BACKGROUND: Identifying urinary biomarkers associated with acute rejection (AR) of kidney allografts could improve recipient care by allowing AR to be diagnosed noninvasively and treated earlier. We attempted to identify novel biomarkers associated with AR by analyzing urinary proteins by using matrix-associated laser desorption ionization time-of-flight mass spectroscopy (MALDI-TOF MS). METHODS: Using MALDI-TOF MS, we analyzed urine samples from 30 renal allograft recipients with biopsy-proven AR, 15 allograft recipients without AR, preoperative samples from 29 kidney donors, and 10 subjects with proteinuric native kidney disease. RESULTS: In samples obtained at the time of AR, we identified a protein peak at 11.7 kd that correlated strongly with AR. In regard to its predictive power for AR, this protein peak showed sensitivity of 83.3%, specificity of 80%, positive predictive value of 89%, and negative predictive value of 70.6%, suggesting that this protein is highly associated with AR. We identified this peak as being beta2-microglobulin. This was validated by using enzyme-linked immunosorbent assay, which documented the presence of high urinary beta2-microglobulin levels in subjects with AR. CONCLUSION: Beta2-microglobulin could be a strong biomarker for AR if used in conjunction with other biomarkers, producing an AR-specific urinary protein signature. This possibility must be confirmed in a larger cohort of kidney transplant recipients.
BACKGROUND: Identifying urinary biomarkers associated with acute rejection (AR) of kidney allografts could improve recipient care by allowing AR to be diagnosed noninvasively and treated earlier. We attempted to identify novel biomarkers associated with AR by analyzing urinary proteins by using matrix-associated laser desorption ionization time-of-flight mass spectroscopy (MALDI-TOF MS). METHODS: Using MALDI-TOF MS, we analyzed urine samples from 30 renal allograft recipients with biopsy-proven AR, 15 allograft recipients without AR, preoperative samples from 29 kidney donors, and 10 subjects with proteinuric native kidney disease. RESULTS: In samples obtained at the time of AR, we identified a protein peak at 11.7 kd that correlated strongly with AR. In regard to its predictive power for AR, this protein peak showed sensitivity of 83.3%, specificity of 80%, positive predictive value of 89%, and negative predictive value of 70.6%, suggesting that this protein is highly associated with AR. We identified this peak as being beta2-microglobulin. This was validated by using enzyme-linked immunosorbent assay, which documented the presence of high urinary beta2-microglobulin levels in subjects with AR. CONCLUSION:Beta2-microglobulin could be a strong biomarker for AR if used in conjunction with other biomarkers, producing an AR-specific urinary protein signature. This possibility must be confirmed in a larger cohort of kidney transplant recipients.
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