Untargeted metabolomics yields insight into ALS disease mechanisms

Stephen A. Goutman, Jonathan Boss, Kai Guo, Fadhl M. Alakwaa, Adam Patterson, Sehee Kim, Masha Georges Savelieff, Junguk Hur, Eva L. Feldman

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Objective To identify dysregulated metabolic pathways in amyotrophic lateral sclerosis (ALS) versus control participants through untargeted metabolomics. Methods Untargeted metabolomics was performed on plasma from ALS participants (n=125) around 6.8 months after diagnosis and healthy controls (n=71). Individual differential metabolites in ALS cases versus controls were assessed by Wilcoxon rank-sum tests, adjusted logistic regression and partial least squares-discriminant analysis (PLS-DA), while group lasso explored sub-pathway-level differences. Adjustment parameters included sex, age and body mass index (BMI). Metabolomics pathway enrichment analysis was performed on metabolites selected by the above methods. Finally, machine learning classification algorithms applied to group lasso-selected metabolites were evaluated for classifying case status. Results There were no group differences in sex, age and BMI. Significant metabolites selected were 303 by Wilcoxon, 300 by logistic regression, 295 by PLS-DA and 259 by group lasso, corresponding to 11, 13, 12 and 22 enriched sub-pathways, respectively. 'Benzoate metabolism', 'ceramides', 'creatine metabolism', 'fatty acid metabolism (acyl carnitine, polyunsaturated)' and 'hexosylceramides' sub-pathways were enriched by all methods, and 'sphingomyelins' by all but Wilcoxon, indicating these pathways significantly associate with ALS. Finally, machine learning prediction of ALS cases using group lasso-selected metabolites achieved the best performance by regularised logistic regression with elastic net regularisation, with an area under the curve of 0.98 and specificity of 83%. Conclusion In our analysis, ALS led to significant metabolic pathway alterations, which had correlations to known ALS pathomechanisms in the basic and clinical literature, and may represent important targets for future ALS therapeutics.

Original languageEnglish (US)
Pages (from-to)1329-1338
Number of pages10
JournalJournal of Neurology, Neurosurgery and Psychiatry
Volume91
Issue number12
DOIs
StatePublished - Dec 1 2020
Externally publishedYes

ASJC Scopus subject areas

  • Surgery
  • Clinical Neurology
  • Psychiatry and Mental health

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