Background and Objectives Pathogenic variations in fused in sarcoma (FUS) are among the most common genetic causes of amyotrophic lateral sclerosis (ALS) worldwide. They are supposedly characterized by a homogeneous pure motor phenotype with early-onset and short disease duration. However, a few FUS-mutated cases with a very late disease onset and slow progression have been reported. To analyze genotype-phenotype correlations and identify the prognostic factors in FUS-ALS cases. Methods We identified and cross-sectionally analyzed 22 FUS-ALS patient histories from a single-center cohort of 2,615 genetically tested patients and reviewed 289 previously published FUS-ALS cases. Survival analysis was performed by Kaplan-Meier survival curves, followed by the log-rank test and multivariate Cox analysis. Results Survival of FUS-ALS is age-dependent: In our cohort, early-onset cases had a rapid disease progression and short survival (p = 0.000003) while the outcome of FUS-mutated patients with mid-to-late onset did not differ from non–FUS-ALS patients (p = 0.437). Meta-analysis of literature data confirmed this trend (p = 0.00003). This survival pattern is not observed in other ALS-related genes in our series. We clustered FUS-ALS patients in 3 phenotypes: (1) axial ALS, with upper cervical and dropped-head onset in mid-to-late adulthood; (2) benign ALS, usually with a late-onset and slow disease progression; and (3) juvenile ALS, often with bulbar onset and preceded by learning disability or mild mental retardation. Those phenotypes arise from different mutations. Discussion We observed specific genotype-phenotype correlations of FUS-ALS and identified age at onset as the most critical prognostic factor. Our results demonstrated that FUS mutations underlie a specific subtype of ALS and enable a careful stratification of newly diagnosed FUS-ALS cases for clinical course and potential therapeutic windows. This will be crucial in the light of incoming gene-specific therapy.

Objective To assess the burden of rare genetic variants and to estimate the contribution of known amyotrophic lateral sclerosis (ALS) genes in an Italian population-based cohort, we performed whole genome sequencing in 959 patients with ALS and 677 matched healthy controls. Methods We performed genome sequencing in a population-based cohort (Piemonte and Valle d9Aosta Registry for ALS [PARALS]). A panel of 40 ALS genes was analyzed to identify potential disease-causing genetic variants and to evaluate the gene-wide burden of rare variants among our population. Results A total of 959 patients with ALS were compared with 677 healthy controls from the same geographical area. Gene-wide association tests demonstrated a strong association with SOD1, whose rare variants are the second most common cause of disease after C9orf72 expansion. A lower signal was observed for TARDBP, proving that its effect on our cohort is driven by a few known causal variants. We detected rare variants in other known ALS genes that did not surpass statistical significance in gene-wise tests, thus highlighting that their contribution to disease risk in our cohort is limited. Conclusions We identified potential disease-causing variants in 11.9% of our patients. We identified the genes most frequently involved in our cohort and confirmed the contribution of rare variants in disease risk. Our results provide further insight into the pathologic mechanism of the disease and demonstrate the importance of genome-wide sequencing as a diagnostic tool.

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. 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. 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. 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.

We describe the telemedicine experience of an Italian ALS tertiary Center during COVID-19 pandemic. A total of 144 visits were scheduled between 6th March and 6th April 2020. These mostly consisted of neurological or psychological visits (139, 96.5%). One hundred thirty-nine (96.5%) visits were performed as telemedicine and mostly via phone call (112, 80.6%). Three (2.1%) visits were considered as urgent and maintained as outpatient care. Additionally, patients were still able to telephone, being put through directly to their neurologists. Many requests of contact were addressed at getting information about the scheduled visits or examinations (45, 43.3%). Globally, patients and caregivers were satisfied with the telemedicine service. However, the majority (85, 65.9%) would prefer a face-to-face visit. In conclusion, telemedicine could be considered a good complement to face-to-face care, even after social restrictions have been eased.

ALS etiology and prognostic factors are mostly unknown. Metabolic diseases and especially diabetes mellitus (DM) have been variously related to ALS. However, pieces of evidence have been variegated and often conflicting so far. This review aims to give an overview of recent contributions focusing on the relationship between DM and ALS. DM seems to reduce the risk of developing ALS if diagnosed at a younger age; conversely, when diagnosed at an older age, DM seems protective against ALS. Such a relationship was not confirmed in Asian countries where DM increases the risk of ALS independently of the age of onset. Interestingly, DM does not affect ALS prognosis, possibly weakening the potential causal relationship between the two diseases. However, since most studies are observational, it is difficult to state the exact nature of such a relationship and several hypotheses have been made. A recent study using Mendelian randomization suggested that DM is indeed protective against ALS in the European population. However, these analyses are not without limits and further evidence is needed. DM is usually the core of a larger metabolic syndrome. Thus, other metabolic changes such as dyslipidemia, body mass index, and cardiovascular diseases should be collectively considered. Finally, hypermetabolism usually found in ALS patients should be considered too since all these metabolic changes could be compensation (or the cause) of the higher energy expenditure.