Genetic Evaluation of Multimorbidity towards INdividualisation of Interventions (GEMINI)

超过50%的65岁以上的人患有一种以上的长期疾病(多发病)。尽管如此，患有多发病的人往往被排除在临床试验之外，而且在确定多发病原因方面的研究有限。例如，我们经常不知道随着年龄的增长，两种常见的长期疾病是否会偶然发生在一起，是否会导致另一种情况，或者它们是否具有共同的风险因素。这个问题在一定程度上是因为卫生保健专业人员和研究人员往往一次只关注一种情况。例如，已经有很多关于骨关节炎的原因和后果的研究，但没有研究为什么骨关节炎患者哮喘的发生率更高，即使考虑到性别、年龄和肥胖。我们研究的目的是揭示长期疾病之间的新联系，这些联系可能导致改善干预措施，包括药物治疗或其他更有针对性的治疗。这些新的联系可能包括更好地了解体内哪些细胞对同一患者出现两种情况最关键。为了实现我们的目标，我们建立了一个名为Gemini(针对干预措施个体化的多发病遗传评估)的合作伙伴关系。该小组包括两名患有多发病的人，包括初级保健专业人员在内的卫生保健专业人员，以及统计和遗传学专家。在双子座，我们将用一种新的方法研究多发病的原因。我们将使用现有的DNA序列信息数据库，这些信息与1万人的疾病有关。使用这种遗传方法，我们的初步研究已经确定了许多以前不为人所知的疾病之间的新的有趣的联系。例如，类风湿性关节炎和中风(但不包括类风湿性关节炎和心脏病)、胃反流病和抑郁症之间，以及哮喘和骨关节炎之间。我们将用来自数百万初级保健患者的数据来补充遗传方法。这些患者代表了整个英国的情况，将使我们能够研究大量患有多种疾病的人，即使这种组合非常罕见。我们的研究计划分为三个部分。我们将让患者和护理人员参与到所有阶段，以确保我们适当地使用他们的数据，并帮助我们继续专注于多病的重要条件和结果。首先，我们将使用来自初级保健(GP)患者的三个数据来源来定义我们将研究的条件。我们将从所有长期存在于超过1%的65岁以上人口中的情况开始。然后，我们将使用数以百万计的DNA序列变化--我们从父母那里继承的遗传信息--来识别哪些疾病具有广泛的生物学机制。其次，我们将使用类似数量的遗传变异来确定所涉及的具体机制。这些技术基于这样的原则，即遗传的DNA序列变化是终身固定的，因此为我们提供了一种评估相关风险因素和疾病的因果方向的方法。例如，我们将使用遗传学来测试一种疾病是否会导致第二种疾病，或者共同的风险因素是否会导致两种疾病。这些风险因素将包括众所周知的风险，如肥胖和更详细的生物学指标，如基因在不同细胞和组织中如何开启和关闭。第三，我们将使用初级保健数据库对前两个步骤中突出显示的情况的患者进行更深入的研究。我们将与患者和护理人员一起举办研讨会，深入了解这些疾病最重要的后果，例如，寿命缩短比频繁住院的风险更重要还是更不重要？然后，我们将研究患有新的疾病组合的患者，看看他们是否会遭受更糟糕的结果。

More than 50% of people over the age of 65 are living with more than one long term condition (multimorbidity). Despite this, people with multimorbidity are often excluded from clinical trials and there has been limited research into identifying the causes of multimorbidity. For example, we often do not know if two common long-term conditions occur together by chance as we get older, whether one leads to the other, or if they share a risk factor. This problem is partly because health care professionals and researchers tend of focus on one condition at a time. For example, there has been a lot of research into the causes and consequences of osteoarthritis but not why people with osteoarthritis have a higher frequency of asthma, even when accounting for sex, age and obesity.The aim of our research is to uncover new links between long term conditions that could lead to improved interventions including drug treatments or other more focused treatments. These new links could include a better understanding of which cells in the body are most critical to the presence of two conditions in the same patient.To achieve our aims, we have formed a partnership called the GEMINI (Genetic Evaluation of Multimorbidity towards INdividualisation of Interventions) collaborative. This team includes two people with multimorbidity, health care professionals including those in primary care and experts in statistics and genetics. In GEMINI we will study the causes of multimorbidity with a new approach. We will use existing databases of DNA sequence information linked to diseases from 10,000s of people. Using this genetic approach our initial research has identified many new and interesting links between conditions that were not previously well known. For example, between Rheumatoid arthritis and stroke (but not Rheumatoid arthritis and heart disease), gastro-reflux disease and depression, and between asthma and osteoarthritis. We will complement the genetic approach with data from millions of patients in primary care. These patients are representative of the UK as a whole and will allow us to study large numbers of people with combinations of conditions even if these combinations are quite rare.Our research plans are divided into three parts. We will involve patients and carers in all stages to ensure we are using their data appropriately and to help us remain focused on the important conditions and outcomes of multimorbidity. First, we will use three sources of data from patients in primary care (GPs) to define the conditions we will study. We will start from all conditions that are long term and present in more than 1% of the people over 65 years. We will then use millions of DNA sequence changes - the genetic information we inherit from our parents - to identify which conditions share broad biological mechanisms. Second, we will use a similar number of genetic variants to identify the specific mechanisms involved. These techniques are based on the principle that inherited DNA sequence changes are fixed for life and so provide us with a way of assessing the causal direction of associated risk factors and diseases. For example, we will use genetics to test whether one disease leads to a second disease, or whether a shared risk factor leads to both. These risk factors will include well known risks such as obesity and more detailed measures of biology, such as how genes are switched on and off in different cells and tissues. Third, we will study in more depth patients with the conditions highlighted in the first two steps using primary care databases. We will hold workshops with patients and carers to understand in depth the most important outcomes of these conditions, for example is reduced lifespan more or less important than risk of frequent hospitalisation? We will then study patients with new combinations of conditions to see if they suffer from worse outcomes.