FloTBI Inc., Cleveland, OH, USA.
Laboratory of Cerebrovascular and Glia Research, Department of Neuroscience, Institute of Functional Genomics (UMR 5203 CNRS - U 1191 INSERM), University of Montpellier, Montpellier, France.
Fluids Barriers CNS. 2022 May 11;19(1):32. doi: 10.1186/s12987-022-00329-9.
Blood biomarkers of neurological diseases are often employed to rule out or confirm the presence of significant intracranial or cerebrovascular pathology or for the differential diagnosis of conditions with similar presentations (e.g., hemorrhagic vs. embolic stroke). More widespread utilization of biomarkers related to brain health is hampered by our incomplete understanding of the kinetic properties, release patterns, and excretion of molecules derived from the brain. This is, in particular, true for S100B, an astrocyte-derived protein released across the blood-brain barrier (BBB). We developed an open-source pharmacokinetic computer model that allows investigations of biomarker's movement across the body, the sources of biomarker's release, and its elimination. This model was derived from a general in silico model of drug pharmacokinetics adapted for protein biomarkers. We improved the model's predictive value by adding realistic blood flow values, organ levels of S100B, lymphatic and glymphatic circulation, and glomerular filtration for excretion in urine. Three key variables control biomarker levels in blood or saliva: blood-brain barrier permeability, the S100B partition into peripheral organs, and the cellular levels of S100B in astrocytes. A small contribution to steady-state levels of glymphatic drainage was also observed; this mechanism also contributed to the uptake of organs of circulating S100B. This open-source model can also mimic the kinetic behavior of other markers, such as GFAP or NF-L. Our results show that S100B, after uptake by various organs from the systemic circulation, can be released back into systemic fluids at levels that do not significantly affect the clinical significance of venous blood or salivary levels after an episode of BBB disruption.
神经疾病的血液生物标志物常用于排除或确认颅内或脑血管疾病的存在，或用于具有相似表现的疾病的鉴别诊断（例如，出血性与栓塞性中风）。由于我们对源自大脑的分子的动力学特性、释放模式和排泄了解不完整，因此与大脑健康相关的生物标志物的广泛应用受到了阻碍。这在 S100B 中尤其如此，S100B 是一种星形胶质细胞衍生的蛋白，可穿过血脑屏障（BBB）释放。我们开发了一种开源的药代动力学计算机模型，该模型可用于研究生物标志物在体内的运动、生物标志物释放的来源及其消除。该模型源自适应于蛋白质生物标志物的一般药物药代动力学的计算机模型。我们通过添加真实的血流值、S100B 在器官中的水平、淋巴和神经胶质循环以及肾小球滤过以从尿液中排泄，来提高模型的预测价值。三个关键变量控制血液或唾液中的生物标志物水平：血脑屏障通透性、S100B 进入外周器官的分配以及星形胶质细胞中的 S100B 细胞水平。还观察到对神经胶质淋巴引流的稳态水平的微小贡献；该机制也有助于循环 S100B 器官的摄取。这种开源模型还可以模拟其他标志物（如 GFAP 或 NF-L）的动力学行为。我们的研究结果表明，S100B 从全身循环中被各种器官摄取后，可在不会显著影响 BBB 破坏后静脉血或唾液水平的临床意义的水平下，重新释放到全身液中。
