Osteopenia Metabolomic Biomarkers for Early Warning of Osteoporosis
<b>Introduction</b>: This study aimed to capture the early metabolic changes before osteoporosis occurs and identify metabolomic biomarkers at the osteopenia stage for the early prevention of osteoporosis. <b>Materials and Methods</b>: Metabolomic data were generated from nor...
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2025-01-01
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| author | Jie Wang Dandan Yan Suna Wang Aihua Zhao Xuhong Hou Xiaojiao Zheng Jingyi Guo Li Shen Yuqian Bao Wei Jia Xiangtian Yu Cheng Hu Zhenlin Zhang |
| author_facet | Jie Wang Dandan Yan Suna Wang Aihua Zhao Xuhong Hou Xiaojiao Zheng Jingyi Guo Li Shen Yuqian Bao Wei Jia Xiangtian Yu Cheng Hu Zhenlin Zhang |
| author_sort | Jie Wang |
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| description | <b>Introduction</b>: This study aimed to capture the early metabolic changes before osteoporosis occurs and identify metabolomic biomarkers at the osteopenia stage for the early prevention of osteoporosis. <b>Materials and Methods</b>: Metabolomic data were generated from normal, osteopenia, and osteoporosis groups with 320 participants recruited from the Nicheng community in Shanghai. We conducted individual edge network analysis (iENA) combined with a random forest to detect metabolomic biomarkers for the early warning of osteoporosis. Weighted Gene Co-Expression Network Analysis (WGCNA) and mediation analysis were used to explore the clinical impacts of metabolomic biomarkers. <b>Results</b>: Visual separations of the metabolic profiles were observed between three bone mineral density (BMD) groups in both genders. According to the iENA approach, several metabolites had significant abundance and association changes in osteopenia participants, confirming that osteopenia is a critical stage in the development of osteoporosis. Metabolites were further selected to identify osteopenia (nine metabolites in females; eight metabolites in males), and their ability to discriminate osteopenia was improved significantly compared to traditional bone turnover markers (BTMs) (female AUC = 0.717, 95% CI 0.547–0.882, versus BTMs: <i>p</i> = 0.036; male AUC = 0.801, 95% CI 0.636–0.966, versus BTMs: <i>p</i> = 0.007). The roles of the identified key metabolites were involved in the association between total fat-free mass (TFFM) and osteopenia in females. <b>Conclusion</b>: Osteopenia was identified as a tipping point during the development of osteoporosis with metabolomic characteristics. A few metabolites were identified as candidate early-warning biomarkers by machine learning analysis, which could indicate bone loss and provide new prevention guidance for osteoporosis. |
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| institution | Kabale University |
| issn | 2218-1989 |
| language | English |
| publishDate | 2025-01-01 |
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| series | Metabolites |
| spelling | doaj-art-e8d7f6dde5a6435aae9d08caa661de482025-01-24T13:41:21ZengMDPI AGMetabolites2218-19892025-01-011516610.3390/metabo15010066Osteopenia Metabolomic Biomarkers for Early Warning of OsteoporosisJie Wang0Dandan Yan1Suna Wang2Aihua Zhao3Xuhong Hou4Xiaojiao Zheng5Jingyi Guo6Li Shen7Yuqian Bao8Wei Jia9Xiangtian Yu10Cheng Hu11Zhenlin Zhang12Department of Osteoporosis, Metabolic Bone Disease and Genetic Research Unit, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, ChinaDepartment of Endocrinology and Metabolism, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center of Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Key Clinical Center for Metabolic Disease, Shanghai 200233, ChinaClinical Research Center, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, ChinaCenter for Translational Medicine, and Shanghai Key Laboratory of Diabetes Mellitus, Department of Endocrinology and Metabolism, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, ChinaShanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, ChinaCenter for Translational Medicine, and Shanghai Key Laboratory of Diabetes Mellitus, Department of Endocrinology and Metabolism, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, ChinaClinical Research Center, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, ChinaClinical Research Center, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, ChinaDepartment of Endocrinology and Metabolism, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center of Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Key Clinical Center for Metabolic Disease, Shanghai 200233, ChinaHong Kong Phenome Research Centre, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong 999077, ChinaClinical Research Center, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, ChinaShanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, ChinaDepartment of Osteoporosis, Metabolic Bone Disease and Genetic Research Unit, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China<b>Introduction</b>: This study aimed to capture the early metabolic changes before osteoporosis occurs and identify metabolomic biomarkers at the osteopenia stage for the early prevention of osteoporosis. <b>Materials and Methods</b>: Metabolomic data were generated from normal, osteopenia, and osteoporosis groups with 320 participants recruited from the Nicheng community in Shanghai. We conducted individual edge network analysis (iENA) combined with a random forest to detect metabolomic biomarkers for the early warning of osteoporosis. Weighted Gene Co-Expression Network Analysis (WGCNA) and mediation analysis were used to explore the clinical impacts of metabolomic biomarkers. <b>Results</b>: Visual separations of the metabolic profiles were observed between three bone mineral density (BMD) groups in both genders. According to the iENA approach, several metabolites had significant abundance and association changes in osteopenia participants, confirming that osteopenia is a critical stage in the development of osteoporosis. Metabolites were further selected to identify osteopenia (nine metabolites in females; eight metabolites in males), and their ability to discriminate osteopenia was improved significantly compared to traditional bone turnover markers (BTMs) (female AUC = 0.717, 95% CI 0.547–0.882, versus BTMs: <i>p</i> = 0.036; male AUC = 0.801, 95% CI 0.636–0.966, versus BTMs: <i>p</i> = 0.007). The roles of the identified key metabolites were involved in the association between total fat-free mass (TFFM) and osteopenia in females. <b>Conclusion</b>: Osteopenia was identified as a tipping point during the development of osteoporosis with metabolomic characteristics. A few metabolites were identified as candidate early-warning biomarkers by machine learning analysis, which could indicate bone loss and provide new prevention guidance for osteoporosis.https://www.mdpi.com/2218-1989/15/1/66bone mineral densityosteopeniametabolomicsbiomarkersearly warning |
| spellingShingle | Jie Wang Dandan Yan Suna Wang Aihua Zhao Xuhong Hou Xiaojiao Zheng Jingyi Guo Li Shen Yuqian Bao Wei Jia Xiangtian Yu Cheng Hu Zhenlin Zhang Osteopenia Metabolomic Biomarkers for Early Warning of Osteoporosis Metabolites bone mineral density osteopenia metabolomics biomarkers early warning |
| title | Osteopenia Metabolomic Biomarkers for Early Warning of Osteoporosis |
| title_full | Osteopenia Metabolomic Biomarkers for Early Warning of Osteoporosis |
| title_fullStr | Osteopenia Metabolomic Biomarkers for Early Warning of Osteoporosis |
| title_full_unstemmed | Osteopenia Metabolomic Biomarkers for Early Warning of Osteoporosis |
| title_short | Osteopenia Metabolomic Biomarkers for Early Warning of Osteoporosis |
| title_sort | osteopenia metabolomic biomarkers for early warning of osteoporosis |
| topic | bone mineral density osteopenia metabolomics biomarkers early warning |
| url | https://www.mdpi.com/2218-1989/15/1/66 |
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