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

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.