Early Prediction of Acute Renal Injury Using Urinary Proteomics

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Abstract
Aims: The lack of early biomarkers for acute renal failure (ARF) has crippled our ability to launch potentially effective therapeutic measures. We tested the hypothesis that urinary proteomics could identify novel early biomarker patterns for ischemic renal injury. Methods: Sixty patients undergoing cardiopulmonary bypass (CPB) were enrolled. Urine samples obtained at 2 and 6 h post CPB were analyzed by Surface-Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (SELDI-TOF-MS). The primary outcome variable was ARF, defined as a 50% or greater increase in serum creatinine. Results: Fifteen patients (25%) developed ARF 2–3 days after CPB. SELDI-TOF-MS analysis of urine from the ARF group at baseline versus at 2 and 6 h post-CPB consistently showed a marked and statistically significant enhancement of protein biomarkers with m/z of 6.4, 28.5, 43 and 66 kDa. The same biomarkers were enhanced when comparing control versus ARF groups at 2 and 6 h post-CPB. The sensitivity and specificity of the 28.5-, 43- and 66-kDa biomarkers for the prediction of ARF at 2 h following CPB was 100%. The receiver operating characteristic curves revealed an area under the curve of 0.98. Conclusion: SELDI-TOF-MS is a novel, non-invasive, sensitive, highly predictive, reproducible, rapid method for the prediction of acute renal injury following CPB.

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