Identifying novel & repurposing drug targets for Atrial Fibrillation MEDicines

识别小说

• 批准号: EP/Z000211/1
• 负责人: Amand Schmidt
• 金额: $ 220.34万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FZ000211%2F1
• 关键词: Identifying; novel; repurposing; drug; targets

Atrial fibrillation (AF) is an arrhythmia of the upper chambers of the heart (i.e. atria) which is characterized by loss of organized contraction. AF is the most frequent cause of sustained arrhythmia, and will affect at least a third of the population at some point. Despite improvements in healthcare delivery and public health, AF is a growing global epidemic, which is forecasted to affect over 18 million people aged 55+ in Europe by 2060 (more than double the number of individuals in 2010: 8.8 million). Clinical outcomes of AF vary considerably, from a single episode, to persistent arrythmia resulting in serious complications and mortality. People with AF are at an increased risk of developing multiple comorbidities, such as lung disease, kidney insufficiencies, cardioembolic stroke, cognitive decline and vascular dementia. Treatment for AF is limited, where since the 2015 introduction of the oral anticoagulants rivaroxaban, apixaban and edoxaban, no novel compounds have been approved.To help re-invigorate AF drug development I propose to develop a novel "multi-modal" research line, combining different data types such as proteomics, metabolomics, genomic and imaging modalities, as well as include distinct analytical methods spanning genetic epidemiology, real-world observational studies, and biological network analysis. Specifically, I propose to leverage my strong background in genetics, pharmaco-epidemiology, and machine learning to explore determinants of AF and AF-related comorbidity to identify (novel and repurposing) drug targets for improved disease management. I will improve AF management by 1) exploring imaging and biomarker disease surrogates, 2) identifying protein drug targets, 3) identify druggable genes associating with atrial ablation traits, 4) evaluating real-world evidence on repurposing candidates, and 5) create knowledge graphs to prioritize AF drug targets by combining genetic and non-genetic evidence.

心房颤动（AF）是心脏上腔（即心房）的心律不齐，其特征是有组织的收缩丧失。 AF是持续心律不齐的最常见原因，在某个时候将影响至少三分之一的人口。尽管医疗保健提供和公共卫生有所改善，但AF是一种日益增长的全球流行病，预计到2060年，欧洲的1800万人将影响超过55岁以上的人（2010年的个人数量是两倍以上：880万）。 AF的临床结果差异很大，从单个发作到持续的雅利氏病，导致严重的并发症和死亡率。患有AF的人患有多种合并症的风险增加，例如肺部疾病，肾脏不足，心脏骨骼中风，认知能力下降和血管性痴呆。 AF的治疗是有限的，自2015年引入口服抗凝剂瑞伐沙班，阿apixaban和Edoxaban以来，没有批准任何新颖的化合物。为了帮助重新启发AF药物开发，我建议开发一种新颖的“多模式”研究系列，将不同的数据类型（例如蛋白质组学，基因组学，模态构成）组合在一起，包括属于属性，代表性属性，成像属性，成像属性，图像构成属性，成像，图像构想，图像构成了图像，图像构成了模式，图像构成了图像，图像构成了图像，图像构成了图像，图像构成了图像，图像构成了模式，图像构成了属于属性的类型，图像类型，图像构成了图像构成类型流行病学，现实世界观察研究和生物网络分析。具体而言，我建议利用我在遗传学，药物 - 流行病学和机器学习方面的强大背景，以探索AF和与AF相关的合并症的决定因素，以识别（新颖和重新利用）药物靶标，以改善疾病管理。我将通过1）探索成像和生物标志物疾病代理，2）确定蛋白质药物靶标，3）识别与房屋消融性状相关的可药物基因，4）4）在重新申请候选者上评估现实世界的证据，以及5）5）通过结合遗传和非遗传学的知识图表来确定知识图。