Precision medicine in diabetes: Pharmacogenetic studies of large randomised controlled trials of diabetes therapies

在2型糖尿病的治疗中，除二甲双胍外，有五种非胰岛素疗法可供使用。它们被称为磺脲类(SU)、噻唑烷二酮类、二肽基肽酶4抑制剂(DPP4i)、葡萄糖转运蛋白2抑制剂(SGLT2i)和GLP-1受体激动剂(GLP-1RA)。最新的指南旨在根据风险(例如低血糖或体重增加)、成本(例如SU价格低廉，可在低收入和中等收入国家使用)和益处(例如使用GLP-1RA和SGLT2i降低心力衰竭或心脏病发作的风险)来指导治疗选择，但这些治疗的受益对象和损害对象存在很大差异。我们已经确定血糖对糖尿病治疗的反应是高度“遗传”的，并确定了基因变异改变糖尿病药物作用效果的例子。随着我们进入不久的将来，当医生开出药物时，患者可以获得遗传信息，在为糖尿病患者选择最佳药物时，将有可能考虑到这些遗传信息。到目前为止，对糖尿病药物反应的基因研究仅限于观察性研究。这些研究在研究新药方面的能力有限，尽管包括遗传学，但在现实世界的研究中仍然容易出现偏差和噪音。目前的英国-加拿大合作首次汇集了较新糖尿病药物的随机对照试验(RCT)的遗传数据，包括证实SGLT2i和GLP-1RA对心血管有益的试验。目前，我们获得了SGLT2i试验(达帕利福秦和恩帕利福秦，n=10,943)、GLP-1RA试验(阿尔比路肽、利塞那肽、多拉鲁肽n=16,596)、DPP-4抑制剂试验(saxagliptin，n=3048)参与者的数据。这些独特的资源仅对主要申请者可用，并提供相当大的力量来识别改变这些药物的血糖反应、副作用和心血管结果的遗传变异，这些药物在英国和加拿大越来越多地使用。我们将进行多种与药物相关的反应的研究，包括血糖反应、体重减轻、血压降低、恶心/呕吐、鹅口疮、肾脏结果和心血管结果。首先，我们将进行遗传学研究，观察每个试验参与者的近500万个遗传变异，以确定将提供对药物作用的机械性洞察的关联，以及可能用于临床预测谁对药物反应好或不好的变异。其次，我们将研究由于共同的潜在原因--称为分区多基因评分(PPS)--增加糖尿病风险的基因变异的组合，并调查不同的PPS如何改变对糖尿病药物的反应和结果。最后，我们将使用遗传信息来询问与较新的糖尿病药物如何起作用(通过什么机制)，特别是它们如何改善心血管结果的问题。通过识别改变SGLT2i、DPP-4i和GLP-1RA反应和结果的遗传变异或PPS，以及在大型高功率临床试验中进行更复杂的机制研究，我们将在糖尿病的精准医学方面取得重大进展。这将使治疗更有针对性，以降低卫生保健系统的成本，从而改善患者的结果。

In the treatment of type 2 diabetes, there are five non-insulin therapies available for use after metformin. These are called sulphonylureas (SU), thiazolidinediones, dipeptidyl-peptidase 4 inhibitors (DPP4i), Sodium Glucose Transporter 2 inhibitors (SGLT2i) and GLP-1 Receptor Agonists (GLP-1RA). The latest guidelines aim to guide treatment choice based upon risks (e.g. of low blood sugar or weight gain), cost (e.g. SU are cheap and could be used in low and middle income countries), and benefit (e.g. reduction in risk of heart failure or heart attack with GLP-1RA and SGLT2i) however there is considerable variation in who benefits, and who is harmed, from any of these treatments. We have established that blood sugar response to diabetes treatments is highly "genetic" and have identified examples where genetic variants alter how well the diabetes drugs work. As we move to a time in the near future when genetic information will be available for a patient when the doctor prescribes a drug, it will be possible to take into account this genetic information when choosing the best medication for a patient with diabetes.To date, genetic studies of drug response in diabetes have been limited to observational studies. These studies are limited in their ability to study newer drugs, and despite including genetics, are still prone to bias and noise seen in real-world studies. The present UK-Canada collaboration brings together, for the first time, genetic data on randomised controlled trials (RCT) of the newer diabetes agents, including trials that established the cardiovascular benefit of SGLT2i and GLP-1RA. Currently we have access to data from participants to SGLT2i trials (Dapagliflozin and Empagliflozin, n=10,943), GLP-1RA trials (Albiglutide, Lixisenatide, Dulaglutide n=16,596), DPP-4 inhibitor trials (Saxagliptin, n=3048). These unique resources are only available to the principal applicants and provide considerable power to identify genetic variants that alter blood sugar response, side effects and cardiovascular outcome of these drugs that are expensive and increasingly used in the UK and Canada.We will undertake studies of multiple drug related responses including glycaemic response, weight reduction, blood pressure reduction, nausea/vomiting, thrush, renal outcomes and cardiovascular outcomes. First, we will undertake genetic studies looking at nearly 5 million genetic variants for each trial participant to identify associations that will provide mechanistic insight into drug action as well as variants that may be used in the clinic to predict who will respond well or poorly to medication. Second, we will then look at combinations of genetic variants that increase risk of diabetes due to a common underlying cause - called partitioned polygenic scores (pPS) - and investigate how different pPS alter response and outcome to the diabetes drugs. Finally, we will use the genetic information to ask questions in relation to how the newer diabetes drugs work (via what mechanism) and in particular how they improve cardiovascular outcomes. By identifying genetic variants or pPS that alter response and outcomes of SGLT2i, DPP-4i and GLP-1RA, and undertaking more complex mechanistic studies in large highly powered clinical trials, we will provide a major advance in precision medicine in diabetes. This will enable better targeting of treatment for better patient outcomes at reduced cost to the health care system.