Background and Aims:

The two-month lockdown period during COVID-19 pandemic had a general impact on health treatments and care assistance. We wanted to assess Quality of life (QoL) of ALS patients and the burden of their caregivers during that period.

Methods:

60 patients and 59 caregivers, visited in telemedicine during March 2020, underwent the assessment of patients’ QoL (McGill QoL Questionnaire), general health status (EQ-5D-5L) and caregiver burden (Zarit Burden Interview [ZBI]). These phone scales were administered in April 2020 (T1) and repeated one month after the end of lockdown (T2), with the addition of a qualitative questionnaire (COVID-QoL-Questionnaire), exploring family reorganization and personal perception of lockdown.

Wilcoxon signed-rank test and the chi-squared test were used.

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 mildly inversely correlated at T1 (p<0.05, rho=-0.265); no significant correlations were found at T2. According to the COVID-QoL-Questionnaire, both patients and caregivers were able to consult their physicians while at home (60% and 66.1% respectively). Moreover, caregivers perceived lower family help compared to patients (p<0.001).

Conclusions:

In our cohort of ALS patients, QoL and caregiver burden were not compromised by restriction measures during COVID-19 pandemic, while caregiver burden significantly increased. Probably, this is due to the motor impairment in ALS patients, which did not perceive changing in life conditions. Instead, the reported increased burden for primary caregivers could be explained by the restriction of family help, reflecting the importance of a wide social support in ALS patients’ management.

Background and Aims:

ALS phenotype widely vary across patients. It is unclear if different etiologies could justify this variability. Spatial epidemiology could give some hints on the etiology of diseases by identifying clusters and looking for their genetic or environmental causes. The aim of the study was to perform a spatial analysis of ALS cases stratified by their clinical presentation.

Methods:

All patients included in the Piemonte and Valle d’Aosta ALS Register who received an ALS diagnosis between 2007 and 2014 and who were resident in Piemonte at the time of diagnosis were considered. Cluster analysis was performed stratifying patients by sex, age at diagnosis, onset site and phenotype (classified as classic, flail arm, flail leg, predominant UMN, bulbar and respiratory). All analyses were performed both including and excluding genetic cases to consider a possible different susceptibility to environmental exposure. Cluster analyses were assessed using the Kulldorff spatial scan statistic.

Results:

A total of 943 patients were included. No significant clusters were revealed for any of the subgroups considered with the only exception of a small low-incidence cluster of flail arm patients located in Northern Piedmont (over 201 municipalities with 655537 residents, 7.86 cases were expected and none was observed, relative risk=0.0, p=0.024). Analyses excluding genetic cases did not modify the results.

Conclusions:

Our data, based on the geographical distribution of cases, do not indicate that different ecological factors underlie the diversity of ALS clinical presentation. A stratification based on genetics could be considered when looking for susceptibility to different environmental factors.

Background and Aims:

Spirometry is commonly used to monitor respiratory function in Amyotrophic Lateral Sclerosis (ALS). However, its use is poorly accurate in patients with bulbar or cognitive impairment. Arterial blood gas analysis (ABG) correlates moderately with forced vital capacity (FVC).

We aimed at investigating if the assessment of the ALSFRS-r respiratory items (10 and 11) increases the correlation between ABG and FVC in a cohort of ALS patients.

Methods:

We selected the first ABG performed before non-invasive ventilation by ALS patients. The best combination to predict FVC was assessed by studying the correlations of different combinations of FVC% with ABG parameters (carbon dioxide, pCO2; carbonate, HCO3-) and respiratory symptoms (dyspnea and orthopnea were considered present if ALSFRS-R items 10 and 11 were <4, respectively). Clinical and epidemiological characteristics were compared between patients with and without respiratory symptoms, grouped according to ABG values.

Results:

A total of 488 ABGs were collected. The best combination to predict FVC was: pCO2 plus HCO3- plus ALSFRS-R item 10 (R=0.430, p <0.001). Patients with dyspnea showed a more severe motor impairment, a higher disease progression rate and lower FVC values. Patients with normal ABG and dyspnea had a reduced survival than patients without dyspnea (0.91 years, IQR 0.46-1.91 vs 1.46 years, IQR 0.89-2.29, p=0.002). Cognitive dysfunction did not influence the complaining of dyspnea (OR 1.009, 95% CI 0.837-1.215, p=0.927).

Conclusions:

Combining ABG with clinical evaluation of dyspnea improves the ability to assess early respiratory dysfunction in ALS, especially in patients with bulbar or cognitive impairment.

Background and Aims:

The complex genetic landscape in ALS presents a significant challenge. Despite the increasing number of pathogenic/risk mutations reported in ALS, the true proportion of cases that can be attributed to genetic factors remains unclear, and the actual role of genome-wide screening in clinical practice is still undetermined. Here we provide a comprehensive analysis of the spectrum of genetic risk in ALS patients and assess the clinical utility of performing whole-genome sequencing (WGS).

Methods:

WGS was performed on 1050 ALS cases and 675 controls from an Italian population-based ALS cohort. We screened for coding single-nucleotide variants, indels and repeated expansions in 40 ALS-related genes. Variants were classified according to a pipeline that accounted for allele frequency, absence from the control cohort, and integrated pathogenicity scores.

Results:

We identified 62 pathogenic variants, 32 loss-of-function variants and 61 variants classified as deleterious according to our pipeline. These variants were observed in 188 patients (17.9% of our cohort). Furthermore, WGS correctly identified 79 patients (7.5%) who carried the C9ORF72 expansion. Overall, 25.4% of our cohort carried a pathogenic mutation, and 3% of cases were found to carry multiple pathogenic variants. Age at onset (p<0.0252) and family history (p< 0.00001) predicted the likelihood of finding an underlying genetic factor.

Conclusions:

We conclusively show that genetic mutations and risk factors in ALS patients are more common than previously thought, thus highlighting that genetics play a central role in ALS pathogenesis. Whole-genome testing should be offered to all patients diagnosed with ALS for both diagnostic and prognostic purposes.

Background and Aims:

Psychological status has already been related to clinical outcome in ALS, as well as in other neurological disease, without considering the specific role of anxiety and depression.

Methods:

We collected all Hospital Anxiety and Depression scale (HADS) questionnaires administered to patients at diagnosis from 2008 to 2018 in the Turin ALS Centre during a full neuropsychological evaluation. We analyzed the frequency of both anxiety and depression in ALS patients, their association to clinical features and their prognostic role, adjusting for different motor and cognitive confounders, using Cox proportional hazard models and Kaplan-Maier curves.

Results:

Data from 569 patients were collected. HADS-A and HADS-D scores showed moderate correlation (0.485, p<0.001). HADS Severity scores are showed in Figure 1.

Depression was significantly correlated to age, total ALSFRS-R score and cognitive impairment, while anxiety showed only a minimal correlation to ALSFRS-R score (-0.108, p=0.022). Cox proportional hazard model showed that HADS-A was related to overall survival, but not HADS-D (HADS-A: HR 1.040, CI 1.012-1.069, p=0.005; HADS-D: HR 1.013, CI 0.976-1.052, p=0.497). The best discriminating cut-off for both HADS-A was 6 (HR HADS-A>6 1.453, CI 1.151-1.835, p=0.002; log-rank test p=0.012, see Figure 2 for KM curves).

Interestingly, HADS-D raw scores resulted to be prognostic only in patients with comorbid anxiety (Figure 3).

Conclusions:

Anxiety is more frequent than depression in ALS patients at diagnosis and, unlike depression, seems not to be related to motor and cognitive features and to disease duration. Anxiety is also an independent prognostic factor, similarly to what happens in other non-neurological disease.

Background and Aims:

ALS phenotype widely vary across patients. It is unclear if different etiologies could justify this variability. Spatial epidemiology could give some hints on the etiology of diseases by identifying clusters and looking for their genetic or environmental causes. The aim of the study was to perform a spatial analysis of ALS cases stratified by their clinical presentation.

Methods:

All patients included in the Piemonte and Valle d’Aosta ALS Register who received an ALS diagnosis between 2007 and 2014 and who were resident in Piemonte at the time of diagnosis were considered. Cluster analysis was performed stratifying patients by sex, age at diagnosis, onset site and phenotype (classified as classic, flail arm, flail leg, predominant UMN, bulbar and respiratory). All analyses were performed both including and excluding genetic cases to consider a possible different susceptibility to environmental exposure. Cluster analyses were assessed using the Kulldorff spatial scan statistic.

Results:

A total of 943 patients were included. No significant clusters were revealed for any of the subgroups considered with the only exception of a small low-incidence cluster of flail arm patients located in Northern Piedmont (over 201 municipalities with 655537 residents, 7.86 cases were expected and none was observed, relative risk=0.0, p=0.024). Analyses excluding genetic cases did not modify the results.

Conclusions:

Our data, based on the geographical distribution of cases, do not indicate that different ecological factors underlie the diversity of ALS clinical presentation. A stratification based on genetics could be considered when looking for susceptibility to different environmental factors.