In vitro models for the blood-brain barrier
In vitro models for the blood-brain barrier
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DOI：
10.1016/j.tiv.2004.06.011
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发表时间：
2005-04-01
影响因子：
3.2
通讯作者：
Österberg, T
中科院分区：
文献类型：
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作者：
Garberg, P;Ball, M;Österberg, T
本研究的目的是确定一个模型的基础上使用的连续细胞系的血脑屏障，并调查该模型的特异性。选择了一组测试化合物，反映了不同的传输机制和不同程度的渗透性，以及不同的理化性质。作为研究的一部分，使用两种不同的体内模型生成这组测试化合物穿过血脑屏障的体内数据。还开发了一个计算预测模型，基于74个专有的Pharmacia化合物，以前在体内模型之一进行了测试。计算Molsurf描述符，并使用偏最小二乘投影到潜在结构（PLS）将21个描述符与log（脑（浓度）/血浆（浓度））相关。然而，预测值和测量值之间的相关性被认为是相当低的，不同的几个化合物之间的一个和两个对数单位。使用与星形胶质细胞共培养的原代牛和人脑内皮细胞，以及使用两种不同的永生化脑内皮细胞系（一种来自大鼠，一种来自小鼠），在体外分析供试化合物。还使用了使用非来源于血脑屏障的细胞、ECV/C6、MDCK和Caco-2细胞系的细胞模型。当分析中包括所有化合物时，未发现任何体外模型的体内和体外渗透性之间存在线性相关性。在牛脑内皮细胞（r（2）= 0.43）和MDCKwt（r（2）= 0.46）细胞模型中观察到最高的r（2）值。当分析中仅包括被动转运的化合物时，观察到更高的相关性，牛脑内皮细胞（r（2）= 0.74）、MDCKwt（r（2）= 0.65）和Caco-2（r（2）= 0.86）。通过绘制体内Parr值对log D-pH 7.4的曲线，可以将化合物分为四种不同的类别：（1）通过被动扩散穿过血-雨屏障的化合物，（2）通过血流受限的被动扩散穿过血-脑屏障的化合物，（3）通过载体介导的流入穿过血-脑屏障的化合物，和（4）通过主动外排从脑中主动排泄的化合物。用不同的体外模型获得的P-app和P-e值也对log D-pH 7.4作图，并与用体内P-app值获得的图进行比较。几种体外模型可以区分被动分布的化合物和外排底物。在本研究中包括的细胞系中，MDCKmr-1细胞系对被动和流出化合物的分离效果最好。还计算了六种化合物的脑中AUC和血液中AUC之间的比率，并与顶侧至基底侧和基底侧至顶侧方向上转运的P-e或P-app之间的比率进行比较。同样，MDCKmdr-1细胞系仅与一种化合物（AZT）具有最佳相关性，这使得体外和体内数据之间存在较大差异。没有一种体外模型能够鉴定出已知为载体介导的内流的底物的化合物，这些结果表明，为了更好地研究载体介导的内流，可能需要一个更紧密的体外血脑屏障模型。这些结果还表明，为了改善体外试验，可能需要鉴定体外试验的“电池”。在体内相关性，并使其有可能进行可接受的预测，在体内脑分布从体外数据。(c)2004爱思唯尔有限公司保留所有权利。
The aim of the present study was to identify a model for the blood-brain barrier based on the use of a continuous cell line, and to investigate the specificity of this model. A set of test compounds, reflecting different transport mechanisms and different degrees of permeability, as well as different physiochemical properties was selected. In vivo data for transport across the blood-brain barrier of this set of test compounds was generated as part of the study using two different in vivo models. A computational prediction model was also developed, based on 74 proprietary Pharmacia compounds, previously tested in one of the in vivo models. Molsurf descriptors were calculated and 21 descriptors were correlated with log(Brain(conc)/Plasma(conc)) using partial least squares projection to latent structures (PLS). However, the correlation between predicted and measured values was found to be rather low and differed between one and two log units for several of the compounds. The test compounds were analyzed in vitro using primary bovine and human brain endothelial cells co-cultured with astrocytes, and also using two different immortalized brain endothelial cell lines, one originating from rat and one from mouse. Cell models using cells not derived from the blood-brain barrier, ECV/C6, MDCK and Caco-2 cell lines, were also used. No linear correlation between in vivo and in vitro permeability was found for any of the in vitro models when all compounds were included in the analysis. The highest r(2) values were seen in the bovine brain endothelial cells (r(2) = 0.43) and MDCKwt (r(2) = 0.46) cell models. Higher correlations were seen when only passively transported compounds were included in the analysis, bovine brain endothelial cells (r(2) = 0.74), MDCKwt (r(2) = 0.65) and Caco-2 (r(2) = 0.86). By plotting in vivo Parr values against log D-pH7.4 it was possible to classify compounds into four different classes: (1) compounds crossing the blood-rain barrier by passive diffusion, (2) compounds crossing the blood-brain barrier by blood-flow limited passive diffusion, (3) compounds crossing the blood-brain barrier by carrier mediated influx, and (4) compounds being actively excreted from the brain by active efflux. P-app and P-e alues obtained using the different in vitro models were also plotted against log D-pH7.4 and compared to the plot obtained when in vivo P-app values were used. Several of the in vitro models could distinguish between passively distributed compounds and efflux substrates. Of the cell lines included in the present study, the MDCKmr-1 cell line gave the best separation of passively and effluxed compounds. Ratios between AUC in brain and AUC in blood were also calculated for six of the compounds and compared to ratios between P-e or P-app for transport in the apical to basolateral and basolateral to apical direction. Again the MDCKmdr-1 cell line gave the best correlation with only one compound (AZT) giving large discrepancy between in vitro and in vivo data. None of the in vitro models could identify compounds known to be substrates for carrier mediated influxed as such, and the results indicate that a tighter in vitro blood-brain barrier model probably is needed in order to facilitate studies on carrier mediated influx.The findings presented also indicate that identification of "batteries" of in vitro tests are likely to be necessary in order to improve in vitro-in vivo correlationsand to make it possible to perform acceptable predictions of in vivo brain distributions from in vitro data. (c) 2004 Elsevier Ltd. All rights reserved.