Department of Surgery, University of Minnesota, 515 Delaware St SE, Minneapolis, MN, 55455, USA.
Department of Medicine, Uniformed Services University, 4301 Jones Bridge Road, Bethesda, MD, 20814, USA.
Crit Care. 2021 Mar 23;25(1):119. doi: 10.1186/s13054-021-03544-2.
Traditionally, patient risk scoring is done by evaluating vital signs and clinical severity scores with clinical intuition. Urinary biomarkers can add objectivity to these models to make risk prediction more accurate. We used metabolomics to identify prognostic urinary biomarkers of mortality or need for renal replacement therapy (RRT). Additionally, we assessed acute kidney injury (AKI) diagnosis, injury severity score (ISS), and AKI stage.
Urine samples (n = 82) from a previous study of combat casualties were evaluated using proton nuclear magnetic resonance (H-NMR) spectroscopy. Chenomx software was used to identify and quantify urinary metabolites. Metabolite concentrations were normalized by urine output, autoscaled, and log-transformed. Partial least squares discriminant analysis (PLS-DA) and statistical analysis were performed. Receiver operating characteristic (ROC) curves were used to assess prognostic utility of biomarkers for mortality and RRT.
Eighty-four (84) metabolites were identified and quantified in each urine sample. Of these, 11 were identified as drugs or drug metabolites and excluded. The PLS-DA models for ISS and AKI diagnosis did not have acceptable model statistics. Therefore, only mortality/RRT and AKI stage were analyzed further. Of 73 analyzed metabolites, 9 were significantly associated with mortality/RRT (p < 0.05) and 11 were significantly associated with AKI stage (p < 0.05). 1-Methylnicotinamide was the only metabolite to be significantly associated (p < 0.05) with all outcomes and was significantly higher (p < 0.05) in patients with adverse outcomes. Elevated lactate and 1-methylnicotinamide levels were associated with higher AKI stage and mortality and RRT, whereas elevated glycine levels were associated with patients who survived and did not require RRT, or had less severe AKI. ROC curves for each of these metabolites and the combined panel had good predictive value (lactate AUC = 0.901, 1-methylnicotinamide AUC = 0.864, glycine AUC = 0.735, panel AUC = 0.858).
We identified urinary metabolites associated with AKI stage and the primary outcome of mortality or need for RRT. Lactate, 1-methylnicotinamide, and glycine may be used as a panel of predictive biomarkers for mortality and RRT. 1-Methylnicotinamide is a novel biomarker associated with adverse outcomes. Additional studies are necessary to determine how these metabolites can be utilized in clinically-relevant risk prediction models.
传统上，通过评估生命体征和临床严重程度评分并结合临床直觉来进行患者风险评分。尿生物标志物可以为这些模型增加客观性，从而使风险预测更加准确。我们使用代谢组学来识别与死亡率或需要肾脏替代治疗（RRT）相关的预后性尿生物标志物。此外，我们评估了急性肾损伤（AKI）的诊断、损伤严重程度评分（ISS）和 AKI 分期。
使用质子核磁共振（H-NMR）光谱法对先前一项关于战斗伤员的研究中的尿液样本（n=82）进行评估。Chenomx 软件用于鉴定和定量尿液中的代谢物。将代谢物浓度通过尿液输出进行归一化、自动缩放和对数转换。进行偏最小二乘判别分析（PLS-DA）和统计分析。使用受试者工作特征（ROC）曲线评估生物标志物对死亡率和 RRT 的预后效用。
在每个尿液样本中都鉴定和定量了 84 种（84）代谢物。其中，有 11 种被鉴定为药物或药物代谢物并被排除在外。ISS 和 AKI 诊断的 PLS-DA 模型没有可接受的模型统计数据。因此，仅进一步分析死亡率/RRT 和 AKI 分期。在分析的 73 种代谢物中，有 9 种与死亡率/RRT 显著相关（p<0.05），有 11 种与 AKI 分期显著相关（p<0.05）。1-甲基烟酰胺是唯一与所有结局均显著相关（p<0.05）的代谢物，并且在预后不良的患者中显著升高（p<0.05）。升高的乳酸和 1-甲基烟酰胺水平与更高的 AKI 分期和死亡率以及 RRT 相关，而升高的甘氨酸水平与存活且不需要 RRT 或 AKI 分期较轻的患者相关。这些代谢物和联合标志物的 ROC 曲线具有良好的预测价值（乳酸 AUC=0.901，1-甲基烟酰胺 AUC=0.864，甘氨酸 AUC=0.735，标志物组合 AUC=0.858）。
我们鉴定了与 AKI 分期和死亡率或需要 RRT 的主要结局相关的尿代谢物。乳酸、1-甲基烟酰胺和甘氨酸可作为死亡率和 RRT 的预测生物标志物组合使用。1-甲基烟酰胺是一种与不良结局相关的新型生物标志物。需要进一步的研究来确定这些代谢物如何用于临床相关的风险预测模型。
