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BackgroundBehavioral and psychological symptoms of dementia (BPSD) have a high prevalence, and their presence is associated with a severe impact in terms of social costs. However, dedicated clinical tools or biomarkers to detect these symptoms are lacking. Thus, BPSD management in clinical settings is challenging. The aim of this study was to investigate the perception and the treatment strategies for BPSD in Italian centers working in the dementia field.MethodsA multicenter, national survey was developed by BPSD Study Group of the Italian Neurological Society for Dementia (SINDEM). The survey consisted of a semi-structured questionnaire that was e-mailed to SINDEM members, dementia centers part of the national network of memory clinics (Centers for Cognitive Deterioration and Dementia [CDCD]), and clinicians working in dementia care settings. The questions were focused on (1) perceived global frequency and relevance of BPSD; (2) tools used to assess BPSD; (3) pharmacological treatment for psychosis, apathy, agitation, aggression, depression, anxiety, sleep, and nutrition disturbances; (4) non-pharmacological treatments; (5) drugs side effects.ResultsOne-hundred and thirty-six clinicians participated in this study. Seventy-nine participants worked in a CDCD and 57 in other settings. The perceived frequency of BPSD was 74%. BPSD are detected by means of a clinical assessment for 96.3% or a caregiver interview for 97%. For psychosis treatment the first choice was atypical antipsychotics (83.3%), followed by typical antipsychotic (8.9%) and antidepressants (4.8%). For agitation, atypical antipsychotics were the first-choice treatment in 64% of cases and antidepressants in 16.1%. For aggression, the most used drugs were atypical antipsychotics (82.9%). For anxiety, 55.2% use antidepressants, 17.9% use atypical antipsychotics, and 16.9% use benzodiazepines. Interestingly, most of the centers apply non-pharmacological treatments for BPSD. Some differences emerged comparing the responses from CDCD and other care settings.ConclusionThe survey results revealed many differences in BPSD perception, treatment options, and observed side effect according to the clinical setting. This variability can be explained by the absence of clear guidelines, by differences in patients' characteristics, and by clinical practice based on subjective experience. These results suggest that producing guidelines for the pharmacological treatment of BPSD is a major need.

Background and ObjectivesTo characterize the clinical and cognitive behavioral phenotype and brain18F-2-fluoro-2-deoxy-d-glucose-PET (18F-FDG-PET) metabolism of patients with amyotrophic lateral sclerosis (ALS) carrying the rs12608932 variant of theUNC13Agene.MethodsThe study population included 1,409 patients with ALS withoutC9orf72, SOD1, TARDBP, andFUSmutations identified through a prospective epidemiologic ALS register. Control participants included 1,012 geographically matched, age-matched, and sex-matched participants. Clinical and cognitive differences between patients carrying the C/C rs12608932 genotype and those carrying the A/A + A/C genotype were assessed. A subset of patients underwent18F-FDG-PET.ResultsThe C/C genotype was associated with an increased risk of ALS (odds ratio: 1.54, 95% confidence interval 1.18–2.01,p= 0.001). Patients with the C/C genotype were older, had more frequent bulbar onset, and manifested a higher rate of weight loss. In addition, they showed significantly reduced performance in the letter fluency test, fluency domain of Edinburgh Cognitive and Behavioural ALS Screen (ECAS) and story-based empathy task (reflecting social cognition). Patients with the C/C genotype had a shorter survival (median survival time, C/C 2.25 years, interquartile range [IQR] 1.33–3.92; A/A + C/C: 2.90 years, IQR 1.74–5.41;p= 0.0001). In Cox multivariable analysis, C/C genotype resulted to be an independent prognostic factor. Finally, patients with a C/C genotype had a specific pattern of hypometabolism on brain18F-FDG-PET extending to frontal and precentral areas of the right hemisphere.DiscussionC/C rs12608932 genotype ofUNC13Ais associated with a specific motor and cognitive/behavioral phenotype, which reflects on18F-FDG-PET findings. Our observations highlight the importance of adding the rs12608932 variant inUNC13Ato the ALS genetic panel to refine the individual prognostic prediction and reduce heterogeneity in clinical trials.

Background MRI studies reported that ALS patients with bulbar and spinal onset showed focal cortical changes in corresponding regions of the motor homunculus. We evaluated the capability of brain 2-[18F]FDG-PET to disclose the metabolic features characterizing patients with pure bulbar or spinal motor impairment. Methods We classified as pure bulbar (PB) patients with bulbar onset and a normal score in the spinal items of the ALSFRS-R, and as pure spinal (PS) patients with spinal onset and a normal score in the bulbar items at the time of PET. Forty healthy controls (HC) were enrolled. We compared PB and PS, and each patient group with HC. Metabolic clusters showing a statistically significant difference between PB and PS were tested to evaluate their accuracy in discriminating the two groups. We performed a leave-one-out cross-validation (LOOCV) over the entire dataset. Four classifiers were considered: support vector machines (SVM), K-nearest neighbours, linear classifier, and decision tree. Then, we used a separate test set, including 10% of patients, with the remaining 90% composing the training set. Results We included 63 PB, 271 PS, and 40 HC. PB showed a relative hypometabolism compared to PS in bilateral precentral gyrus in the regions of the motor cortex involved in the control of bulbar function. SVM showed the best performance, resulting in the lowest error rate in both LOOCV (4.19%) and test set (9.09 ± 2.02%). Conclusions Our data support the concept of the focality of ALS onset and the use of 2-[18F]FDG-PET as a biomarker for precision medicine-oriented clinical trials.

Purpose Neuropathological data suggest that ALS with SOD1 mutations (SOD1-ALS) is a distinct form of ALS. We evaluated brain metabolic changes characterizing SOD1-ALS as compared to sporadic ALS (sALS), employing 18fluorodeoxyglucose-positron-emission tomography (18F-FDG-PET). Methods We included 18 SOD1-ALS patients, 40 healthy controls (HC), and 46 sALS patients without mutations in SOD1, TARDBP, FUS, and C9ORF72, randomly selected from 665 subjects who underwent brain 18F-FDG-PET at diagnosis between 2008 and 2019 at the ALS Centre of Turin. We excluded patients with frontotemporal dementia. We used the full factorial design in SPM12 to evaluate whether differences among groups exist overall. In case the hypothesis was confirmed, group comparisons were performed through the two-sample t-test model of SPM12. In all the analyses, the height threshold was P < 0.001 (P < 0.05 FWE-corrected at cluster level). Results The full factorial design resulted in a significant main effect of groups. We identified a relative hypometabolism in sALS patients compared to SOD1-ALS cases in the right precentral and medial frontal gyrus, right paracentral lobule, and bilateral postcentral gyrus. SOD1 patients showed a relative hypermetabolism as compared to HC in the right precentral gyrus and paracentral lobule. As compared to HC, sALS patients showed relative hypometabolism in frontal, temporal, and occipital cortices. Conclusion SOD1-ALS was characterized by a relative hypermetabolism in the motor cortex as compared to sALS and HC. Since promising, targeted, therapeutic strategies are upcoming for SOD1-ALS, our data support the use of PET to study disease pathogenesis and to track its course in clinical trials, in both asymptomatic and symptomatic mutation carriers.

Amyotrophic lateral sclerosis (ALS) is known to represent a collection of overlapping syndromes. Various classification systems based on empirical observations have been proposed, but it is unclear to what extent they reflect ALS population substructures. We aimed to use machine-learning techniques to identify the number and nature of ALS subtypes to obtain a better understanding of this heterogeneity, enhance our understanding of the disease, and improve clinical care.In this retrospective study, we applied unsupervised Uniform Manifold Approximation and Projection [UMAP]) modelling, semi-supervised (neural network UMAP) modelling, and supervised (ensemble learning based on LightGBM) modelling to a population-based discovery cohort of patients who were diagnosed with ALS while living in the Piedmont and Valle d'Aosta regions of Italy, for whom detailed clinical data, such as age at symptom onset, were available. We excluded patients with missing Revised ALS Functional Rating Scale (ALSFRS-R) feature values from the unsupervised and semi-supervised steps. We replicated our findings in an independent population-based cohort of patients who were diagnosed with ALS while living in the Emilia Romagna region of Italy.Between Jan 1, 1995, and Dec 31, 2015, 2858 patients were entered in the discovery cohort. After excluding 497 (17%) patients with missing ALSFRS-R feature values, data for 42 clinical features across 2361 (83%) patients were available for the unsupervised and semi-supervised analysis. We found that semi-supervised machine learning produced the optimum clustering of the patients with ALS. These clusters roughly corresponded to the six clinical subtypes defined by the Chiò classification system (ie, bulbar, respiratory, flail arm, classical, pyramidal, and flail leg ALS). Between Jan 1, 2009, and March 1, 2018, 1097 patients were entered in the replication cohort. After excluding 108 (10%) patients with missing ALSFRS-R feature values, data for 42 clinical features across 989 patients were available for the unsupervised and semi-supervised analysis. All 1097 patients were included in the supervised analysis. The same clusters were identified in the replication cohort. By contrast, other ALS classification schemes, such as the El Escorial categories, Milano-Torino clinical staging, and King's clinical stages, did not adequately label the clusters. Supervised learning identified 11 clinical parameters that predicted ALS clinical subtypes with high accuracy (area under the curve 0·982 [95% CI 0·980-0·983]).Our data-driven study provides insight into the ALS population substructure and confirms that the Chiò classification system successfully identifies ALS subtypes. Additional validation is required to determine the accuracy and clinical use of these algorithms in assigning clinical subtypes. Nevertheless, our algorithms offer a broad insight into the clinical heterogeneity of ALS and help to determine the actual subtypes of disease that exist within this fatal neurodegenerative syndrome. The systematic identification of ALS subtypes will improve clinical care and clinical trial design.US National Institute on Aging, US National Institutes of Health, Italian Ministry of Health, European Commission, University of Torino Rita Levi Montalcini Department of Neurosciences, Emilia Romagna Regional Health Authority, and Italian Ministry of Education, University, and Research.For the Italian and German translations of the abstract see Supplementary Materials section.

Social cognition (SC) deficits are included in amyotrophic lateral sclerosis (ALS)-frontotemporal spectrum disorder revised diagnostic criteria. However, SC performance among ALS patients is heterogeneous due to the phenotypic variability of the disease and the wide range of neuropsychological tools employed. The aim of the present study was to assess facial emotion recognition and theory of mind in ALS patients compared to controls and to evaluate correlations with the other cognitive domains and degree of motor impairment.Eighty-three patients and 42 controls underwent a cognitive evaluation and SC assessment through the Ekman 60 Faces Test (EK-60F), the Reading the Mind in the Eyes Test-36 Faces (RMET-36), and the Story-Based Empathy Task (SET).ALS patients showed significantly worse performance compared to controls in EK-60F global score (p lt; 0.001), recognition of disgust (p = 0.032), anger (p = 0.038), fear (p lt; 0.001), and sadness (p lt; 0.001); RMET-36 (p lt; 0.001), and SET global score (p lt; 0.001). Also, cognitively normal patients (ALS-CN) showed significantly worse performance compared to controls in EK-60F global score (p lt; 0.001), recognition of fear (p = 0.002), sadness (p lt; 0.001), and SET (p lt; 0.001). RMET-36 showed a significant correlation with the Category Fluency Test (p = 0.041). SC tests showed no correlation with motor impairment expressed by Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised.ALS patients, also when categorized as ALS-CN, may show impairment in SC performance. The frequent identification of early SC impairment in ALS patients supports the need to routinely assess SC for its impact on end-of-life decisions and its potential influence on patients' quality of life.

Since its first description by Charcot, amyotrophic lateral sclerosis (ALS) has been classified as a single neurodegenerative disease involving motor neurons. More recently, however, it has become clear that ALS is pleiotropic and its phenotype could vary depending on several factors: age of onset, prevalent damage to the upper (UMN) or the lower motor neuron, body region mostly affected, progression rate and presence of non-motor symptoms, the most frequent being cognitive impairment.1 As a consequence, different phenotypes have been described.2 It remains unclear whether these presentations should be considered as distinct clinical entities or as variants of the same disease.3 More importantly, we do not know if different aetiologies justify this variability.3 Despite these uncertainties, we approach clinical trials by administering the same treatment to all patients with ALS.3 Spatial epidemiology could give some clues on aetiology by identifying clusters and subsequently seeking for causative genetic or environmental factors. Previously, we analysed the spatial distribution of a large ALS cohort in Northwestern Italy. Patients resulted to be homogeneously distributed, suggesting either that a single environmental factor was evenly distributed or that multiple factors acted on distinct subgroups, the latter being the more likely.4 Moving from the hypothesis that aetiology could vary according to phenotypes, here we performed a spatial analysis of ALS cases stratified according to their clinical presentation. Data from the Piemonte and Valle d’Aosta ALS Register were used.4 All patients with ALS diagnosed between 2007 and 2014 and who were resident in Piemonte at the time of diagnosis were included. The cluster analysis was conducted considering municipalities; …

Recent advances in the genetic causes of ALS reveals that about 10% of ALS patients have a genetic origin and that more than 30 genes are likely to contribute to this disease. However, four genes are more frequently associated with ALS: C9ORF72, TARDBP, SOD1, and FUS. The relationship between genetic factors and ALS progression rate is not clear. In this study, we carried out a causal analysis of ALS disease with a genetics perspective in order to assess the contribution of the four mentioned genes to the progression rate of ALS.In this work, we applied a novel causal learning model to the CRESLA dataset which is a longitudinal clinical dataset of ALS patients including genetic information of such patients. This study aims to discover the relationship between four mentioned genes and ALS progression rate from a causation perspective using machine learning and probabilistic methods.The results indicate a meaningful association between genetic factors and ALS progression rate with causality viewpoint. Our findings revealed that causal relationships between ALSFRS-R items associated with bulbar regions have the strongest association with genetic factors, especially C9ORF72; and other three genes have the greatest contribution to the respiratory ALSFRS-R items with a causation point of view.The findings revealed that genetic factors have a significant causal effect on the rate of ALS progression. Since C9ORF72 patients have higher proportion compared to those carrying other three gene mutations in the CRESLA cohort, we need a large multi-centric study to better analyze SOD1, TARDBP and FUS contribution to the ALS clinical progression. We conclude that causal associations between ALSFRS-R clinical factors is a suitable predictor for designing a prognostic model of ALS.

SUMMARYBackgroundThe disease entity known as amyotrophic lateral sclerosis (ALS) is now known to represent a collection of overlapping syndromes. A better understanding of this heterogeneity and the ability to distinguish ALS subtypes would improve the clinical care of patients and enhance our understanding of the disease. Subtype profiles could be incorporated into the clinical trial design to improve our ability to detect a therapeutic effect. A variety of classification systems have been proposed over the years based on empirical observations, but it is unclear to what extent they genuinely reflect ALS population substructure.MethodsWe applied machine learning algorithms to a prospective, population-based cohort consisting of 2,858 Italian patients diagnosed with ALS for whom detailed clinical phenotype data were available. We replicated our findings in an independent population-based cohort of 1,097 Italian ALS patients.FindingsWe found that semi-supervised machine learning based on UMAP applied to the output of a multi-layered perceptron neural network produced the optimum clustering of the ALS patients in the discovery cohort. These clusters roughly corresponded to the six clinical subtypes defined by the Chiò classification system (bulbar ALS, respiratory ALS, flail arm ALS, classical ALS, pyramidal ALS, and flail leg ALS). The same clusters were identified in the replication cohort. A supervised learning approach based on ensemble learning identified twelve clinical parameters that predicted ALS clinical subtype with high accuracy (area under the curve = 0·94).InterpretationOur data-driven study provides insight into the ALS population’s substructure and demonstrates that the Chiò classification system robustly identifies ALS subtypes. We provide an interactive website (https://share.streamlit.io/anant-dadu/machinelearningforals/main) so that clinical researchers can predict the clinical subtype of an ALS patient based on a small number of clinical parameters.FundingNational Institute on Aging and the Italian Ministry of Health.RESEARCH IN CONTEXTEvidence before this studyWe searched PubMed for articles published in English from database inception until January 5, 2021, about the use of machine learning and the identification of clinical subtypes within the amyotrophic lateral sclerosis (ALS) population, using the search terms “machine learning”, AND “classification”, AND “amyotrophic lateral sclerosis”. This inquiry identified twenty-nine studies. Most previous studies used machine learning to diagnose ALS (based on gait, imaging, electromyography, gene expression, proteomic, and metabolomic data) or improve brain-computer interfaces. One study used machine learning algorithms to stratify ALS postmortem cortex samples into molecular subtypes based on transcriptome data. Kueffner and colleagues crowdsourced the development of machine learning algorithms to approximately thirty teams to obtain a consensus in an attempt to identify ALS patients subpopulation. In addition to clinical trial information in the PRO-ACT database (www.ALSdatabase.org), this effort used data from the Piedmont and Valle d’Aosta Registry for ALS (PARALS). Four ALS patient categories were identified: slow progressing, fast progressing, early stage, and late stage. This approach’s clinical relevance was unclear, as all ALS patients will necessarily pass through an early and late stage of the disease.Furthermore, no attempt was made to discern which of the existing clinical classification systems, such as the El Escorial criteria, the Chiò classification system, and the King’s clinical staging system, can identify ALS subtypes. We concluded that there remained an unmet need to identify the ALS population’s substructure in a data-driven, non-empirical manner. Building on this, there was a need for a tool that reliably predicts the clinical subtype of an ALS patient. This knowledge would improve our understanding of the clinical heterogeneity associated with this fatal neurodegenerative disease.Added value of this studyThis study developed a machine learning algorithm to detect ALS patients’ clinical subtypes using clinical data collected from the 2,858 Italian ALS patients in PARALS. Ascertainment of these patients within the catchment area was near complete, meaning that the dataset truly represented the ALS population. We replicated our approach using clinical data obtained from an independent cohort of 1,097 Italian ALS patients that had also been collected in a population-based, longitudinal manner. Semi-supervised learning based on Uniform Manifold Approximation and Projection (UMAP) applied to a multilayer perceptron neural network provided the optimum results based on visual inspection. The observed clusters equated to the six clinical subtypes previously defined by the Chiò classification system (bulbar ALS, respiratory ALS, flail arm ALS, classical ALS, pyramidal ALS, and flail leg ALS). Using a small number of clinical parameters, an ensemble learning approach could predict the ALS clinical subtype with high accuracy (area under the curve = 0·94).Implications of all available evidenceAdditional validation is required to determine these algorithms’ accuracy and clinical utility in assigning clinical subtypes. Nevertheless, our algorithms offer a broad insight into the clinical heterogeneity of ALS and help to determine the actual subtypes of disease that exist within this fatal neurodegenerative syndrome. The systematic identification of ALS subtypes will improve clinical care and clinical trial design.

Purpose To assess the brain metabolic correlates of the different regional extent of ALS, evaluated with the King’s staging system, using brain 18F-2-fluoro-2-deoxy-d-glucose-PET (18F-FDG-PET). Methods Three hundred ninety ALS cases with King’s stages 1, 2, and 3 (n = 390), i.e., involvement of 1, 2, and 3 body regions respectively, underwent brain 18F-FDG-PET at diagnosis. King’s stage at PET was derived from ALSFRS-R and was regressed out against whole-brain metabolism in the whole sample. The full factorial design confirmed the hypothesis that differences among groups (King’s 1, King’s 2, King’s 3, and 40 healthy controls (HC)) existed overall. Comparisons among stages and between each group and HC were performed. We included age at PET and sex as covariates. Results Brain metabolism was inversely correlated with stage in medial frontal gyrus bilaterally, and right precentral and postcentral gyri. The full factorial design resulted in a significant main effect of groups. There was no significant difference between stages 1 and 2. Comparing stage 3 to stage 1+2, a significant relative hypometabolism was highlighted in the former in the left precentral and medial frontal gyri, and in the right medial frontal, postcentral, precentral, and middle frontal gyri. The comparisons between each group and HC showed the extension of frontal metabolic changes from stage 1 to stage 3, with the larger metabolic gap between stages 2 and 3. Conclusions Our findings support the hypothesis that in ALS, the propagation of neurodegeneration follows a corticofugal, regional ordered pattern, extending from the motor cortex to posterior and anterior regions.

The aetiology of Amyotrophic Lateral Sclerosis (ALS), a fatal and incurable disease caused by motor neuron degeneration, is still poorly understood. The discovery of genetic forms of ALS helped to shed light on the mechanisms underlying this pathology, but also showed how complex these mechanisms are. Excitotoxicity is one of the processes strongly suspected to play a role in motor neuron degeneration in ALS. This process consists in 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 excitotoxicity. In detail, the profile of eight proteins (TDP-43, C9ORF72, p62/SQSTM1, matrin3, 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 significant decrease in the levels of TDP-43, C9ORF72, matrin3, VCP, FUS, SOD1 and profilin-1 and an increase in p62/SQSTM1. These events are associated to the proteolytic action of two proteases, calpains and caspases, as well as to the activation of autophagy, a process responsible for the degradation and recycling of cytoplasmic components. Interestingly, Ca2+ appears to both favour and hinder autophagy. The discovery of when Ca2+ levels become toxic for the cell, as well as understanding why the physiological processes of calpain proteolysis and autophagy become pathological, may elucidate the mechanisms responsible for ALS and help discover new therapeutic targets.

Objective: To assess patients Quality of life (QoL) and the burden of their caregivers during Covid-19 pandemic and specifically the impact of two-month lockdown period. Methods: In April 2020, a total of 60 patients and 59 caregivers were administered by phone scales assessing patients��� QoL (McGill QoL Questionnaire), general health status (EQ-5D-5L), and caregiver burden (Zarit Burden Interview). The administration was repeated one month after the end of lockdown measures, with the addition of a qualitative questionnaire (COVID-QoL Questionnaire) exploring family reorganization and personal perception of lock down. Results: QoL and perceived health status did not worsen during lockdown, while caregiver burden increased (p = 0.01). Patient���s QoL and caregiver burden were inversely correlated at T1 (ZBI total score mildly correlated with Mc Gill existential subscore, p = 0.02, rho = 0.30 and with Mc Gill total score, p = 0.05, rho = 0.265). No significant correlations were found at T2. According to the COVID-QoL questionnaire, caregivers perceived lower family help compared to patients (p Conclusions: Restricted measures of lockdown period during COVID-19 pandemic did not result in a significant reduction of QoL in our cohort of ALS patients, while caregiver burden significantly increased. ALS motor impairment may have played a role in the unchanged life conditions of patients. Instead, the restriction of family help for primary caregivers could be responsible of their increased burden, reflecting the importance of a wide social support in the management of this clinical condition.

Objective: To assess amyotrophic lateral sclerosis (ALS) prevalence and to analyze how this estimate vary according to the historical depth of data collection. Methods: Data from the PARALS register have been used. Crude prevalence ratio was estimated on 31 December 2015 for the period 2015–2013 and then repeated extending the time interval by 3 years each time. For each time interval, prevalence ratio was calculated globally and stratified by sex, age at diagnosis, and phenotype. Prevalence was also calculated considering patients who underwent tracheostomy during the same study period. Results: Prevalence ratios increased proportionally to the length of the time period considered, ranging from 6 (95% CI 5.3–6.7) for a 3-year period to 12.1 (95% CI 11.1–13.1) per 100,000 population for a 21-year period. Prevalence ratio increase was inversely proportional to age at diagnosis, being null in the >85 years class and maximal in the 25–35 age class (+1700%). Among phenotypes, predominant UMN showed the highest increase (from 0.5, 95% CI 0.3–0.8, to 2.1, 95% CI 1.7 − 2.6, +320%). Discussion: Because of the variability of ALS survival, prevalence ratio strongly depends on the length of the follow-up period. A 12-year period should be sufficient to get a reliable estimate of ALS prevalence including long-survival patients.

Cervical spondylogenic myelopathy (CSM) represents a common differential diagnosis for spinal onset Amyotrophic Lateral Sclerosis (ALS). Identifying occurrence of ALS in patients with CSM may be challenging. We evaluated the accuracy of Awaji criteria in the diagnosis of ALS in a cohort of patients with CSM. We screened all patients attending Turin ALS Center during the 2006–2018 period. We selected only patients for whom cervical cord MRI showed radiological signs of CSM. All patients underwent electromyography (EMG), and Awaji criteria were used for diagnosis of clinically probable ALS. All patients were followed up clinically for at least 6 months, and ALS diagnosis was eventually confirmed according to El-Escorial revised criteria, based on disease progression. Of 2,059 patients screened, in 42 cases, MRI showed signs of CSM; CSM incidence and prevalence risks were 0.16 and 2.04%, respectively. Based on clinical progression, 72.7% of patients were diagnosed as CSM and 27.3% as CSM + ALS. At EMG 6 (18.2%) patients fulfilled the criteria for ALS, 5 of them (83.3%) during clinical follow-up were diagnosed as clinical definite ALS + CSM. Accuracy of Awaji criteria in diagnosing ALS was good (AUC = 0.757, p = 0.03). Sensitivity and specificity of Awaji criteria were, respectively, 55.6 and 95.8%. Positive predictive value was 83.3%, while negative predictive value was 85.2%. CSM-ALS comorbidity is a relatively common problem in clinical practice. To better choose patients who could benefit from surgery, EMG should be performed in CSM patients, due to its good accuracy in recognizing ALS.

Introduction The burden of non-motor symptoms is a major determinant of quality of life and outcome in amyotrophic lateral sclerosis (ALS) and has profound negative effect also on caregivers. Areas covered Non-motor symptoms in ALS include cognitive impairment, neurobehavioral symptoms, depression and anxiety, suicidal ideation, pain, disordered sleep, fatigue, weight loss and reduced appetite, and autonomic dysfunctions. This review summarizes the measures used for the assessment of non-motor symptoms and their properties and recaps the frequency and progression of these symptoms along the course of ALS. Expert opinion Non-motor symptoms in ALS represent a major component of the disease and span over several domains. These symptoms require a high level of medical attention and should be checked at each visit using ad hoc questionnaires and proactively treated. Several instruments assessing non-motor symptoms have been used in ALS. Specific screening questionnaires for non-motor symptoms can be used for monitoring patients during telehealth visits and for remote surveillance through sensors and apps installed on smartphones. Novel trials for non-motor symptoms treatment specifically designed for ALS are necessary to increase and refine the therapeutic armamentarium. Finally, scales assessing the most frequent and burdensome non-motor symptoms should be included in clinical trials.

Objective: To assess the frequency and predictors of plateaus in ALS progression as assessed by the Medical Research Council (MRC) Scale. Methods: All patients attending the ALS Center of Turin, with a diagnosis between 2007 and 2014 were considered. At each visit, muscle strength was evaluated in several muscles and assessed using the MRC scale. Concomitant ALSFRSr scores were retrieved. Plateaus were calculated as a stable overall MRC or ALSFRSr score lasting at least 6, 12 or 18 months. Results: According to MRC scale scores, 122 (22.8%), 71 (13.2%) and 59 (11.0%) patients experienced a plateau lasting at least 6, 12 and 18 months. ALSFRSr scores revealed similar estimates [134, (25.0%), 89 (16.6%) and 67 (12.5%), respectively]. Plateaus were more frequent at high scores and appeared a median of 24.6 months (IQR 6.7-47.7) after the diagnosis. Only the predominant upper motor neuron phenotype (OR 4.06, 95% CI 2-06-8.10, p-value

We report a case of childhood-onset ALS with a FUS gene mutation presenting cognitive impairment and a rapid clinical progression. The patient, an 11-year-old girl, presented with right distal upper limb weakness and mild intellectual disability at the Griffith Mental Development Scales. The disease rapidly worsened and the patient became tetraplegic and bed-ridden 2 years after symptom onset. A c.1509_1510delAG mutation in exon 14 of the FUS gene was detected, resulting in a predicted truncated protein, p.G504Wfs*12, lacking the nuclear localization signal. The levels of FUS mRNA in the proband were not significantly different compared to controls. Western immunoblot analysis showed that one antibody (500-526) detected in the proband ~50% of the amount of FUS protein compared to controls, while 3 other antibodies (2-27, 400-450 and FUS C-terminal), which recognize both wild type and the mutated FUS, detected 60% to 75% of the amount of the protein. These findings indicate that p.G504Wfs*12 FUS is more prone to undergo post-translational modification respect to wild type FUS.

Purpose Poor control of eye movement and coordination may impair the use of eye-trackers for communication in patients affected by severe motor diseases. Recently, the “voluntary” pupil accommodative response (PAR) was suggested as a possible alternative to traditional assistive technology. Aim of this study is to provide a proof of concept of this methodology in a clinical setting. Materials and methods A low-cost communication system was implemented, which detects the accommodative pupillary constrictions in real time and generates trigger events to drive a commercial scanning-selection interface. As a first implementation, a simple binary yes/no selection interface was designed to be tested with a brainstem stroke patient, unable to use standard communicators based on eye tracking. The patient was instructed to operate the intended selection by switching the focus of attention from a far to a near target, and was then presented with 10 questions with obvious answer. Results The patient easily understood how to perform the accommodative task. The pupillary constrictions were marked and clearly detectable in spite of the disturbing action of persistent nystagmus. On the first presentation of the device, the patient managed to correctly answer 8 out of 10 questions. Conclusions The present results provide a proof-of-concept for PAR-based communication in a clinical setting and support its usefulness with patients who, due to impaired control of eye movements, may be unable to use tracking-based devices.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with an estimated heritability of around 50%. DNA methylation patterns can serve as biomarkers of (past) exposures and disease progression, as well as providing a potential mechanism that mediates genetic or environmental risk. Here, we present a blood-based epigenome-wide association study (EWAS) meta-analysis in 10,462 samples (7,344 ALS patients and 3,118 controls), representing the largest case-control study of DNA methylation for any disease to date. We identified a total of 45 differentially methylated positions (DMPs) annotated to 42 genes, which are enriched for pathways and traits related to metabolism, cholesterol biosynthesis, and immunity. We show that DNA-methylation-based proxies for HDL-cholesterol, BMI, white blood cell (WBC) proportions and alcohol intake were independently associated with ALS. Integration of these results with our latest GWAS showed that cholesterol biosynthesis was causally related to ALS. Finally, we found that DNA methylation levels at several DMPs and blood cell proportion estimates derived from DNA methylation data, are associated with survival rate in patients, and could represent indicators of underlying disease processes.

Aggregation and cytoplasmic mislocalization of TDP-43 are pathological hallmarks of amyotrophic lateral sclerosis and frontotemporal dementia spectrum. However, the molecular mechanism by which TDP-43 aggregates form and cause neurodegeneration remains poorly understood. Cyclophilin A, also known as peptidyl-prolyl cis-trans isomerase A (PPIA), is a foldase and molecular chaperone. We previously found that PPIA interacts with TDP-43 and governs some of its functions, and its deficiency accelerates disease in a mouse model of amyotrophic lateral sclerosis. Here we characterized PPIA knock-out mice throughout their lifespan and found that they develop a neurodegenerative disease with key behavioural features of frontotemporal dementia, marked TDP-43 pathology and late-onset motor dysfunction. In the mouse brain, deficient PPIA induces mislocalization and aggregation of the GTP-binding nuclear protein Ran, a PPIA interactor and a master regulator of nucleocytoplasmic transport, also for TDP-43. Moreover, in absence of PPIA, TDP-43 autoregulation is perturbed and TDP-43 and proteins involved in synaptic function are downregulated, leading to impairment of synaptic plasticity. Finally, we found that PPIA was downregulated in several patients with amyotrophic lateral sclerosis and amyotrophic lateral sclerosis-frontotemporal dementia, and identified a PPIA loss-of-function mutation in a patient with sporadic amyotrophic lateral sclerosis . The mutant PPIA has low stability, altered structure and impaired interaction with TDP-43. These findings strongly implicate that defective PPIA function causes TDP-43 mislocalization and dysfunction and should be considered in future therapeutic approaches., Pasetto et al. show that PPIA helps protect against TDP-43-mediated neurodegeneration. They identify a PPIA loss-of-function mutation in a patient with sporadic ALS, and reveal reduced PPIA levels in several other ALS and ALS-FTD patients. PPIA knock-out mice develop a neurodegenerative disease with a clear ALS-FTD phenotype.

Objective: To evaluate how Amyotrophic Lateral Sclerosis (ALS) patients��� mortality rates change, based on different levels of forced vital capacity (FVC) and disease duration, providing a scheme of mortality rates of a real population of ALS patients to improve the design of future RCTs. Methods: One random spirometry for each ALS patient was selected during four time intervals from disease onset: (1) ���12 months; (2) ���18 months; (3) ���24 months; (4) ���36 months. Date of spirometry corresponded to date of trial entry, while time interval onset-spirometry to disease duration at enrollment. Mortality rates from inclusion were computed at different time intervals. Based on progression rates, patients were stratified in slow, intermediate and fast progressors. Survival from recruitment was calculated depending on FVC, disease duration and progression rate. Results: We included 659 patients in group 1, 888 in group 2, 1019 in group 3 and 1102 in group 4. Mortality rates were higher in each group at reducing the FVC cutoff used for recruitment (p p Conclusions: This is a simple model for setting eligibility criteria, based on mortality rates of patients depending on FVC and disease duration, to select the best population for RCTs, tailored to trials��� primary endpoints and duration.

Objective: To investigate the impact of a novel heterozygous FUS mutation in the acceptor splice site of intron 14 (c.1542 ��� 1 g > t) on protein expression in Peripheral Blood Mononuclear Cells (PBMC) from a familial ALS patient. Methods: PBMC were isolated for mRNA analysis (cDNA synthesis, sequencing and one-step RT-PCR), Western Immunoblot (WI), and Immunofluorescence (IF). Results: cDNA analysis revealed the skipping of exon 15 and a premature stop codon at c.228. RT-PCR showed reduced FUS mRNA by more than half compared to a healthy control (HC) and an ALS patient without genetic mutations (wtALS). In WI FUS band intensity in the proband was 30���50% compared to HC and wtALS. An antibody expected to detect only the wild-type protein did not reveal any reduction of FUS band intensity compared to the other antibodies. IF showed no difference among HC, wtALS, and the proband. Discussion: The reduction of FUS mRNA and protein in PBMC suggests the absence of the truncated protein, probably due to nonsense-mediated decay, leading to loss of function.

Objective. Up to 50% of patients affected by amyotrophic lateral sclerosis (ALS) show behavioral changes within the spectrum of frontotemporal degeneration (FTD). Behavioral dysfunctions in ALS patients negatively impact on management, prognosis and survival. It is, thus, crucial to develop ALS-specific psychometric tools for early detecting alterations in behavior. This study aimed at investigating psychometric properties and feasibility of the Beaumont Behavioral Impairment (BBI), a proxy-report questionnaire designed to screen for FTD-like behavioral symptoms in ALS patients.Methods. Ninety ALS patients were compared to 100 healthy participants (HPs) on the BBI. ALS patients underwent clinical, cognitive, mood/anxiety and further behavioral (Frontal System Behavior Scale, FrSBe; Frontal Behavioral Inventory, FBI) evaluation. Validity, reliability, sensitivity and specificity of the BBI were assessed.Results. The BBI was significantly related to FrSBe and FBI scores, whereas not to other measures. A Principal Component Analysis yielded a mono-component structure; Cronbach's α was .93. The BBI proved to be sensitive to changes in behavior as well as to discriminate between different degrees of dysfunction. By addressing the FrSBe as the gold standard, the BBI reached optimal sensitivity (85.7%) and specificity (79.7%) at a cutoff of 10.5. Moreover, the BBI proved to be more accurate than the FrSBe and the FBI in clinical classifications.Conclusion. The BBI showed high internal consistency, as well as good construct, convergent and divergent validity. Its clinical usability is encouraged in ALS patients as being able to sensitively and specifically detect FTD-like behavioral changes.

BackgroundAmyotrophic 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.MethodsWe analyzed plasma-derived EVs of ALS patients (n = 106) and controls (n = 96), and SOD1G93Aand TDP-43Q331Kmouse 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.ResultsOur 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.ConclusionsOur 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.

(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&mdash, 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&rsquo, 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.

Background and purpose: The aim of this study was to evaluate brain metabolic correlates of apathy in amyotrophic lateral sclerosis (ALS). Methods: A total of 165 ALS patients underwent 18F-2-fluoro-2-deoxy-D-glucose positron emission tomography (18F-FDG-PET) and Frontal Systems Behaviour Scale (FrSBe) evaluation. FrSBe provides “before” and “after” apathy subscores, referring to premorbid and morbid conditions. “After” apathy subscore and “before-after” gap, i.e. the difference between “before” and “after” subscores, were regressed against whole-brain metabolism. Among patients with a pathological “after” apathy subscore (i.e., ≥65), we compared patients with “before” apathy subscores ≥65 and

BackgroundAmyotrophic 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.MethodsWe 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.ResultsOur procedure resulted in high-yield isolation of intact and polydisperse plasma EVs, with minimal lipoprotein contamination. There were more particles in the plasma of ALS patients and the two mouse models of ALS while their average diameter was smaller. HSP90 was differentially represented in ALS patients and mice 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, suggesting a new means for patient stratification. We also measured the levels of phosphorylated TDP-43 and showed that is not an intravesicular cargo of plasma-derived EVs.ConclusionsOur 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.

Because hyper-excitability has been shown to be a shared pathophysiological mechanism, we used the latest and largest genome-wide studies in amyotrophic lateral sclerosis (n = 36,052) and epilepsy (n = 38,349) to determine genetic overlap between these conditions. First, we showed no significant genetic correlation, also when binned on minor allele frequency. Second, we confirmed the absence of polygenic overlap using genomic risk score analysis. Finally, we did not identify pleiotropic variants in meta-analyses of the 2 diseases. Our findings indicate that amyotrophic lateral sclerosis and epilepsy do not share common genetic risk, showing that hyper-excitability in both disorders has distinct origins. ispartof: NEUROBIOLOGY OF AGING vol:92 ispartof: location:United States status: published

Aggregation and cytoplasmic mislocalization of TDP-43 are pathological hallmarks of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) spectrum. However, the molecular mechanism by which TDP-43 aggregates form and cause neurodegeneration remains poorly understood. Cyclophilin A, also known as peptidyl-prolyl cis-trans isomerase A (PPIA), is a foldase and molecular chaperone. We previously found that PPIA interacts with TDP-43 and governs some of its functions, and its deficiency accelerates disease in a mouse model of ALS. Here we characterized PPIA knock-out mice throughout their lifespan and found that they develop a neurodegenerative disease with key behavioural features of FTD, marked TDP-43 pathology and late-onset motor dysfunction. In the mouse brain, deficient PPIA induces aggregation of the GTP-binding nuclear protein Ran, a PPIA substrate required for TDP-43 nucleocytoplasmic trafficking. Moreover, in absence of PPIA, TDP-43 autoregulation is perturbed and TDP-43 and proteins involved in synaptic function are downregulated, leading to impairment of synaptic plasticity. Finally, we found that PPIA was downregulated in several ALS and ALS-FTD patients and identified a PPIA loss-of-function mutation in a sporadic ALS patient. The mutant PPIA has low stability, altered structure and impaired interaction with TDP-43. These findings strongly implicate that defective PPIA function causes TDP-43 mislocalization and dysfunction and should be considered in future therapeutic approaches.

We tested the Cognitive Reserve (CR) hypothesis in Amyotrophic Lateral Sclerosis (ALS), enrolling 111 patients, using education as CR proxy, 18F-FDG-PET to assess brain damage, and ECAS to measure cognition. Education was regressed out against brain metabolism, including age, sex, spinal/bulbar onset, ALSFRS-R, and ECAS as covariates. Clusters showing a significant correlation were used as seed regions in an interregional correlation analysis (IRCA) in the ALS group and in 40 controls. In the ALS group, we found a negative correlation between brain metabolism and education in the right anterior cingulate and bilateral medial frontal gyrus. In the IRCA in the ALS group, the medial frontal cluster metabolism positively correlated with that of frontotemporal regions (right > left), bilateral caudate nuclei, and right insula, and negatively correlated with that of corticospinal tracts, cerebellum, and pons. In controls, the IRCA showed significant positive correlations in the same regions but less extended. Our results agree with the CR hypothesis. The negative correlation between the medial frontal cluster and the cerebellum found only in ALS patients might reflect cerebellar compensation.

To identify the metabolic changes related to the various levels of cognitive deficits in amyotrophic lateral sclerosis (ALS) using274 ALS patients underwent neuropsychological assessment and brainWe identified frontal lobe relative hypometabolism in cognitively impaired patients that resulted more extensive and significant across the continuum from ALS-Ci, through ALS-Cbi, to ALS-FTD. ALS-FTD patients also showed cerebellar relative hypermetabolism. ALS-Bi patients did not show any difference compared with ALS-Cn.These data support the concept that patients with cognitive impairment have a more widespread neurodegenerative process compared with patients with a pure motor disease: the more severe the cognitive impairment, the more diffuse the metabolic changes. Otherwise, metabolic changes related to pure behavioural impairment need further characterisation.

To determine whether the neuropsychological profiles of patients with amyotrophic lateral sclerosis (ALS) with (ALSC9+) and without (ALSC9-)The study population includes 741 patients with ALS who were consecutively diagnosed at the Turin ALS expert center in the 2010-2018 period and who underwent both cognitive/behavioral and genetic testing. Patients' neuropsychological patterns were compared (1) at the same degree of cognitive and behavioral deficit according to the revised ALS-Frontotemporal Dementia Consensus Criteria and (2) at the same level of motor impairment according to the King staging system.Despite being about 7 years younger, ALSC9+ patients had significantly lower scores in tests exploring executive function and verbal memory both when classified as cognitively normal and when diagnosed in the intermediate cognitive categories. Considering the clinical perspective, ALSC9+ patients showed significantly lower scores compared to ALSC9- patients at King stage 1 and 3 in almost all the examined neuropsychological domains; at King stage 2, ALSC9+ patients were more severely affected only in the verbal memory domain. Behavioral function was comparably impaired in the 2 cohorts.ALSC9+ patients show a different neuropsychological profile compared to ALSC9- patients, being more impaired in executive functions and verbal memory domains at all King stages. Verbal memory emerged as a particularly vulnerable function in ALSC9+, with worse performances even when patients were still classified as cognitively normal.

ObjectiveTo investigate structural and functional neural organization in amyotrophic lateral sclerosis (ALS), primary lateral sclerosis (PLS), and progressive muscular atrophy (PMA).MethodsA total of 173 patients with sporadic ALS, 38 patients with PLS, 28 patients with PMA, and 79 healthy controls were recruited from 3 Italian centers. Participants underwent clinical, neuropsychological, and brain MRI evaluations. Using graph analysis and connectomics, global and lobar topologic network properties and regional structural and functional brain connectivity were assessed. The association between structural and functional network organization and clinical and cognitive data was investigated.ResultsCompared with healthy controls, patients with ALS and patients with PLS showed altered structural global network properties, as well as local topologic alterations and decreased structural connectivity in sensorimotor, basal ganglia, frontal, and parietal areas. Patients with PMA showed preserved global structure. Patient groups did not show significant alterations of functional network topologic properties relative to controls. Increased local functional connectivity was observed in patients with ALS in the precentral, middle, and superior frontal areas, and in patients with PLS in the sensorimotor, basal ganglia, and temporal networks. In patients with ALS and patients with PLS, structural connectivity alterations correlated with motor impairment, whereas functional connectivity disruption was closely related to executive dysfunction and behavioral disturbances.ConclusionsThis multicenter study showed widespread motor and extramotor network degeneration in ALS and PLS, suggesting that graph analysis and connectomics might represent a powerful approach to detect upper motor neuron degeneration, extramotor brain changes, and network reorganization associated with the disease. Network-based advanced MRI provides an objective in vivo assessment of motor neuron diseases, delivering potential prognostic markers.

Motor neuron disease (MND) is a heterogeneous group of neurodegenerative disorders defined by a progressive upper motor neuron (UMN) and lower motor neuron (LMN) loss in a varying combination, encompassing a heterogeneous clinical spectrum depending on a different body region involvement at onset, extent and rate of motor neuron (MN) loss and disease spread. Amyotrophic lateral sclerosis (ALS) is the most common and severe form of MND, leading to death in approximately 4 years from symptoms onset. To date, the mainstay neuroprotective therapy is riluzole, despite its limited efficacy, while the role of edaravon is still debated. Phenotypic heterogeneity is increasingly recognised within the MND spectrum, ranging from selective UMN or LMN involvement, to classic ALS, when widespread combination of UMN and LMN dysfunction occurs.1 The clinical spectrum of MND has been further detailed with the recognition of flail arm (FA), flail leg (FL) and pure lower motor neuron (PLMN) phenotypes, considered to be restricted MND phenotypes characterised by a predominant or selective LMN disease (LMND), when UMN dysfunction is absent or marginal.1 2 Furthermore, patients with MND can show an extra-motor involvement such as cognitive impairment with the development, in approximately 10%–15% of cases, of frontotemporal dementia. Few studies have previously focused on these LMN-restricted phenotypes, therefore, the aim of the present study is to retrospectively investigate the differentiating features of FA, FL and PLMN phenotypes in a large Italian MND cohort. 2648 patients with MND were recruited in 13 Italian ALS referral centres from January 2009 to December 2013 and data collected in a common database, which was cleaned before data analysis. To highlight the distinguishing features of patients with FA, FL and PLMN, the classic and bulbar phenotypes were used as controls. The final dataset consisted of 1944 patients. ALS diagnosis was established in accordance with …

Objectives: The aim of the study is to analyze the ALS disease progression and respiratory function of Italian patients treated with edaravone (EVN), as well as the adherence to, and the effects of, the therapy. Methods: We performed an observational study of patients treated with EVN from May 2017 to May 2019, in 39 Italian ALS Centers. Taking into account ALS patients with at least 12months of EVN treatment, we compared the decline of ALSFRS-R and FVC with a group of matched historical controls from the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database, using both descriptive and survival analysis approaches. Results: A total of 331 ALS Italian patients treated with EVN and 290 matched historical controls were recruited in this study. No significant differences on disease progression or respiratory function were found comparing the two cohorts in both descriptive and survival analyses. The EVN treatment was overall well tolerated. Conclusions: The study showed that EVN treatment was well tolerated. No significant differences were reported in ALS patients treated and not treated with EVN, in terms of both disease progression and respiratory function. These findings prove that further studies are required to better clarify whether EVN could be considered an effective treatment for ALS disease.

Background: A cognitive impairment, ranging from frontotemporal dementia (FTD) to milder forms of dysexecutive or behavioral dysfunction, is detected in 30–50% of patients affected by amyotrophic lateral sclerosis (ALS) at diagnosis. Such condition considerably influences the prognosis, and possibly impacts on the decision-making process with regards to end-of-life choices. The aim of our study is to examine the changes of cognitive and behavioral impairment in a large population of ALS from the time of diagnosis to a 6-month follow-up (IQR 5.5–9.0 months), and to examine to what extent the progression of cognitive impairment affects survival time and rate of disease progression. Methods: We recruited 146 ALS patients classified according to revised criteria of ALS and FTD spectrum disorder. In a multidisciplinary setting, during two subsequent visits we examined clinical features with ALSFRS-r score, FVC% and BMI, and cognitive status with an extensive neuropsychological evaluation. Results: At second examination, one-third of patients showed a worsening of cognitive impairment, namely 88% of ALSbi, 27% of ALSci, 40% of ALScbi, and, interestingly, also 24% of cognitive normal ALS developed a significant cognitive dysfunction. We find that those who changed their cognitive status presented a lower ALSFRS-r score at t1 and a shorter survival time compared to those who did not change, regardless of the type of cognitive impairment. Conclusion: We show how cognitive disorders in ALS patients can not only be present at diagnosis, but also manifest during disease and influence the progression of motor deficit and the prognosis.

Background and purpose The analysis of the spatial distribution of cases could give important cues on putative environmental causes of a disease. Our aim was to perform a spatial analysis of an amyotrophic lateral sclerosis (ALS) cohort from the Piedmont and Aosta Valley ALS register (PARALS) over a 20-year period. Methods The address at the moment of diagnosis was considered for each ALS case. Municipalities' and census divisions' resident populations during the 1995-2014 period were obtained. A cluster analysis was performed adopting both Moran's index and the Kulldorff spatial scan statistic. Results A total of 2702 ALS patients were identified. An address was retrieved for 2671 (99%) patients. Moran's index was -0.01 (P value 0.83), thus revealing no clusters. SaTScan identified no statistically significant clusters. When census divisions were considered, Moran's index was 0.13 (P value 0.45); SaTScan revealed one statistically significant small cluster in the province of Alessandria. Here, 0.0099 cases were expected and three cases were observed (relative risk 304.60; 95% confidence interval 109.83-845.88, P value 0.03). Discussion Our study showed a substantial homogeneous distribution of ALS cases in Piedmont and Aosta Valley. The population-based setting and the adoption of proper statistical analyses strengthen the validity of our results. Such a finding further suggests the involvement of multiple environmental and genetic factors in ALS pathogenesis.