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BackgroundPhosphorylated-tau181 (p-tau181), a specific marker of Alzheimer’s disease (AD) pathology, was found elevated in plasma but not in cerebrospinal fluid (CSF) of patients with amyotrophic lateral sclerosis (ALS). We expanded these findings in a larger patient cohort, exploring clinical/electrophysiological associations, prognostic value and longitudinal trajectories of the biomarker.MethodsWe obtained baseline plasma samples from 148 ALS, 12 spinal muscular atrophy (SMA), and 88 AD patients, and 60 healthy controls. Baseline CSF and longitudinal plasma samples were from 130 and 39 patients with ALS. CSF AD markers were measured with the Lumipulse platform, and plasma p-tau181 with SiMoA.ResultsPatients with ALS showed higher plasma p-tau181 levels than controls (pConclusionsPlasma p-tau181 is elevated in patients with ALS, independently from CSF levels, and is firmly associated with LMN dysfunction. The finding indicates that p-tau181 of putative peripheral origin might represent a confounding factor in using plasma p-tau181 for AD pathology screening, which deserves further investigation.

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Few studies have focused on elderly (>80 years) amyotrophic lateral sclerosis (ALS) patients, who represent a fragile subgroup generally not included in clinical trials and often neglected because they are more difficult to diagnose and manage. We analyzed the clinical and genetic features of very late-onset ALS patients through a prospective, population-based study in the Emilia Romagna Region of Italy. From 2009 to 2019, 222 (13.76%) out of 1613 patients in incident cases were over 80 years old at diagnosis, with a female predominance (F:M = 1.18). Elderly ALS patients represented 12.02% of patients before 2015 and 15.91% from 2015 onwards (p = 0.024). This group presented with bulbar onset in 38.29% of cases and had worse clinical conditions at diagnosis compared to younger patients, with a lower average BMI (23.12 vs. 24.57 Kg/m2), a higher progression rate (1.43 vs. 0.95 points/month), and a shorter length of survival (a median of 20.77 vs. 36 months). For this subgroup, genetic analyses have seldom been carried out (25% vs. 39.11%) and are generally negative. Finally, elderly patients underwent less frequent nutritional- and respiratory-supporting procedures, and multidisciplinary teams were less involved at follow-up, except for specialist palliative care. The genotypic and phenotypic features of elderly ALS patients could help identify the different environmental and genetic risk factors that determine the age at which disease onset occurs. Since multidisciplinary management can improve a patient’s prognosis, it should be more extensively applied to this fragile group of patients.

Amyotrophic lateral sclerosis (ALS) and Alzheimer’s disease (AD) patients show a higher prevalence of Lewy body disease than the general population. Additionally, parkinsonian features were found in about 30% of ALS patients. We aimed to explore the frequency of Parkinson’s disease (PD)-causative genes in ALS patients, compared to AD and healthy controls (HCs). We used next-generation sequencing multigene panels by analyzing SNCA, LRRK2, PINK1, PARK2, PARK7, SYNJ1, CHCHD2, PLA2G6, GCH1, ATP13A2, DNAJC6 and FBXO genes. GBA gene, a risk factor for PD, was also analyzed. In total, 130 ALS and 100 AD patients were investigated. PD-related genes were found to be altered in 26.2% of ALS, 20% of AD patients and 19.2% of HCs. Autosomal recessive genes were significantly more involved in ALS as compared to AD and HCs (p = 0.021). PARK2 variants were more frequent in ALS than in AD and HCs, although not significantly. However, the p.Arg402Cys variant was increased in ALS than in HCs (p = 0.025). This finding is consistent with current literature, as parkin levels were found to be decreased in ALS animal models and patients. Our results confirm the possible role of PD-related genes as risk modifier in ALS pathogenesis.

There are currently no standardized therapies for Parkinson disease (PD). Curcumin shows anti-amyloidogenic properties in vitro and may be a promising treatment for PD. We evaluated the effects of curcumin supplementation on clinical scales and misfolded, phosphorylated α-synuclein (p-syn) accumulation in skin biopsies in 19 PD patients who received curcumin supplementation for 12 months and 14 PD patients to treated with curcumin. The patients underwent autonomic (COMPASS-31), motor (MDS-UPDRS and H&Y) and nonmotor (NMSS) questionnaires and skin biopsies to evaluate clinical involvement and p-syn load in skin nerves at the beginning and the end of study. Curcumin and curcuminoid levels were assayed in plasma and CSF. Supplemented patients showed detectable CSF curcuminoid levels that were lower than those in plasma. They showed a decrease of COMPASS-31 and NMSS scores, and a slight p-syn load decrease versus untreated patients who displayed a worsening of these parameters despite increased levodopa doses. Multiple regression models showed a significant effect of curcumin supplementation in decreasing the worsening of the clinical parameters and p-syn load at after curcumin treatment. These data suggest that curcumin can cross the blood-brain barrier, that it is effective in ameliorating clinical parameters and that it shows a tendency to decrease skin p-syn accumulation in PD patients.

Objective To employ Artificial Intelligence to model, predict and simulate the amyotrophic lateral sclerosis (ALS) progression over time in terms of variable interactions, functional impairments, and survival. Methods We employed demographic and clinical variables, including functional scores and the utilisation of support interventions, of 3940 ALS patients from four Italian and two Israeli registers to develop a new approach based on Dynamic Bayesian Networks (DBNs) that models the ALS evolution over time, in two distinct scenarios of variable availability. The method allows to simulate patients’ disease trajectories and predict the probability of functional impairment and survival at different time points. Results DBNs explicitly represent the relationships between the variables and the pathways along which they influence the disease progression. Several notable inter-dependencies were identified and validated by comparison with literature. Moreover, the implemented tool allows the assessment of the effect of different markers on the disease course, reproducing the probabilistically expected clinical progressions. The tool shows high concordance in terms of predicted and real prognosis, assessed as time to functional impairments and survival (integral of the AU-ROC in the first 36 months between 0.80–0.93 and 0.84–0.89 for the two scenarios, respectively). Conclusions Provided only with measurements commonly collected during the first visit, our models can predict time to the loss of independence in walking, breathing, swallowing, communicating, and survival and it can be used to generate in silico patient cohorts with specific characteristics. Our tool provides a comprehensive framework to support physicians in treatment planning and clinical decision-making.

Assessing the safety of SARS-CoV-2 mRNA vaccines and the effect of immunotherapies on the seroconversion rate in patients with autoimmune neurological conditions (ANC) is relevant to clinical practice. Our aim was to assess the antibody response to and safety of SARS-CoV-2 mRNA vaccines in ANC.This longitudinal study included ANC patients vaccinated with two doses of BNT162b2 or mRNA-1273 between March and August 2021. Side effects were assessed 2-10 days after each dose. Neurological status and anti-spike receptor binding domain antibody levels were evaluated before vaccination and 4 weeks after the second dose. Healthcare-workers served as controls for antibody levels.We included 300 ANC patients (median age 52, IQR 40-65), and 347 healthcare-workers (median age 45, IQR 34-54). mRNA-1273 vaccine was associated with an increased risk of both local (OR 2.52 95% CI 1.45-4.39, p = 0.001) and systemic reactions (OR 2.51% CI 1.49-4.23, p = 0.001). The incidence of relapse was not different before and after vaccine (Incidence rate ratio 0.72, 95% CI 0.29-1.83). Anti-SARS-CoV-2 IgG were detected in 268 (89.9%) patients and in all controls (p 0.0001). BNT162b2 vaccine (OR 8.84 95% CI 2.32-33.65, p = 0.001), anti-CD20 mAb (OR 0.004 95% CI 0.0007-0.026, p 0.0001) and fingolimod (OR 0.036 95% CI 0.002-0.628, p = 0·023) were associated with an increased risk of not developing anti-SARS-CoV-2 IgG.SARS-CoV-2 mRNA vaccines were safe in a large group of ANC patients. Anti-CD20 and fingolimod treatment, as well as vaccination with the BNT162b2 vaccine, led to a reduced humoral response. These findings could inform vaccine policies in ANC patients undergoing immunotherapy.

To retrospectively evaluate quality of life (QoL) in a large multicenter cohort of adult patients affected by spinal muscular atrophy (SMA) during nusinersen treatment.We included adult (≥ 18 years) patients clinically and genetically defined as SMA2, SMA3 and SMA4, who started nusinersen treatment in adulthood. QoL was rated by the Individualized Neuromuscular Quality of Life (INQoL) questionnaire. Concurrent motor function evaluation included the Hammersmith Functional Motor Scale Expanded (HFMSE), the Revised Upper Limb Module (RULM), the 6 min walking test (6MWT).189 completed questionnaires were collected during a 14 months' treatment period. 78 patients were included (7 SMA2 and 69 SMA3 and 2 SMA4) with mean disease duration at first nusinersen administration of 33.2 years (± 12.5 years). All the scores for each INQoL domain (weakness, fatigue, activities, independence, social relationship, emotions, body images) and the derived QoL total score, significantly improved during the observation period, except the muscle locking and pain items. Exploratory analyses suggested that emotions and social relationships were more relevant issues for females compared to males. Social relationships were affected also by a longer disease duration ( 30 years). In SMA3 non-walker patients, activities ameliorate better compared to walkers. The HFMSE and RULM significantly improved from baseline; however, no associations with QoL total score and weakness, activities or independence were demonstrated.In our cohort, adult SMA patients showed a global improvement at the INQoL assessment over 14 months of nusinersen treatment. QoL assessment is relevant to SMA multidisciplinary evaluation.

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.