Clinical and Experimental Medicine · 2023 · 14 citations · 23 references
Life SciencesBiochemistryInflammationMetabolismMetabolomicsClinical MetabolomicsIdiopathic Inflammatory MyopathiesMetabolite AnnotationMetabolite ProfilingMetabolomics Data AnalysisMuscle PathologyBiomarkersCaffeine MetabolismClinical Metabolite ProfilingDisease Metabolite ProfilingMetabolic Pathway ProfilingTryptophan MetabolismTyrosine MetabolismVery-long-chain Fatty Acids
Idiopathic inflammatory myopathy (IIM) are heterogeneous autoimmune diseases that primarily affect the proximal muscles. IIM subtypes include dermatomyositis (DM), polymyositis (PM), and anti-synthetase syndrome (ASS). Metabolic disturbances may cause irreversible structural damage to muscle fibers in patients with IIM. However, the metabolite profile of patients with different IIM subtypes remains elusive. To investigate metabolic alterations and identify patients with different IIM subtypes, we comprehensively profiled plasma metabolomics of 46 DM, 13 PM, 12 ASS patients, and 30 healthy controls (HCs) using UHPLC-Q Exactive HF mass spectrometer. Multiple statistical analyses and random forest were used to discover differential metabolites and potential biomarkers. We found that tryptophan metabolism, phenylalanine and tyrosine metabolism, fatty acid biosynthesis, beta-oxidation of very long chain fatty acids, alpha-linolenic acid and linoleic acid metabolism, steroidogenesis, bile acid biosynthesis, purine metabolism, and caffeine metabolism are all enriched in the DM, PM, and ASS groups. We also found that different subtypes of IIM have their unique metabolic pathways. We constructed three models (five metabolites) to identify DM, PM, ASS from HC in the discovery and validation sets. Five to seven metabolites can distinguish DM from PM, DM from ASS, and PM from ASS. A panel of seven metabolites can identify anti-melanoma differentiation-associated gene 5 positive (MDA5 +) DM with high accuracy in the discovery and validation sets. Our results provide potential biomarkers for diagnosing different subtypes of IIM and a better understanding of the underlying mechanisms of IIM.
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Ingrid E. Lundberg, Anna Tjärnlund, Matteo Bottai et al. · Annals of the Rheumatic Diseases · 2017 · 1.5K citations · Full text
Medicine, Dermatology, Pediatrics +13
metaX: a flexible and comprehensive software for processing metabolomics data
Bo Wen, Zhanlong Mei, Chunwei Zeng et al. · BMC Bioinformatics · 2017 · 1K citations · Full text
Life Sciences, Bioinformatics, Mass Spectrometric Analysis +11