组成型雄烷受体(CAR 或 NR1I3)转录因子的同工酶水平表达能更好地预测人体肝脏样本中细胞色素 P450s 的 mRNA 表达。

IF 4.4 3区 医学 Q1 PHARMACOLOGY & PHARMACY
Joseph M Collins, Danxin Wang
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引用次数: 0

摘要

许多因素会导致肝脏细胞色素 P450(CYP)药物代谢酶的活性和表达的人际变异,从而导致不同的药物暴露和治疗结果。几种富含肝脏的转录因子(TFs)与 CYP 的表达有关,其中雌激素受体α(ESR1)和组成型雄烷受体(CAR 或 NR1I3)是最主要的两个因子。ESR1 和 NR1I3 经过广泛的替代剪接,产生了许多剪接异构体,但这些剪接异构体如何与 CYP 表达相关尚不清楚。在这里,我们对来自非裔美国人(AA,n=125)和欧裔美国人(EA,n=135)的 260 份肝脏样本中的 18 种 NR1I3 剪接异构体和三种最丰富的 ESR1 异构体进行了量化。我们的研究结果表明,肝脏中 NR1I3 和 ESR1 的剪接同工酶群各不相同。多元线性回归分析显示,与基因水平的 NR1I3 相比,同工酶水平的 NR1I3 表达能更好地预测大多数 CYPs 和三种 UDP-葡萄糖醛酸转移酶(UGTs)的 mRNA 表达,而 ESR1 同工酶能改善 UGTs 和 CYP2D6 的预测模型,但不能预测大多数 CYPs。此外,不同的 NR1I3 同工酶与不同的 CYPs 有关联,且关联因样本血统而异。令人惊讶的是,保留了内含子(内含子 2 或 6)的非规范 NR1I3 同工型表达丰富,并与大多数 CYPs 和 UGTs 的表达相关,而参考同工型(NR1I3-205)仅与 CYP2D6 相关。此外,在诱导多能干细胞向肝细胞分化的过程中,NR1I3 同工酶多样性增加,与 CYP 表达的增加同步。这些结果表明,同工酶水平的 TF 表达可能有助于解释不同个体之间 CYP 或 UGT 表达的差异。意义声明 我们对来自 AA 和 EA 供体的 260 份肝脏样本中的 18 种 NR1I3 拼接同工酶和 3 种 ESR1 拼接同工酶进行了定量分析,发现肝脏中 NR1I3 和 ESR1 拼接同工酶的表达存在差异。多元线性回归分析表明,与基因水平的表达相比,NR1I3 和 ESR1 的同工酶水平表达能更好地预测某些 CYPs 和 UGTs 的 mRNA 表达,这凸显了同工酶水平分析对于加深我们对控制药物代谢酶表达的基因转录调控网络的了解的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Isoform-level expression of the constitutive androstane receptor (CAR or NR1I3) transcription factor better predicts the mRNA expression of the cytochrome P450s in human liver samples.

Many factors cause inter-person variability in the activity and expression of liver cytochrome P450 (CYP) drug-metabolizing enzymes, leading to variable drug exposure and treatment outcomes. Several liver-enriched transcription factors (TFs) are associated with CYP expression, with estrogen receptor alpha (ESR1) and constitutive androstane receptor (CAR or NR1I3) being the two top factors. ESR1 and NR1I3 undergo extensive alternative splicing that results in numerous splice isoforms, but how these splice isoforms associate with CYP expression is unknown. Here, we quantified 18 NR1I3 splice isoforms and the three most abundant ESR1 isoforms in 260 liver samples derived from African Americans (AA, n=125) and European Americans (EA, n=135). Our results showed variable splice isoform populations in the liver for both NR1I3 and ESR1. Multiple linear regression analyses revealed that, compared to gene-level NR1I3, isoform-level NR1I3 expression better predicted the mRNA expression of most CYPs and three UDP-glucuronosyltransferases (UGTs), while ESR1 isoforms improved predictive models for the UGTs and CYP2D6, but not for most CYPs. Also, different NR1I3 isoforms were associated with different CYPs, and the associations varied depending on sample ancestry. Surprisingly, non-canonical NR1I3 isoforms having retained introns (introns 2 or 6) were abundantly expressed and associated with the expression of most CYPs and UGTs, whereas the reference isoform (NR1I3-205) only associated with CYP2D6. Moreover, NR1I3 isoform diversity increased during the differentiation of induced pluripotent stem cells to hepatocytes, paralleling increasing CYP expression. These results suggest that isoform-level TF expression may help to explain variation in CYP or UGT expression between individuals. Significance Statement We quantified 18 NR1I3 splice isoforms and three ESR1 splice isoforms in 260 liver samples derived from AA and EA donors and found variable NR1I3 and ESR1 splice isoform expression in the liver. Multiple linear regression analysis showed that, compared to gene-level expression, isoform-level expression of NR1I3 and ESR1 better predicted the mRNA expression of some CYPs and UGTs, highlighting the importance of isoform-level analyses to enhance our understanding of gene transcriptional regulatory networks controlling the expression of drug-metabolizing enzymes.

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来源期刊
CiteScore
6.50
自引率
12.80%
发文量
128
审稿时长
3 months
期刊介绍: An important reference for all pharmacology and toxicology departments, DMD is also a valuable resource for medicinal chemists involved in drug design and biochemists with an interest in drug metabolism, expression of drug metabolizing enzymes, and regulation of drug metabolizing enzyme gene expression. Articles provide experimental results from in vitro and in vivo systems that bring you significant and original information on metabolism and disposition of endogenous and exogenous compounds, including pharmacologic agents and environmental chemicals.
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