School of Public Health and Health Policy, City University of New York, 55 West 125th St, NY, 10027, New York, USA.
School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
Curr Cardiol Rep. 2023 Feb;25(2):67-76. doi: 10.1007/s11886-022-01829-8. Epub 2023 Jan 14.
This review summarizes major insights into causal risk factors for cardiovascular disease (CVD) by using Mendelian randomization (MR) to obtain unconfounded estimates, contextualized within its strengths and weaknesses.
MR studies have confirmed the role of major CVD risk factors, including alcohol, smoking, adiposity, blood pressure, type 2 diabetes, lipids, and possibly inflammation, but added that the relation with alcohol is likely linear, confirmed the role of diastolic blood pressure, identified apolipoprotein B as the major target lipid, and foreshadowed results of some trials concerning anti-inflammatories. Identifying a healthy diet and the role of early life influences, such as birth weight, has proved more difficult. Use of MR has winnowed empirically driven hypotheses about CVD into a set of genetically validated targets of intervention. Greater inclusion of global diversity in genetic studies and the use of an overarching framework would enable even more informative MR studies.
本综述通过使用孟德尔随机化（MR）来获得无偏估计，总结了心血管疾病（CVD）因果风险因素的主要见解，并结合其优缺点进行了阐述。
MR 研究证实了主要 CVD 风险因素的作用，包括酒精、吸烟、肥胖、血压、2 型糖尿病、脂质，以及可能的炎症，但也表明酒精与 CVD 的关系可能呈线性，证实了舒张压的作用，确定了载脂蛋白 B 是主要的目标脂质，并预示了一些关于抗炎药的试验结果。确定健康饮食和出生体重等早期生活影响的作用则更为困难。MR 的使用已经将 CVD 的经验驱动假说筛选为一组经过基因验证的干预靶点。在遗传研究中更大程度地纳入全球多样性，并采用一个总体框架，将使 MR 研究更具信息量。
