Current single AKI biomarkers are not very specific, and the diagnosis of acute kidney injury (AKI) events is sometimes delayed. An understanding of the intricacy of AKI and the ability to identify potentially targetable molecular pathways may be aided by analyzing the peptidome of the urine. A peptide-based score predictive of AKI (7-day KDIGO classification) was developed, validated, and compared to the reference biomarkers urinary NGAL and NephroCheck and clinical scores in a total of 1,170 patients undergoing major cardiac bypass surgery in the derivation and validation cohorts and in an external cohort of 1569 ICU patients.

A set of 204 urinary peptides made from 48 proteins related to hemolysis, inflammation, immune cell trafficking, innate immunity, and cell growth and survival were found and proved to be better than reference biomarkers (urinary NGAL and [IGFBP7].[TIMP2] product) and clinical scores at predicting the risk of AKI in patients (OR 6.13 [3.96–9.59], P<0.001) within 4 hours. In an outside group of 1,569 ICU patients, the signature worked about the same (OR 5.92 [4.73–7.45], P<0.001), and was also linked to death in the hospital (OR 2.62 [2.05–3.38], P<0.001).

Urinary peptide signatures generated by AKI physiopathology indicate great potential for early identification of people at risk for developing AKI and the subsequent development of individualized treatments for this common and potentially lethal disorder. The urine peptide signature performs as well as or better than individual biomarkers, but it also includes mechanistic information that could be used to differentiate between AKI sub-phenotypes and hence identify novel therapeutic targets.

Source: ccforum.biomedcentral.com/articles/10.1186/s13054-022-04193-9