ArticleJournal of molecular medicine (Berlin, Germany)2019
Novel plasma peptide markers involved in the pathology of CKD identified using mass spectrometric approach.
Article in Journal of molecular medicine (Berlin, Germany), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 16 citations in OpenAlex.
- Prediction Modeling With Many Correlated and Zero-Inflated Predictors: Assessing the Nonnegative Garrote Approach.Statistics in medicine · 2025Article
- Proteomic Analysis Identifies Dysregulated Proteins in Albuminuria: A South African Pilot Study.Biology · 2024Article
- Salivary proteomics profiling reveals potential biomarkers for chronic kidney disease: a pilot study.Frontiers in medicine · 2024Article
- MS-Based Proteomics of Body Fluids: The End of the Beginning.Molecular & cellular proteomics : MCP · 2023Article
- A simple, time- and cost-effective, high-throughput depletion strategy for deep plasma proteomics.Science advances · 2023Article
- Applying Proteomics and Integrative "Omics" Strategies to Decipher the Chronic Kidney Disease-Related Atherosclerosis.International journal of molecular sciences · 2021Review
Corrections and comments
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Authors and funding
11 authors at 8 institutions in 3 countries.
Funding
Abstract
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
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Registered trials
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