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心血管医学中的治疗学与基因组学的界面。

The Interface of Therapeutics and Genomics in Cardiovascular Medicine.

机构信息

William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.

Department of Clinical Pharmacology, Cardiovascular Medicine, Barts Health NHS Trust, London, UK.

出版信息

Cardiovasc Drugs Ther. 2021 Jun;35(3):663-676. doi: 10.1007/s10557-021-07149-3. Epub 2021 Feb 2.

Abstract

Pharmacogenomics has a burgeoning role in cardiovascular medicine, from warfarin dosing to antiplatelet choice, with recent developments in sequencing bringing the promise of personalised medicine ever closer to the bedside. Further scientific evidence, real-world clinical trials, and economic modelling are needed to fully realise this potential. Additionally, tools such as polygenic risk scores, and results from Mendelian randomisation analyses, are only in the early stages of clinical translation and merit further investigation. Genetically targeted rational drug design has a strong evidence base and, due to the nature of genetic data, academia, direct-to-consumer companies, healthcare systems, and industry may meet in an unprecedented manner. Data sharing navigation may prove problematic. The present manuscript addresses these issues and concludes a need for further guidance to be provided to prescribers by professional bodies to aid in the consideration of such complexities and guide translation of scientific knowledge to personalised clinical action, thereby striving to improve patient care. Additionally, technologic infrastructure equipped to handle such large complex data must be adapted to pharmacogenomics and made user friendly for prescribers and patients alike.

摘要

药物基因组学在心血管医学中发挥着日益重要的作用,从华法林剂量到抗血小板药物的选择,最近测序技术的发展使个体化医学的前景更接近临床。需要进一步的科学证据、真实世界的临床试验和经济建模来充分实现这一潜力。此外,多基因风险评分等工具和孟德尔随机分析的结果仅处于临床转化的早期阶段,值得进一步研究。基于遗传学的合理药物设计具有坚实的证据基础,由于遗传数据的性质,学术界、直接面向消费者的公司、医疗保健系统和行业可能以前所未有的方式汇聚在一起。数据共享导航可能会被证明是有问题的。本文讨论了这些问题,并得出结论,需要专业机构向处方者提供进一步的指导,以帮助考虑这些复杂性,并指导科学知识转化为个性化的临床行动,从而努力改善患者护理。此外,必须对配备有处理此类大型复杂数据的技术基础设施进行调整,使其对处方者和患者都友好易用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5de6/7851637/3453446b99e9/10557_2021_7149_Fig1_HTML.jpg

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