A KIT FOR THE EARLY DETECTION OF KIDNEY INJURY

Acute kidney injury presents as a rapid decrease in renal function and can be caused by severe trauma, illness, surgery or chronic medication, such as the use of antiretroviral treatment. Many assays used in disease detection were developed decades ago, and their performance is lacking. This is the case with the diagnosis of kidney injury. Diagnosis is based on enzymatic tests for increased serum creatinine levels and a decline in glomerular filtration rate. But glomerular filtration rate often generates misleading results as serum creatinine levels and renal filtration are in a state of continuous homeostasis, even under normal kidney function. 

To address the challenges outlined, CSIR researchers applied a novel approach powered by liquid chromatography-mass spectrometry-based proteome profiling to develop a diagnostic test capable of monitoring HIV/Aids patients on antiretrovirals, specifically Tenofovir disoproxil fumarate (hereafter referred to as Tenofovir), for the early onset of acute kidney injury. The research team monitored renal function using urine as the biological sample; it is non-invasive, and the abundant biofluid in the form of urine is directly associated with the kidneys as the site of the disease, thus making it ideal as a prognostic indicator for acute kidney disease. The application of machine learning to extract highly specific molecular patterns for acute kidney injury adds to the novelty of the approach. Using multiplexed protein panels (or signatures), rather than single protein molecules, as has been the status quo, allows much more accurate detection of kidney damage before it becomes significant or irreversible, in addition to being able to differentiate between the various stages of kidney injury, which current clinical tests are not capable of doing efficiently. This makes it possible to address the most urgent needs regarding the diagnosis of kidney diseases: early and accurate detection, monitoring the response to therapy and predicting progression across the various stages of kidney injury.