In preclinical studies rapamycin was found to target neuroinflammation, by expanding regulatory T cells, and affecting autophagy, two pillars of amyotrophic lateral sclerosis (ALS) pathogenesis. Herein we report a multicenter, randomized, double-blind trial, in 63 ALS patients who were randomly assigned in a 1:1:1 ratio to receive rapamycin 2 mg/m²/day,1 mg/m²/day or placebo (EUDRACT 2016-002399-28; NCT03359538). The primary outcome, the number of patients exhibiting an increase >30% in regulatory T cells from baseline to treatment end, was not attained. Secondary outcomes were changes from baseline of T, B, NK cell subpopulations, inflammasome mRNA expression and activation status, S6-ribosomal protein phosphorylation, neurofilaments; clinical outcome measures of disease progression; survival; safety and quality of life. Of the secondary outcomes, rapamycin decreased mRNA relative expression of the pro-inflammatory cytokine IL-18, reduced plasmatic IL-18 protein, and increased the percentage of classical monocytes and memory switched B cells, although no corrections were applied for multiple tests. In conclusion, we show that rapamycin treatment is well tolerated and provides reassuring safety findings in ALS patients, but further trials are necessary to understand the biological and clinical effects of this drug in ALS.

Amyotrophic lateral sclerosis (ALS) is known to represent a collection of overlapping syndromes. A better understanding of this heterogeneity and the ability to distinguish ALS subtypes would improve clinical care and enhance our understanding of the disease. Various classification systems have been proposed based on empirical observations, but it is unclear to what extent they reflect ALS population substructure. We hypothesized that machine learning techniques could identify the number and nature of ALS subtypes. We applied unsupervised (Uniform Manifold Approximation and Projection, UMAP), semi-supervised (neural network-UMAP), and supervised (ensemble based on LightGBM) modeling to a population-based cohort of 2,858 Italian ALS patients for whom detailed phenotype data were available. We replicated our findings in an independent population-based cohort of 1,097 Italian ALS patients. We 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. These clusters roughly corresponded to the six clinical subtypes defined by the Chiò classification system (bulbar, respiratory, flail arm, classical, pyramidal, and flail leg ALS). The same clusters were identified in the replication cohort. In contrast, other ALS classification schema, such as the El Escorial categories, Milano-Torino clinical Staging (MiToS), and King’s clinical stages, did not adequately label the clusters. Ensemble learning identified twelve clinical parameters that predicted ALS clinical subtype with high accuracy (area under the curve = 0·982, 95% confidence interval = 0·980–0·983). Our 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 researchers can predict the clinical subtype of an ALS patient based on a small number of clinical parameters. National Institute on Aging and the Italian Ministry of Health.

Background: Amyotrophic lateral sclerosis (ALS) is a devastating and untreatable motor neuron disease, with a 3–5-year survival from diagnosis. Possible prognostic serum biomarkers include albumin, C-reactive protein, ferritin, creatinine, uric acid, hemoglobin, potassium, sodium, calcium, glucose, and the neutrophil-to-lymphocyte ratio (NLR), a marker of subclinical inflammation. Objective: To ascertain the influence of NLR on ALS progression rate and survival. Methods: Cross-sectional multicenter study including 146 consecutive incident and prevalent patients (88 males), aged >18 years, diagnosed according to the El Escorial criteria. The exclusion criteria were: (1) patients with tracheostomy or receiving mechanical ventilation; (2) patients with percutaneous endoscopic gastrostomy; and (3) patients who did not sign the informed consent. The rate of disease progression (ΔFS score) represents the monthly decline of the ALSFRS-R score, and was computed as (48 − total ALSFRS-R at recruitment)/symptom duration in months. Patients were followed up to tracheotomy, death, or the end of the follow-up, whichever occurred first. To validate our findings, we used data retrieved from the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) Database. Results: The median disease duration was 15 (range = 2–30) months. The mean ALSFRS-R score at recruitment was 35.8 ± 8.0 (range: 10–48), and the median ΔFS was 0.66 (range: 0–5.33). Age at onset, at diagnosis, and at recruitment were significantly lower in the lowest NLR tertile. NLR values positively correlated with ΔFS values (r = 0.28): the regression slope of NLR (log-values) was 0.60 (p < 0.001) before and 0.49 (p = 0.006) after adjustment for age at recruitment. The ΔFS score progressively increased from the lowest to the highest NLR tertile: 0.35 (IQR: 0.18–0.93), 0.62 (IQR: 0.25–1.09), and 0.86 (IQR: 0.53–1.92). Patients were followed for a median of 2 years. The mortality rate passed from 15.9 events per 100 person-years in patients belonging to the lowest NLR tertile to 52.8 in those in the highest tertile. The optimal cut-off value which best classified patients with the lowest and the highest mortality rate was set at the NLR value of 2.315. Indeed, the mortality rate of patients with an NLR value above such cut-off was twice the mortality rate of patients with a value below the cut-off (age adjusted hazard ratio (HR): 2.16, 95% confidence interval (CI): 1.32–3.53). In the PRO-ACT validation sample, patients with an NLR value above the cut-off consistently had a higher mortality rate than those with a value below the cut-off (age adjusted HR: 1.17, 95%CI: 1.01–1.35). Conclusions: NLR could be a candidate easy, fast, and low-cost marker of disease progression and survival in ALS. It may be associated with low-grade inflammation either as a direct mirror of the pathological process of disease progression, or as a consequence of neuronal death (reverse causation). However, prospective studies are needed to understand whether NLR changes during the course of the disease, before using it to monitor disease progression in ALS.

Amyotrophic lateral sclerosis is the most common form of motor neuron disease. Mutations in TARDBP, the gene encoding the RNA-binding protein TDP-43, are responsible for about 5% of familial ALS. Here we report the clinical and biological features of an ALS patients with pA382T mutation in TPD-43 protein. Disease began with right hand muscles weakness, and equally involved upper and lower motor neuron with a classic phenotype, without cognitive impairment. While a family history of neurological diseases was reported, there was no evidence of familial frontotemporal dementia. Cultured fibroblasts from the patient were characterized by profound alterations of cell proteome, which impacts particularly the mitochondrial metabolic pathways and the endoplasmic reticulum. TDP-43 levels were similar to control, healthy fibroblasts, but a higher fraction localized in mitochondria. Mitochondrial network appeared fragmented, and the organelles smaller and more spheric. In agreement with impaired proteome and morphology of mitochondria, basal cell respiration was reduced. Mitochondrial DNA levels appeared normal. However, a higher amount of mitochondrial DNA was present in the cytosol, suggesting a pronounced mitochondrial DNA misplacement which can promote a pro-inflammatory response mediating by cGAS/STING. Thus, this case report further expands the clinical and pathological phenotype of A382T mutation.

Increased incidence rates of amyotrophic lateral sclerosis (ALS) have been recently reported across various Western countries, although geographic and temporal variations in terms of incidence, clinical features and genetics are not fully elucidated. This study aimed to describe demographic, clinical feature and genotype–phenotype correlations of ALS cases over the last decade in the Emilia Romagna Region (ERR). From 2009 to 2019, our prospective population-based registry of ALS in the ERR of Northern Italy recorded 1613 patients receiving a diagnosis of ALS. The age- and sex-adjusted incidence rate was 3.13/100,000 population (M/F ratio: 1.21). The mean age at onset was 67.01 years; women, bulbar and respiratory phenotypes were associated with an older age, while C9orf72-mutated patients were generally younger. After peaking at 70–75 years, incidence rates, among women only, showed a bimodal distribution with a second slight increase after reaching 90 years of age. Familial cases comprised 12%, of which one quarter could be attributed to an ALS-related mutation. More than 70% of C9orf72-expanded patients had a family history of ALS/fronto-temporal dementia (FTD); 22.58% of patients with FTD at diagnosis had C9orf72 expansion (OR 6.34, p = 0.004). In addition to a high ALS incidence suggesting exhaustiveness of case ascertainment, this study highlights interesting phenotype–genotype correlations in the ALS population of ERR.

Although mutations in the superoxide dismutase 1 gene account for only a minority of total amyotrophic lateral sclerosis cases, the discovery of this gene has been crucial for amyotrophic lateral sclerosis research. Since the identification of superoxide dismutase 1 in 1993, the field of amyotrophic lateral sclerosis genetics has considerably widened, improving our understanding of the diverse pathogenic basis of amyotrophic lateral sclerosis. In this review, we focus on cognitive impairment in superoxide dismutase 1-amyotrophic lateral sclerosis patients. Literature has mostly reported that cognition remains intact in superoxide dismutase 1-amyotrophic lateral sclerosis patients, but recent reports highlight frontal lobe function frailty in patients carrying different superoxide dismutase 1-amyotrophic lateral sclerosis mutations. We thoroughly reviewed all the various mutations reported in the literature to contribute to a comprehensive database of superoxide dismutase 1-amyotrophic lateral sclerosis genotype-phenotype correlation. Such a resource could ultimately improve our mechanistic understanding of amyotrophic lateral sclerosis, enabling a more robust assessment of how the amyotrophic lateral sclerosis phenotype responds to different variants across genes, which is important for the therapeutic strategy targeting genetic mutations. Cognition in superoxide dismutase 1-amyotrophic lateral sclerosis deserves further longitudinal research since this peculiar frailty in patients with similar mutations can be conditioned by external factors, including environment and other unidentified agents including modifier genes.