Genetic Evaluation of Multimorbidity towards INdividualisation of Interventions (GEMINI)

对干预措施个体化的多发病的遗传评估（GEMINI）

• 批准号: MR/W014548/1
• 负责人: Timothy Frayling
• 金额: $ 325.77万
• 依托单位: UNIVERSITY OF EXETER
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FW014548%2F1
• 关键词: Genetic; Evaluation; Multimorbidity; towards; INdividualisation

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.

超过50%的65岁以上的人患有一种以上的长期疾病（多病）。尽管如此，患有多重疾病的人经常被排除在临床试验之外，而且在确定多重疾病原因方面的研究也很有限。例如，我们常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同时出现，是一种导致另一种，还是它们有共同的风险因素。造成这个问题的部分原因是卫生保健专业人员和研究人员倾向于一次只关注一种疾病。例如，人们对骨关节炎的起因和后果进行了大量的研究，但却没有研究为什么患有骨关节炎的人患哮喘的频率更高，即使考虑到性别、年龄和肥胖。我们研究的目的是发现长期疾病之间的新联系，从而改善干预措施，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为关键。为了实现我们的目标，我们已经形成了一个合作伙伴关系，称为GEMINI（面向个性化干预的多病遗传评估）合作。该小组包括两名多病患者、包括初级保健人员在内的卫生保健专业人员以及统计和遗传学专家。在GEMINI，我们将用一种新的方法来研究多重发病的原因。我们将使用现有的DNA序列信息数据库，这些数据库与成千上万人的疾病有关。使用这种遗传方法，我们的初步研究已经确定了许多新的和有趣的条件之间的联系，而这些联系以前并不为人所知。例如，在类风湿关节炎和中风之间（但不是类风湿关节炎和心脏病之间），胃反流疾病和抑郁症之间，以及哮喘和骨关节炎之间。我们将利用数百万初级保健患者的数据来补充遗传方法。这些患者是整个英国的代表，这将使我们能够研究大量患有多种疾病的人，即使这些组合非常罕见。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所有阶段，以确保我们正确使用他们的数据，并帮助我们继续关注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65岁以上人群中超过1%的人长期存在的所有疾病开始。然后，我们将利用数以百万计的DNA序列变化——我们从父母那里继承的遗传信息——来确定哪些疾病具有广泛的生物机制。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。这些技术是基于遗传DNA序列变化是终生固定不变的原则，因此为我们提供了一种评估相关风险因素和疾病因果方向的方法。例如，我们将使用遗传学来测试一种疾病是否会导致另一种疾病，或者一个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测量，如基因如何在不同的细胞和组织中开启和关闭。第三，我们将使用初级保健数据库更深入地研究前两步中强调的病症患者。我们将与患者和护理人员举行研讨会，以深入了解这些疾病最重要的结果，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，我们将研究患有新疾病组合的患者，看看他们是否会遭受更糟糕的结果。

项目成果

Using genetics to explore the role of BMI as a shared risk factor in multimorbidity

利用遗传学探讨 BMI 作为多发病的共同危险因素的作用

• 发表时间: 2024
• 期刊: EUROPEAN JOURNAL OF HUMAN GENETICS
• 影响因子: 5.2
• 作者: Mounier Ninon

Genomics and multimorbidity.

基因组学和多发病。

• DOI: 10.1093/ageing/afac285
• 发表时间: 2022
• 期刊: Age and ageing
• 影响因子: 6.7
• 作者: Masoli JAH