重编程
疾病
医学
表观遗传学
炎症
人口
心理干预
生物信息学
不利影响
免疫学
重症监护医学
生物
内科学
基因
遗传学
环境卫生
精神科
作者
Robin P. Choudhury,Rupen Hargreaves,Jason Chai,Edward A. Fisher
标识
DOI:10.1016/j.xcrm.2025.102288
摘要
The current generation of highly successful atherosclerosis treatments, such as low-density lipoprotein (LDL)-cholesterol reduction, blood pressure management, and smoking cessation, has largely focused on ameliorating factors perceived to drive incident disease and its complications. The adverse contributions of these factors have typically been identified through epidemiological studies. The therapeutic strategies that arose in response focused on risk factors for disease development and tended to overlook the fact that patients already have established disease, by the time of presentation. However, by capitalizing on contemporary biological knowledge and technologies, it is becoming increasingly possible to shift from a model based on population-derived risk factor management to next-generation treatments (including monoclonal antibodies, small interfering RNA [siRNA], mRNA, epigenetic reprogramming, and gene editing) for atherosclerosis that are tailored to patient-level disease processes, informed by mechanistic characterization, offer potential to reverse or regress disease, and incorporate systems-level interventions that extend beyond the atherosclerotic plaque.
科研通智能强力驱动
Strongly Powered by AbleSci AI