Integrating polygenic risk scores with clinical drug development

该博士提案将建立在多基因风险评分（PRS）作为疾病风险预测因子的基础上，以评估其在药物开发价值链中的效用，从早期研究到随机临床试验，重点是患者人群的选择[1]。 我们对临床疾病的理解已经被成功识别与疾病风险相关的遗传变异所改变。全基因组关联研究（GWAS）表明，这些疾病背后的遗传结构是高度多基因的，有数百或数千种变异导致遗传风险。通常情况下，许多变体具有与疾病相关的强有力的统计学证据，但单独地仅赋予很小的影响。在整个基因组中，这些相关的变异可以组合成多基因风险评分，它提供了一个个体水平的遗传易感性的测量性状。PRS可用于风险分层以预测临床结果，并且当与其他生物标志物组合时可获得临床效用。在这个博士论文中，我们将研究如何在药物开发中使用多基因风险评分，以加强支持临床前和早期研究中药物开发的证据，并改善3期随机对照试验（RCT）的研究设计。 遗传学在药物开发中的重要性是公认的，因为具有遗传关联支持的药物靶点在早期和后期研究中更有可能成功，并导致批准药物[2]。遗传关联的现有效用是基于单个遗传变异的证据。在这个博士论文中，我们将从单一变异扩展到多基因风险评分（PRS）捕获的全基因组支持，并评估PRS如何整合到药物开发和评估管道中。学生将进行一系列项目，涵盖药物开发的步骤，从目标选择到试验设计，提出和测试方法，以整合PRS。开发的方法将应用于关键的UCB领域的利益，帕金森病（PD）和阿尔茨海默病（AD）。主要研究问题：多基因风险评分如何最好地促进药物开发过程？

This PhD proposal will build on the development of polygenic risk scores (PRS) as predictors of disease risk to assess their utility across the drug-development value chain from early phase studies to randomised clinical trials, focussing on the selection of patient population [1]. Our understanding of clinical disorders has been transformed by the success in identifying genetic variants associated with disease risk. Genome-wide association studies (GWAS) have showed that the genetic architecture underlying these disorders is highly polygenic with hundreds or thousands of variants contributing to genetic risk. Typically, numerous variants have strong statistical evidence of association with disease, but individually confer only a small effect. Across the genome, these associated variants can be combined into a polygenic risk score, which provides an individual-level measure of genetic liability for a trait. PRS can be used for risk stratification to predict clinical outcomes, and when combined with other biomarkers can attain clinical utility. In this PhD proposal, we will investigate how polygenic risk scores can be used within drug development, to strengthen evidence supporting drug development in preclinical and early phase studies, and to improve study design in phase 3 randomised control trials (RCT). The importance of genetics in drug development is well-recognised, as drug targets with genetic association support are substantially more likely to be successful in early and late-stage studies, and to lead to an approved drug [2]. The existing utility of genetic associations is based on evidence at a single genetic variant. In this PhD proposal we will extend beyond a single variant to the genome-wide support as captured by polygenic risk scores (PRS), and assess how PRS can be integrated within drug development and assessment pipelines. The student will undertake a series of projects covering steps in drug development, from target choice to trial design, proposing and testing methods to integrate PRS. The methods developed will be applied to key UCB areas of interest, Parkinson's disease (PD) and Alzheimer's disease (AD). Primary research question: How can polygenic risks scores best contribute to the process of drug development?