Onishi Shinya, Matsumoto Hisatake, Sugihara Fuminori, Ebihara Takeshi, Matsuura Hiroshi, Osuka Akinori, Okuzaki Daisuke, Ogura Hiroshi, Oda Jun
Department of Traumatology and Acute Critical Medicine, Osaka University Graduate School of Medicine, 2-15 Yamadaoka, Suita, Osaka 565-0871, Japan.
Institute for Open and Transdisciplinary Research Initiatives, Osaka University, 1-1 Yamadaoka, Suita, Osaka 565-0871, Japan.
iScience. 2023 Jul 3;26(8):107271. doi: 10.1016/j.isci.2023.107271. eCollection 2023 Aug 18.
Recent advancements in proteomics allow for the concurrent identification and quantification of multiple proteins. This study aimed to identify proteins associated with severe burn pathology and establish a clinically useful molecular pathology classification. In a retrospective observational study, blood samples were collected from severe burn patients. Proteins were measured using mass spectrometry, and prognosis-related proteins were extracted by comparing survivors and non-survivors. Enrichment and ROC analyses evaluated the extracted proteins, followed by latent class analysis. Measurements were performed on 83 burn patients. In the non-survivor group, ten proteins significantly changing on the day of injury were associated with metabolic processes and toxin responses. ROC analysis identified HBA1, TTR, and SERPINF2 with AUCs > 0.8 as predictors of 28-day mortality. Latent class analysis classified three molecular pathotypes, and plasma mass spectrometry revealed ten proteins associated with severe burn prognosis. Molecular pathotypes based on HBA1, TTR, and SERPINF2 significantly correlated with outcomes.
蛋白质组学的最新进展使得能够同时鉴定和定量多种蛋白质。本研究旨在鉴定与严重烧伤病理相关的蛋白质，并建立一种临床有用的分子病理学分类。在一项回顾性观察研究中，收集了严重烧伤患者的血样。使用质谱法测量蛋白质，并通过比较幸存者和非幸存者来提取与预后相关的蛋白质。富集分析和ROC分析评估提取的蛋白质，随后进行潜在类别分析。对83名烧伤患者进行了测量。在非幸存者组中，受伤当天显著变化的十种蛋白质与代谢过程和毒素反应相关。ROC分析确定HBA1、TTR和SERPINF2的AUC>0.8作为28天死亡率的预测指标。潜在类别分析将三种分子病理类型进行了分类，血浆质谱分析揭示了十种与严重烧伤预后相关的蛋白质。基于HBA1、TTR和SERPINF2的分子病理类型与预后显著相关。
