Identification of serum biomarkers for chronic kidney disease using serum metabolomics
This study aimed to identify biomarkers for chronic kidney disease (CKD) by studying serum metabolomics. Serum samples were collected from 194 non-dialysis CKD patients and 317 healthy controls (HC). Using ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS), untargeted me...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | Renal Failure |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/0886022X.2024.2409346 |
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| author | Xi Gu Yindi Dong Xuemei Wang Zhigang Ren Guanhua Li Yaxin Hao Jian Wu Shiyuan Guo Yajuan Fan Hongyan Ren Chao Liu Suying Ding Weikang Li Ge Wu Zhangsuo Liu |
| author_facet | Xi Gu Yindi Dong Xuemei Wang Zhigang Ren Guanhua Li Yaxin Hao Jian Wu Shiyuan Guo Yajuan Fan Hongyan Ren Chao Liu Suying Ding Weikang Li Ge Wu Zhangsuo Liu |
| author_sort | Xi Gu |
| collection | DOAJ |
| description | This study aimed to identify biomarkers for chronic kidney disease (CKD) by studying serum metabolomics. Serum samples were collected from 194 non-dialysis CKD patients and 317 healthy controls (HC). Using ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS), untargeted metabolomics analysis was conducted. A random forest model was developed and validated in separate sets of HC and CKD patients. The serum metabolomic profiles of patients with chronic kidney disease (CKD) exhibited significant differences compared to healthy controls (HC). A total of 314 metabolites were identified as significantly different, with 179 being upregulated and 135 being downregulated in CKD patients. KEGG enrichment analysis revealed several key pathways, including arginine biosynthesis, phenylalanine metabolism, linoleic acid metabolism, and purine metabolism. The diagnostic efficacy of the classifier was high, with an area under the curve of 1 in the training and validation sets and 0.9435 in the cross-validation set. This study provides comprehensive insights into serum metabolism in non-dialysis CKD patients, highlighting the potential involvement of abnormal biological metabolism in CKD pathogenesis. Exploring metabolites may offer new possibilities for the management of CKD. |
| format | Article |
| id | doaj-art-2f7f56e56a4c406696cde90b6df6fe4d |
| institution | DOAJ |
| issn | 0886-022X 1525-6049 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Renal Failure |
| spelling | doaj-art-2f7f56e56a4c406696cde90b6df6fe4d2025-08-20T03:22:00ZengTaylor & Francis GroupRenal Failure0886-022X1525-60492024-12-0146210.1080/0886022X.2024.2409346Identification of serum biomarkers for chronic kidney disease using serum metabolomicsXi Gu0Yindi Dong1Xuemei Wang2Zhigang Ren3Guanhua Li4Yaxin Hao5Jian Wu6Shiyuan Guo7Yajuan Fan8Hongyan Ren9Chao Liu10Suying Ding11Weikang Li12Ge Wu13Zhangsuo Liu14Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaCollege of Public Health, Zhengzhou University, Zhengzhou, ChinaDepartment of Nephrology, Xinxiang Central Hospital, Xinxiang, ChinaDepartment of Nephrology, Zhumadian Central Hospital, Zhumadian, ChinaShanghai Mobio Biomedical Technology Co., Ltd, Shanghai, ChinaShanghai Mobio Biomedical Technology Co., Ltd, Shanghai, ChinaHealth Management Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaHealth Management Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaThis study aimed to identify biomarkers for chronic kidney disease (CKD) by studying serum metabolomics. Serum samples were collected from 194 non-dialysis CKD patients and 317 healthy controls (HC). Using ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS), untargeted metabolomics analysis was conducted. A random forest model was developed and validated in separate sets of HC and CKD patients. The serum metabolomic profiles of patients with chronic kidney disease (CKD) exhibited significant differences compared to healthy controls (HC). A total of 314 metabolites were identified as significantly different, with 179 being upregulated and 135 being downregulated in CKD patients. KEGG enrichment analysis revealed several key pathways, including arginine biosynthesis, phenylalanine metabolism, linoleic acid metabolism, and purine metabolism. The diagnostic efficacy of the classifier was high, with an area under the curve of 1 in the training and validation sets and 0.9435 in the cross-validation set. This study provides comprehensive insights into serum metabolism in non-dialysis CKD patients, highlighting the potential involvement of abnormal biological metabolism in CKD pathogenesis. Exploring metabolites may offer new possibilities for the management of CKD.https://www.tandfonline.com/doi/10.1080/0886022X.2024.2409346Chronic kidney diseaseserum metabolomicsmetabolic pathwaysbiomarkersgut microbiome |
| spellingShingle | Xi Gu Yindi Dong Xuemei Wang Zhigang Ren Guanhua Li Yaxin Hao Jian Wu Shiyuan Guo Yajuan Fan Hongyan Ren Chao Liu Suying Ding Weikang Li Ge Wu Zhangsuo Liu Identification of serum biomarkers for chronic kidney disease using serum metabolomics Renal Failure Chronic kidney disease serum metabolomics metabolic pathways biomarkers gut microbiome |
| title | Identification of serum biomarkers for chronic kidney disease using serum metabolomics |
| title_full | Identification of serum biomarkers for chronic kidney disease using serum metabolomics |
| title_fullStr | Identification of serum biomarkers for chronic kidney disease using serum metabolomics |
| title_full_unstemmed | Identification of serum biomarkers for chronic kidney disease using serum metabolomics |
| title_short | Identification of serum biomarkers for chronic kidney disease using serum metabolomics |
| title_sort | identification of serum biomarkers for chronic kidney disease using serum metabolomics |
| topic | Chronic kidney disease serum metabolomics metabolic pathways biomarkers gut microbiome |
| url | https://www.tandfonline.com/doi/10.1080/0886022X.2024.2409346 |
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