Discovering chronic inflammation biomarkers that define key stages in the Healthy-to-NASH (non-alcoholic steatohepatitis) transition to inform early prevention and treatment strategies
Discovering chronic inflammation biomarkers that define key stages in the Healthy-to-NASH (non-alcoholic steatohepatitis) transition to inform early prevention and treatment strategies
批准号:
10064561
负责人:
金额:
$2.34万
依托单位:
依托单位国家:
英国
项目类别:
EU-Funded
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --
中文摘要
非酒精性脂肪性肝病(NAFLD)是一种多因素慢性炎症性疾病,流行于四分之一的个体,具有显著的个人、社会经济和医疗负担,特别是在疾病晚期、更严重的炎症阶段——非酒精性脂肪性肝炎(NASH)。尽管该疾病对社会造成严重的负面影响,但NAFLD仍然难以诊断和治疗。此外,由于缺乏忠实反映人类疾病复杂性的模型,从健康到脂肪肝再到NASH转变的分子机制仍然知之甚少。因此,Halt-RONIN旨在通过实施系统生物学方法和综合疾病建模来揭示疾病起始的早期触发因素和疾病进展的复杂机制驱动因素,从而为改进现有的检测方法提供机会,为NAFLD的个性化干预策略和药物发现提供蓝图。为了实现这一目标,Halt-RONIN将把来自先进的体外和体内模型的实验数据与来自广泛的人类NAFLD队列和生物库的多模态数据结合起来,并在计算机机器学习方法中使用,以发现针对健康到疾病过渡的每个阶段的新的生物标志物和分子靶点。通过用真实世界的数据验证临床前实验结果,RONIN将允许发现针对个体患者病理的新型生物标志物和分子靶点。因此,医疗保健专业人员将获得诊断和建立预防和治疗炎症驱动的健康疾病指南所需的工具和知识。因此,从长期来看,RONIN将减少进展为NASH的NAFL患者数量,并提供疾病改善策略以改善患者预后。
英文摘要
Non-alcoholic fatty liver disease (NAFLD) is a multifactorial chronic inflammatory disease that is prevalent in 1 of 4 individuals with a significant personal, socioeconomic and healthcare burden, especially at the later, more severe inflammatory stage of disease - non alcoholic steatohepatitis (NASH). Despite the severe negative impact of the disease on society, NAFLD remains difficult to diagnose and treat. Additionally, the molecular mechanisms underlying the transition from health to fatty liver to NASH remain poorly understood due to the lack of models that faithfully reflect the complexity of human disease. Hence, Halt-RONIN aims to uncover the early triggers of disease initiation and complex mechanistic drivers of disease progression by implementing a systems biology approach with integrative disease modelling resulting in opportunities for the improvement of the existing detection methods, providing a blueprint to inform personalized intervention strategies and drug discovery for NAFLD. To achieve this goal, Halt-RONIN will combine experimental data from advanced in vitro and in vivo models with multimodal data from extensive human NAFLD cohorts and biobanks and use in silico machine learning approaches, to discover new biomarkers and molecular targets specific to each stage of the health-to-disease transition. By validating preclinical experimental findings with real-world data, RONIN will allow for the discovery of novel biomarkers and molecular targets that are specific to the individual patient’s pathology. Consequently, healthcare professionals will gain the tools and knowledge required to diagnose and establish guidelines for the prevention and treatment of inflammation-driven health to disease. As such, in the long-term RONIN will decrease the number of NAFL patients who progress into NASH and provide disease-modifying strategies to improve patient outcomes.
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