative cues to precision biomarkers

INTRODUCTION

: Hereditary spastic paraplegias (HSP) include a clinically and genetically heterogeneous group of conditions. Novel imaging modalities have been increasingly applied to HSP cohorts which helps to quantitatively evaluate the integrity of specific anatomical structures and develop monitoring markers for both clinical care and future clinical trials.

AREAS COVERED

: Advances in HSP imaging are systematically reviewed with a focus on cohort sizes, imaging modalities, study design, clinical correlates, methodological approaches, and key findings.

EXPERT OPINION

: A wide range of imaging techniques have been recently applied to HSP cohorts. Common shortcomings of existing studies include the evaluation of genetically unconfirmed or admixed cohorts, limited sample sizes, unimodal imaging approaches, lack of postmortem validation, and a limited clinical battery, often exclusively focusing on motor aspects of the condition. A number of innovative methodological approaches have also be identified, such as robust longitudinal study designs, the implementation of multimodal imaging protocols, complementary cognitive assessments, and the comparison of HSP cohorts to MND cohorts. Collaborative multicentre initiatives may overcome sample limitations, and comprehensive clinical profiling with motor, extrapyramidal, cerebellar, and neuropsychological assessments would permit systematic clinico-radiological correlations. Academic achievements in HSP imaging have the potential to be developed into viable clinical applications to expedite the diagnosis and monitor disease progression.

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.

Pre-symptomatic radiological changes in frontotemporal dementia: propagation characteristics, predictive value and implications for clinical trials

Computational imaging and quantitative biomarkers offer invaluable insights in the pre-symptomatic phase of neurodegenerative conditions several years before clinical manifestation. In recent years, there has been a focused effort to characterize pre-symptomatic cerebral changes in familial frontotemporal dementias using computational imaging. Accordingly, a systematic literature review was conducted of original articles investigating pre-symptomatic imaging changes in frontotemporal dementia focusing on study design, imaging modalities, data interpretation, control cohorts and key findings. The review is limited to the most common genotypes: chromosome 9 open reading frame 72 (C9orf72), progranulin (GRN), or microtubule-associated protein tau (MAPT) genotypes. Sixty-eight studies were identified with a median sample size of 15 (3-141) per genotype. Only a minority of studies were longitudinal (28%; 19/68) with a median follow-up of 2 (1-8) years. MRI (97%; 66/68) was the most common imaging modality, and primarily grey matter analyses were conducted (75%; 19/68). Some studies used multimodal analyses 44% (30/68). Genotype-associated imaging signatures are presented, innovative study designs are highlighted, common methodological shortcomings are discussed and lessons for future studies are outlined. Emerging academic observations have potential clinical implications for expediting the diagnosis, tracking disease progression and optimising the timing of pharmaceutical trials.

Mapping cortical disease-burden at individual-level in frontotemporal dementia: implications for clinical care and pharmacological trials

Imaging studies of FTD typically present group-level statistics between large cohorts of genetically, molecularly or clinically stratified patients. Group-level statistics are indispensable to appraise unifying radiological traits and describe genotype-associated signatures in academic studies. However, in a clinical setting, the primary objective is the meaningful interpretation of imaging data from individual patients to assist diagnostic classification, inform prognosis, and enable the assessment of progressive changes compared to baseline scans. In an attempt to address the pragmatic demands of clinical imaging, a prospective computational neuroimaging study was undertaken in a cohort of patients across the spectrum of FTD phenotypes. Cortical changes were evaluated in a dual pipeline, using standard cortical thickness analyses and an individualised, z-score based approach to characterise subject-level disease burden. Phenotype-specific patterns of cortical atrophy were readily detected with both methodological approaches. Consistent with their clinical profiles, patients with bvFTD exhibited orbitofrontal, cingulate and dorsolateral prefrontal atrophy. Patients with ALS-FTD displayed precentral gyrus involvement, nfvPPA patients showed widespread cortical degeneration including insular and opercular regions and patients with svPPA exhibited relatively focal anterior temporal lobe atrophy. Cortical atrophy patterns were reliably detected in single individuals, and these maps were consistent with the clinical categorisation. Our preliminary data indicate that standard T1-weighted structural data from single patients may be utilised to generate maps of cortical atrophy. While the computational interpretation of single scans is challenging, it offers unrivalled insights compared to visual inspection. The quantitative evaluation of individual MRI data may aid diagnostic classification, clinical decision making, and assessing longitudinal changes.

Clusters of anatomical disease-burden patterns in ALS: a data-driven approach confirms radiological subtypes

Amyotrophic lateral sclerosis (ALS) is associated with considerable clinical heterogeneity spanning from diverse disability profiles, differences in UMN/LMN involvement, divergent progression rates, to variability in frontotemporal dysfunction. A multitude of classification frameworks and staging systems have been proposed based on clinical and neuropsychological characteristics, but disease subtypes are seldom defined based on anatomical patterns of disease burden without a prior clinical stratification. A prospective research study was conducted with a uniform imaging protocol to ascertain disease subtypes based on preferential cerebral involvement. Fifteen brain regions were systematically evaluated in each participant based on a comprehensive panel of cortical, subcortical and white matter integrity metrics. Using min–max scaled composite regional integrity scores, a two-step cluster analysis was conducted. Two radiological clusters were identified; 35.5% of patients belonging to ‘Cluster 1’ and 64.5% of patients segregating to ‘Cluster 2’. Subjects in Cluster 1 exhibited marked frontotemporal change. Predictor ranking revealed the following hierarchy of anatomical regions in decreasing importance: superior lateral temporal, inferior frontal, superior frontal, parietal, limbic, mesial inferior temporal, peri-Sylvian, subcortical, long association fibres, commissural, occipital, ‘sensory’, ‘motor’, cerebellum, and brainstem. While the majority of imaging studies first stratify patients based on clinical criteria or genetic profiles to describe phenotype- and genotype-associated imaging signatures, a data-driven approach may identify distinct disease subtypes without a priori patient categorisation. Our study illustrates that large radiology datasets may be potentially utilised to uncover disease subtypes associated with unique genetic, clinical or prognostic profiles.

The changing landscape of neuroimaging in frontotemporal lobar degeneration: from group-level observations to single-subject data interpretation

INTRODUCTION

While the imaging signatures of frontotemporal lobar degeneration (FTLD) phenotypes and genotypes are well-characterised based on group-level descriptive analyses, the meaningful interpretation of single MRI scans remains challenging. Single-subject MRI classification frameworks rely on complex computational models and large training datasets to categorise individual patients into diagnostic subgroups based on distinguishing imaging features. Reliable individual subject data interpretation is hugely important in the clinical setting to expedite the diagnosis and classify individuals into relevant prognostic categories.

AREAS COVERED

This article reviews (1) the neuroimaging studies that propose single-subject MRI classification strategies in symptomatic and pre-symptomatic FTLD, (2) potential practical implications and (3) the limitations of current single-subject data interpretation models.

EXPERT OPINION

Classification studies in FTLD have demonstrated the feasibility of categorising individual subjects into diagnostic groups based on multiparametric imaging data. Preliminary data indicate that pre-symptomatic FTLD mutation carriers may also be reliably distinguished from controls. Despite momentous advances in the field, significant further improvements are needed before these models can be developed into viable clinical applications.

White matter microstructure alterations in frontotemporal dementia: Phenotype-associated signatures and single-subject interpretation

BACKGROUND

Frontotemporal dementias (FTD) include a genetically heterogeneous group of conditions with distinctive molecular, radiological and clinical features. The majority of radiology studies in FTD compare FTD subgroups to healthy controls to describe phenotype- or genotype-associated imaging signatures. While the characterization of group-specific imaging traits is academically important, the priority of clinical imaging is the meaningful interpretation of individual datasets.

METHODS

To demonstrate the feasibility of single-subject magnetic resonance imaging (MRI) interpretation, we have evaluated the white matter profile of 60 patients across the clinical spectrum of FTD. A z-score-based approach was implemented, where the diffusivity metrics of individual patients were appraised with reference to demographically matched healthy controls. Fifty white matter tracts were systematically evaluated in each subject with reference to normative data.

RESULTS

The z-score-based approach successfully detected white matter pathology in single subjects, and group-level inferences were analogous to the outputs of standard track-based spatial statistics.

CONCLUSIONS

Our findings suggest that it is possible to meaningfully evaluate the diffusion profile of single FTD patients if large normative datasets are available. In contrast to the visual review of FLAIR and T2-weighted images, computational imaging offers objective, quantitative insights into white matter integrity changes even at single-subject level.

Phenotypic categorisation of individual subjects with motor neuron disease based on radiological disease burden patterns: A machine-learning approach

Motor neuron disease is an umbrella term encompassing a multitude of clinically heterogeneous phenotypes. The early and accurate categorisation of patients is hugely important, as MND phenotypes are associated with markedly different prognoses, progression rates, care needs and benefit from divergent management strategies. The categorisation of patients shortly after symptom onset is challenging, and often lengthy clinical monitoring is needed to assign patients to the appropriate phenotypic subgroup. In this study, a multi-class machine-learning strategy was implemented to classify 300 patients based on their radiological profile into diagnostic labels along the UMN-LMN spectrum. A comprehensive panel of cortical thickness measures, subcortical grey matter variables, and white matter integrity metrics were evaluated in a multilayer perceptron (MLP) model. Additional exploratory analyses were also carried out using discriminant function analyses (DFA). Excellent classification accuracy was achieved for amyotrophic lateral sclerosis in the testing cohort (93.7%) using the MLP model, but poor diagnostic accuracy was detected for primary lateral sclerosis (43.8%) and poliomyelitis survivors (60%). Feature importance analyses highlighted the relevance of white matter diffusivity metrics and the evaluation of cerebellar indices, cingulate measures and thalamic radiation variables to discriminate MND phenotypes. Our data suggest that radiological data from single patients may be meaningfully interpreted if large training data sets are available and the provision of diagnostic probability outcomes may be clinically useful in patients with short symptom duration. The computational interpretation of multimodal radiology datasets herald viable diagnostic, prognostic and clinical trial applications.

Neuroinflammation in Amyotrophic Lateral Sclerosis and Frontotemporal Dementia and the Interest of Induced Pluripotent Stem Cells to Study Immune Cells Interactions With Neurons

Inflammation is a shared hallmark between amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). For long, studies were conducted on tissues of post-mortem patients and neuroinflammation was thought to be only bystander result of the disease with the immune system reacting to dying neurons. In the last two decades, thanks to improving technologies, the identification of causal genes and the development of new tools and models, the involvement of inflammation has emerged as a potential driver of the diseases and evolved as a new area of intense research. In this review, we present the current knowledge about neuroinflammation in ALS, ALS-FTD, and FTD patients and animal models and we discuss reasons of failures linked to therapeutic trials with immunomodulator drugs. Then we present the induced pluripotent stem cell (iPSC) technology and its interest as a new tool to have a better immunopathological comprehension of both diseases in a human context. The iPSC technology giving the unique opportunity to study cells across differentiation and maturation times, brings the hope to shed light on the different mechanisms linking neurodegeneration and activation of the immune system. Protocols available to differentiate iPSC into different immune cell types are presented. Finally, we discuss the interest in studying monocultures of iPS-derived immune cells, co-cultures with neurons and 3D cultures with different cell types, as more integrated cellular approaches. The hope is that the future work with human iPS-derived cells helps not only to identify disease-specific defects in the different cell types but also to decipher the synergistic effects between neurons and immune cells. These new cellular tools could help to find new therapeutic approaches for all patients with ALS, ALS-FTD, and FTD.

Pathological neural networks and artificial neural networks in ALS: diagnostic classification based on pathognomonic neuroimaging features

The description of group-level, genotype- and phenotype-associated imaging traits is academically important, but the practical demands of clinical neurology centre on the accurate classification of individual patients into clinically relevant diagnostic, prognostic and phenotypic categories. Similarly, pharmaceutical trials require the precision stratification of participants based on quantitative measures. A single-centre study was conducted with a uniform imaging protocol to test the accuracy of an artificial neural network classification scheme on a cohort of 378 participants composed of patients with ALS, healthy subjects and disease controls. A comprehensive panel of cerebral volumetric measures, cortical indices and white matter integrity values were systematically retrieved from each participant and fed into a multilayer perceptron model. Data were partitioned into training and testing and receiver-operating characteristic curves were generated for the three study-groups. Area under the curve values were 0.930 for patients with ALS, 0.958 for disease controls, and 0.931 for healthy controls relying on all input imaging variables. The ranking of variables by classification importance revealed that white matter metrics were far more relevant than grey matter indices to classify single subjects. The model was further tested in a subset of patients scanned within 6 weeks of their diagnosis and an AUC of 0.915 was achieved. Our study indicates that individual subjects may be accurately categorised into diagnostic groups in an observer-independent classification framework based on multiparametric, spatially registered radiology data. The development and validation of viable computational models to interpret single imaging datasets are urgently required for a variety of clinical and clinical trial applications.

Evaluation and categorisation of individual patients based on white matter profiles: Single-patient diffusion data interpretation in neurodegeneration

The majority of radiology studies in neurodegenerative conditions infer group-level imaging traits from group comparisons. While this strategy is helpful to define phenotype-specific imaging signatures for academic use, the meaningful interpretation of single scans of individual subjects is more important in everyday clinical practice. Accordingly, we present a computational method to evaluate individual subject diffusion tensor data to highlight white matter integrity alterations. Fifty white matter tracts were quantitatively evaluated in 132 patients with amyotrophic lateral sclerosis (ALS) with respect to normative values from 100 healthy subjects. Fractional anisotropy and radial diffusivity alterations were assessed individually in each patient. The approach was validated against standard tract-based spatial statistics and further scrutinised by the assessment of 78 additional data sets with a blinded diagnosis. Our z-score-based approach readily detected white matter degeneration in individual ALS patients and helped to categorise single subjects with a 'blinded diagnosis' as likely 'ALS' or 'control'. The group-level inferences from the z-score-based approach were analogous to the standard TBSS output maps. The benefit of the z-score-based strategy is that it enables the interpretation of single DTI datasets as well as the comparison of study groups. Outputs can be summarised either visually by highlighting the affected tracts, or, listing the affected tracts in a text file with reference to normative data, making it particularly useful for clinical applications. While individual diffusion data cannot be visually appraised, our approach provides a viable framework for single-subject imaging data interpretation.

Segmental involvement of the corpus callosum in C9orf72-associated ALS: a tract of interest-based DTI study

Background:

C9orf72 hexanucleotide repeat expansions are associated with widespread cerebral alterations, including white matter alterations. However, there is lack of information on changes in commissure fibres. Diffusion tensor imaging (DTI) can identify amyotrophic lateral sclerosis (ALS)-associated patterns of regional brain alterations at the group level. The objective of this study was to investigate the structural connectivity of the corpus callosum (CC) in ALS patients with C9orf72 expansions.

Methods:

DTI-based white matter mapping was performed by a hypothesis-guided tractwise analysis of fractional anisotropy (FA) maps for 25 ALS patients with C9orf72 expansion versus 25 matched healthy controls. Furthermore, a comparison with a patient control group of 25 sporadic ALS patients was performed. DTI-based tracts that originate from callosal sub-areas I to V were identified and correlated with clinical data.

Results:

The analysis of white matter integrity demonstrated regional FA reductions for tracts of the callosal areas II and III for ALS patients with C9orf72 expansions while FA reductions in sporadic ALS patients were observed only for tracts of the callosal area III; these reductions were correlated with clinical parameters.

Conclusion:

The tract-of-interest-based analysis showed a microstructural callosal involvement pattern in C9orf72-associated ALS that included the motor segment III together with frontal callosal connections, as an imaging signature of the C9orf72-associated overlap of motor neuron disease and frontotemporal pathology.

Eye movement alterations in presymptomatic C9orf72 expansion gene carriers

Objective

The clinical manifestation of amyotrophic lateral sclerosis (ALS) is characterized by motor neuron degeneration, whereas frontotemporal dementia (FTD) patients show alterations of behavior and cognition. Both share repeat expansions in C9orf72 as the most prevalent genetic cause. Before disease-defining symptoms onset, structural and functional changes at cortical level may emerge in C9orf72 carriers. Here, we characterized oculomotor parameters and their association to neuropsychological domains in apparently asymptomatic individuals with mutations in ALS/FTD genes.

Patients and methods

Forty-eight carriers of ALS genes, without any clinical symptoms underwent video-oculographic examination, including 22 subjects with C9orf72 mutation, 17 with SOD1, and 9 with other ALS associated gene mutations (n = 3 KIF5A; n = 3 FUS/FUS + TBK1; n = 1 NEK1; n = 1 SETX; n = 1 TDP43). A total of 17 subjects underwent a follow-up measurement. Data were compared to 54 age- and gender-matched healthy controls. Additionally, mutation carriers performed a neuropsychological assessment.

Results

In comparison to controls, the presymptomatic subjects performed significantly worse in executive oculomotor tasks such as the ability to perform correct anti-saccades. A gene mutation subgroup analysis showed that dysfunctions in C9orf72 carriers were much more pronounced than in SOD1 carriers. The anti-saccade error rate of ALS mutation carriers was associated with cognitive deficits: this correlation was increased in subjects with C9orf72 mutation, whereas SOD1 carriers showed no associations.

Conclusion

In C9orf72 carriers, executive eye movement dysfunctions, especially the increased anti-saccade error rate, were associated with cognitive impairment and unrelated to time. These oculomotor impairments are in support of developmental deficits in these mutations, especially in prefrontal areas.

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.