背景:蛋白质氨基甲酰化,主要由尿素驱动的翻译后蛋白质修饰,CKD患者的不良临床结局独立相关.用于量化氨基甲酰化负荷的生物标志物主要包括氨基甲酰化白蛋白(C-Alb)和高瓜氨酸(HCit,氨基甲酰化赖氨酸)。在这项研究中,我们的目的是比较这两种标志物的预后效用,以便于比较现有的单独使用任一标志物的研究,并为未来的氨基甲酸酯化研究提供信息。
方法:在前瞻性慢性肾功能不全队列(CRIC)研究中纳入的1632名CKD2-4期个体中,从同一时间点测定血清C-Alb和游离HCit水平。调整后的Cox比例风险模型用于评估死亡(原发性)和终末期肾病(ESKD)的风险。C-统计,净重新分类改进,和综合辨别改进被用来比较每个标记的预后价值。
结果:参与者的人口统计学包括平均(SD)年龄59(11)岁;702(43%)女性;700(43%)白人。C-Alb和HCit水平呈正相关(Pearson相关系数0.64)。较高的C-Alb和HCit水平显示出类似的死亡风险增加(例如,对于C-Alb,与第1位相比,第4位氨基甲酰化四分位数死亡的校正风险比[HR]为1.90(95%置信区间[CI]1.35-2.66),HCit为1.89[1.27-2.81];在连续规模上,使用C-Alb的死亡校正HR为1.24[1.11至1.39]每标准偏差增加,和1.27[1.10-1.46]使用HCit)。两种生物标志物对于ESKD也具有相似的HR。当将每个氨基甲酸酯化生物标志物添加到基础模型时,C统计量是相似的(例如,对于死亡率模型,C-Alb的C统计量为0.725[0.707-0.743],HCit的C统计量为0.725[0.707-0.743],两者都与基本模型0.723相比)。还观察到净重新分类改进和综合歧视改进指标的相似性。
结论:C-Alb和HCit在多个预后评估中具有相似的表现。这些标记在CKD流行病学研究中似乎很容易具有可比性。
BACKGROUND: Protein
carbamylation, a post-translational protein modification primarily driven by urea, independently associates with adverse clinical outcomes in patients with CKD. Biomarkers used to quantify
carbamylation burden have mainly included carbamylated albumin (C-Alb) and homocitrulline (HCit, carbamylated lysine). In this study, we aimed to compare the prognostic utility of these two markers in order to facilitate comparisons of existing studies employing either marker alone, and to inform future
carbamylation studies.
METHODS: Both serum C-Alb and free HCit levels were assayed from the same timepoint in 1632 individuals with CKD stages 2-4 enrolled in the prospective Chronic Renal Insufficiency Cohort (CRIC) study. Adjusted Cox proportional hazard models were used to assess risks for the outcomes of death (primary) and end stage kidney disease (ESKD) using each marker. C-statistics, net reclassification improvement, and integrated discrimination improvement were used to compare the prognostic value of each marker.
RESULTS: Participant demographics included mean (SD) age 59 (11) years; 702 (43%) females; 700 (43%) white. C-Alb and HCit levels were positively correlated with one another (Pearson correlation coefficient 0.64). Higher C-Alb and HCit levels showed similar increased risk of death (e.g., the adjusted hazard ratio [HR] for death in the 4th
carbamylation quartile compared to the 1st was 1.90 (95% confidence interval [CI] 1.35-2.66) for C-Alb, and 1.89 [1.27-2.81] for HCit; and on a continuous scale, the adjusted HR for death using C-Alb was 1.24 [1.11 to 1.39] per standard deviation increase, and 1.27 [1.10-1.46] using HCit). Both biomarkers also had similar HRs for ESKD. The C-statistics were similar when adding each
carbamylation biomarker to base models (e.g., for mortality models, the C-statistic was 0.725 [0.707-0.743] with C-Alb and 0.725 [0.707-0.743] with HCit, both compared to a base model 0.723). Similarities were also observed for the net reclassification improvement and integrated discrimination improvement metrics.
CONCLUSIONS: C-Alb and HCit had similar performance across multiple prognostic assessments. The markers appear readily comparable in CKD epidemiological studies.