{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Liu D"],"funding":["Natural Science Foundation of Hunan Province","National Natural Science Foundation of China","Natural Science Foundation of Hunan Province"],"pagination":["2456-2472"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9530549"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["13(5)"],"pubmed_abstract":["<h4>Objectives</h4>Idiopathic inflammatory myopathies (IIM) are a class of autoimmune diseases with high heterogeneity that can be divided into different subtypes based on clinical manifestations and myositis-specific autoantibodies (MSAs). However, even in each IIM subtype, the clinical symptoms and prognoses of patients are very different. Thus, the identification of more potential biomarkers associated with IIM classification, clinical symptoms, and prognosis is urgently needed.<h4>Methods</h4>Plasma and urine samples from 79 newly diagnosed IIM patients (mean disease duration 4 months) and 52 normal control (NC) samples were analysed by high-performance liquid chromatography of quadrupole time-of-flight mass spectrometry (HPLC-Q-TOF-MS)/MS-based untargeted metabolomics. Orthogonal part"],"journal":["Journal of cachexia, sarcopenia and muscle"],"pubmed_title":["Integrated analysis of plasma and urine reveals unique metabolomic profiles in idiopathic inflammatory myopathies subtypes."],"pmcid":["PMC9530549"],"funding_grant_id":["2020JJ8056","82101880"],"pubmed_authors":["Jiang Y","Guo M","Zhao L","Mu Y","Zhu H","Liu D","Li L"],"additional_accession":[]},"is_claimable":false,"name":"Integrated analysis of plasma and urine reveals unique metabolomic profiles in idiopathic inflammatory myopathies subtypes.","description":"<h4>Objectives</h4>Idiopathic inflammatory myopathies (IIM) are a class of autoimmune diseases with high heterogeneity that can be divided into different subtypes based on clinical manifestations and myositis-specific autoantibodies (MSAs). However, even in each IIM subtype, the clinical symptoms and prognoses of patients are very different. Thus, the identification of more potential biomarkers associated with IIM classification, clinical symptoms, and prognosis is urgently needed.<h4>Methods</h4>Plasma and urine samples from 79 newly diagnosed IIM patients (mean disease duration 4 months) and 52 normal control (NC) samples were analysed by high-performance liquid chromatography of quadrupole time-of-flight mass spectrometry (HPLC-Q-TOF-MS)/MS-based untargeted metabolomics. Orthogonal part","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Oct","modification":"2025-04-05T11:38:29.072Z","creation":"2025-04-05T11:38:29.072Z"},"accession":"S-EPMC9530549","cross_references":{"pubmed":["35860906"],"doi":["10.1002/jcsm.13045"]}}