Glauber Harry S, Rishe Naphtali, Karnieli Eddy
Department of Endocrinology, Northwest Permanente, Portland, Oregon, USA; ; Galil Center for Telemedicine, Medical Informatics and Personalized Medicine, RB Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel.
Florida International University, Miami, Florida, USA;
Rambam Maimonides Med J. 2014 Jan 21;5(1):e0002. doi: 10.5041/RMMJ.10136. eCollection 2014 Jan.
The world is facing an epidemic rise in diabetes mellitus (DM) incidence, which is challenging health funders, health systems, clinicians, and patients to understand and respond to a flood of research and knowledge. Evidence-based guidelines provide uniform management recommendations for "average" patients that rarely take into account individual variation in susceptibility to DM, to its complications, and responses to pharmacological and lifestyle interventions. Personalized medicine combines bioinformatics with genomic, proteomic, metabolomic, pharmacogenomic ("omics") and other new technologies to explore pathophysiology and to characterize more precisely an individual's risk for disease, as well as response to interventions. In this review we will introduce readers to personalized medicine as applied to DM, in particular the use of clinical, genetic, metabolic, and other markers of risk for DM and its chronic microvascular and macrovascular complications, as well as insights into variations in response to and tolerance of commonly used medications, dietary changes, and exercise. These advances in "omic" information and techniques also provide clues to potential pathophysiological mechanisms underlying DM and its complications.
全球糖尿病(DM)发病率呈流行趋势上升,这对卫生资助者、卫生系统、临床医生和患者构成挑战,要求他们理解并应对大量的研究和知识。循证指南为“普通”患者提供统一的管理建议,但很少考虑到个体在糖尿病易感性、并发症以及对药物和生活方式干预反应方面的差异。精准医学将生物信息学与基因组学、蛋白质组学、代谢组学、药物基因组学(“组学”)及其他新技术相结合,以探索病理生理学,并更精确地描述个体的疾病风险以及对干预措施的反应。在本综述中,我们将向读者介绍应用于糖尿病的精准医学,特别是糖尿病及其慢性微血管和大血管并发症风险的临床、遗传、代谢及其他标志物的应用,以及对常用药物反应和耐受性、饮食变化及运动方面个体差异的见解。“组学”信息和技术的这些进展也为糖尿病及其并发症潜在的病理生理机制提供了线索。