From the College of Public Health, University of Kentucky, Lexington.
Circ Res. 2018 May 11;122(10):1409-1419. doi: 10.1161/CIRCRESAHA.118.311342.
Essential hypertension is a common, complex disorder affecting ≤1 billion adults globally. Blood pressure is a highly heritable trait, with ≤50% of the variation between individuals accounted for by familial relationships. Despite this strong heritability, determining the genetic architecture of hypertension in humans has proved challenging. Recent technological and methodological developments have given rise to what is now known as omics-a domain of study that includes genomics, as well as epigenomics, transcriptomics, proteomics, and metabolomics. For complex traits like hypertension, which involve multiple pathways and organs, omic approaches offer the advantage of allowing identification of novel hypertensive mechanisms to help further dissect and characterize the disorder's pathophysiology. This review provides a primer on the genomics, transcriptomics, proteomics, and metabolomics of blood pressure and hypertension. We provide an introduction to each approach with examples chosen to illustrate its potential. We conclude with a brief assessment of current methods aimed at integrating multiomic data. A review of the literature found genomic, epigenomic, transcriptomic, proteomic, and metabolomic methods have been applied to dissect the pathophysiology of blood pressure and hypertension. Omic methods and integration of multiomic data represent a potentially fruitful approach to illuminating the complex pathophysiology of hypertension and, ultimately, may point to novel diagnostics and treatments.
原发性高血压是一种常见的、复杂的疾病,影响着全球≤10 亿成年人。血压是一种高度遗传的特征,个体之间的差异只有≤50%可以用家族关系来解释。尽管这种遗传力很强,但确定人类高血压的遗传结构一直具有挑战性。最近的技术和方法学的发展催生了所谓的组学——这一领域的研究包括基因组学,以及表观基因组学、转录组学、蛋白质组学和代谢组学。对于像高血压这样涉及多个途径和器官的复杂特征,组学方法的优势在于可以识别新的高血压机制,有助于进一步剖析和描述该疾病的病理生理学。这篇综述提供了血压和高血压的基因组学、转录组学、蛋白质组学和代谢组学的入门知识。我们介绍了每种方法,并选择了一些例子来说明其潜力。最后,我们对目前旨在整合多组学数据的方法进行了简要评估。对文献的回顾发现,基因组学、表观基因组学、转录组学、蛋白质组学和代谢组学方法已被应用于剖析血压和高血压的病理生理学。组学方法和多组学数据的整合代表了一种有前途的方法,可以阐明高血压的复杂病理生理学,并最终可能指向新的诊断和治疗方法。