TY - JOUR
T1 - Novel plasma peptide markers involved in the pathology of CKD identified using mass spectrometric approach
AU - Gajjala, Prathibha R.
AU - Bruck, Heike
AU - Noels, Heidi
AU - Heinze, Georg
AU - Ceccarelli, Francesco
AU - Kribben, Andreas
AU - Saez-Rodriguez, Julio
AU - Marx, Nikolaus
AU - Zidek, Walter
AU - Jankowski, Joachim
AU - Jankowski, Vera
N1 - Funding Information:
This work was supported by the German Research Foundation (DFG) (SFB/TRR219 S-03, C-04, IHST 948/4S-1 FU6.6).
Publisher Copyright:
© 2019, The Author(s).
PY - 2019/10
Y1 - 2019/10
N2 - Chronic kidney disease (CKD) may progress to end-stage renal disease (ESRD) at different pace. Early markers of disease progression could facilitate and improve patient management. However, conventional blood and urine chemistry have proven unable to predict the progression of disease at early stages. Therefore, we performed untargeted plasma peptidome analysis to select the peptides involved in progression, which are suitable for long prospective studies in future. The study consists of non-CKD (n = 66) and CKD (n = 106) patients with different stages. We performed plasma peptidomics on these subjects using chromatography and mass spectrometric approaches. Initially, we performed LC-ESI-MS and applied least absolute shrinkage and selection operator logistic regressions to select the peptides that are differentially expressed and we generated a peptidomic score for each subject. Later, we identified and sequenced the peptides with MALDI-MS/MS and also performed univariate and multivariate analyses with the clinical variables and peptidomic score to reveal their association with progression of renal disease. A logistic regression model selected 14 substances showing different concentrations according to renal function, of which seven substances were most likely occur in CKD patients. The peptidomic model had a global P value of <0.01 with R-2 of 0.466, and the area under the curve was 0.87 (95% CI, 0.8149-0.9186; P <0.0001). The predicted score was significantly higher in CKD than in non-CKD patients (2.539 +/- 0.2637 vs - 0.9382 +/- 0.1691). The model was also able to predict stages of CKD: the Spearman correlation coefficient of the linear predictor with CKD stages was 0.83 with concordance indices of 0.899 (95% CI 0.863-0.927). In univariate analysis, the most consistent association of peptidomic score in CKD patients was with C-reactive protein, sodium level, and uric acid, which are unanticipated substances. Peptidomic analysis enabled to list some unanticipated substances that have not been extensively studied in the context of CKD but were associated with CKD progression, thus revealing interesting candidate markers or mediators of CKD of potential use in CKD progression management. Key messages center dot Conventional blood and urine chemistry have proven unable to predict the progression of disease at early stages of chronic kidney disease (CKD). center dot We performed untargeted plasma peptidome analysis to select the peptides involved in progression. center dot A logistic regression model selected 14 substances showing different concentrations according to renal function. center dot These peptides are unanticipated substances that have not been extensively studied in the context of CKD but were associated with CKD progression, thus revealing markers or mediators of CKD of potential use in CKD progression management.
AB - Chronic kidney disease (CKD) may progress to end-stage renal disease (ESRD) at different pace. Early markers of disease progression could facilitate and improve patient management. However, conventional blood and urine chemistry have proven unable to predict the progression of disease at early stages. Therefore, we performed untargeted plasma peptidome analysis to select the peptides involved in progression, which are suitable for long prospective studies in future. The study consists of non-CKD (n = 66) and CKD (n = 106) patients with different stages. We performed plasma peptidomics on these subjects using chromatography and mass spectrometric approaches. Initially, we performed LC-ESI-MS and applied least absolute shrinkage and selection operator logistic regressions to select the peptides that are differentially expressed and we generated a peptidomic score for each subject. Later, we identified and sequenced the peptides with MALDI-MS/MS and also performed univariate and multivariate analyses with the clinical variables and peptidomic score to reveal their association with progression of renal disease. A logistic regression model selected 14 substances showing different concentrations according to renal function, of which seven substances were most likely occur in CKD patients. The peptidomic model had a global P value of <0.01 with R-2 of 0.466, and the area under the curve was 0.87 (95% CI, 0.8149-0.9186; P <0.0001). The predicted score was significantly higher in CKD than in non-CKD patients (2.539 +/- 0.2637 vs - 0.9382 +/- 0.1691). The model was also able to predict stages of CKD: the Spearman correlation coefficient of the linear predictor with CKD stages was 0.83 with concordance indices of 0.899 (95% CI 0.863-0.927). In univariate analysis, the most consistent association of peptidomic score in CKD patients was with C-reactive protein, sodium level, and uric acid, which are unanticipated substances. Peptidomic analysis enabled to list some unanticipated substances that have not been extensively studied in the context of CKD but were associated with CKD progression, thus revealing interesting candidate markers or mediators of CKD of potential use in CKD progression management. Key messages center dot Conventional blood and urine chemistry have proven unable to predict the progression of disease at early stages of chronic kidney disease (CKD). center dot We performed untargeted plasma peptidome analysis to select the peptides involved in progression. center dot A logistic regression model selected 14 substances showing different concentrations according to renal function. center dot These peptides are unanticipated substances that have not been extensively studied in the context of CKD but were associated with CKD progression, thus revealing markers or mediators of CKD of potential use in CKD progression management.
KW - Chronic kidney disease
KW - End-stage renal disease
KW - Disease progression
KW - Systems medicine
KW - proteomics
KW - peptidomics
KW - CELL-MIGRATION
KW - KIDNEY
KW - INFLAMMATION
KW - DISEASE
KW - CALCIFICATION
KW - PROGRESSION
KW - MECHANISMS
KW - FIBROSIS
KW - ALDH3A1
KW - SLC4A11
U2 - 10.1007/s00109-019-01823-8
DO - 10.1007/s00109-019-01823-8
M3 - Article
C2 - 31385015
SN - 0946-2716
VL - 97
SP - 1451
EP - 1463
JO - Journal of Molecular Medicine
JF - Journal of Molecular Medicine
IS - 10
ER -