Characterization of Trivalently Crosslinked C‐Terminal Telopeptide of Type I Collagen (CTX) Species in Human Plasma and Serum Using High‐Resolution Mass Spectrometry

With an aging population, the increased interest in the monitoring of skeletal diseases such as osteoporosis led to significant progress in the discovery and measurement of bone turnover biomarkers since the 2000s. Multiple markers derived from type I collagen, such as CTX, NTX, PINP, and ICTP, have been developed. Extensive efforts have been devoted to characterizing these molecules; however, their complex crosslinked structures have posed significant analytical challenges, and to date, these biomarkers remain poorly characterized. Previous attempts at characterization involved gel-based separation methods and MALDI-TOF analysis on collagen peptides directly extracted from bone. However, using bone powder, which is rich in collagen, does not represent the true structure of the peptides in the biofluids as it was cleaved. In this study, our goal was to characterize plasma and serum CTX for subsequent LC-MS/MS method development. We extracted and characterized type I collagen peptides directly from human plasma and serum using a proteomics workflow that integrates preparative LC, affinity chromatography, and HR-MS. Subsequently, we successfully identified numerous CTX species, providing valuable insights into the characterization of these crucial biomarkers.

Authors

Institutions

Publication Details

Journal
PROTEOMICS
Published
2024-10-27
DOI
https://doi.org/10.1002/pmic.202400027
Citations
2
Primary Topic
Bone health and osteoporosis research
Type
article
Field-Weighted Citation Impact
0.96

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Characterization of Trivalently Crosslinked C‐Terminal Telopeptide of Type I Collagen (CTX) Species in Human Plasma and Serum Using High‐Resolution Mass Spectrometry

Philippe Massonnet, Loreen Huyghebeart, Justine Demeuse, Elodie Grifnée et al.
2 citations
PROTEOMICS
Bone health and osteoporosis research
0.96
article

Characterization of Trivalently Crosslinked C‐Terminal Telopeptide of Type I Collagen (CTX) Species in Human Plasma and Serum Using High‐Resolution Mass Spectrometry

Philippe Massonnet, Loreen Huyghebeart, Justine Demeuse, Elodie Grifnée, Thomas Dubrowski, Stéphanie Peeters, Étienne Cavalier, Matthieu Schoumacher, Caroline Le Goff, William Determe
article en
2 citations

Abstract

With an aging population, the increased interest in the monitoring of skeletal diseases such as osteoporosis led to significant progress in the discovery and measurement of bone turnover biomarkers since the 2000s. Multiple markers derived from type I collagen, such as CTX, NTX, PINP, and ICTP, have been developed. Extensive efforts have been devoted to characterizing these molecules; however, their complex crosslinked structures have posed significant analytical challenges, and to date, these biomarkers remain poorly characterized. Previous attempts at characterization involved gel-based separation methods and MALDI-TOF analysis on collagen peptides directly extracted from bone. However, using bone powder, which is rich in collagen, does not represent the true structure of the peptides in the biofluids as it was cleaved. In this study, our goal was to characterize plasma and serum CTX for subsequent LC-MS/MS method development. We extracted and characterized type I collagen peptides directly from human plasma and serum using a proteomics workflow that integrates preparative LC, affinity chromatography, and HR-MS. Subsequently, we successfully identified numerous CTX species, providing valuable insights into the characterization of these crucial biomarkers.

PROTEOMICSVol. 25(4)
University of Liège (BE)
Université de Liège
Life in Land
Openalex Percentile: Top 26%
Bone health and osteoporosis research
0.96
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.