Improving treatment efficacy in hypertension by biomarker-guided personalised decision support (HT- ADVANCE)

通过生物标志物引导的个性化决策支持（HT-ADVANCE）提高高血压的治疗效果

• 批准号: 10068872
• 金额: $ 292.09万
• 依托单位: UNIVERSITY OF DUNDEE
• 依托单位国家: 英国
• 项目类别: EU-Funded
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10068872
• 关键词: Improving; treatment; efficacy; hypertension; biomarker

In HT-ADVANCE we aim to revolutionise personalised management of arterial hypertension (HT) by using multi-omics (MOMICS) stratification biomarkers as companion diagnostics for the prescription of existing drugs. HT is the most important global risk factor for death and morbidity but is uncontrolled in more than 50% of patients. Causes of treatment failure include lack of identification of secondary forms such as endocrine hypertension (EHT) which can be curable by specific therapy. In addition, there is variable response to individual drugs and trial-and-error treatment leads to poor HT control and frustration for both patients and clinicians. The objective of HT-ADVANCE is to validate two multicomponent stratification biomarkers in patients with HT in order to i) identify patients with EHT, and ii) predict response to treatment in patients with primary hypertension. The hypothesis is that MOMICS biomarkers reflect specific forms of hypertension and susceptibility to specific drugs. To this end, we will run three clinical trials (HT-ENDO, HT-TREAT and HT-PREDICT) and apply machine learning techniques to integrate the genetic, genomic and metabolomic features that constitute the MOMICS biomarkers in order to generate accurate diagnostic and therapeutic response predictions for clinicians. We will also perform economic evaluation of the use of MOMICS for the treatment of HT, produce ethical and legal recommendations for clinical decision making, and develop a plan for their implementation as companion diagnostics. The study will be conducted by several HT Centres of Excellence and will build on the success of the ENSAT-HT project that has established methods and pipelines for integrating datasets derived from multiple platforms. We expect that HT-ADVANCE will provide a step change in the management of HT by enabling a personalised, more efficient and cost-effective treatment strategy, and importantly, will prevent the ensuing cardio-metabolic complications.

在HT- advance中，我们的目标是通过使用多组学（MOMICS）分层生物标志物作为现有药物处方的伴随诊断，彻底改变动脉高血压（HT）的个性化管理。HT是全球最重要的死亡和发病危险因素，但在50%以上的患者中不受控制。治疗失败的原因包括缺乏可通过特定治疗治愈的继发性形式，如内分泌高血压（EHT）的识别。此外，对个别药物的反应不一，试错治疗导致HT控制不佳，使患者和临床医生都感到沮丧。HT- advance的目的是验证HT患者中的两种多组分分层生物标志物，以便i)识别EHT患者，ii)预测原发性高血压患者对治疗的反应。假设是MOMICS生物标志物反映了特定形式的高血压和对特定药物的易感性。为此，我们将进行三项临床试验（HT-ENDO、HT-TREAT和HT-PREDICT），并应用机器学习技术整合构成MOMICS生物标志物的遗传、基因组和代谢组学特征，以便为临床医生生成准确的诊断和治疗反应预测。我们还将对使用MOMICS治疗高温疗法进行经济评估，为临床决策提出伦理和法律建议，并制定将其作为伴随诊断实施的计划。该研究将由几个HT卓越中心进行，并将以ENSAT-HT项目的成功为基础，该项目已经建立了整合来自多个平台的数据集的方法和管道。我们预计HT- advance将通过个性化、更有效和更具成本效益的治疗策略，为HT的管理提供一个阶梯性的改变，重要的是，将预防随之而来的心脏代谢并发症。