Identification of Metabolic Signature Associated with Idiopathic Inflammatory Myopathy Reveals Polyamine Pathway Alteration in Muscle Tissue
Idiopathic inflammatory myopathy (IIM) is hard to diagnose without a muscle biopsy. We aimed to identify a metabolite panel for IIM detection by metabolomics approach in serum samples and to explore the metabolomic signature in tissue samples from a mouse model. We obtained serum samples from IIM pa...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-10-01
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| Series: | Metabolites |
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| Online Access: | https://www.mdpi.com/2218-1989/12/10/1004 |
| _version_ | 1797471400389246976 |
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| author | Jihyun Kang Jeong Yeon Kim Youjin Jung Seon Uk Kim Eun Young Lee Joo-Youn Cho |
| author_facet | Jihyun Kang Jeong Yeon Kim Youjin Jung Seon Uk Kim Eun Young Lee Joo-Youn Cho |
| author_sort | Jihyun Kang |
| collection | DOAJ |
| description | Idiopathic inflammatory myopathy (IIM) is hard to diagnose without a muscle biopsy. We aimed to identify a metabolite panel for IIM detection by metabolomics approach in serum samples and to explore the metabolomic signature in tissue samples from a mouse model. We obtained serum samples from IIM patients, ankylosing spondylitis (AS) patients, healthy volunteers and muscle tissue samples from IIM murine model. All samples were subjected to a targeted metabolomic approach with various statistical analyses on serum and tissue samples to identify metabolic alterations. Three machine learning methods, such as logistic regression (LR), support vector machine (SVM), and random forest (RF), were applied to build prediction models. A set of 7 predictive metabolites was calculated using backward stepwise selection, and the model was evaluated within 5-fold cross-validation by using three machine algorithms. The model produced an area under the receiver operating characteristic curve values of 0.955 (LR), 0.908 (RF) and 0.918 (SVM). A total of 68 metabolites were significantly changed in mouse tissue. Notably, the most influential pathways contributing to the inflammation of muscle were the polyamine pathway and the beta-alanine pathway. Our metabolomic approach offers the potential biomarkers of IIM and reveals pathologically relevant metabolic pathways that are associated with IIM. |
| first_indexed | 2024-03-09T19:47:57Z |
| format | Article |
| id | doaj.art-0da5997824c647e7a18d458dc3addfba |
| institution | Directory Open Access Journal |
| issn | 2218-1989 |
| language | English |
| last_indexed | 2024-03-09T19:47:57Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Metabolites |
| spelling | doaj.art-0da5997824c647e7a18d458dc3addfba2023-11-24T01:16:45ZengMDPI AGMetabolites2218-19892022-10-011210100410.3390/metabo12101004Identification of Metabolic Signature Associated with Idiopathic Inflammatory Myopathy Reveals Polyamine Pathway Alteration in Muscle TissueJihyun Kang0Jeong Yeon Kim1Youjin Jung2Seon Uk Kim3Eun Young Lee4Joo-Youn Cho5Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul 03080, KoreaDivision of Cellular Genomics, GENOME INSIGHT Technologies, Seoul 06735, KoreaDivision of Rheumatology, Department of Internal Medicine, Seoul Metropolitan Seoul Medical Center, Seoul 02053, KoreaDivision of Rheumatology, Department of Internal Medicine, Seoul National University College of Medicine, Seoul 03080, KoreaDivision of Rheumatology, Department of Internal Medicine, Seoul National University College of Medicine, Seoul 03080, KoreaDepartment of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul 03080, KoreaIdiopathic inflammatory myopathy (IIM) is hard to diagnose without a muscle biopsy. We aimed to identify a metabolite panel for IIM detection by metabolomics approach in serum samples and to explore the metabolomic signature in tissue samples from a mouse model. We obtained serum samples from IIM patients, ankylosing spondylitis (AS) patients, healthy volunteers and muscle tissue samples from IIM murine model. All samples were subjected to a targeted metabolomic approach with various statistical analyses on serum and tissue samples to identify metabolic alterations. Three machine learning methods, such as logistic regression (LR), support vector machine (SVM), and random forest (RF), were applied to build prediction models. A set of 7 predictive metabolites was calculated using backward stepwise selection, and the model was evaluated within 5-fold cross-validation by using three machine algorithms. The model produced an area under the receiver operating characteristic curve values of 0.955 (LR), 0.908 (RF) and 0.918 (SVM). A total of 68 metabolites were significantly changed in mouse tissue. Notably, the most influential pathways contributing to the inflammation of muscle were the polyamine pathway and the beta-alanine pathway. Our metabolomic approach offers the potential biomarkers of IIM and reveals pathologically relevant metabolic pathways that are associated with IIM.https://www.mdpi.com/2218-1989/12/10/1004idiopathic inflammatory myopathybiomarkerpolyamine pathway |
| spellingShingle | Jihyun Kang Jeong Yeon Kim Youjin Jung Seon Uk Kim Eun Young Lee Joo-Youn Cho Identification of Metabolic Signature Associated with Idiopathic Inflammatory Myopathy Reveals Polyamine Pathway Alteration in Muscle Tissue Metabolites idiopathic inflammatory myopathy biomarker polyamine pathway |
| title | Identification of Metabolic Signature Associated with Idiopathic Inflammatory Myopathy Reveals Polyamine Pathway Alteration in Muscle Tissue |
| title_full | Identification of Metabolic Signature Associated with Idiopathic Inflammatory Myopathy Reveals Polyamine Pathway Alteration in Muscle Tissue |
| title_fullStr | Identification of Metabolic Signature Associated with Idiopathic Inflammatory Myopathy Reveals Polyamine Pathway Alteration in Muscle Tissue |
| title_full_unstemmed | Identification of Metabolic Signature Associated with Idiopathic Inflammatory Myopathy Reveals Polyamine Pathway Alteration in Muscle Tissue |
| title_short | Identification of Metabolic Signature Associated with Idiopathic Inflammatory Myopathy Reveals Polyamine Pathway Alteration in Muscle Tissue |
| title_sort | identification of metabolic signature associated with idiopathic inflammatory myopathy reveals polyamine pathway alteration in muscle tissue |
| topic | idiopathic inflammatory myopathy biomarker polyamine pathway |
| url | https://www.mdpi.com/2218-1989/12/10/1004 |
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