Department of Human Genetics and Molecular Medicine, Central University of Punjab, Bathinda, Punjab.
Int J Neurosci. 2020 Dec;130(12):1250-1266. doi: 10.1080/00207454.2020.1732964. Epub 2020 Feb 27.
Stroke or 'brain attack' is considered to be the major cause of mortality and morbidity worldwide after myocardial infraction. Inspite of the years of research and clinical practice, the pathogenesis of stroke still remains incompletely understood. Omics approaches not only enable the description of a huge number of molecular platforms but also have a potential to recognize new factors associated with various complex disorders including stroke. The most significant development among all other omics technologies over the recent years has been seen by genomics which is a powerful tool for exploring the genetic architecture of stroke. Genomics has decisively established itself in stroke research and by now wealth of data has been generated providing new insights into the physiology and pathophysiology of stroke. However, the efficacy of genomic data is restricted to risk prediction only. Omics approaches not only enable the description of a huge number of molecular platforms but also have a potential to recognize new factors associated with various complex disorders including stroke. The data generated by omics technologies enables clinicians to provide detailed insight into the makeup of stroke in individual patients, which will further help in developing diagnostic procedures to direct therapies. Present review has been compiled with an aim to understand the potential of integrated omics approach to help in characterization of mechanisms leading to stroke, to predict the patient risk of getting stroke by analyzing signature biomarkers and to develop targeted therapeutic strategies.
中风或“脑中风”被认为是全球继心肌梗死之后导致死亡率和发病率的主要原因。尽管经过多年的研究和临床实践，中风的发病机制仍不完全清楚。组学方法不仅能够描述大量的分子平台，而且还有可能识别与各种复杂疾病（包括中风）相关的新因素。在近年来所有其他组学技术中，基因组学是一个探索中风遗传结构的强大工具，它是最显著的发展。基因组学已在中风研究中占据了决定性地位，到目前为止，已经产生了大量的数据，为中风的生理学和病理生理学提供了新的见解。然而，基因组数据的有效性仅限于风险预测。组学方法不仅能够描述大量的分子平台，而且还有可能识别与各种复杂疾病（包括中风）相关的新因素。组学技术产生的数据使临床医生能够深入了解个别患者中风的构成，这将有助于进一步开发诊断程序以指导治疗。本综述的目的是了解综合组学方法在帮助阐明导致中风的机制、通过分析特征生物标志物预测患者中风风险以及开发靶向治疗策略方面的潜力。
