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一种健康状态下神经丝运输的与年龄相关的数学模型。

An age-dependent mathematical model of neurofilament trafficking in healthy conditions.

机构信息

Fondazione The Microsoft Research - University of Trento Centre for Computational and Systems Biology, Rovereto, Italy.

Biogen, Inc., Cambridge, Massachusetts, USA.

出版信息

CPT Pharmacometrics Syst Pharmacol. 2022 Apr;11(4):447-457. doi: 10.1002/psp4.12770. Epub 2022 Mar 2.

Abstract

Neurofilaments (Nfs) are the major structural component of neurons. Their role as a potential biomarker of several neurodegenerative diseases has been investigated in past years with promising results. However, even under physiological conditions, little is known about the leaking of Nfs from the neuronal system and their detection in the cerebrospinal fluid (CSF) and blood. This study aimed at developing a mathematical model of Nf transport in healthy subjects in the 20-90 age range. The model was implemented as a set of ordinary differential equations describing the trafficking of Nfs from the nervous system to the periphery. Model parameters were calibrated on typical Nf levels obtained from the literature. An age-dependent function modeled on CSF data was also included and validated on data measured in serum. We computed a global sensitivity analysis of model rates and volumes to identify the most sensitive parameters affecting the model's steady state. Age, Nf synthesis, and degradation rates proved to be relevant for all model variables. Nf levels in the CSF and in blood were observed to be sensitive to the Nf leakage rates from neurons and to the blood clearance rate, and CSF levels were also sensitive to rates representing CSF turnover. An additional parameter perturbation analysis was also performed to investigate possible transient effects on the model variables not captured by the sensitivity analysis. The model provides useful insights into Nf transport and constitutes the basis for implementing quantitative system pharmacology extensions to investigate Nf trafficking in neurodegenerative diseases.

摘要

神经丝 (Nfs) 是神经元的主要结构成分。近年来,它们作为几种神经退行性疾病的潜在生物标志物的作用已经过研究,结果令人鼓舞。然而,即使在生理条件下,人们对 Nfs 从神经元系统漏出及其在脑脊液 (CSF) 和血液中的检测也知之甚少。本研究旨在为 20-90 岁健康受试者的 Nf 转运建立数学模型。该模型被实现为一组描述 Nfs 从神经系统向周围系统转运的常微分方程。模型参数通过文献中获得的典型 Nf 水平进行校准。还包括了一个基于 CSF 数据的年龄依赖性函数,并在血清中测量的数据上进行了验证。我们对模型速率和体积进行了全局敏感性分析,以确定影响模型稳态的最敏感参数。年龄、Nf 合成和降解速率被证明对所有模型变量都很重要。CSF 和血液中的 Nf 水平被观察到对神经元 Nf 漏出率和血液清除率敏感,而 CSF 水平也对代表 CSF 周转率的速率敏感。还进行了额外的参数扰动分析,以研究敏感性分析未捕获的对模型变量的可能瞬态影响。该模型提供了对 Nf 转运的有用见解,并为实施定量系统药理学扩展以研究神经退行性疾病中的 Nf 转运奠定了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9193/9007607/28da5ed2eaae/PSP4-11-447-g002.jpg

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