Transforming Diabetic Kidney Disease Care: Harnessing Integrative Multi-Omics Analysis for Precision Diagnosis and Management
Transforming Diabetic Kidney Disease Care: Harnessing Integrative Multi-Omics Analysis for Precision Diagnosis and Management
批准号:
10081229
负责人:
金额:
$89.17万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --
中文摘要
英国肾脏研究中心最近发表的一份报告发现,肾脏疾病每年给英国经济造成70亿英镑的损失,其中64亿英镑是NHS的直接成本。如果没有重大的政府干预,该报告指出,到2033年,这些费用可能会上升到139亿英镑。糖尿病肾病(DKD)是最常见的肾脏疾病,由高血糖水平导致的肾脏血管损伤引起。这种慢性疾病会增加肾衰竭和严重心血管事件的风险。目前,批准的DKD治疗方法采用一刀切的方法,未能解决疾病的根本原因。这种方法忽视了生物多样性患者人群的差异,对许多接受治疗的患者造成了疾病进展的重大风险。必须实施精准医疗方法,以优化针对每个亚群独特需求的护理路径。为了解决这一问题,必须开发数据驱动的诊断工具,例如体外诊断或医疗器械软件。这些工具可以通过整合和分析来自各种生物水平的患者数据集来开发,例如基因,蛋白质和代谢物。通过使用这些数据来生成诊断工具,MultiOmic Health提供了一种新的方法,可以有效地将对某些治疗策略反应良好的患者与可能需要替代方法的患者进行分组和区分。这将能够提供量身定制的护理,以满足糖尿病人群中个体患者的独特需求虽然类似的方法已经成功地应用于创建癌症的精确诊断,但是迄今为止还没有针对DKD开发和商业化的精确方法,留下了一个关键的和不断增长的未满足的临床需求。通过我们与贝尔法斯特女王大学的DKD专家的合作,我们在MultiOmic Health的团队将揭示1型和2型糖尿病患者肾脏疾病在分子水平上的相似性和差异。通过分子谱分析,我们将确定诊断和预后生物标志物,这些生物标志物指示特定患者亚群中疾病进展和可能并发症的风险。项目成果将作为未来诊断工具的基础。这些工具将生成对临床医生友好的报告,为疾病进展率、并发症风险和药物反应性提供有价值的见解。这些信息将使临床医生能够提供以患者为中心的护理,例如,通过更有针对性的DKD管理方法,我们可以优化医疗资源分配,减少疾病进展,并最终改善DKD患者的生活质量。
英文摘要
A recent report published by Kidney Research UK found that kidney disease costs the UK economy £7bn/year, £6.4bn of which as direct costs to the NHS. Without significant government intervention, the report states these costs could rise to £13.9bn by 2033\.Diabetic kidney disease (DKD) is the most common form of kidney disease, caused by damage to the kidney's blood vessels due to high blood-sugar levels. This chronic condition increases the risk of kidney failure and serious cardiovascular events. Currently, approved treatments for DKD take a one-size-fits-all approach and fail to address the underlying cause of the condition. This approach disregards the differences of a biologically diverse patient population, posing a significant risk of disease progression for many patients receiving treatment. It is imperative that precision medicine approaches are implemented to optimise care pathways for each subpopulation's unique needs.To address this, data-driven diagnostic tools, such as In Vitro Diagnostics or Software as Medical Device, must be developed. These tools can be developed by integrating and analysing patient datasets from various biological levels, such as genes, proteins, and metabolites. By using this data to generate a diagnostic tool, MultiOmic Health offers a new way to effectively group and distinguish between patients who will respond well to certain treatment strategies from those who may require alternative approaches. This would enable the delivery of tailored care to suit the unique needs of individual patients within the diabetes population (type 1 and type 2 diabetes).Whilst similar methods have been successfully applied to create precision diagnostics for cancer, no precision approaches have been developed and commercialised for DKD to date, leaving a critical and growing unmet clinical need.Through our collaboration with DKD experts at Queen's University Belfast, our team at MultiOmic Health will uncover molecular-level similarities and differences in kidney disease among patients with type 1 and type 2 diabetes. Through molecular profiling, we will identify diagnostic and prognostic biomarkers that indicate the risk of disease progression and likely complications within specific patient subpopulations.The project outputs will serve as the foundation for future diagnostic tools. These tools will generate clinician-friendly reports, providing valuable insights into disease progression rates, complication risks, and drug responsiveness. This information will allow clinicians to deliver patient-centric care, e.g., supporting treatment decisions.With a more targeted approach to DKD management, we can optimise healthcare resource allocation, reduce disease progression, and ultimately improve quality-of-life for individuals with DKD.
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