Investigation of the Urinary Peptidome to Unravel Collagen Degradation in Health and Kidney Disease.

IF 3.4 4区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Proteomics Pub Date : 2024-12-30 DOI:10.1002/pmic.202400279
Ioanna K Mina, Luis F Iglesias-Martinez, Matthias Ley, Lucas Fillinger, Paul Perco, Justyna Siwy, Harald Mischak, Vera Jankowski
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引用次数: 0

Abstract

Naturally occurring fragments of collagen type I alpha 1 chain (COL1A1) have been previously associated with chronic kidney disease (CKD), with some fragments showing positive and others negative associations. Using urinary peptidome data from healthy individuals (n = 1131) and CKD patients (n = 5585) this aspect was investigated in detail. Based on the hypothesis that many collagen peptides are derived not from the full, mature collagen molecule, but from (larger) collagen degradation products, relationships between COL1A1 peptides containing identical sequences were investigated, with the smaller (offspring) peptide being a possible degradation product of the larger (parent) one. The strongest correlations were found for relationships where the parent differed by a maximum of three amino acids from the offspring, indicating an exopeptidase-regulated stepwise degradation process. Regression analysis indicated that CKD affects this degradation process. A comparison of matched CKD patients and control individuals (n = 612 each) showed that peptides at the start of the degradation process were consistently downregulated in CKD, indicating an attenuation of COL1A1 endopeptidase-mediated degradation. However, as these peptides undergo further degradation, likely mediated by exopeptidases, this downregulation can become less significant or even reverse, leading to an upregulation of later-stage fragments and potentially explaining the inconsistencies observed in previous studies.

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来源期刊
Proteomics
Proteomics 生物-生化研究方法
CiteScore
6.30
自引率
5.90%
发文量
193
审稿时长
3 months
期刊介绍: PROTEOMICS is the premier international source for information on all aspects of applications and technologies, including software, in proteomics and other "omics". The journal includes but is not limited to proteomics, genomics, transcriptomics, metabolomics and lipidomics, and systems biology approaches. Papers describing novel applications of proteomics and integration of multi-omics data and approaches are especially welcome.
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