Mitochondrial D-loop methylation levels inversely correlate with disease duration in amyotrophic lateral sclerosis

Supplementary material</p

Microstructural Correlates of Emotional Attribution Impairment in Non-Demented Patients with Amyotrophic Lateral Sclerosis

<div><p>Impairments in the ability to recognize and attribute emotional states to others have been described in amyotrophic lateral sclerosis patients and linked to the dysfunction of key nodes of the emotional empathy network. Microstructural correlates of such disorders are still unexplored. We investigated the white-matter substrates of emotional attribution deficits in a sample of amyotrophic lateral sclerosis patients without cognitive decline. Thirteen individuals with either probable or definite amyotrophic lateral sclerosis and 14 healthy controls were enrolled in a Diffusion Tensor Imaging study and administered the Story-based Empathy Task, assessing the ability to attribute mental states to others (i.e., Intention and Emotion attribution conditions). As already reported, a significant global reduction of empathic skills, mainly driven by a failure in Emotion Attribution condition, was found in amyotrophic lateral sclerosis patients compared to healthy subjects. The severity of this deficit was significantly correlated with fractional anisotropy along the forceps minor, genu of corpus callosum, right uncinate and inferior fronto-occipital fasciculi. The involvement of frontal commissural fiber tracts and right ventral associative fronto-limbic pathways is the microstructural hallmark of the impairment of high-order processing of socio-emotional stimuli in amyotrophic lateral sclerosis. These results support the notion of the neurofunctional and neuroanatomical continuum between amyotrophic lateral sclerosis and frontotemporal dementia.</p></div

Demographic information and clinical characteristics.

<p>Demographic information and clinical characteristics.</p

TBSS Whole-brain comparison between ALS patients and HC.

<p>Whole-brain comparison between ALS patients and HC showing a significant fractional anisotropy (FA) reduction (p>0.01 uncorrected) along the bilateral corticospinal tract (CST). Statistical map is superimposed to the FMRIB standard-space FA template.</p

Correlation between white-matter microstructure and Emotion Attribution (EA) scores in ALS patients.

<p>Significant correlation between microstructural white-matter integrity (i.e., fractional anisotropy index) and EA performances in ALS patients. Statistical maps (p<0.05, FWE-corrected) are superimposed to the FMRIB standard-space FA template.</p

group differences on mental states attribution abilities.

<p>group differences on mental states attribution abilities.</p

The natural history of ALS: Baseline characteristics from a multicenter clinical cohort

Amyotrophic lateral sclerosis (ALS) is a rare disease with urgent need for improved treatment. Despite the acceleration of research in recent years, there is a need to understand the full natural history of the disease. As only 40% of people living with ALS are eligible for typical clinical trials, clinical trial datasets may not generalize to the full ALS population. While biomarker and cohort studies have more generous inclusion criteria, these too may not represent the full range of phenotypes, particularly if the burden for participation is high. To permit a complete understanding of the heterogeneity of ALS, comprehensive data on the full range of people with ALS is needed. The ALS Natural History Consortium (ALS NHC) consists of nine ALS clinics and was created to build a comprehensive dataset reflective of the ALS population. At each clinic, most patients are asked to participate and about 95% do. After obtaining consent, a minimum dataset is abstracted from each participant’s electronic health record. Participant burden is therefore minimal. Data on 1925 ALS patients were submitted as of 9 December 2022. ALS NHC participants were more heterogeneous relative to anonymized clinical trial data from the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database. The ALS NHC includes ALS patients of older age of onset and a broader distribution of El Escorial categories, than the PRO-ACT database. ALS NHC participants had a higher diversity of diagnostic and demographic data compared to ALS clinical trial participants.Key MessagesWhat is already known on this topic: Current knowledge of the natural history of ALS derives largely from regional and national registries that have broad representation of the population of people living with ALS but do not always collect covariates and clinical outcomes. Clinical studies with rich datasets of participant characteristics and validated clinical outcomes have stricter inclusion and exclusion criteria that may not be generalizable to the full ALS population.What this study adds: To bridge this gap, we collected baseline characteristics for a sample of the population of people living with ALS seen at a consortium of ALS clinics that collect extensive, pre-specified participant-level data, including validated outcome measures.How this study might affect research, practice, or policy: A clinic-based longitudinal dataset can improve our understanding of the natural history of ALS and can be used to inform the design and analysis of clinical trials and health economics studies, to help the prediction of clinical course, to find matched controls for open label extension trials and expanded access protocols, and to document real-world evidence of the impact of novel treatments and changes in care practice. What is already known on this topic: Current knowledge of the natural history of ALS derives largely from regional and national registries that have broad representation of the population of people living with ALS but do not always collect covariates and clinical outcomes. Clinical studies with rich datasets of participant characteristics and validated clinical outcomes have stricter inclusion and exclusion criteria that may not be generalizable to the full ALS population. What this study adds: To bridge this gap, we collected baseline characteristics for a sample of the population of people living with ALS seen at a consortium of ALS clinics that collect extensive, pre-specified participant-level data, including validated outcome measures. How this study might affect research, practice, or policy: A clinic-based longitudinal dataset can improve our understanding of the natural history of ALS and can be used to inform the design and analysis of clinical trials and health economics studies, to help the prediction of clinical course, to find matched controls for open label extension trials and expanded access protocols, and to document real-world evidence of the impact of novel treatments and changes in care practice.</p