An integrated genetic and proteomic approach to understanding cardiovascular disease aetiology

我的研究计划专注于使用基因组技术来了解炎症和心血管疾病之间的联系。尽管在预防和治疗方面取得了进展，但心血管疾病仍是全球主要的死亡原因，这突显了需要新的治疗策略。大多数死亡是由于心肌梗死或“心脏病发作”。当动脉壁中的脂肪沉积破裂，引发血栓形成，阻断心脏的血液供应时，就会发生心脏病发作。这些脂肪堆积在动脉粥样硬化的过程中会持续多年。传统上，动脉粥样硬化被认为完全是由于过量脂肪的积累，但在过去的几十年里，炎症在这一过程中的重要性得到了越来越多的认识。炎症通常是对感染或伤害的一种保护性反应，但在某些情况下可能是有害的。已经开发了大量药物来治疗类风湿性关节炎等自身免疫性疾病中的有害炎症。这增加了这些或类似治疗方法对心血管疾病有效的可能性。事实上，最近的Cantos试验表明，Canakinumab，一种针对IL1-β蛋白的药物(最初是为风湿病设计的)，减少了高炎症水平患者的冠状动脉事件。炎症涉及多种蛋白质，因此确定哪些是最有希望的药物靶点是一个挑战。我建议通过整合‘高维’遗传和蛋白质组数据来解决这个问题。由于技术的进步，现在可以同时测量大量个体血液中的大量蛋白质(蛋白质组)。然而，仅仅显示一种蛋白质与心血管疾病的关联并不一定表明该蛋白质是有效的药物靶点，因为相关性并不总是反映因果关系。为了绕过这个问题，我将整合遗传信息，使用一种名为“孟德尔随机化”的方法。这种方法利用了生殖过程中发生的遗传变异的随机化，实际上提供了一种自然的随机试验。第一步是确定影响特定蛋白质水平的遗传变异。然后，通过检查遗传这些基因变异的个体患心血管疾病的风险是高还是低，我们可以确定这种蛋白是否可能在疾病中发挥因果作用，从而确定它是否是有效的药物靶点。在与帝国理工学院教授贾斯汀·梅森(Justin Mason)合作的一个补充链中，我正在研究大动脉炎患者，这是一种罕见的疾病，其特征是动脉炎症，通常会导致血管狭窄，或者不太常见的扩张(动脉瘤)。心血管并发症是发病率的主要原因。大动脉炎的预后非常不稳定--一些患者的病程是良性的，而另一些患者则发展为进行性血管损伤。我们将检查血浆蛋白质组，以了解影响这种变异性的因素，并确定可用于区分需要更强免疫抑制治疗的高危患者与那些温和、毒性较低的治疗就足够的患者。此外，我们预计，对一种极端形式的血管炎症的更好的理解应该能更全面地提供对心血管疾病的洞察。

My research programme is focussed on using genomic technologies to understand the links between inflammation and cardiovascular disease. Despite advances in prevention and treatment, cardiovascular disease is the leading cause of death worldwide, highlighting the need for new therapeutic strategies. Most deaths are due to myocardial infarction or "heart attack". Heart attacks occur when fatty deposits in the wall of an artery rupture, triggering formation of a clot which blocks the blood supply to the heart. These fatty deposits build up over many years in a process called atherosclerosis. Traditionally atherosclerosis was thought to be solely due to build-up of excess fats, but over the last few decades the importance of inflammation in this process has been increasingly recognised. Inflammation usually occurs as a protective response to infection or injury, but in certain circumstances it can be harmful. A large number of drugs have been developed to treat harmful inflammation in autoimmune diseases such as rheumatoid arthritis. This raises the possibility that these or similar treatments could be effective in cardiovascular disease. Indeed, the recent CANTOS trial showed that canakinumab, a drug (originally designed for rheumatic diseases) which targets the IL1-beta protein, reduced coronary events in patients with high inflammation levels. There are multiple proteins involved in inflammation and so the challenge is identifying those that are the most promising drug targets.I propose to address this by integrating 'high-dimensional' genetic and proteomic data. As a result of advances in technology, it now possible to simultaneously measure large numbers of proteins (the 'proteome') in the blood in large numbers of individuals. However, simply showing an association of a protein with cardiovascular disease does not necessarily indicate that the protein is a valid drug target, as correlation does not always reflect causation. To circumvent this issue, I will integrate genetic information, utilising an approach called 'Mendelian randomisation'. This method takes advantage of the randomisation of genetic variants that occurs during reproduction, providing in effect a natural randomised trial. The first step is to identify genetic variants that affect the level of a particular protein. Then, by examining whether individuals who inherit such genetic variants are at higher or lower risk of cardiovascular disease, we can establish whether that protein is likely plays a causal role in disease and thus whether it is a valid drug target.In a complementary strand of work in collaboration with Prof. Justin Mason (Imperial College London), I am studying patients with Takayasu arteritis, a rare disease characterised by arterial inflammation, which often results in vascular narrowing, or, less commonly, dilatation (aneurysm). Cardiovascular complications are a major cause of morbidity. The prognosis in Takayasu arteritis is very variable - some patients have a benign course, while others develop progressive vascular injury. We will examine the plasma proteome to understand factors that influence this variability and to identify signatures that could be used to distinguish high-risk patients in need of stronger immunosuppressive treatment from those in whom milder, less toxic treatments would be sufficient. In addition, we anticipate that improved understanding of an extreme form of vascular inflammation should provide insights into cardiovascular disease more generally.