Urinary Metabolome Analyses of Patients with Acute Kidney Injury Using Capillary Electrophoresis-Mass Spectrometry
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
Affiliations
Rintaro Saito
Institute for Advanced Biosciences, Keio University, Tsuruoka 997-0052, Japan
Akiyoshi Hirayama
Institute for Advanced Biosciences, Keio University, Tsuruoka 997-0052, Japan
Arisa Akiba
Institute for Advanced Biosciences, Keio University, Tsuruoka 997-0052, Japan
Yushi Kamei
Institute for Advanced Biosciences, Keio University, Tsuruoka 997-0052, Japan
Yuyu Kato
Institute for Advanced Biosciences, Keio University, Tsuruoka 997-0052, Japan
Satsuki Ikeda
Institute for Advanced Biosciences, Keio University, Tsuruoka 997-0052, Japan
Brian Kwan
Division of Biostatistics and Bioinformatics, Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA 92093, USA
Minya Pu
Division of Biostatistics and Bioinformatics, Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA 92093, USA
Loki Natarajan
Division of Biostatistics and Bioinformatics, Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA 92093, USA
Hibiki Shinjo
Department of Nephrology, Nagoya University Graduate School of Medicine, Nagoya 466-8560, Japan
Shin’ichi Akiyama
Department of Nephrology, Nagoya University Graduate School of Medicine, Nagoya 466-8560, Japan
Masaru Tomita
Institute for Advanced Biosciences, Keio University, Tsuruoka 997-0052, Japan
Tomoyoshi Soga
Institute for Advanced Biosciences, Keio University, Tsuruoka 997-0052, Japan
Shoichi Maruyama
Department of Nephrology, Nagoya University Graduate School of Medicine, Nagoya 466-8560, Japan
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.