美国神经系统疾病领域个性化药物

神经系统疾病是导致人类残疾和死亡的重要原因之一,对人类健康和社会经济造成极大的危害。在美国,每年用于神经系统疾病的支出接近8 000亿美元。近年来,精准医学已成为医疗健康领域关注的热点,个性化用药作为精准医学的重要组成部分,通过对患者进行分层,提高了药物使用的有效性和安全性。该文参照美国食品药品监督管理局(U.S. Food and Drug Administration, FDA)和个性化医学联盟(Personalized Medicine Coalition, PMC)的个性化药物报告,从基因标签、适应症等方面对美国神经系统疾病领域个性化药物进行简要分析,为临床合理用药提供依据,并为个性化药物开发提供参考。     

4P医学在音乐健康管理中的应用

21世纪的医学模式正在经历一场由疾病医学向健康医学转化的战略转移,其根本的标志是4P医学理念与框架的建立,其包括预测医学(predictive medicine)、预防医学(preventive medicine)、参与医学(participatory medicine)和个体化医学(presonalized medicine)。随着国外音乐治疗的引入,我们对音乐的认识也在不断提高,但目前仍缺少系统的管理理念,因此,本文首次提出4P音乐健康管理理念,即在4P医学理念的基础上,建立预测、预防、个性化和公众参与式的音乐健康理念,它为人们身心健康提供了新的方法论。     

转化医学与生物样本库现状

转化医学(translational medicine)是近10年来国际生物医学领域出现的新概念和重点研究方向,其为一种倡导实验室与临床研究双向转化的模式,而这种模式的核心意义之一便体现在协作与资源共享方面。这便促使生物样本库成为了转化医学的战略资源。本文在分析发达国家促进转化医学发展政策的同时分析了生物样本库建设的现状、趋势和问题,旨在为我国制定转化医学发展战略,建设生物样本库,促进转化医学发展提供参考。     

微生态学与医学的关系简析

作为生命科学的一个新兴领域 ,微生态学正在显示出巨大的生命力和科学价值。微生态学与医学的结合 ,产生了一门新的学科——医学微生态学 ,不仅对医学的发展进步起到了积极的推动和促进作用 ,也为生态学原理和方法的应用开拓了新的领域 ,丰富和发展了生态学作为生命科学学科领域的一个重要支柱的内涵和价值。因此 ,研究和探讨微生态与医学的关系 ,无疑是有着重要的理论和实践意义。1　有关微生态学的两个基本问题1.1　基本概念　微生态学的形成与发展 ,是现代生态学 (e-cology)发展的一个新成果。生态学经历了 12 0多年的历程 ,已经发展成为…     

组学在转化医学中的应用进展

作为当前医学科学研究领域的热点方向,转化医学(translational medicine)是指以患者为中心,从临床应用的实际需求出发,将基础研究成果快速有效地转化为临床技术的过程,并通过临床数据的深入分析进一步指导基础研究,以循环的方式不断高效促成医疗水平的提升与完善,从而更好地服务于人类健康。作为转化医学的重要研究手段,基因组学、转录组学、蛋白组学和代谢组学等技术平台为其高速发展提供了强劲的动力。文章对转化医学及其相关组学平台的应用进行了阐述,并对其发展趋势进行了探讨。     

信息科学在生理学及医学领域的应用及意义

2021年美国科学家戴维·朱利叶斯(David Julius)和阿登·帕塔普蒂安(Ardem Patapoutian)因“发现温度和触觉感受器”而获得诺贝尔生理学或医学奖，该发现为信息科学(information science)在生理学及医学中的应用指引了新方向。信息科学是研究信息运动规律和应用方法的科学，其中计算机大数据、数学建模模型具有来源多样、数据量增长快和高频等特征，为生理学和医学研究提供了新的分析视野。本文梳理了生理学及医学领域数据信息的提取步骤，比较了传统机器学习、深度学习、推荐系统和传统统计学方法的实现原理和技术特点，探讨了未来的信息科学和生理学及医学相结合的研究方向，以揭示信息科学在生理学及医学中应用的基本方法和原理及其对科学发展的意义。     

2015年中国医学遗传学研究领域若干重要进展

2015年中国医学遗传学稳步发展,众多具有原创性的研究论文在国际顶级杂志上发表。中国科学家在医学遗传学的诸多领域,如罕见疾病的致病基因、复杂疾病的易感基因、癌症的体细胞突变、遗传学新方法新技术、疾病相关微小RNA(microRNA,miRNA)、疾病相关长链非编码RNA(Long non-coding RNA,lncRNA)、疾病相关竞争性内源RNA(Competing endogenous RNA,ceRNA)、疾病相关可变剪接和分子进化等研究领域均取得了突破性的进展。中国科学家在医学遗传学研究中逐步从常见变异延伸到罕见变异,从遗传学现象的描述到功能机制的确证,从单组学分析扩展至多组学数据整合,从基础研究走向临床应用。同时,中国科学家的研究成果引起了国际同行的高度关注。本文概括性综述了2015年中国科学家在医学遗传学领域取得的若干重要研究进展,旨在追踪当前中国医学遗传学领域发展的前沿,与国内读者分享我国科学家在该领域取得的重要成果以及研究思路。     

循证医学在慢性充血性心力衰竭药物治疗中的应用

循证医学(evidence-based medicine,EBM)是近年来国际临床医学领域迅速发展起来的新学科,强调"为每位病人作出医疗决定时,应明确而仔细地使用现有的最好证据"。本文利用循证医学的方法,参照若干著名的大规模多中心的随机对照试验(ran- domized controlled trial,RCT)来评估目前几类临床常用药物在治疗慢性充血性心力衰竭中的作用,试图找出针对不同NYHA等级患者的最佳治疗建议。     

13-甲基肉豆蔻酸药理活性研究进展

根据近年文献报道13-甲基肉豆蔻酸(13-MTD)存在的广泛药理功效,综述了13-MTD在医学领域的研究概况及其药理学特性,并对13-MTD在医学领域的研究方向和发展前景进行了展望,以期为今后更深层次的研究作综合性的参考.     

干细胞与再生医学

多能干细胞(PSCs)具有发育的多潜能性,可以分化为机体各种细胞类型,是再生医学领域进行细胞替代治疗以及组织/器官再生的基础.如何由终末分化的体细胞重编程获得病人特异的PSCs,是再生医学领域的核心问题之一,目前主要采取两种重编程策略:借助核移植技术由早期胚胎体外建系获得,或通过诱导重编程技术获得.本文将综述不同多能性等级PSCs的获得方法以及其在多能性机制研究中的应用,并讨论PSCs通过异种嵌合实现组织/器官再造的潜在应用价值.PSCs的研究不仅推动了基础生物学研究的发展,同时也为再生医学走向临床开辟了道路.     

Proteomics and personalized medicine: a focus on kidney disease

ABSTRACT

Introduction: Inter-individual variability in response to drug treatment has induced an increased demand for decisions via personalize medicine. Also, the contribution of proteomics to the era of personalized medicine would seem to be vital in improving therapeutic outcomes.

Areas covered: We review validated biomarkers discovered by proteomics techniques and their use in personalized medicine with the focus on kidney diseases. We discuss this topic with a special emphasis on recent publications and relevant initiatives and depict some limitations that remain for personalized medicine.

Expert opinion: The development of highly accurate biomarkers is essential for optimizing the management of kidney diseases. Various biomarkers of kidney diseases have been identified using proteomic techniques. However, only a few of these biomarkers showed the potential to be used in clinical practice concerning personalized medicine. Therefore, it becomes evident that the combination of multiple biomarkers confers higher accuracy and the ability to depict complex pathophysiological conditions, a prerequisite for personalized treatment. CKD273, a multimarker panel for early CKD detection may serve as a first example for personalized medicine in nephrology. Based on this successful example, proteomics is expected to develop into the key technology to guide personalized intervention.     

Integrate personalized medicine into clinical practice to improve patient safety

Medical practice is based on the experience of practitioners and on learned medical knowledge. This knowledge is based on studies of patient's population. Modern medicine is facing a variety of clinical forms and also variable patients’ responses to treatment. Pharmacogenomics has brought insights to this variability and has led to the development of personalized medicine. The adoption of personalized medicine is slowed down by a number of technical and methodology barriers. The concept of personalized medicine should not be only limited to genetics but must reuse all patient information to get the most suitable patient profile. In this paper we present a methodology for the integration of personalized medicine into clinical practice.     

The path to personalized medicine

Advances in personalized medicine, or the use of an individual's molecular profile to direct the practice of medicine, have been greatly enabled through human genome research. This research is leading to the identification of a range of molecular markers for predisposition testing, disease screening and prognostic assessment, as well as markers used to predict and monitor drug response. Successful personalized medicine research programs will not only require strategies for developing and validating biomarkers, but also coordinating these efforts with drug discovery and clinical development.     

Precision medicine in human heart modeling

Precision medicine is a new frontier in healthcare that uses scientific methods to customize medical treatment to the individual genes, anatomy, physiology, and lifestyle of each person. In cardiovascular health, precision medicine has emerged as a promising paradigm to enable cost-effective solutions that improve quality of life and reduce mortality rates. However, the exact role in precision medicine for human heart modeling has not yet been fully explored. Here, we discuss the challenges and opportunities for personalized human heart simulations, from diagnosis to device design, treatment planning, and prognosis. With a view toward personalization, we map out the history of anatomic, physical, and constitutive human heart models throughout the past three decades. We illustrate recent human heart modeling in electrophysiology, cardiac mechanics, and fluid dynamics and highlight clinically relevant applications of these models for drug development, pacing lead failure, heart failure, ventricular assist devices, edge-to-edge repair, and annuloplasty. With a view toward translational medicine, we provide a clinical perspective on virtual imaging trials and a regulatory perspective on medical device innovation. We show that precision medicine in human heart modeling does not necessarily require a fully personalized, high-resolution whole heart model with an entire personalized medical history. Instead, we advocate for creating personalized models out of population-based libraries with geometric, biological, physical, and clinical information by morphing between clinical data and medical histories from cohorts of patients using machine learning. We anticipate that this perspective will shape the path toward introducing human heart simulations into precision medicine with the ultimate goals to facilitate clinical decision making, guide treatment planning, and accelerate device design.

     

Predictive diagnostics and personalized medicine for the prevention of chronic degenerative diseases

Progressive increase of mean age and life expectancy in both industrialized and emerging societies parallels an increment of chronic degenerative diseases (CDD) such as cancer, cardiovascular, autoimmune or neurodegenerative diseases among the elderly. CDD are of complex diagnosis, difficult to treat and absorbing an increasing proportion in the health care budgets worldwide. However, recent development in modern medicine especially in genetics, proteomics, and informatics is leading to the discovery of biomarkers associated with different CDD that can be used as indicator of disease's risk in healthy subjects. Therefore, predictive medicine is merging and medical doctors may for the first time anticipate the deleterious effect of CDD and use markers to identify persons with high risk of developing a given CDD before the clinical manifestation of the diseases. This innovative approach may offer substantial advantages, since the promise of personalized medicine is to preserve individual health in people with high risk by starting early treatment or prevention protocols. The pathway is now open, however the road to an effective personalized medicine is still long, several (diagnostic) predictive instruments for different CDD are under development, some ethical issues have to be solved. Operative proposals for the heath care systems are now needed to verify potential benefits of predictive medicine in the clinical practice. In fact, predictive diagnostics, personalized medicine and personalized therapy have the potential of changing classical approaches of modern medicine to CDD.     

Personalized health care: from theory to practice

The practice of medicine stands at the threshold of a transformation from its current focus on the treatment of disease events to an emphasis on enhancing health, preventing disease and personalizing care to meet each individual's specific health needs. Personalized health care is a new and strategic approach that is driven by personalized health planning empowered by personalized medicine tools, which are facilitated by advances in science and technology. These tools improve the capability to predict health risks, to determine and quantify the dynamics of disease development, and to target therapeutic approaches to the needs of the individual. Personalized health care can be implemented today using currently available technologies and know-how and thereby provide a market for the rational introduction of new personalized medicine tools. The need for early adoption of personalized health care stems from the necessity to reduce the egregious and wasteful burden of preventable chronic diseases, which is not effectively addressed by our current approach to care.     

Editorial: Systems biology and personalized medicine - the future is now

This special issue on "Systems biology and personalized medicine" includes five complementary articles that highlight how functional genomics and computational physiology can contribute to the development of predictive, preventive, personalized and participatory (P4) medicine. Edited by Prof. Leroy Hood and Prof. Charles Auffray.     

An economic perspective on personalized medicine

The concept of personalized medicine not only promises to enhance the life of patients and increase the quality of clinical practice and targeted care pathways, but also to lower overall healthcare costs through early-detection, prevention, accurate risk assessments and efficiencies in care delivery. Current inefficiencies are widely regarded as substantial enough to have a significant impact on the economies of major nations like the US and China, and, therefore the world economy. A recent OECD report estimates healthcare expenditure for some of the developed western and eastern nations to be anywhere from 10% to 18%, and growing (with the US at the highest). Personalized medicine aims to use state-of-the-art genomic technologies, rich medical record data, tissue and blood banks and clinical knowledge that will allow clinicians and payors to tailor treatments to individuals, thereby greatly reducing the costs of ineffective therapies incurred through the current trial and error clinical paradigm. Pivotal to the field are drugs that have been designed to target a specific molecular pathway that has gone wrong and results in a diseased condition and the diagnostic tests that allow clinicians to separate responders from non-responders. However, the truly personalized approach in medicine faces two major problems: complex biology and complex economics; the pathways involved in diseases are quite often not well understood, and most targeted drugs are very expensive. As a result of all current efforts to translate the concepts of personalized healthcare into the clinic, personalized medicine becomes participatory and this implies patient decisions about their own health. Such a new paradigm requires powerful tools to handle significant amounts of personal information with the approach to be known as “P4 medicine”, that is predictive, preventive, personalized and participatory. P4 medicine promises to increase the quality of clinical care and treatments and will ultimately save costs. The greatest challenges are economic, not scientific.     

Personalized medicine: new genomics,old lessons

Personalized medicine uses traditional, as well as emerging concepts of the genetic and environmental basis of disease to individualize prevention, diagnosis and treatment. Personalized genomics plays a vital, but not exclusive role in this evolving model of personalized medicine. The distinctions between genetic and genomic medicine are more quantitative than qualitative. Personalized genomics builds on principles established by the integration of genetics into medical practice. Principles shared by genetic and genomic aspects of medicine, include the use of variants as markers for diagnosis, prognosis, prevention, as well as targets for treatment, the use of clinically validated variants that may not be functionally characterized, the segregation of these variants in non-Mendelian as well as Mendelian patterns, the role of gene–environment interactions, the dependence on evidence for clinical utility, the critical translational role of behavioral science, and common ethical considerations. During the current period of transition from investigation to practice, consumers should be protected from harms of premature translation of research findings, while encouraging the innovative and cost-effective application of those genomic discoveries that improve personalized medical care.