Transforming Diabetic Kidney Disease Care: Harnessing Integrative Multi-Omics Analysis for Precision Diagnosis and Management

英国肾脏研究中心最近发布的一份报告发现，肾脏疾病每年给英国经济造成70亿GB的损失，其中64亿GB是NHS的直接成本。报告指出，如果没有政府的重大干预，到2033年，这些成本可能会上升到139亿GB。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。这种慢性疾病增加了肾衰竭和严重心血管事件的风险。目前，已批准的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群体的差异，对许多接受治疗的患者构成了疾病进展的重大风险。实施精确医疗方法以优化护理路径以满足每个亚群的独特需求是当务之急。为了解决这一问题，必须开发数据驱动的诊断工具，如体外诊断或作为医疗设备的软件。这些工具可以通过整合和分析来自不同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，MultiOic 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那些可能需要替代方法的患者进行分组和区分。这将使我们能够提供量身定制的护理，以满足糖尿病人群(1型和2型糖尿病)患者的独特需求。尽管类似的方法已经成功地应用于癌症的精确诊断，但迄今为止还没有针对DKD的精确方法开发和商业化，留下了一个关键的、不断增长的临床需求未得到满足。通过我们与贝尔法斯特女王大学的DKD专家的合作，我们在多奥姆健康公司的团队将发现1型和2型糖尿病患者肾脏疾病在分子水平上的相似和差异。通过分子图谱，我们将识别诊断和预后生物标记物，这些生物标记物指示特定患者亚群内疾病进展和可能的并发症的风险。项目成果将作为未来诊断工具的基础。这些工具将生成临床医生友好的报告，提供对疾病进展率、并发症风险和药物反应的有价值的见解。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，支持治疗决策。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，并最终提高DKD患者的生活质量。

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.