Köller Adrian, Grzegorzewski Jan, König Matthias
Institute for Theoretical Biology, Institute of Biology, Humboldt University, Berlin, Germany.
Front Physiol. 2021 Nov 22;12:757293. doi: 10.3389/fphys.2021.757293. eCollection 2021.
Accurate evaluation of liver function is a central task in hepatology. Dynamic liver function tests (DLFT) based on the time-dependent elimination of a test substance provide an important tool for such a functional assessment. These tests are used in the diagnosis and monitoring of liver disease as well as in the planning of hepatobiliary surgery. A key challenge in the evaluation of liver function with DLFTs is the large inter-individual variability. Indocyanine green (ICG) is a widely applied test compound used for the evaluation of liver function. After an intravenous administration, pharmacokinetic (PK) parameters are calculated from the plasma disappearance curve of ICG which provide an estimate of liver function. The hepatic elimination of ICG is affected by physiological factors such as hepatic blood flow or binding of ICG to plasma proteins, anthropometric factors such as body weight, age, and sex, or the protein amount of the organic anion-transporting polypeptide 1B3 (OATP1B3) mediating the hepatic uptake of ICG. Being able to account for and better understand these various sources of inter-individual variability would allow to improve the power of ICG based DLFTs and move toward an individualized evaluation of liver function. Within this work we systematically analyzed the effect of various factors on ICG elimination by the means of computational modeling. For the analysis, a recently developed and validated physiologically based pharmacokinetics (PBPK) model of ICG distribution and hepatic elimination was utilized. Key results are (i) a systematic analysis of the variability in ICG elimination due to hepatic blood flow, cardiac output, OATP1B3 abundance, liver volume, body weight and plasma bilirubin level; (ii) the evaluation of the inter-individual variability in ICG elimination via a large cohort of = 100,000 subjects based on the NHANES cohort with special focus on stratification by age, sex, and body weight; (iii) the evaluation of the effect of various degrees of cirrhosis on variability in ICG elimination. The presented results are an important step toward individualizing liver function tests by elucidating the effects of confounding physiological and anthropometric parameters in the evaluation of liver function via ICG.
准确评估肝功能是肝病学的核心任务。基于测试物质随时间消除的动态肝功能测试(DLFT)为这种功能评估提供了重要工具。这些测试用于肝病的诊断和监测以及肝胆手术的规划。使用DLFT评估肝功能的一个关键挑战是个体间差异很大。吲哚菁绿(ICG)是一种广泛应用于肝功能评估的测试化合物。静脉注射后,根据ICG的血浆消失曲线计算药代动力学(PK)参数,这些参数可提供肝功能的估计值。ICG的肝脏消除受生理因素如肝血流量或ICG与血浆蛋白的结合、人体测量因素如体重、年龄和性别,或介导ICG肝脏摄取的有机阴离子转运多肽1B3(OATP1B3)的蛋白量的影响。能够解释并更好地理解这些个体间差异的各种来源将有助于提高基于ICG的DLFT的效能,并朝着肝功能的个体化评估迈进。在这项工作中,我们通过计算建模系统地分析了各种因素对ICG消除的影响。为了进行分析,我们使用了最近开发并验证的基于生理的ICG分布和肝脏消除药代动力学(PBPK)模型。主要结果包括:(i)对由于肝血流量、心输出量、OATP1B3丰度、肝脏体积、体重和血浆胆红素水平导致的ICG消除变异性进行系统分析;(ii)基于美国国家健康与营养检查调查(NHANES)队列,通过100,000名受试者的大型队列评估ICG消除的个体间差异,特别关注按年龄、性别和体重分层;(iii)评估不同程度肝硬化对ICG消除变异性的影响。通过阐明在通过ICG评估肝功能时混杂的生理和人体测量参数的影响,所呈现的结果是朝着肝功能测试个体化迈出的重要一步。