{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Goutman SA"],"funding":["National ALS Registry/CDC/ATSDR","ATSDR CDC HHS","NCATS NIH HHS","NCI","NIEHS NIH HHS","NIEHS","NCI NIH HHS","National Institutes of Health"],"pagination":["4425-4439"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9762943"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["145(12)"],"pubmed_abstract":["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."],"journal":["Brain : a journal of neurology"],"pubmed_title":["Metabolomics identifies shared lipid pathways in independent amyotrophic lateral sclerosis cohorts."],"pmcid":["PMC9762943"],"funding_grant_id":["U01 CA235487","K23 ES027221","200-2013-56856","UL1 TR002240","K23ES027221","UL1TR002240","R01 ES030049","R01ES030049","1U01CA235487","1R01TS000289","R01 TS000289"],"pubmed_authors":["Habra H","Savelieff MG","Hur J","Guo K","Feldman EL","Patterson A","Goutman SA","Karnovsky A","Sakowski SA"],"additional_accession":[]},"is_claimable":false,"name":"Metabolomics identifies shared lipid pathways in independent amyotrophic lateral sclerosis cohorts.","description":"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.","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Dec","modification":"2026-06-02T16:19:49.268Z","creation":"2025-04-07T01:56:26.419Z"},"accession":"S-EPMC9762943","cross_references":{"pubmed":["35088843"],"doi":["10.1093/brain/awac025"]}}