Molecular Prediction of Osteoarthritis to enable its Prevention: Post-traumatic Osteoarthritis as an exemplar

骨关节炎(OA)是最常见的关节炎形式，在英国有850万人受到影响。这是髋关节和膝关节置换手术的主要原因，相关的医疗预算估计为20亿英镑，社会成本要高得多。我们目前还没有预防、减缓或治愈骨性关节炎的药物治疗。膝关节损伤，如前交叉韧带断裂，是未来膝关节骨性关节炎的最大危险因素。所有膝盖受伤的人中约有一半会患上骨性关节炎；治疗这种损伤的手术并不能降低这种风险。这种类型的骨性关节炎被称为“创伤后骨关节炎”(PTOA)。当个人患上PTOA时，他们往往更年轻，但我们不知道这种形式的OA是否与通常的OA有其他不同。膝关节对损伤的炎症反应在不同的人之间有很大的不同。我们的实验室研究将这种最初的‘关节损伤反应’与后来的骨性关节炎联系起来。我们可以测量不同方面的反应：膝关节液中的蛋白质“标记物”、血液中基因的信息水平、个人的基因构成以及年龄、性别或受伤类型等临床因素。研究关节损伤反应使我们有机会了解导致骨性关节炎的过程，并通过挑选高危人群并在受伤时进行治疗来预防创伤后骨性关节炎。我的目的是确定和测试膝关节损伤后PTOA进展的预测因素，这可以在临床上使用。我将：-确定膝关节损伤时预测PTOA的临床因素和可测量的标记物(在关节和血液中)-评估PTOA的遗传风险-开发一种测试或风险分数，可以评估一个人未来PTOA的个人风险-提高我们设计临床试验的能力，目的是预防PTOA。我们将通过三种不同的方法实现这一点：(1)通过收集临床样本、问卷和扫描或X光，对特定的膝关节损伤的个人进行长期跟踪；(2)联合其他一些国际膝关节损伤队列，在PTOA中询问遗传学问题，但也检查我们的发现，以及(3)访问具有相关医疗数据的更大规模的现有个人研究：UK Biobank(约32,000人有膝骨性关节炎及相关遗传信息)，以及一大组普通膝骨性关节炎研究(遗传学)，有额外的61,000例膝骨性关节炎。这些大数字是提出基因问题所必需的。我们将询问“普通”骨性关节炎的已知遗传风险是否与PTOA相同，以及我们是否能识别出任何新的遗传风险因素。我们还将同时观察单个关节液样本中的5000个标记物，并看看基因和标记物之间是如何相互关联的。如果我们确定了预测骨性关节炎的标记物，我们就可以开发出一种测试或风险评分，给出个人患骨性关节炎的个人风险。这将有许多好处：帮助那些受伤的人，帮助他们进行工作和生活规划，以及围绕运动和潜在的治疗方法进行选择。这将使这一领域的临床试验成为可能，因为我们将第一次能够挑选出风险最高的患者。这将使临床试验更容易被参与者接受，也增加了我们衡量治疗真正效果的机会，允许更少的数字和更大的确定性来确定我们的发现。它还可能在试验中给我们更快、更准确的答案。最后，这种测试可以在临床上使用，将稀缺的医疗资源输送到风险最高的人手中，而不会进行不必要的治疗。有可能这些类型的标志物也可能与其他原因的早期骨性关节炎相关，我们将对此进行测试。鉴于办公自动化的频率越来越高，找到一种在这一领域发挥作用的方法可能会降低我们未来的医疗和社会保健成本。

Osteoarthritis (OA) is the commonest form of arthritis, affecting 8.5 million people in the UK. It is the main reason for hip and knee joint replacement surgery, with an associated healthcare budget estimated at £2 billion, with much greater societal cost. We currently have no drug treatments that prevent, slow or cure OA. Knee joint injury, such as anterior cruciate ligament rupture, is the biggest risk factor for future knee OA. About half of all people with knee injuries will develop OA; surgery to treat the injury does not reduce this risk. This type of OA is known as 'post traumatic osteoarthritis' (PTOA). Individuals are often younger when they develop PTOA, but we don't know if this form of OA is otherwise different from 'usual' OA. There is an inflammation response in the knee to the injury which varies considerably between people. Our laboratory studies link this initial 'joint injury response' to later OA. We can measure different aspects of the response: protein 'markers' in knee joint fluid, message levels of genes in blood, an individual's genetic makeup and clinical factors like age, sex or type of injury. Studying the joint injury response gives us an opportunity to understand the processes which cause OA, and to aim to prevent PTOA by picking out those who are at high risk and treating them at the time of their injury. My aim is to identify and test predictors of progression to PTOA after knee injury which can be used in the clinic. I will:-Identify clinical factors and measurable markers at the time of the knee injury which predict PTOA (in the joint and in blood)-Assess the genetic risk of PTOA-Develop a test or risk score which can rate a person's individual risk of future PTOA-Improve our ability to design clinical trials with the aim of preventing PTOAWe will achieve this by using 3 different approaches: (1) work in specific knee injury 'cohorts' (groups) of individuals who have been followed over time with the collection of clinical samples, questionnaires and scans or X-rays; (2) join together a number of other international knee injury cohorts to ask genetic questions in PTOA, but also to check our findings and (3) access much larger existing research studies of individuals with associated healthcare data: UK Biobank (~32,000 individuals have knee OA and associated genetic information), and a large group of general OA studies (Genetics of Osteoarthritis) has an additional 61,000 cases of knee OA. These big numbers are needed to ask genetic questions. We will ask whether known genetic risks for 'usual' OA are the same for PTOA, and whether we can identify any new inherited risk factors. We will also look at 5000 markers in a single joint fluid sample at once, and look at how genes and markers relate to each other.If we identify markers that predict OA, we can develop a test or risk score which gives an individual their personal risk of OA. This would have a number of benefits: helping those with injury, with work and life planning and choices around exercise and potential treatments. It would enable clinical trials in this area, because for the first time we would be able to pick out those at the highest risk. This would make clinical trials more acceptable to participants, and also increase our chances of measuring a true effect of a treatment, allowing smaller numbers and greater certainty about our findings. It may also give us faster, more accurate answers in trials. Lastly, the test could be used in the clinic, channelling scarce healthcare resources to those who are at greatest risk and not giving unnecessary treatments. It is possible that these types of markers may also be relevant to those with early OA of other causes and we will test this. Given the high and growing frequency of OA, finding a way of making any difference in this area is likely to reduce our future health and social care costs.