Manifold learning for amyotrophic lateral sclerosis functional loss assessment : Development and validation of a prognosis model.

Amyotrophic lateral sclerosis (ALS) is an inexorably progressive neurodegenerative condition with no effective disease-modifying therapy at present. Given the striking clinical heterogeneity of the condition, the development and validation of reliable prognostic models is a recognised research priority. We present a prognostic model for functional decline in ALS where outcome uncertainty is taken into account. Patient data were reduced and projected onto a 2D space using Uniform Manifold Approximation and Projection (UMAP), a novel non-linear dimension reduction technique. Information from 3756 patients was included. Development data were sourced from past clinical trials. Real-world population data were used as validation data. Predictors included age, gender, region of onset, symptom duration, weight at baseline, functional impairment, and estimated rate of functional loss. UMAP projection of patients showed an informative 2D data distribution. As limited data availability precluded complex model designs, the projection was divided into three zones defined by a functional impairment range probability. Zone membership allowed individual patient prediction. Patients belonging to the first zone had a probability of [Formula: see text] (± [Formula: see text]) to have an ALSFRS score over 20 at 1-year follow-up. Patients within the second zone had a probability of [Formula: see text] (± [Formula: see text]) to have an ALSFRS score between 10 and 30 at 1 year follow-up. Finally, patients within the third zone had a probability of [Formula: see text] (± [Formula: see text]) to have an ALSFRS score lower than 20 at 1 year follow-up. This approach requires a limited set of features, is easily updated, improves with additional patient data, and accounts for results uncertainty. This method could therefore be used in a clinical setting for patient stratification and outcome projection.

Development and validation of a 1-year survival prognosis estimation model for Amyotrophic Lateral Sclerosis using manifold learning algorithm UMAP.

Amyotrophic Lateral Sclerosis (ALS) is an inexorably progressive neurodegenerative condition with no effective disease modifying therapies. The development and validation of reliable prognostic models is a recognised research priority. We present a prognostic model for survival in ALS where result uncertainty is taken into account. Patient data were reduced and projected onto a 2D space using Uniform Manifold Approximation and Projection (UMAP), a novel non-linear dimension reduction technique. Information from 5,220 patients was included as development data originating from past clinical trials, and real-world population data as validation data. Predictors included age, gender, region of onset, symptom duration, weight at baseline, functional impairment, and estimated rate of functional loss. UMAP projection of patients shows an informative 2D data distribution. As limited data availability precluded complex model designs, the projection was divided into three zones with relevant survival rates. These rates were defined using confidence bounds: high, intermediate, and low 1-year survival rates at respectively [Formula: see text] ([Formula: see text]), [Formula: see text] ([Formula: see text]) and [Formula: see text] ([Formula: see text]). Predicted 1-year survival was estimated using zone membership. This approach requires a limited set of features, is easily updated, improves with additional patient data, and accounts for results uncertainty.

Alexithymia in Amyotrophic Lateral Sclerosis and Its Neural Correlates.

Introduction: Amyotrophic lateral sclerosis (ALS) is a severe neurodegenerative disease that causes progressive and extensive motor deficits. Patients may also have cognitive impairments or alteration of emotional processing. Very few studies, however, have looked at deficits in how they experience their own feelings (alexithymia). Methods: We assessed alexithymia in 28 patients with ALS using the 20-item Toronto Alexithymia Scale (TAS-20), comparing them with a control group matched for sex, age, and education level. We took into account both the total score of the TAS-20 and its three subscores corresponding to the three dimensions of alexithymia: Difficulty Identifying Feelings (DIF), Difficulty Describing Feelings (DDF), and Externally Oriented Thinking (EOT). Patients also underwent a neuropsychological assessment and anatomical magnetic resonance imaging (MRI) in order to correlate cognitive performances and gray matter volume and level of alexithymia. Results: On average, ALS subjects had a significantly higher total score and DIF sub-score of the TAS-20 than controls indicating an increased alexithymia in patients. Total and DIF Scores correlated significantly and negatively to gray matter volume of the prefrontal cortex, right superior temporal pole and parahippocampal gyri. No correlations were found between scores on executive functions and those on the TAS-20. Conclusion: The first stage of one's own emotional processing seems to be affected in ALS independently of executive dysfunction. This trouble seems to be underpinned by cerebral regions that are well known to be both implicated in alexithymia in healthy subjects and altered in ALS.

Neural substrate of cognitive theory of mind impairment in amyotrophic lateral sclerosis.

We now know that amyotrophic lateral sclerosis (ALS) is not restricted to the motor system. Indeed, a large proportion of patients with ALS exhibit cognitive impairment, especially executive dysfunction or language impairment. Although researchers have recently turned their attention to theory of mind (ToM) in ALS, only five studies have been performed so far, and they reported somewhat contradictory results. Moreover, the neural basis of the potential ToM deficit in ALS remains largely unknown. The present study was therefore designed to clarify whether a cognitive ToM deficit is indeed associated with ALS, specify the putative link between cognitive ToM deficits and executive dysfunction in ALS, and identify the dysfunctional brain regions responsible for any social cognition deficits. We investigated cognitive ToM and executive functions in a group of 23 patients with ALS and matched healthy controls, using an original false-belief task and a specially designed battery of executive tasks. We also performed an (18)F-fluorodeoxyglucose positron emission tomography examination. Results confirmed the presence of cognitive ToM deficits in patients compared with controls, and revealed significant correlations between ToM and executive functions, although the cognitive ToM deficit persisted when a composite executive function score was entered as a covariate. Using statistical parametric mapping, we calculated positive correlations between tracer uptake and false-belief scores on a voxel-by-voxel basis in the patient sample. Results showed that the cognitive ToM deficit correlated with the dorsomedial and dorsolateral prefrontal cortices, as well as the supplementary motor area. Our findings provide compelling clinical and imaging evidence for the presence of a genuine cognitive ToM deficit in patients with ALS.