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Abstract Objective The resting‐state functional connectome has not been extensively investigated in amyotrophic lateral sclerosis (ALS) spectrum disease, in particular in relationship with patients' genetic status. Methods Here we studied the network‐to‐network connectivity of 19 ALS patients carrying the C9orf72 hexanucleotide repeat expansion (C9orf72+), 19 ALS patients not affected by C9orf72 mutation (C9orf72−), and 19 ALS‐mimic patients (ALSm) well‐matched for demographic and clinical variables. Results When compared with ALSm, we observed greater connectivity of the default mode and frontoparietal networks with the visual network for C9orf72+ patients (P = 0.001). Moreover, the whole‐connectome showed greater node degree (P

Abstract Background Systemic inflammation has been proposed as a relevant mechanism in amyotrophic lateral sclerosis (ALS). Still, comprehensive data on ALS patients' innate and adaptive immune responses and their effect on the clinical phenotype are lacking. Here, we investigate systemic immunity in a population‐based ALS cohort using readily available hematological indexes. Methods We collected clinical data and the complete blood count (CBC) at diagnosis in ALS patients from the Piemonte and Valle d'Aosta Register for ALS (PARALS) from 2007 to 2019. Leukocytes populations, neutrophil‐to‐lymphocyte ratio (NLR), platelet‐to‐lymphocyte ratio (PLR), systemic‐immune‐inflammation index (SII), and lymphocyte‐to‐monocyte ratio (LMR) were derived from CBC. All variables were analyzed for association with clinical features in the entire cohort and then in sex‐ and age‐based subgroups. Results Neutrophils (P = 0.001) and markers of increased innate immunity (NLR, P = 0.008 and SII, P = 0.006) were associated with a faster disease progression. Similarly, elevated innate immunity correlated with worse pulmonary function and shorter survival. The prognosis in women also correlated with low lymphocytes (P = 0.045) and a decreased LMR (P = 0.013). ALS patients with cognitive impairment exhibited lower monocytes (P = 0.0415). Conclusions and Relevance The dysregulation of the systemic immune system plays a multifaceted role in ALS. More specifically, an elevated innate immune response is associated with faster progression and reduced survival. Conversely, ALS patients with cognitive impairment showed a reduction in monocyte count. Additionally, immune response varied according to sex and age, thus suggesting that involved immune pathways are patient specific. Further studies will help translate those findings into clinical practice or targeted treatments.

Abstract Background Given the large genetic heterogeneity in amyotrophic lateral sclerosis (ALS), it seems likely that genetic subgroups may benefit differently from treatment. An exploratory meta-analysis identified that patients homozygous for the C-allele at SNP rs12608932, a single nucleotide polymorphism in the gene UNC13A, had a statistically significant survival benefit when treated with lithium carbonate. We aim to confirm the efficacy of lithium carbonate on the time to death or respiratory insufficiency in patients with ALS homozygous for the C-allele at SNP rs12608932 in UNC13A. Methods A randomized, group-sequential, event-driven, double-blind, placebo-controlled trial will be conducted in 15 sites across Europe and Australia. Patients will be genotyped for UNC13A; those homozygous for the C-allele at SNP rs12608932 will be eligible. Patients must have a diagnosis of ALS according to the revised El Escorial criteria, and a TRICALS risk-profile score between −6.0 and −2.0. An expected number of 1200 patients will be screened in order to enroll a target sample size of 171 patients. Patients will be randomly allocated in a 2:1 ratio to lithium carbonate or matching placebo, and treated for a maximum duration of 24 months. The primary endpoint is the time to death or respiratory insufficiency, whichever occurs first. Key secondary endpoints include functional decline, respiratory function, quality of life, tolerability, and safety. An interim analysis for futility and efficacy will be conducted after the occurrence of 41 events. Discussion Lithium carbonate has been proven to be safe and well-tolerated in patients with ALS. Given the favorable safety profile, the potential benefits are considered to outweigh the burden and risks associated with study participation. This study may provide conclusive evidence about the life-prolonging potential of lithium carbonate in a genetic ALS subgroup. Trial registration EudraCT number 2020-000579-19 . Registered on 29 March 2021.

Respiratory failure assessment is among the most debatable research topics in amyotrophic lateral sclerosis (ALS) clinical research due to the wide heterogeneity of its presentation. Among the different pulmonary function tests (PFTs), maximal voluntary ventilation (MVV) has shown potential utility as a diagnostic and monitoring marker, able to capture early respiratory modification in neuromuscular disorders. In the present study, we explored calculated MVV (cMVV) as a prognostic biomarker in a center-based, retrospective ALS population belonging to the Piemonte and Valle d’Aosta registry for ALS (PARALS). A Spearman’s correlation analysis with clinical data and PFTs showed a good correlation of cMVV with forced vital capacity (FVC) and a moderate correlation with some other features such as bulbar involvement, ALSFRS-R total score, blood oxygen (pO2), carbonate (HCO3−), and base excess (BE), measured with arterial blood gas analysis. Both the Cox proportional hazard models for survival and the time to non-invasive ventilation (NIV) measurement highlighted that cMVV at diagnosis (considering cMVV(40) ≥ 80) is able to stratify patients across different risk levels for death/tracheostomy and NIV indication, especially considering patients with FVC% ≥ 80. In conclusion, cMVV is a useful marker of early respiratory failure in ALS, and is easily derivable from standard PFTs, especially in asymptomatic ALS patients with normal FVC measures.

Abstract Amyotrophic lateral sclerosis (ALS) is a highly complex and heterogeneous neurodegenerative disease that affects motor neurons. Since life expectancy is relatively low, it is essential to promptly understand the course of the disease to better target the patient’s treatment. Predictive models for disease progression are thus of great interest. One of the most extensive and well-studied open-access data resources for ALS is the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) repository. In 2015, the DREAM-Phil Bowen ALS Prediction Prize4Life Challenge was held on PRO-ACT data, where competitors were asked to develop machine learning algorithms to predict disease progression measured through the slope of the ALSFRS score between 3 and 12 months. However, although it has already been successfully applied in several studies on ALS patients, to the best of our knowledge deep learning approaches still remain unexplored on the ALSFRS slope prediction in PRO-ACT cohort. Here, we investigate how deep learning models perform in predicting ALS progression using the PRO-ACT data. We developed three models based on different architectures that showed comparable or better performance with respect to the state-of-the-art models, thus representing a valid alternative to predict ALS disease progression.

A wide range of neurological manifestations have been reported during the COVID-19 pandemic, including a variety of Parkinsonian cases. The association of numerous viruses with the development of persistent or transient Parkinsonism has been well-documented. We observed a patient who developed a levodopa non-responsive Parkinsonian syndrome with dysautonomia during a prolonged stay at home for COVID-19. Although the temporal proximity of the emerging Parkinsonian features with a COVID-19 diagnosis suggested a causal relationship, we considered the possibility of a coincidental occurrence of multiple system atrophy. We discuss the patient's clinical features in relation to the established clinical diagnostic criteria and review differential diagnoses as well as the role of SARS-CoV-2 infection.

Humans are thought to be more susceptible to neurodegeneration than equivalently-aged primates. It is not known whether this vulnerability is specific to anatomically-modern humans or shared with other hominids. The contribution of introgressed Neanderthal DNA to neurodegenerative disorders remains uncertain. It is also unclear how common variants associated with neurodegenerative disease risk are maintained by natural selection in the population despite their deleterious effects. In this study, we aimed to quantify the genome-wide contribution of Neanderthal introgression and positive selection to the heritability of complex neurodegenerative disorders to address these questions.We used stratified-linkage disequilibrium score regression to investigate the relationship between five SNP-based signatures of natural selection, reflecting different timepoints of evolution, and genome-wide associated variants of the three most prevalent neurodegenerative disorders: Alzheimer's disease, amyotrophic lateral sclerosis and Parkinson's disease.We found no evidence for enrichment of positively-selected SNPs in the heritability of Alzheimer's disease, amyotrophic lateral sclerosis and Parkinson's disease, suggesting that common deleterious disease variants are unlikely to be maintained by positive selection. There was no enrichment of Neanderthal introgression in the SNP-heritability of these disorders, suggesting that Neanderthal admixture is unlikely to have contributed to disease risk.These findings provide insight into the origins of neurodegenerative disorders within the evolution of Homo sapiens and addresses a long-standing debate, showing that Neanderthal admixture is unlikely to have contributed to common genetic risk of neurodegeneration in anatomically-modern humans.

Respiratory failure is the most common cause of death in patients with amyotrophic lateral sclerosis (ALS) and occurs with great variability among patients according to different phenotypic features. Early predictors of respiratory failure in ALS are important to start non-invasive ventilation (NIV). Venous serum chloride values correlate with carbonate (HCO3-) blood levels and reflect metabolic compensation of respiratory acidosis. Despite its wide availability and low cost, few data on serum chloride as a prognostic marker exist in ALS literature. In the present study, we evaluated serum chloride values at diagnosis as prognostic biomarkers for overall survival and NIV adaptation in a retrospective center-based cohort of ALS patients. We collected all ALS patients with serum chloride assessment at diagnosis, identified through the Piemonte and Valle d’Aosta Register for ALS, evaluating the correlations among serum chloride, clinical features, and other serum biomarkers. Thereafter, time-to-event analysis was modeled to predict overall survival and NIV start. We found a significant correlation between serum chloride and inflammatory status markers, serum sodium, forced vital capacity (FVC), ALS functional rating scale-revised (ALSFRS-R) item 10 and 11, age at diagnosis, and weight loss. Time-to-event analysis confirmed both in univariate analysis and after multiple confounders’ adjustment that serum chloride value at diagnosis significantly influenced survival and time to NIV start. According to our analysis, based on a large ALS cohort, we found that serum chloride analyzed at diagnosis is a low-cost marker of impending respiratory decompensation. In our opinion, it should be added among the serum prognostic biomarkers that are able to stratify patients into different prognostic categories even when performed in the early phases of the disease.

Abstract The aetiology of Amyotrophic Lateral Sclerosis (ALS) is still poorly understood. The discovery of genetic forms of ALS pointed out the mechanisms underlying this pathology, but also showed how complex these mechanisms are. Excitotoxicity is strongly suspected to play a role in ALS pathogenesis. Excitotoxicity is defined as neuron damage due to excessive intake of calcium ions (Ca2+) by the cell. This study aims to find a relationship between the proteins coded by the most relevant genes associated with ALS and intracellular Ca2+ accumulation. In detail, the profile of eight proteins (TDP-43, C9orf72, p62/sequestosome-1, matrin-3, VCP, FUS, SOD1 and profilin-1), was analysed in three different cell types induced to raise their cytoplasmic amount of Ca2+. Intracellular Ca2+ accumulation causes a decrease in the levels of TDP-43, C9orf72, matrin3, VCP, FUS, SOD1 and profilin-1 and an increase in those of p62/sequestosome-1. These events are associated with the proteolytic action of two proteases, calpains and caspases, as well as with the activation of autophagy. Interestingly, Ca2+ appears to both favour and hinder autophagy. Understanding how and why calpain-mediated proteolysis and autophagy, which are physiological processes, become pathological may elucidate the mechanisms responsible for ALS and help discover new therapeutic targets.

Objective: C9orf72 mutation carriers with different neurological phenotypes show cortical and subcortical atrophy in multiple different brain regions, even in pre-symptomatic phases. Despite there is a substantial amount of knowledge, small sample sizes, clinical heterogeneity, as well as different choices of image analysis may hide anatomical abnormalities that are unique to amyotrophic lateral sclerosis (ALS) patients with this genotype or that are indicative of the C9orf72-specific trait overlain in fronto-temporal dementia patients. Methods: Brain structural and resting state functional magnetic imaging was obtained in 24 C9orf72 positive (ALSC9+) ALS patients paired for burden disease with 24 C9orf72 negative (ALSC9-) ALS patients. A comprehensive structural evaluation of cortical thickness and subcortical volumes between ALSC9+ and ALSC9- patients was performed while a region of interest (ROI)-ROI analysis of functional connectivity was implemented to assess functional alterations among abnormal cortical and subcortical regions. Results were corrected for multiple comparisons. Results: Compared to ALSC9- patients, ALSC9+ patients exhibited extensive disease-specific patterns of thalamo-cortico-striatal atrophy, supported by functional alterations of the identified abnormal regions. Cortical thinning was most pronounced in posterior areas and extended to frontal regions. Bilateral atrophy of the mediodorsal and pulvinar nuclei was observed, emphasizing a focal rather than global thalamus atrophy. Volume loss in a large portion of bilateral caudate and left putamen was reported. The marked reduction of functional connectivity observed between the left posterior thalamus and almost all the atrophic cortical regions support the central role of the thalamus in the pathogenic mechanism of C9orf72-mediated disease. Conclusions: These findings constitute a coherent and robust picture of ALS patients with C9orf72-mediated disease, unveiling a specific structural and functional characterization of thalamo-cortico-striatal circuit alteration. Our study introduces new evidence in the characterization of the pathogenic mechanisms of C9orf72 mutation.

Abstract Background Amyotrophic lateral sclerosis (ALS) is a multifactorial, multisystem motor neuron disease for which currently there is no effective treatment. There is an urgent need to identify biomarkers to tackle the disease’s complexity and help in early diagnosis, prognosis, and therapy. Extracellular vesicles (EVs) are nanostructures released by any cell type into body fluids. Their biophysical and biochemical characteristics vary with the parent cell’s physiological and pathological state and make them an attractive source of multidimensional data for patient classification and stratification. Methods We analyzed plasma-derived EVs of ALS patients (n = 106) and controls (n = 96), and SOD1G93A and TDP-43Q331K mouse models of ALS. We purified plasma EVs by nickel-based isolation, characterized their EV size distribution and morphology respectively by nanotracking analysis and transmission electron microscopy, and analyzed EV markers and protein cargos by Western blot and proteomics. We used machine learning techniques to predict diagnosis and prognosis. Results Our procedure resulted in high-yield isolation of intact and polydisperse plasma EVs, with minimal lipoprotein contamination. EVs in the plasma of ALS patients and the two mouse models of ALS had a distinctive size distribution and lower HSP90 levels compared to the controls. In terms of disease progression, the levels of cyclophilin A with the EV size distribution distinguished fast and slow disease progressors, a possibly new means for patient stratification. Immuno-electron microscopy also suggested that phosphorylated TDP-43 is not an intravesicular cargo of plasma-derived EVs. Conclusions Our analysis unmasked features in plasma EVs of ALS patients with potential straightforward clinical application. We conceived an innovative mathematical model based on machine learning which, by integrating EV size distribution data with protein cargoes, gave very high prediction rates for disease diagnosis and prognosis.

BackgroundAmyotrophic lateral sclerosis (ALS) is a chronic neurodegenerative rare disease that affects motor neurons in the brain, brainstem, and spinal cord, resulting in progressive weakness and atrophy of voluntary skeletal muscles. Although much has been achieved in understanding the disease pathogenesis, treatment options are limited, and in Europe, riluzole is the only approved drug. Recently, some other drugs showed minor effects.MethodsThe TUDCA-ALS trial is a phase III, multicenter, randomized, double-blind, placebo-controlled, parallel-group clinical trial. The study aims to enroll 320 patients in 25 centers across seven countries in Europe. Enrolled patients are randomized to one of two treatment arms: TUDCA or identical placebo by oral route. The study measures disease progression during the treatment period and compares it to natural progression during a no-treatment run-in phase. Clinical data and specific biomarkers are measured during the trial. The study is coordinated by a consortium composed of leading European ALS centers.ConclusionThis trial is aimed to determine whether TUDCA has a disease-modifying activity in ALS. Demonstration of TUDCA efficacy, combined with the validation of new biomarkers, could advance ALS patient care.Clinical trial registrationClinicalTrials.gov, identifier: NCT03800524.

ObjectiveMutations in the TARDBP gene are a rare cause of genetic motor neuron disease (MND). Morphologic MRI characteristics of MND patients carrying this mutation have been poorly described. Our objective was to investigate distinctive clinical and MRI features of a relatively large sample of MND patients carrying TARDBP mutations.MethodsEleven MND patients carrying a TARDBP mutation were enrolled. Eleven patients with sporadic MND (sMND) and no genetic mutations were also selected and individually matched by age, sex, clinical presentation and disease severity, along with 22 healthy controls. Patients underwent clinical and cognitive evaluations, as well as 3D T1-weighted and diffusion tensor (DT) MRI on a 3 Tesla scanner. Gray matter (GM) atrophy was first investigated at a whole-brain level using voxel-based morphometry (VBM). GM volumes and DT MRI metrics of the main white matter (WM) tracts were also obtained. Clinical, cognitive and MRI features were compared between groups.ResultsMND with TARDBP mutations was associated with all possible clinical phenotypes, including isolated upper/lower motor neuron involvement, with no predilection for bulbar or limb involvement at presentation. Greater impairment at naming tasks was found in TARDBP mutation carriers compared with sMND. VBM analysis showed significant atrophy of the right lateral parietal cortex in TARDBP patients, compared with controls. A distinctive reduction of GM volumes was found in the left precuneus and right angular gyrus of TARDBP patients compared to controls. WM microstructural damage of the corticospinal tract (CST) and inferior longitudinal fasciculi (ILF) was found in both sMND and TARDBP patients, compared with controls, although decreased fractional anisotropy of the right CST and increased axial diffusivity of the left ILF (p = 0.017) was detected only in TARDBP mutation carriers.ConclusionsTARDBP patients showed a distinctive parietal pattern of cortical atrophy and greater damage of motor and extra-motor WM tracts compared with controls, which sMND patients matched for disease severity and clinical presentation were lacking. Our findings suggest that TDP-43 pathology due to TARDBP mutations may cause deeper morphologic alterations in both GM and WM.

Abstract Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease associated with motor neuron degeneration, muscle atrophy and paralysis. To date, multiple panels of biomarkers have been described in ALS patients and murine models. Nevertheless, none of them has sufficient specificity and thus the molecular signature for ALS prognosis and progression remains to be elucidated. Here we overcome this limitation through a longitudinal study, analyzing serum levels of circulating miRNAs, stable molecules that are recently used as promising biomarkers for many types of human disorders, in ALS patients during the progression of the pathology. We performed next-generation sequencing (NGS) analysis and absolute RT quantification of serum samples of ALS patients and healthy controls. The expression levels of five selected miRNAs were quantitatively analyzed during disease progression in each patient and we demonstrated that high levels of miR-206, miR-133a and miR-151a-5p can predict a slower clinical decline of patient functionality. In particular, we found that miR-206 and miR-151a-5p serum levels were significantly up-regulated at the mild stage of ALS pathology, to decrease in the following moderate and severe stages, whereas the expression levels of miR-133a and miR-199a-5p remained low throughout the course of the disease, showing a diagnostic significance in moderate and severe stages for miR-133a and in mild and terminal ones for miR-199a-5p. Moreover, we found that miR-423–3p and 151a-5p were significantly downregulated respectively in mild and terminal stages of the disease. These data suggest that these miRNAs represent potential prognostic markers for ALS disease.

Abstract Background Clinical registers constitute an invaluable resource in the medical data-driven decision making context. Accurate machine learning and data mining approaches on these data can lead to faster diagnosis, definition of tailored interventions, and improved outcome prediction. A typical issue when implementing such approaches is the almost unavoidable presence of missing values in the collected data. In this work, we propose an imputation algorithm based on a mutual information-weighted k-nearest neighbours approach, able to handle the simultaneous presence of missing information in different types of variables. We developed and validated the method on a clinical register, constituted by the information collected over subsequent screening visits of a cohort of patients affected by amyotrophic lateral sclerosis. Methods For each subject with missing data to be imputed, we create a feature vector constituted by the information collected over his/her first three months of visits. This vector is used as sample in a k-nearest neighbours procedure, in order to select, among the other patients, the ones with the most similar temporal evolution of the disease over time. An ad hoc similarity metric was implemented for the sample comparison, capable of handling the different nature of the data, the presence of multiple missing values and include the cross-information among features captured by the mutual information statistic. Results We validated the proposed imputation method on an independent test set, comparing its performance with those of three state-of-the-art competitors, resulting in better performance. We further assessed the validity of our algorithm by comparing the performance of a survival classifier built on the data imputed with our method versus the one built on the data imputed with the best-performing competitor. Conclusions Imputation of missing data is a crucial –and often mandatory– step when working with real-world datasets. The algorithm proposed in this work could effectively impute an amyotrophic lateral sclerosis clinical dataset, by handling the temporal and the mixed-type nature of the data and by exploiting the cross-information among features. We also showed how the imputation quality can affect a machine learning task.

Abstract Purpose Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease leading to neuromuscular palsy and death. We propose a computational approach to [18F]-fluorodeoxyglucose (FDG) PET/CT images to analyze the structure and metabolic pattern of skeletal muscle in ALS and its relationship with disease aggressiveness. Materials and methods A computational 3D method was used to extract whole psoas muscle’s volumes and average attenuation coefficient (AAC) from CT images obtained by FDG PET/CT performed in 62 ALS patients and healthy controls. Psoas average standardized uptake value (normalized on the liver, N-SUV) and its distribution heterogeneity (defined as N-SUV variation coefficient, VC-SUV) were also extracted. Spinal cord and brain motor cortex FDG uptake were also estimated. Results As previously described, FDG uptake was significantly higher in the spinal cord and lower in the brain motor cortex, in ALS compared to controls. While psoas AAC was similar in patients and controls, in ALS a significant reduction in psoas volume (3.6 ± 1.02 vs 4.12 ± 1.33 mL/kg; p < 0.01) and increase in psoas N-SUV (0.45 ± 0.19 vs 0.29 ± 0.09; p < 0.001) were observed. Higher heterogeneity of psoas FDG uptake was also documented in ALS (VC-SUV 8 ± 4%, vs 5 ± 2%, respectively, p < 0.001) and significantly predicted overall survival at Kaplan–Meier analysis. VC-SUV prognostic power was confirmed by univariate analysis, while the multivariate Cox regression model identified the spinal cord metabolic activation as the only independent prognostic biomarker. Conclusion The present data suggest the existence of a common mechanism contributing to disease progression through the metabolic impairment of both second motor neuron and its effector.

Background: Data from published studies about the effect of HFE polymorphisms on ALS risk, phenotype, and survival are still inconclusive. We aimed at evaluating whether the p.H63D polymorphism is a modifier of phenotype and survival in SOD1-mutated patients. Methods: We included 183 SOD1-mutated ALS patients. Mutations were classified as severe or mild according to the median survival of the study population. Patients were screened for the HFE p.H63D polymorphism. Survival was calculated using the Kaplan–Meier modeling, and differences were measured by the log-rank test. Multivariable analysis was performed with the Cox proportional hazards model (stepwise backward). Results: SOD1 severe mutation carriers show more frequent familial history for ALS and shorter survival compared to mild mutation carriers. Carriers and non-carriers of the p.H63D polymorphism did not differ in terms of sex ratio, frequency of positive familial history, age at onset, and bulbar/spinal ratio. In univariate and in Cox multivariable analysis using sex, age at onset, site of onset, family history, country of origin, and mutation severity as covariates, p.H63D carriers had a longer survival (p = 0.034 and p = 0.004). Conclusions: We found that SOD1-mutated ALS patients carrying the p.H63D HFE polymorphism have a longer survival compared to non-carriers, independently of sex, age and site of onset, family history, nation of origin, and severity of mutations, suggesting a possible role as disease progression modifier for the p.H63D HFE polymorphism in SOD1-ALS.

Summary: Various genetic and environmental risk factors have been implicated in the pathogenesis of amyotrophic lateral sclerosis (ALS). Despite this, the cause of most ALS cases remains obscure. In this review, we describe the current evidence implicating genetic and environmental factors in motor neuron degeneration. While the risk exerted by many environmental factors may appear small, their effect could be magnified by the presence of a genetic predisposition. We postulate that gene-environment interactions account for at least a portion of the unknown etiology in ALS. Climate underlies multiple environmental factors, some of which have been implied in ALS etiology, and the impact of global temperature increase on the gene-environment interactions should be carefully monitored. We describe the main concepts underlying such interactions. Although a lack of large cohorts with detailed genetic and environmental information hampers the search for gene-environment interactions, newer algorithms and machine learning approaches offer an opportunity to break this stalemate. Understanding how genetic and environmental factors interact to cause ALS may ultimately pave the way towards precision medicine becoming an integral part of ALS care.

Abstract Background Amyotrophic lateral sclerosis (ALS) is an adult-onset neurodegenerative disease progressively affecting upper and lower motor neurons in the brain and spinal cord. Mean life expectancy is three to five years, with paralysis of muscles, respiratory failure and loss of vital functions being the common causes of death. Clinical manifestations of ALS are heterogeneous due to the mix of anatomic regions involvement and the variability in disease course; consequently, diagnosis and prognosis at the level of individual patient is really challenging. Prediction of ALS progression and stratification of patients into meaningful subgroups have been long-standing interests to clinical practice, research and drug development. Methods We developed a Dynamic Bayesian Network (DBN) model on more than 4500 ALS patients included in the Pooled Resource Open-Access ALS Clinical Trials Database (PRO-ACT), in order to detect probabilistic relationships among clinical variables and identify risk factors related to survival and loss of vital functions. Furthermore, the DBN was used to simulate the temporal evolution of an ALS cohort predicting survival and the time to impairment of vital functions (communication, swallowing, gait and respiration). A first attempt to stratify patients by risk factors and simulate the progression of ALS subgroups was also implemented. Results The DBN model provided the prediction of ALS most probable trajectories over time in terms of important clinical outcomes, including survival and loss of autonomy in functional domains. Furthermore, it allowed the identification of biomarkers related to patients’ clinical status as well as vital functions, and unrevealed their probabilistic relationships. For instance, DBN found that bicarbonate and calcium levels influence survival time; moreover, the model evidenced dependencies over time among phosphorus level, movement impairment and creatinine. Finally, our model provided a tool to stratify patients into subgroups of different prognosis studying the effect of specific variables, or combinations of them, on either survival time or time to loss of autonomy in specific functional domains. Conclusions The analysis of the risk factors and the simulation allowed by our DBN model might enable better support for ALS prognosis as well as a deeper insight into disease manifestations, in a context of a personalized medicine approach.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease that affects both lower and upper motor neurons (MNs) in the central nervous system. ALS etiology is highly multifactorial and multifarious, and an effective treatment is still lacking. Neuroinflammation is a hallmark of ALS and could be targeted to develop new therapeutic approaches. Interestingly, the transcription factor Nurr1 has been demonstrated to have an important role in the inflammatory process in several neurological disorders, such as Parkinson's disease and multiple sclerosis. In the present paper, we demonstrate for the first time that Nurr1 expression levels are upregulated in the peripheral blood of ALS patients. Moreover, we investigated Nurr1 function in the SOD1-G93A mouse model of ALS. Nurr1 was strongly upregulated in the spinal cord during the asymptomatic and early symptomatic phases of the disease, where it promoted the expression of brain-derived neurotrophic factor mRNA and the repression of NFκB pro-inflammatory targets, such as inducible nitric oxide synthase. Therefore, we hypothesize that Nurr1 is activated in an early phase of the disease as a protective endogenous anti-inflammatory mechanism, although not sufficient to reverse disease progression. On the basis of these observations, Nurr1 could represent a potential biomarker for ALS and a promising target for future therapies.

Abstract A pathogenic hexanucleotide repeat expansion within the C9orf72 gene has been identified as the major cause of two neurodegenerative syndromes, amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). This mutation is known to have incomplete penetrance, with some patients developing disease in their twenties and a small portion of carriers surviving to their ninth decade without developing symptoms. Describing penetrance by age among C9orf72 carriers and identifying parameters that alter onset age are essential to better understanding this locus and to enhance predictive counseling. To do so, data from 1,170 individuals were used to model penetrance. Our analysis showed that the penetrance was incomplete and age-dependent. Additionally, familial and sporadic penetrance did not significantly differ from one another; ALS cases exhibited earlier age of onset than FTD cases; and individuals with spinal-onset exhibited earlier age of onset than those with bulbar-onset. The older age of onset among female cases in general, and among female bulbar-onset cases in particular, was the most striking finding, and there may be an environmental, lifestyle, or hormonal factor that is influencing these penetrance patterns. These results will have important applications for future clinical research, the identification of disease modifiers, and genetic counseling.

Objective: To evaluate the metabolic correlates of lifetime sport practice in ALS through brain 18F-FDG-PET. Methods: 131 patients completed a questionnaire about lifetime exposures, including physical activity related to sports, hobbies and occupations, and underwent brain 18F-FDG-PET. Exposure to sports was expressed as MET (Metabolic Equivalent of Task). We considered only regular practice (at least 2 h/week, for at least three months). We compared brain metabolism between two groups: subjects who did not report regular sport practice during life (N-group) and patients who did (Y-group). The resulting significant clusters were used in each group as seed regions in an interregional correlation analysis (IRCA) to evaluate the impact of lifetime sport practice on brain networks typically involved by the neurodegenerative process of ALS. Each group was compared to healthy controls (HC, n = 40). Results: We found a significant, relative cerebellar hypermetabolism in the N-group compared to the Y-group. The metabolism of such cerebellar cluster resulted correlated to more significant and widespread metabolic changes in areas known to be affected by ALS (i.e. frontotemporal regions and corticospinal tracts) in the N-group as compared to the Y-group, despite the same level of disability as expressed by the ALS FRS-R. Such findings resulted independent of age, sex, site of onset (bulbar/spinal), presence/absence of C9ORF72 expansion, cognitive status and physical activity related to hobbies and occupations. When compared to HC, the N-group showed more widespread metabolic changes than the Y-group in cortical regions known to be relatively hypometabolic in ALS patients as compared to HC. Conclusions: We hypothesize that patients of the N-group might cope better with the neurodegenerative process, since they show more widespread metabolic changes as compared to the Y-group, despite the same level of disability. Nevertheless, further studies are necessary to corroborate this hypothesis.

We investigated whether the C9orf72 repeat expansion is associated with specific clinical features, comorbidities, and prognosis in patients with amyotrophic lateral sclerosis (ALS). A cohort of 1417 ALS patients, diagnosed between January 1, 2009 and December 31, 2013 by 13 Italian ALS Referral Centers, was screened for the C9orf72 repeat expansion, and the analyses were performed comparing patients carrying this expansion (ALS-C9Pos) to those negative for this and other explored ALS-related mutations (ALS without genetic mutations, ALSwoGM). Compared to the ALSwoGM group, ALS-C9Pos patients (n = 84) were younger at disease onset, at the first clinical observation and at diagnosis (p < 0.001). After correcting for these differences, we found that ALS-C9Pos patients had higher odds of bulbar onset, diagnosis of frontotemporal dementia (FTD) and family history of ALS, FTD, and Alzheimer's disease and had lower odds of spinal onset, non-invasive ventilation, hypertension and psychiatric diseases than ALSwoGM patients. Among these variables, those related to shorter survival time were: bulbar onset, presence of FTD, hypertension, psychiatric disease, and family history of ALS (p < 0.05). Cox proportional hazards regression multivariate analysis suggested that carrying the C9orf72 repeat expansion was an independent factor negatively impacting on survival time in men (HR 1.58, 95% CI 1.07–2.33, p = 0.021), but not in women (p > 0.05) as well as in the whole sample (p > 0.05). When compared to ALSwoGM, ALS-C9Pos showed an earlier disease onset, no significant diagnostic delay and a higher odds of bulbar onset, FTD and family history of ALS and dementia. Moreover, male sex drove the negative effect of expanded variant on survival, confirming the hypothesis that sex is likely to be a crucial factor in the biology of C9orf72-related disease.

This prospective study developed an MRI-based method for identification of individual motor neuron disease (MND) patients and test its accuracy at the individual patient level in an independent sample compared with mimic disorders. 123 patients with amyotrophic lateral sclerosis (ALS), 44 patients with predominantly upper motor neuron disease (PUMN), 20 patients with ALS-mimic disorders, and 78 healthy controls were studied. The diagnostic accuracy of precentral cortical thickness and diffusion tensor (DT) MRI metrics of corticospinal and motor callosal tracts were assessed in a training cohort and externally proved in a validation cohort using a random forest analysis. In the training set, precentral cortical thickness showed 0.86 and 0.89 accuracy in differentiating ALS and PUMN patients from controls, while DT MRI distinguished the two groups from controls with 0.78 and 0.92 accuracy. In ALS vs controls, the combination of cortical thickness and DT MRI metrics (combined model) improved the classification pattern (0.91 accuracy). In the validation cohort, the best accuracy was reached by DT MRI (0.87 and 0.95 accuracy in ALS and PUMN vs mimic disorders). The combined model distinguished ALS and PUMN patients from mimic syndromes with 0.87 and 0.94 accuracy. A multimodal MRI approach that incorporates motor cortical and white matter alterations yields statistically significant improvement in accuracy over using each modality separately in the individual MND patient classification. DT MRI represents the most powerful tool to distinguish MND from mimic disorders. Keywords: Motor neuron disease, Amyotrophic lateral sclerosis, Diagnosis, MRI, Random forest analysis

The socioeconomic burden of amyotrophic lateral sclerosis (ALS) is high, but the projected number of cases in the upcoming years is unclear. Here, the authors estimate the number and distribution of ALS cases to 2040, and show that cases are projected to increase, particularly in developing nations.

(1) Background: Cognitive features of patients with amyotrophic lateral sclerosis (ALS) have never been specifically analyzed according to the lateralization of motor impairment. In the present study we investigated the cognitive performances of ALS patients to describe the relationship between motor and cognitive dysfunction, according to site and side of disease onset. (2) Methods: Six-hundred and nine ALS patients underwent a comprehensive neuropsychological evaluation at diagnosis in Turin ALS Centre Tests included—mini-mental state examination (MMSE), frontal assessment battery (FAB), trail-making test A/B (TMT A-B), digit span forward and backward (digit span FW/digit span BW), letter fluency test (FAS), category fluency test (CAT), Rey auditory verbal learning test (RAVLT), Babcock story recall test (BSRT), Rey-Osterrieth complex figure test (ROCFT), Wisconsin card sorting test (WCST), Raven’s coloured progressive matrices (CPM47). Cognitive performances of patients, grouped by side and site of onset, were statistically compared using z-scores, as appropriate. (3) Results: Bulbar patients and bilateral spinal onset patients (Sbil) were generally characterized by lower cognitive performances in most neuropsychological tests, when compared to patients with lateralized onset (right-side spinal onset, Sri and left-side spinal onset, Sle). Digit span backward and visual memory task (ROCFT) median z-scores were significantly higher, reflecting a better cognitive performance, in Sri patients when compared to bulbar/Sbil patients, while verbal memory tasks (RAVLT and BRST) resulted in significantly higher scores in Sle patients. Our results are in keeping with hemispheric functional lateralization of language and visuospatial abilities. (4) Conclusions: In ALS patients, as in other neurodegenerative diseases, we found a direct relationship between lateralized motor and cognitive features.