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. 2022 Jul 21;13(5):2456–2472. doi: 10.1002/jcsm.13045

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© 2022 The Authors. Journal of Cachexia, Sarcopenia and Muscle published by John Wiley & Sons Ltd on behalf of Society on Sarcopenia, Cachexia and Wasting Disorders.

This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

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Urine metabolomic profiles in the MSA‐defined IIM subtypes. (A and B) The orthogonal partial least‐squares discriminate analysis (OPLS‐DA) score plots of urine metabolomics data compared anti‐EJ+, anti‐Jo1+, anti‐MDA5+, anti‐Mi2+, anti‐TIF1γ+, anti‐PL12+, anti‐PL7+, and anti‐SRP + IIM patients to normal control (NC) samples in positive (A) and negative (B) ion mode, respectively. (C) The UpSet plot analysis based on the selected urine important metabolites (VIP > 1, FC > 1.2 or <0.83). (D) KEGG pathway analysis of exclusively important metabolites in each IIM subtype. (E) The linear discriminant analysis (LDA) plot based on the top 12 metabolites in the AdaBoost machine model. (F) The most specific metabolites identified by the AdaBoost machine model to classify urine samples from NC, anti‐EJ+, anti‐Jo1+, anti‐MDA5+, anti‐Mi2+, anti‐TIF1γ+, anti‐PL12+, anti‐PL7+, and anti‐SRP+ myositis patients, respectively (P value compared with NC, *, <0.05; **, <0.01; ***, <0.001, ****, <0.0001).