Sunyoung Ahn1, Su Hwan Lee2, Kyung Soo Chung2, Nam Su Ku3, Young-Min Hyun4, Sail Chun5, Moo Suk Park6, Sang-Guk Lee7. 1. Department of Laboratory Medicine, Yonsei University College of Medicine, Severance Hospital, Seoul, Republic of Korea. 2. Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Yonsei University College of Medicine, Severance Hospital, Seoul, Republic of Korea. 3. Division of Infection, Department of Internal Medicine, Yonsei University College of Medicine, Severance Hospital, Seoul, Republic of Korea. 4. Department of Anatomy, Yonsei University College of Medicine, Seoul, Republic of Korea. 5. Department of Laboratory Medicine, Ulsan University College of Medicine, Asan Medical Center, Seoul, Republic of Korea. 6. Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Yonsei University College of Medicine, Severance Hospital, Seoul, Republic of Korea. Electronic address: pms70@yuhs.ac. 7. Department of Laboratory Medicine, Yonsei University College of Medicine, Severance Hospital, Seoul, Republic of Korea. Electronic address: comforter6@yuhs.ac.
Abstract
BACKGROUND & AIMS: Sepsis is a potentially fatal condition influenced by pathogens and host factors. Current sepsis biomarkers such as white blood cell count and C-reactive protein and procalcitonin levels show unsatisfactory performance in terms of diagnostic sensitivity and specificity in clinical practice. Thus, we developed and validated a new sepsis biomarker based on amino acid profiling. METHODS: We used two independent groups. The training and validation groups included 161 and 22 healthy controls, 123 and 50 patients with systemic inflammatory response syndrome, and 115 and 45 patients with sepsis, respectively. Using mass spectrometry, we measured and analyzed serum amino acid levels to select candidate amino acids that could differentiate sepsis from other conditions. Then, several possible multivariate indexes were developed by generating formulae with different combinations of candidate amino acids. The formula showing the best performance was selected and validated further. RESULTS: Kynurenine, tryptophan, phenylalanine, arginine, aspartic acid, glutamic acid, and glutamine were selected as candidate amino acids. Ten possible formulae were generated, and the formula with the highest diagnostic performance, which included kynurenine, tryptophan, phenylalanine, and arginine, was selected. In the validation group, the area under the receiving operating characteristic curve of the selected multivariate index (0.931) was similar to that of procalcitonin (0.945). Moreover, the generated multivariate index showed potential as a prognostic marker. CONCLUSIONS: Serum amino acid composition in patients with sepsis differs significantly from that in healthy individuals and patients with inflammation only. The newly developed multivariate index is expected to be implementable as a sepsis biomarker in clinical practice in the near future.
BACKGROUND & AIMS: Sepsis is a potentially fatal condition influenced by pathogens and host factors. Current sepsis biomarkers such as white blood cell count and C-reactive protein and procalcitonin levels show unsatisfactory performance in terms of diagnostic sensitivity and specificity in clinical practice. Thus, we developed and validated a new sepsis biomarker based on amino acid profiling. METHODS: We used two independent groups. The training and validation groups included 161 and 22 healthy controls, 123 and 50 patients with systemic inflammatory response syndrome, and 115 and 45 patients with sepsis, respectively. Using mass spectrometry, we measured and analyzed serum amino acid levels to select candidate amino acids that could differentiate sepsis from other conditions. Then, several possible multivariate indexes were developed by generating formulae with different combinations of candidate amino acids. The formula showing the best performance was selected and validated further. RESULTS: Kynurenine, tryptophan, phenylalanine, arginine, aspartic acid, glutamic acid, and glutamine were selected as candidate amino acids. Ten possible formulae were generated, and the formula with the highest diagnostic performance, which included kynurenine, tryptophan, phenylalanine, and arginine, was selected. In the validation group, the area under the receiving operating characteristic curve of the selected multivariate index (0.931) was similar to that of procalcitonin (0.945). Moreover, the generated multivariate index showed potential as a prognostic marker. CONCLUSIONS: Serum amino acid composition in patients with sepsis differs significantly from that in healthy individuals and patients with inflammation only. The newly developed multivariate index is expected to be implementable as a sepsis biomarker in clinical practice in the near future.