Metabolomics in amyotrophic lateral sclerosis: how far can it take us?

Amyotrophic lateral sclerosis (ALS) is the most common adult-onset motor neuron disease. Alongside identification of aetiologies, development of biomarkers is a foremost research priority. Metabolomics is one promising approach that is being utilized in the search for diagnosis and prognosis markers. Our aim is to provide an overview of the principal research in metabolomics applied to ALS. References were identified using PubMed with the terms 'metabolomics' or 'metabolomic' and 'ALS' or 'amyotrophic lateral sclerosis' or 'MND' or 'motor neuron disorders'. To date, nine articles have reported metabolomics research in patients and a few additional studies examined disease physiology and drug effects in patients or models. Metabolomics contribute to a better understanding of ALS pathophysiology but, to date, no biomarker has been validated for diagnosis, principally due to the heterogeneity of the disease and the absence of applied standardized methodology for biomarker discovery. A consensus on best metabolomics methodology as well as systematic independent validation will be an important accomplishment on the path to identifying the long-awaited biomarkers for ALS and to improve clinical trial designs.

Biomarkers in amyotrophic lateral sclerosis: combining metabolomic and clinical parameters to define disease progression.

BACKGROUND AND PURPOSE: The objectives of this study were to define the metabolomic profile of cerebrospinal fluid in amyotrophic lateral sclerosis (ALS) patients, to model outcome through combined clinical and metabolomic parameters and independently to validate predictive models. METHODS: In all, 74 consecutive newly diagnosed patients were enrolled into training (Tr, n = 49) and test (Te, n = 25) cohorts. Investigators recorded clinical data and the metabalomic profile of cerebrospinal fluid at baseline was analyzed with (1)H nuclear magnetic resonance spectroscopy. Markers of disease progression, collected in 1-year prospective follow-up, included change in ALS Functional Rating Scale (var_ALSFRS), change in weight (var_weight) and survival time. Stepwise multiple regression selected from metabolomic and clinical parameters to model rate of progression in the Tr cohort. Best fit models were validated independently in the Te cohort. RESULTS: The best-fit statistical models, using both metabolomic and clinical covariates, predicted outcome with 70.8% (var_weight), 72% (var_ALSFRS) and 76% (survival) accuracy in the Te cohort. Models that used metabolomics or clinical data alone predicted outcome less well. Highlighted metabolites are involved in pathophysiological pathways previously described in ALS. CONCLUSION: Cerebrospinal fluid metabolomics can aid in predicting the clinical course of ALS and tap into pathophysiological processes. The precision of predictive models, independently reproduced in this study, is enhanced through inclusion of both metabolomic and clinical parameters. The findings bring the field closer to a clinically meaningful disease marker.

Biological follow-up in amyotrophic lateral sclerosis: decrease in creatinine levels and increase in ferritin levels predict poor prognosis.

BACKGROUND AND PURPOSE: Amyotrophic lateral sclerosis (ALS) is a fatal disorder of the motor neuron system, with a median survival of 2 to 4 years and a wide variety of prognosis. Thus, there is a critical need for diagnosis and prognosis biomarkers to improve the care of patients in routine practice. In this study, we aimed to determine prognostic value of routine biochemical markers in sporadic ALS (SALS). METHODS: We retrospectively collected clinical and biological data obtained during the systematic routine monitoring of 216 sporadic ALS patients. The main outcomes were disease duration and annual decline of Revised ALS Functional Rating Scale (ALSFRS-R). Changes to these biological variables over time were assessed, in link with disease progression. RESULTS: We found that concentrations of creatinine (P=0.0166) and ferritin (P=0.0306) changed significantly during the progression of ALS. A reduction of creatinine levels and an increase of ferritin levels were associated with disease progression. Multivariate analysis showed that early variation of ferritin was an independent predictive factor of patient survival (P=0.0048). CONCLUSION: Changes to ferritin and creatinine levels with time are associated with ALS progression. This is the first study describing the changes to these biological variables during ALS progression.