ArticleJournal of mass spectrometry and advances in the clinical lab2021
Development and Validation of a Novel LC-MS/MS Assay for C-Peptide in Human Serum.
Article in Journal of mass spectrometry and advances in the clinical lab, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 15 citations in OpenAlex.
- Biomarkers, Proteoforms, and Mass Spectrometry-Based Assays for Diabetes Clinical Research.The Journal of clinical endocrinology and metabolism · 2025Review
- MRM-based LC-MS method for accurate C-peptide quantitation.Journal of mass spectrometry and advances in the clinical lab · 2025Article
- Development and Validation of a Novel Isotope Dilution-Ultraperformance Liquid Chromatography-Tandem Mass Spectrometry Method for Serum C-Peptide.Annals of laboratory medicine · 2025Article
- A Streamlined High-Throughput LC-MS Assay for Quantifying Peptide Degradation in Cell Culture.Journal of biomedical materials research. Part A · 2025Article
- A Streamlined High-Throughput LC-MS Assay for Quantifying Peptide Degradation in Cell Culture.bioRxiv : the preprint server for biology · 2024Article
- Interlaboratory Comparison of Antibody-Free LC-MS/MS Measurements of C-peptide and Insulin.Clinical chemistry · 2024Article
- Clinical Proteomics for Solid Organ Tissues.Molecular & cellular proteomics : MCP · 2023Article
- Quantitation of endogenous GnRH by validated nano-HPLC-HRMS method: a pilot study on ewe plasma.Analytical and bioanalytical chemistry · 2022Article
- Multiplexed quantification of insulin and C-peptide by LC-MS/MS without the use of antibodies.Journal of mass spectrometry and advances in the clinical lab · 2022Article
- Listening to your mass spectrometer: An open-source toolkit to visualize mass spectrometer data.Journal of mass spectrometry and advances in the clinical lab · 2022Article
- The potential for isotope dilution-LC-MS/MS to improve laboratory measurement of C-peptide: Reasons and critical determinants.Journal of mass spectrometry and advances in the clinical lab · 2021Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
introductionC-peptide is used as a marker of endogenous insulin secretion in the assessment of residual β-cell function in diabetes and in the diagnostic workup of hypoglycemia. Previously developed LC-MS/MS methods to quantify serum concentrations of C-peptide have monitored intact peptide, which ionizes poorly. As a result, methods have leveraged immunoaffinity enrichment or two-dimensional chromatography. In this study, we aimed to use proteolysis during sample preparation to enhance the sensitivity of traditional LC-MS/MS.
methodsDue to the absence of arginine and lysine residues in C-peptide, we utilized Glu-C as the proteolytic enzyme in the method. After protein precipitation using acetonitrile and solid phase extraction with mixed anion exchange, lower molecular weight polypeptides were reduced, alkylated, and proteolyzed. The two amino-terminal peptide fragments, EAEDLQVGQVE and LGGGPGAGSLQPLALE, were monitored using multiple reaction monitoring in positive ion mode (Acquity ULPC-Xevo TQ-S, Waters). The former peptide was used for quantification and the latter for quality assurance.
resultsGlu-C was determined to be a reliable proteolytic enzyme with monotonic digestion kinetics. The assay was linear between 0.1 and 15 ng/mL and had a lower limit of quantification of 0.06 ng/mL. Total imprecision was 7.7 %CV and long-term imprecision at 0.16 ng/mL was 10.0%. Spike-recovery experiments demonstrated a mean recovery of 98.2 % (± 9.1 %) and the method compared favorably with a commercially available immunoassay and a reference measurement procedure.
conclusionProtein precipitation with solid phase extraction and proteolysis with Glu-C is a robust sample preparation method for quantification of C-peptide in human serum by LC-MS/MS.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.