Causal associations of circulating biomarkers with cardiovascular disease

项目总结/摘要 心血管疾病（CVD）构成全球发病率和死亡率的主要原因，并且在美国， 在美国，CVD占所有死亡人数的三分之一以上，其中每年约有150，000人死亡， 65岁以下的人。在过去的几十年里，数百种循环生物标志物已经被 与CVD相关，但它们在实际疾病过程中的相对重要性和潜在参与 很少被调查。 使用一个非常大的队列研究，最近成为科学界，我们将部署 孟德尔随机化方法研究与CVD相关的生物标志物的因果作用。 2006-2010年，英国生物银行招募了502，650名年龄在37-73岁之间的参与者， 测量、关于风险因素和未来疾病事件的详细评估，以及血液采样， 尿液和唾液。在英国生物库Axiom阵列上进行全基因组基因分型（820，967个遗传标记）， 2016年将完成36种与CVD相关的循环生物标志物的测量。 我们将研究代表凝血和炎症的36种循环生物标志物的相关性， （纤维蛋白原、D-二聚体、hsCRP、类风湿因子）、葡萄糖稳态（HbA 1c、葡萄糖、IGF-1）、脂质 代谢（总胆固醇、LDL-C、HDL-C、甘油三酯、ApoAI、ApoB、Lp（a））、肝功能（ALT、AST、ALP， 直接胆红素和总胆红素、GGT、白蛋白、总蛋白）、肾功能（肌酸酐、胱抑素C、磷酸盐、尿酸盐， 尿素，尿钠，钾，微量白蛋白和肌酸酐），生殖系统（SHBG，睾酮， 雌二醇）和矿物质代谢（钙，维生素D）与冠心病，中风， 心力衰竭、心房颤动和2型糖尿病。 然后，我们将对所有36种生物标志物进行全基因组关联研究（GWAS），以建立共同的 与各自生物标志物相关的遗传变异。样本量约为39万人，我们将 具有出色的统计能力，可以揭示与以下疾病相关的大量常见遗传变异： 生物标志物。这些关联将用于开发强大的工具变量。 最后，使用工具变量分析，我们将研究这些循环生物标志物的因果作用 心血管疾病的发展。本研究的大样本量将允许 具有充分统计学意义的CVD生物标志物的孟德尔随机化研究的前所未有的可能性 功率和多效性风险低。 了解心血管疾病相关生物标志物对冠心病发生的因果作用， 中风、心力衰竭、心房颤动和2型糖尿病将提供关于病因学的重要见解。 这些疾病的认识和加速新的预防战略，包括药物的目标。

PROJECT SUMMARY/ABSTRACT Cardiovascular diseases (CVD) comprise the global leading cause of morbidity and mortality, and in the United States, CVD account for more than one-third of all deaths, of which ~150,000 deaths per year occurs in individuals younger than 65 years. Over the past decades, hundreds of circulating biomarkers have been associated with CVD, but their relative importance and potential involvement in the actual disease processes have been less investigated. Using a very large cohort study that recently became available to the scientific community, we will deploy Mendelian randomization methods to study the causal role of biomarkers proposed to be associated with CVD. In 2006-2010, the UK Biobank recruited 502,650 participants aged 37-73 years to undergo physical measurements, detailed assessments about risk factors and future disease events, and sampling of blood, urine and saliva. Genome-wide genotyping on the UK Biobank Axiom Array (820,967 genetic markers) and measurement of 36 circulating biomarkers with relevance for CVD will be finished during 2016. We will study the associations of 36 circulating biomarkers representing coagulation and inflammation (fibrinogen, D-dimer, hsCRP, rheumatoid factor), glucose homeostasis (HbA1c, glucose, IGF-1), lipid metabolism (total cholesterol, LDL-C, HDL-C, triglycerides, ApoAI, ApoB, Lp(a)), liver function (ALT, AST, ALP, direct and total bilirubin, GGT, albumin, total protein), kidney function (creatinine, cystatin C, phosphate, urate, urea, urinary sodium, potassium, microalbumin and creatinine), reproductive system (SHBG, testosterone, oestradiol), and mineral metabolism (calcium, vitamin D) with incidence of coronary heart disease, stroke, heart failure, atrial fibrillation and type 2 diabetes in traditional observational multivariable-adjusted analyses. We will then perform genome-wide association studies (GWAS) of all 36 biomarkers to establish common genetic variation associated with respective biomarker. With a sample size of ~390,000 individuals, we will have excellent statistical power to uncover a substantial fraction of common genetic variants associated with the biomarkers. These associations will be used to develop robust instrumental variables. Finally, using instrumental variable analyses, we will study the causal roles of these circulating biomarkers for development of cardiovascular disease. The large sample size of the present study will allow for unprecedented possibilities of Mendelian randomization studies of CVD biomarkers with adequate statistical power and with low risk of pleiotropy. Knowledge about the causal roles of CVD-related biomarkers for development of coronary heart disease, stroke, heart failure, atrial fibrillation and type 2 diabetes will provide important insights regarding the etiological understanding of these diseases and accelerate new prevention strategies, including druggable targets.