Cullaro Giuseppe, Allegretti Andrew S, Patidar Kavish R, Verna Elizabeth C, Lai Jennifer C
University of California-San Francisco.
Massachusetts General Hospital.
Res Sq. 2024 May 9:rs.3.rs-4344179. doi: 10.21203/rs.3.rs-4344179/v1.
A case-control study of 97 patients hospitalized at our institution. We performed aptamer-based proteomics and metabolomics on serum biospecimens obtained within 72 hours of admission. We compared the proteome and metabolome by the AKI phenotype (i.e., HRS-AKI, ATN) and by AKI recovery (decrease in sCr within 0.3 mg/dL of baseline) using ANCOVA analyses adjusting for demographics and clinical characteristics. We completed Random Forest (RF) analyses to identify metabolites and proteins associated with AKI phenotype and recovery. Lasso regression models were developed to highlight metabolites and proteins could improve diagnostic accuracy. Results: ANCOVA analyses showed no metabolomic or proteomic differences by AKI phenotype while identifying differences by AKI recovery status. Our RF and Lasso analyses showed that metabolomics can improve the diagnostic accuracy of both AKI diagnosis and recovery, and aptamer-based proteomics can enhance the diagnostic accuracy of AKI recovery. Discussion: Our analyses provide novel insight into pathophysiologic pathways, highlighting the metabolomic and proteomic similarities between patients with cirrhosis with HRS-AKI and ATN while also identifying differences between those with and without AKI recovery.
一项针对我院97例住院患者的病例对照研究。我们对入院72小时内采集的血清生物样本进行了基于适配体的蛋白质组学和代谢组学分析。我们使用协方差分析,并对人口统计学和临床特征进行校正,按急性肾损伤(AKI)表型(即肝肾综合征相关性急性肾损伤、急性肾小管坏死)以及AKI恢复情况(血清肌酐较基线水平下降0.3mg/dL以内)对蛋白质组和代谢组进行比较。我们完成了随机森林(RF)分析,以识别与AKI表型和恢复相关的代谢物和蛋白质。构建套索回归模型以突出可提高诊断准确性的代谢物和蛋白质。结果:协方差分析显示,按AKI表型未发现代谢组学或蛋白质组学差异,但按AKI恢复状态发现了差异。我们的RF和套索分析表明,代谢组学可提高AKI诊断和恢复的诊断准确性,基于适配体的蛋白质组学可提高AKI恢复的诊断准确性。讨论:我们的分析为病理生理途径提供了新的见解,突出了肝硬化合并肝肾综合征相关性急性肾损伤和急性肾小管坏死患者之间的代谢组学和蛋白质组学相似性,同时也确定了有和没有AKI恢复患者之间的差异。