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Amyotrophic lateral sclerosis (ALS) is a fatal disease of motor neuron degeneration with typical survival of only 2–5 years from diagnosis. The causes of ALS are multifactorial: known genetic mutations account for only around 70% of cases of familial ALS and 15% of sporadic cases, and heritability estimates range from 8% to 61%, indicating additional causes beyond genetics. Consequently, interest has grown in environmental contributions to ALS risk and progression. The gene–time–environment hypothesis posits that ALS onset occurs through an interaction of genes with environmental exposures during ageing. An alternative hypothesis, the multistep model of ALS, suggests that several hits, at least some of which could be environmental, are required to trigger disease onset, even in the presence of highly penetrant ALS-associated mutations. Studies have sought to characterize the ALS exposome — the lifetime accumulation of environmental exposures that increase disease risk and affect progression. Identifying the full scope of environmental toxicants that enhance ALS risk raises the prospect of preventing disease by eliminating or mitigating exposures. In this Review, we summarize the evidence for an ALS exposome, discussing the strengths and limitations of epidemiological studies that have identified contributions from various sources. We also consider potential mechanisms of exposure-mediated toxicity and suggest future directions for ALS exposome research. The amyotrophic lateral sclerosis exposome is the lifetime accumulation of environmental exposures that increase disease risk and affect progression. This Review summarizes the literature that has sought to characterize aspects of the amyotrophic lateral sclerosis exposome and considers potential mechanisms of exposure-induced toxicity. Key points: Amyotrophic lateral sclerosis (ALS) is a fatal disease of motor neuron degeneration, with both genetic and environmental factors contributing to the risk and rate of disease progression. The gene–time–environment hypothesis of ALS posits that disease arises from an interaction of genetic burden with environmental burden over the life course. The multistep model of ALS posits that multiple 'hits', some of which are presumed to be environmental in origin, trigger disease onset, even in carriers of highly penetrant mutations. Epidemiological studies suggest potential contributions to the ALS exposome from pesticides, occupational exposures, sports and physical activity, metals, air pollution, trauma, electromagnetic fields, the gut microbiome, diet and lifestyle factors. The mechanisms underlying the effects of environmental factors on ALS risk remain incompletely understood but might involve neurotoxicity from specific environmental toxins, microbiome-mediated changes, epigenetic restructuring, systemic and central inflammation and excitotoxicity. Most studies of the ALS exposome have a retrospective design using questionnaires and are, therefore, prone to recall bias and other limitations. Future studies will require prospective, longitudinal designs that include quantification of exposures in biosamples in addition to questionnaires. [ABSTRACT FROM AUTHOR]

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease lacking effective treatments. This is due, in part, to a complex and incompletely understood pathophysiology. To shed light, we conducted untargeted metabolomics on plasma from two independent cross-sectional ALS cohorts versus control participants to identify recurrent dysregulated metabolic pathways. Untargeted metabolomics was performed on plasma from two ALS cohorts (cohort 1, n = 125; cohort 2, n = 225) and healthy controls (cohort 1, n = 71; cohort 2, n = 104). Individual differential metabolites in ALS cases versus controls were assessed by Wilcoxon, adjusted logistic regression and partial least squares-discriminant analysis, while group lasso explored sub-pathway level differences. Adjustment parameters included age, sex and body mass index. Metabolomics pathway enrichment analysis was performed on metabolites selected using the above methods. Additionally, we conducted a sex sensitivity analysis due to sex imbalance in the cohort 2 control arm. Finally, a data-driven approach, differential network enrichment analysis (DNEA), was performed on a combined dataset to further identify important ALS metabolic pathways. Cohort 2 ALS participants were slightly older than the controls (64.0 versus 62.0 years, P = 0.009). Cohort 2 controls were over-represented in females (68%, P < 0.001). The most concordant cohort 1 and 2 pathways centred heavily on lipid sub-pathways, including complex and signalling lipid species and metabolic intermediates. There were differences in sub-pathways that were enriched in ALS females versus males, including in lipid sub-pathways. Finally, DNEA of the merged metabolite dataset of both ALS and control cohorts identified nine significant subnetworks; three centred on lipids and two encompassed a range of sub-pathways. In our analysis, we saw consistent and important shared metabolic sub-pathways in both ALS cohorts, particularly in lipids, further supporting their importance as ALS pathomechanisms and therapeutics targets. [ABSTRACT FROM AUTHOR]

Amyotrophic lateral sclerosis (ALS) is a complex, fatal neurodegenerative disease. Disease pathophysiology is incompletely understood but evidence suggests gut dysbiosis occurs in ALS, linked to impaired gastrointestinal integrity, immune system dysregulation and altered metabolism. Gut microbiome and plasma metabolome have been separately investigated in ALS, but little is known about gut microbe-plasma metabolite correlations, which could identify robust disease biomarkers and potentially shed mechanistic insight. Here, gut microbiome changes were longitudinally profiled in ALS and correlated to plasma metabolome. Gut microbial structure at the phylum level differed in ALS versus control participants, with differential abundance of several distinct genera. Unsupervised clustering of microbe and metabolite levels identified modules, which differed significantly in ALS versus control participants. Network analysis found several prominent amplicon sequence variants strongly linked to a group of metabolites, primarily lipids. Similarly, identifying the features that contributed most to case versus control separation pinpointed several bacteria correlated to metabolites, predominantly lipids. Mendelian randomization indicated possible causality from specific lipids related to fatty acid and acylcarnitine metabolism. Overall, the results suggest ALS cases and controls differ in their gut microbiome, which correlates with plasma metabolites, particularly lipids, through specific genera. These findings have the potential to identify robust disease biomarkers and shed mechanistic insight into ALS. [ABSTRACT FROM AUTHOR]

Introduction/Aims: Body mass index (BMI) is linked to amyotrophic lateral sclerosis (ALS) risk and prognosis, but additional research is needed. The aim of this study was to identify whether and when historical changes in BMI occurred in ALS participants, how these longer term trajectories associated with survival, and whether metabolomic profiles provided insight into potential mechanisms. Methods: ALS and control participants self‐reported body height and weight 10 (reference) and 5 years earlier, and at study entry (diagnosis for ALS participants). Generalized estimating equations evaluated differences in BMI trajectories between cases and controls. ALS survival was evaluated by BMI trajectory group using accelerated failure time models. BMI trajectories and survival associations were explored using published metabolomic profiling and correlation networks. Results: Ten‐year BMI trends differed between ALS and controls, with BMI loss in the 5 years before diagnosis despite BMI gains 10 to 5 years beforehand in both groups. An overall 10‐year drop in BMI associated with a 27.1% decrease in ALS survival (P =.010). Metabolomic networks in ALS participants showed dysregulation in sphingomyelin, bile acid, and plasmalogen subpathways. Discussion: ALS participants lost weight in the 5‐year period before enrollment. BMI trajectories had three distinct groups and the group with significant weight loss in the past 10 years had the worst survival. Participants with a high BMI and increase in weight in the 10 years before symptom onset also had shorter survival. Certain metabolomics profiles were associated with the BMI trajectories. Replicating these findings in prospective cohorts is warranted. See Editorial on pages 191‐192 in this issue [ABSTRACT FROM AUTHOR]

Amyotrophic lateral sclerosis is a fatal CNS neurodegenerative disease. Despite intensive research, current management of amyotrophic lateral sclerosis remains suboptimal from diagnosis to prognosis. Recognition of the phenotypic heterogeneity of amyotrophic lateral sclerosis, global CNS dysfunction, genetic architecture, and development of novel diagnostic criteria is clarifying the spectrum of clinical presentation and facilitating diagnosis. Insights into the pathophysiology of amyotrophic lateral sclerosis, identification of disease biomarkers and modifiable risks, along with new predictive models, scales, and scoring systems, and a clinical trial pipeline of mechanism-based therapies, are changing the prognostic landscape. Although most recent advances have yet to translate into patient benefit, the idea of amyotrophic lateral sclerosis as a complex syndrome is already having tangible effects in the clinic. This Seminar will outline these insights and discuss the status of the management of amyotrophic lateral sclerosis for the general neurologist, along with future prospects that could improve care and outcomes for patients with amyotrophic lateral sclerosis. [ABSTRACT FROM AUTHOR]

The diagnosis of amyotrophic lateral sclerosis can be challenging due to its heterogeneity in clinical presentation and overlap with other neurological disorders. Diagnosis early in the disease course can improve outcomes as timely interventions can slow disease progression. An evolving awareness of disease genotypes and phenotypes and new diagnostic criteria, such as the recent Gold Coast criteria, could expedite diagnosis. Improved prognosis, such as that achieved with the survival model from the European Network for the Cure of ALS, could inform the patient and their family about disease course and improve end-of-life planning. Novel staging and scoring systems can help monitor disease progression and might potentially serve as clinical trial outcomes. Lastly, new tools, such as fluid biomarkers, imaging modalities, and neuromuscular electrophysiological measurements, might increase diagnostic and prognostic accuracy. [ABSTRACT FROM AUTHOR]

Amyotrophic lateral sclerosis is a fatal neurodegenerative disease. The discovery of genes associated with amyotrophic lateral sclerosis, commencing with SOD1 in 1993, started fairly gradually. Recent advances in genetic technology have led to the rapid identification of multiple new genes associated with the disease, and to a new understanding of oligogenic and polygenic disease risk. The overlap of genes associated with amyotrophic lateral sclerosis with those of other neurodegenerative diseases is shedding light on the phenotypic spectrum of neurodegeneration, leading to a better understanding of genotype-phenotype correlations. A deepening knowledge of the genetic architecture is allowing the characterisation of the molecular steps caused by various mutations that converge on recurrent dysregulated pathways. Of crucial relevance, mutations associated with amyotrophic lateral sclerosis are amenable to novel gene-based therapeutic options, an approach in use for other neurological illnesses. Lastly, the exposome-the summation of lifetime environmental exposures-has emerged as an influential component for amyotrophic lateral sclerosis through the gene-time-environment hypothesis. Our improved understanding of all these aspects will lead to long-awaited therapies and the identification of modifiable risks factors. [ABSTRACT FROM AUTHOR]