Identifying patients at high-risk for end-stage renal disease (ESRD) is crucial for providing the best possible care and targeted prevention strategies.
Currently, healthcare staff use a tool called the kidney failure risk equation (KFRE) to predict the risk for patients with chronic kidney disease (CKD) of needing dialysis or a kidney transplant. This uses the patient’s urine, sex, age and estimated glomerular filtration rate – a way of calculating how many millilitres of waste your kidneys should be able to filter in a minute.
But now renal experts at Northern Care Alliance NHS Foundation Trust have shown that this prediction could be made more accurate using biomarkers in patients’ plasma samples.
The work was based on samples from the Salford Kidney Study biobank, one of the largest CKD biobanks in the world, and has recently been published in the journal Clinical Proteomics. It was funded by the Medical Research Council and led at NCA by Professor Phil Kalra (pictured above) and Dr Ivona Baricevic-Jones.
Earlier identification
Professor Kalra said: “Signs and symptoms of ESRD are often non-specific and might not appear until irreversible kidney damage has already occurred. Patients with ESRD require dialysis or kidney transplantation to survive, causing considerable burdens on patients and their families. If we could identify these patients earlier through biomarkers, then they could be referred to specialist services in more timely fashion increasing the chance of improving outcomes.
“While KFRE offers a more accurate prediction of two and five- year risk of developing ESRD than estimated glomerular filtration rate-based thresholds alone, it doesn’t tell us about patient-specific biological mechanisms that drive ESRD.
“This study investigated the value of adding a proteomic signature to the KFRE in predicting ESRD in patients from the Salford Kidney Study. The research identified that a few particular proteins in plasma from these patients did enhance the prediction.”
The team used what is known as a SWATH-mass spectrometry approach to identify nine biomarkers/proteins that were significant for distinguishing between ESRD patients and the rest of the CKD patients. The top three proteins (SPTA1, MYL6 and C6) when combined with the KFRE tool, improved prediction of ESRD developing within five years.
Dr Baricevic-Jones (pictured above) explained ‘’We discovered that these proteins were associated with certain biological pathways that have been shown to be closely associated with kidney failure. These pathways are implicated in the development of dysfunction in particular cells in the kidneys and could be potential targets for new treatments’’.
The relationships of the protein biomarkers identified in the study with ESRD outcomes now need to be verified in samples from patients from another large non-dialysis CKD biobank.
- Carlos Medina, Ibrahim Ali, Ivona Baricevic-Jones, Moin Saleem, Anthony Whetton, Philip Kalra, Nophar Geifman: Evaluation of a proteomic signature coupled with the kidney failure risk equation in predicting end stage kidney disease in a chronic kidney disease cohort