Abstract
Current diagnostic measures for Chronic Kidney Disease (CKD) include detection of reduced estimated glomerular filtration rate (eGFR) and albuminuria, which have suboptimal accuracies in predicting disease progression. The disease complexity and heterogeneity underscore the need for multiplex quantification of different markers. The goal of this study was to determine the association of six previously reported CKD-associated plasma proteins [B2M (Beta-2-microglobulin), SERPINF1 (Pigment epithelium-derived factor), AMBP (Protein AMBP), LYZ (Lysozyme C), HBB (Hemoglobin subunit beta) and IGHA1 (Immunoglobulin heavy constant alpha 1)], as measured in a multiplex format, with kidney function, and outcome. Antibody-free, multiple reaction monitoring mass spectrometry (MRM) assays were developed, characterized for their analytical performance, and used for the analysis of 72 plasma samples from a patient cohort with longitudinal follow-up. The MRM significantly correlated (Rho = 0.5–0.9) with results from respective ELISA. Five proteins [AMBP, B2M, LYZ, HBB and SERPINF1] were significantly associated with eGFR, with the three former also associated with unfavorable outcome. The combination of these markers provided stronger associations with outcome (p < 0.0001) compared to individual markers. Collectively, our study describes a multiplex assay for absolute quantification and verification analysis of previously described putative CKD prognostic markers, laying the groundwork for further use in prospective validation studies.
Highlights
Current diagnostic measures for Chronic Kidney Disease (CKD) include detection of reduced estimated glomerular filtration rate and albuminuria, which have suboptimal accuracies in predicting disease progression
A urinary peptide classifier, CKD273, consisting of 273 peptides, fragments of multiple kidney-specific as well as plasma proteins detected by the use of capillary electrophoresis (CE) in combination to mass spectrometry (MS) has been developed, subsequently evaluated[26,27,28] and received a letter of support by the US Food and Drug Administration (FDA, USA) for use in early detection of nephropathy in diabetic patients[29]
To avoid extensive pre-fractionation steps potentially compromising assay reproducibility and applicability, only markers with expected relatively high (>100 ng/ml) plasma abundance levels reported in the literature and existing proteomic databases were considered (Supplementary Table S1)
Summary
Current diagnostic measures for Chronic Kidney Disease (CKD) include detection of reduced estimated glomerular filtration rate (eGFR) and albuminuria, which have suboptimal accuracies in predicting disease progression. CKD diagnosis is currently based on the detection of reduced estimated glomerular filtration rate (eGFR) and/or albuminuria, as indicators of renal dysfunction[12,13] These markers have substantial www.nature.com/scientificreports limitations in evaluating CKD progression. Even though associations with outcome have been reported, the overall suboptimal accuracies of individual markers emphasize the need to establish panels or multi-parametric classifiers, better reflective of the substantial phenotypic and molecular heterogeneity of CKD Along these lines, a urinary peptide classifier, CKD273, consisting of 273 peptides, fragments of multiple kidney-specific as well as plasma proteins detected by the use of capillary electrophoresis (CE) in combination to mass spectrometry (MS) has been developed, subsequently evaluated[26,27,28] and received a letter of support by the US Food and Drug Administration (FDA, USA) for use in early detection of nephropathy in diabetic patients[29]. CKD273 has been found to predict progression at early CKD stages (eGFR > 70 mL/min/1.73 m2) more accurately than albuminuria[30], and has been applied in the proteome-guided intervention trial, PRIORITY31
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