Urinary Metabolome Analyses of Patients with Acute Kidney Injury Using Capillary Electrophoresis-Mass Spectrometry
Acute kidney injury (AKI) is defined as a rapid decline in kidney function. The associated syndromes may lead to increased morbidity and mortality, but its early detection remains difficult. Using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS), we analyzed the urinary metabolo...
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| Format: | Article |
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MDPI AG
2021-09-01
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| Series: | Metabolites |
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| Online Access: | https://www.mdpi.com/2218-1989/11/10/671 |
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| author | Rintaro Saito Akiyoshi Hirayama Arisa Akiba Yushi Kamei Yuyu Kato Satsuki Ikeda Brian Kwan Minya Pu Loki Natarajan Hibiki Shinjo Shin’ichi Akiyama Masaru Tomita Tomoyoshi Soga Shoichi Maruyama |
| author_facet | Rintaro Saito Akiyoshi Hirayama Arisa Akiba Yushi Kamei Yuyu Kato Satsuki Ikeda Brian Kwan Minya Pu Loki Natarajan Hibiki Shinjo Shin’ichi Akiyama Masaru Tomita Tomoyoshi Soga Shoichi Maruyama |
| author_sort | Rintaro Saito |
| collection | DOAJ |
| description | Acute kidney injury (AKI) is defined as a rapid decline in kidney function. The associated syndromes may lead to increased morbidity and mortality, but its early detection remains difficult. Using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS), we analyzed the urinary metabolomic profile of patients admitted to the intensive care unit (ICU) after invasive surgery. Urine samples were collected at six time points: before surgery, at ICU admission and 6, 12, 24 and 48 h after. First, urine samples from 61 initial patients (non-AKI: 23, mild AKI: 24, severe AKI: 14) were measured, followed by the measurement of urine samples from 60 additional patients (non-AKI: 40, mild AKI: 20). Glycine and ethanolamine were decreased in patients with AKI compared with non-AKI patients at 6–24 h in the two groups. The linear statistical model constructed at each time point by machine learning achieved the best performance at 24 h (median AUC, area under the curve: 89%, cross-validated) for the 1st group. When cross-validated between the two groups, the AUC showed the best value of 70% at 12 h. These results identified metabolites and time points that show patterns specific to subjects who develop AKI, paving the way for the development of better biomarkers. |
| first_indexed | 2024-03-10T06:23:53Z |
| format | Article |
| id | doaj.art-4bf4674cf0f14f098120f303523c5a60 |
| institution | Directory Open Access Journal |
| issn | 2218-1989 |
| language | English |
| last_indexed | 2024-03-10T06:23:53Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Metabolites |
| spelling | doaj.art-4bf4674cf0f14f098120f303523c5a602023-11-22T19:07:09ZengMDPI AGMetabolites2218-19892021-09-01111067110.3390/metabo11100671Urinary Metabolome Analyses of Patients with Acute Kidney Injury Using Capillary Electrophoresis-Mass SpectrometryRintaro Saito0Akiyoshi Hirayama1Arisa Akiba2Yushi Kamei3Yuyu Kato4Satsuki Ikeda5Brian Kwan6Minya Pu7Loki Natarajan8Hibiki Shinjo9Shin’ichi Akiyama10Masaru Tomita11Tomoyoshi Soga12Shoichi Maruyama13Institute for Advanced Biosciences, Keio University, Tsuruoka 997-0052, JapanInstitute for Advanced Biosciences, Keio University, Tsuruoka 997-0052, JapanInstitute for Advanced Biosciences, Keio University, Tsuruoka 997-0052, JapanInstitute for Advanced Biosciences, Keio University, Tsuruoka 997-0052, JapanInstitute for Advanced Biosciences, Keio University, Tsuruoka 997-0052, JapanInstitute for Advanced Biosciences, Keio University, Tsuruoka 997-0052, JapanDivision of Biostatistics and Bioinformatics, Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA 92093, USADivision of Biostatistics and Bioinformatics, Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA 92093, USADivision of Biostatistics and Bioinformatics, Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA 92093, USADepartment of Nephrology, Nagoya University Graduate School of Medicine, Nagoya 466-8560, JapanDepartment of Nephrology, Nagoya University Graduate School of Medicine, Nagoya 466-8560, JapanInstitute for Advanced Biosciences, Keio University, Tsuruoka 997-0052, JapanInstitute for Advanced Biosciences, Keio University, Tsuruoka 997-0052, JapanDepartment of Nephrology, Nagoya University Graduate School of Medicine, Nagoya 466-8560, JapanAcute kidney injury (AKI) is defined as a rapid decline in kidney function. The associated syndromes may lead to increased morbidity and mortality, but its early detection remains difficult. Using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS), we analyzed the urinary metabolomic profile of patients admitted to the intensive care unit (ICU) after invasive surgery. Urine samples were collected at six time points: before surgery, at ICU admission and 6, 12, 24 and 48 h after. First, urine samples from 61 initial patients (non-AKI: 23, mild AKI: 24, severe AKI: 14) were measured, followed by the measurement of urine samples from 60 additional patients (non-AKI: 40, mild AKI: 20). Glycine and ethanolamine were decreased in patients with AKI compared with non-AKI patients at 6–24 h in the two groups. The linear statistical model constructed at each time point by machine learning achieved the best performance at 24 h (median AUC, area under the curve: 89%, cross-validated) for the 1st group. When cross-validated between the two groups, the AUC showed the best value of 70% at 12 h. These results identified metabolites and time points that show patterns specific to subjects who develop AKI, paving the way for the development of better biomarkers.https://www.mdpi.com/2218-1989/11/10/671AKIcapillary electrophoresis-mass spectrometry (CE-MS)biomarkerurine |
| spellingShingle | Rintaro Saito Akiyoshi Hirayama Arisa Akiba Yushi Kamei Yuyu Kato Satsuki Ikeda Brian Kwan Minya Pu Loki Natarajan Hibiki Shinjo Shin’ichi Akiyama Masaru Tomita Tomoyoshi Soga Shoichi Maruyama Urinary Metabolome Analyses of Patients with Acute Kidney Injury Using Capillary Electrophoresis-Mass Spectrometry Metabolites AKI capillary electrophoresis-mass spectrometry (CE-MS) biomarker urine |
| title | Urinary Metabolome Analyses of Patients with Acute Kidney Injury Using Capillary Electrophoresis-Mass Spectrometry |
| title_full | Urinary Metabolome Analyses of Patients with Acute Kidney Injury Using Capillary Electrophoresis-Mass Spectrometry |
| title_fullStr | Urinary Metabolome Analyses of Patients with Acute Kidney Injury Using Capillary Electrophoresis-Mass Spectrometry |
| title_full_unstemmed | Urinary Metabolome Analyses of Patients with Acute Kidney Injury Using Capillary Electrophoresis-Mass Spectrometry |
| title_short | Urinary Metabolome Analyses of Patients with Acute Kidney Injury Using Capillary Electrophoresis-Mass Spectrometry |
| title_sort | urinary metabolome analyses of patients with acute kidney injury using capillary electrophoresis mass spectrometry |
| topic | AKI capillary electrophoresis-mass spectrometry (CE-MS) biomarker urine |
| url | https://www.mdpi.com/2218-1989/11/10/671 |
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