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孕妇转化系统药理学研究。

Translational Systems Pharmacology Studies in Pregnant Women.

机构信息

Department of Obstetrics and Gynecology, Indiana University School of Medicine, Indianapolis, Indiana, USA.

Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA.

出版信息

CPT Pharmacometrics Syst Pharmacol. 2018 Feb;7(2):69-81. doi: 10.1002/psp4.12269. Epub 2017 Dec 14.

DOI:10.1002/psp4.12269
PMID:29239132
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5824114/
Abstract

Pregnancy involves rapid physiological adaptation and complex interplay between mother and fetus. New analytic technologies provide large amounts of genomic, proteomic, and metabolomics data. The integration of these data through bioinformatics, statistical, and systems pharmacology techniques can improve our understanding of the mechanisms of normal maternal physiologic changes and fetal development. New insights into the mechanisms of pregnancy-related disorders, such as preterm birth (PTB), may lead to the development of new therapeutic interventions and novel biomarkers.

摘要

妊娠涉及母体和胎儿之间的快速生理适应和复杂相互作用。新的分析技术提供了大量的基因组、蛋白质组和代谢组学数据。通过生物信息学、统计和系统药理学技术整合这些数据,可以提高我们对正常母体生理变化和胎儿发育机制的理解。对妊娠相关疾病(如早产)机制的新认识可能会导致新的治疗干预和新的生物标志物的发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f74/5824114/57eb77196180/PSP4-7-69-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f74/5824114/599a3d840318/PSP4-7-69-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f74/5824114/57eb77196180/PSP4-7-69-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f74/5824114/599a3d840318/PSP4-7-69-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f74/5824114/57eb77196180/PSP4-7-69-g002.jpg

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本文引用的文献

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Genome-wide approach identifies a novel gene-maternal pre-pregnancy BMI interaction on preterm birth.全基因组方法鉴定出一个新的基因-母亲孕前 BMI 对早产的交互作用。
Nat Commun. 2017 Jun 9;8:15608. doi: 10.1038/ncomms15608.
2
The association among cytochrome P450 3A, progesterone receptor polymorphisms, plasma 17-alpha hydroxyprogesterone caproate concentrations, and spontaneous preterm birth.细胞色素P450 3A、孕激素受体多态性、血浆己酸17-α羟孕酮浓度与自发性早产之间的关联。
Am J Obstet Gynecol. 2017 Sep;217(3):369.e1-369.e9. doi: 10.1016/j.ajog.2017.05.019. Epub 2017 May 15.
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Application of physiologically based pharmacokinetic modeling to predict drug disposition in pregnant populations.
基于网络药理学策略探索淫羊藿苷治疗骨质疏松症的机制
Med Sci Monit. 2020 Nov 24;26:e924699. doi: 10.12659/MSM.924699.
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Reverse Translational Pharmacology Research Is Driven by Big Data.逆向转化药理学研究由大数据驱动。
CPT Pharmacometrics Syst Pharmacol. 2018 Feb;7(2):63-64. doi: 10.1002/psp4.12277. Epub 2018 Feb 19.
基于生理的药代动力学模型在预测孕妇群体药物处置中的应用。
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Gestation-Specific Changes in the Anatomy and Physiology of Healthy Pregnant Women: An Extended Repository of Model Parameters for Physiologically Based Pharmacokinetic Modeling in Pregnancy.妊娠女性健康的解剖学和生理学的妊娠期特异性变化:妊娠生理基于药代动力学模型的扩展模型参数库。
Clin Pharmacokinet. 2017 Nov;56(11):1303-1330. doi: 10.1007/s40262-017-0539-z.
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The maternal plasma proteome changes as a function of gestational age in normal pregnancy: a longitudinal study.正常妊娠中母血血浆蛋白质组随孕周变化:一项纵向研究。
Am J Obstet Gynecol. 2017 Jul;217(1):67.e1-67.e21. doi: 10.1016/j.ajog.2017.02.037. Epub 2017 Mar 3.
6
Pharmacogenomics of 17-alpha hydroxyprogesterone caproate for recurrent preterm birth: a case-control study.17-α羟孕酮己酸酯用于复发性早产的药物基因组学:一项病例对照研究。
BJOG. 2018 Feb;125(3):343-350. doi: 10.1111/1471-0528.14485. Epub 2017 Jan 31.
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Births: Final Data for 2015.出生情况:2015年最终数据。
Natl Vital Stat Rep. 2017 Jan;66(1):1.
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Amniotic Fluid and Maternal Serum Metabolic Signatures in the Second Trimester Associated with Preterm Delivery.孕中期羊水和母血清代谢特征与早产的相关性
J Proteome Res. 2017 Feb 3;16(2):898-910. doi: 10.1021/acs.jproteome.6b00845. Epub 2017 Jan 23.
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Proteomic Profiling of the Blood Serum for Prediction of Premature Delivery.用于预测早产的血清蛋白质组分析
Bull Exp Biol Med. 2016 Oct;161(6):829-832. doi: 10.1007/s10517-016-3522-z. Epub 2016 Oct 26.
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A Physiologically-Based Pharmacokinetic Model to Predict Human Fetal Exposure for a Drug Metabolized by Several CYP450 Pathways.一种基于生理学的药代动力学模型,用于预测经多种细胞色素P450途径代谢的药物对人类胎儿的暴露情况。
Clin Pharmacokinet. 2017 May;56(5):537-550. doi: 10.1007/s40262-016-0457-5.