Clinical proteomics offers a new dimension in the diagnosis of disease, with the ability for more sensitive and precise measurements than traditional diagnostics. To achieve this goal, proteomics must be taken from the laboratory to the clinic - a translational journey not without its challenges.
A proteomics discovery pipeline was applied to determine biomarkers for Diabetic Kidney Disease (DKD) which is a serious complication arising from diabetes. The International Diabetes Federation estimates there are 537 million adults living with diabetes globally, and one-in-three currently have DKD. DKD leads to renal failure which requires dialysis or kidney transplant, and the total cost of DKD is USD130 Bn per year in the USA alone.
The translation of candidate biomarkers into a clinical test followed validation and refinement in long-term clinical studies, plus method development through a series of cross-platform technical studies from an initial immuno-depletion targeted mass spectrometry test (MRM-MS), via an MS-antibody bead method, to an immunoassay applicable to standard clinical use.
The outcome of this work is PromarkerD, a novel prognostic test that can predict future kidney function decline in patients with type 2 diabetes and no existing DKD. The end product uses a simple blood test to detect the early onset of the disease by measuring three serum proteins (ApoA4, IBP3, CD5L), combined with three routinely available conventional clinical variables (age, HDL-cholesterol and estimated glomerular filtration rate (eGFR)). A cloud based algorithm integrates the results into a patient risk report.
In clinical studies PromarkerD correctly predicted up to 86% of otherwise healthy diabetics who went on to develop diabetic kidney disease within four years. The PromarkerD test is patented, CE Mark registered in the European Union, and now poised for clinical use globally. The quest has been complex but rewarding.