GEroscience and Multi-Morbidity: identifying targets for intervention (GEMM)

目前医学倾向于单独治疗不同的疾病。我们越来越认识到，人们不是孤立地患有一种疾病。目前的治疗方法意味着许多人正在服用多种药物，这增加了副作用，并可能导致有害的药物相互作用。我们现在知道，一组疾病倾向于聚集在一起，因此，患有一种疾病的个体更有可能在这组疾病中患有其他疾病。我们认为这是因为有一些潜在的机制同时也是许多疾病的根本原因。年龄是许多疾病的主要危险因素。生物学家多年来一直在研究模式生物和人类的衰老。这一领域被称为地质科学。现在，老年科学已经确定了在衰老过程中发生并导致生理和健康变化的关键机制。我们想要研究这些过程与疾病聚集性发展的关系。通过了解这些疾病集群发展背后的机制，我们的目标是制定战略，以消除根本原因，从而同时预防或治疗多种疾病。老年科学已经确定了随着年龄的增长而发生并导致健康问题的三个关键变化：细胞衰老（老细胞不会死亡，但仍留在组织中，分泌扰乱健康细胞的分子）；营养感知的改变（细胞系统不恰当地评估生长和健康之间的平衡）和自噬的改变（细胞中蛋白质的再循环问题，导致它们积累并影响细胞功能）。所有这三种机制都有可能用于阻止潜在过程的治疗方法。重要的是，其中一些治疗方法是像二甲双胍这样的药物，或者改变生活方式，比如改变饮食，这些已经在人类身上使用，并且已知是相对安全的。我们的联盟包括来自五所大学的国际公认的专家，来自发现科学、衰老生物学、计算生物学、临床试验设计和医学的专家，他们将共同努力制定新的治疗策略。我们的愿景是通过调节主要疾病集群的上游驱动因素，在与年龄相关的多病的临床管理中带来范式转变，取代目前单独治疗疾病的方法。我们建议的总体目标是建立一个多学科合作，以确定这些老化机制是否支持不同的多病集群的发展。该联盟由医生领导，并将包括临床试验专家，以使我们专注于快速开发新的治疗策略。我们的计划是使用已经具有许多生物学和健康测量特征的大型队列的数据，来调查多病集群背后的生物学。我们将从TwinsUK队列开始，该队列已经进行了详细的分子生物学分析，从基因到基因、蛋白质、代谢物和细胞亚群的表达。在第一个六个月的巩固阶段，我们将在这个数据集中构建集群，并研究生物学与集群之间的关系。我们还将扩大小组，让更多的科学专家参与进来。在联合阶段，我们将扩展到其他队列，并对来自参与者的细胞进行实验，然后在临床研究中证明因果关系，并研究我们如何安全地修改和治疗多种疾病（图1）。结合我们合作伙伴在新型临床试验设计方面的专业知识，我们将开发针对已确定机制的多种疾病患者的治疗方案。

Currently medicine tends to treat distinct diseases individually. We are increasingly aware that people do not suffer from one disease in isolation. Current treatment means that many people are taking multiple medications, which increases side-effects and can lead to harmful drug interactions.We now know that groups of diseases tend to cluster together, such that an individual with one disease is more likely to have others in the cluster. We think this is because there are underlying mechanisms which are root causes of many diseases at the same time.Age is the major risk factor for getting many diseases. Biologists have studied ageing in model organisms and humans for many years. This body of work is called Geroscience. Geroscience has now identified key mechanisms which occur in ageing and contribute to changes in physiology and health. We want to investigate how these processes relate to the development of disease clusters. By understanding the mechanisms behind the development of these disease clusters we aim to develop strategies to combat the root causes, thereby preventing or treating multiple diseases at once.Geroscience has identified three key changes which occur with ageing and contribute to health problems: cell senescence (where old cells do not die but remain in tissues secreting molecules which upset healthy cells); changes in nutrient sensing (where the cell system inappropropriately assesses the balance between growth and health), and altered autophagy (problems recycling proteins in the cells such that they accumulate and affect cell function). All three of these mechanisms have possible therapies which could be used to stop the underying process. Importantly, some of these therapies are drugs like metformin or lifestyle changes such as diet alterations which are already used in humans and known to be relatively safe.Our consortium contains internationally recognised expertise across five universities with experts from discovery science, ageing biology, computational biology, clinical trial design, and medicine who will work together to develop a new strategy for treatment. Our vision is to bring a paradigm shift in the clinical management of age-related multimorbidity, via modulation of the upstream drivers of the major disease clusters, replacing the current approach of treating diseases separately.The overarching aim of our proposal is to build a multidisciplinary collaborative to identify whether these ageing mechanisms underpin the development of distinct multimorbidity clusters. The consortium is led by doctors and will involve clinical trial experts to keep us focused on developing new treatment strategies quickly. Our plan is to use data from large cohorts which already have many biological and health measures characterised, to investigate the biology behind multimorbidity clusters. We will start with the TwinsUK cohort which has had molecular biology assayed in detail, from genes, to expression of genes, proteins, metabolites and cell subsets. In the first six-month consolidation phase, we will construct the clusters in this dataset and look at the relationships between biology and the clusters. We will also extend the team to involve additional scientific experts. In the consortium phase we will extend this to other cohorts and perform experiments on cells derived from participants and then in clinical studies to demonstrate cause and effect, and investigate how we can modify and treat multiple diseases safely (Figure 1). Combining this understanding with our collaborative's expertise in novel clinical trial designs, we will develop protocols for testing treatments targeting the identified mechanisms in people suffering from multiple diseases.