Interlaboratory Comparison of Antibody-Free LC-MS/MS Measurements of C-peptide and Insulin.


Journal

Clinical chemistry
ISSN: 1530-8561
Titre abrégé: Clin Chem
Pays: England
ID NLM: 9421549

Informations de publication

Date de publication:
29 Mar 2024
Historique:
received: 07 09 2023
accepted: 29 01 2024
medline: 29 3 2024
pubmed: 29 3 2024
entrez: 29 3 2024
Statut: aheadofprint

Résumé

The enhanced precision and selectivity of liquid chromatography-tandem mass spectrometry (LC-MS/MS) makes it an attractive alternative to certain clinical immunoassays. Easily transferrable work flows could help facilitate harmonization and ensure high-quality patient care. We aimed to evaluate the interlaboratory comparability of antibody-free multiplexed insulin and C-peptide LC-MS/MS measurements. The laboratories that comprise the Targeted Mass Spectrometry Assays for Diabetes and Obesity Research (TaMADOR) consortium verified the performance of a validated peptide-based assay (reproducibility, linearity, and lower limit of the measuring interval [LLMI]). An interlaboratory comparison study was then performed using shared calibrators, de-identified leftover laboratory samples, and reference materials. During verification, the measurements were precise (2.7% to 3.7%CV), linear (4 to 15 ng/mL for C-peptide and 2 to 14 ng/mL for insulin), and sensitive (LLMI of 0.04 to 0.10 ng/mL for C-peptide and 0.03 ng/mL for insulin). Median imprecision across the 3 laboratories was 13.4% (inter-quartile range [IQR] 11.6%) for C-peptide and 22.2% (IQR 20.9%) for insulin using individual measurements, and 10.8% (IQR 8.7%) and 15.3% (IQR 14.9%) for C-peptide and insulin, respectively, when replicate measurements were averaged. Method comparison with the University of Missouri reference method for C-peptide demonstrated a robust linear correlation with a slope of 1.044 and r2 = 0.99. Our results suggest that combined LC-MS/MS measurements of C-peptide and insulin are robust and adaptable and that standardization with a reference measurement procedure could allow accurate and precise measurements across sites, which could be important to diabetes research and help patient care in the future.

Sections du résumé

BACKGROUND UNASSIGNED
The enhanced precision and selectivity of liquid chromatography-tandem mass spectrometry (LC-MS/MS) makes it an attractive alternative to certain clinical immunoassays. Easily transferrable work flows could help facilitate harmonization and ensure high-quality patient care. We aimed to evaluate the interlaboratory comparability of antibody-free multiplexed insulin and C-peptide LC-MS/MS measurements.
METHODS UNASSIGNED
The laboratories that comprise the Targeted Mass Spectrometry Assays for Diabetes and Obesity Research (TaMADOR) consortium verified the performance of a validated peptide-based assay (reproducibility, linearity, and lower limit of the measuring interval [LLMI]). An interlaboratory comparison study was then performed using shared calibrators, de-identified leftover laboratory samples, and reference materials.
RESULTS UNASSIGNED
During verification, the measurements were precise (2.7% to 3.7%CV), linear (4 to 15 ng/mL for C-peptide and 2 to 14 ng/mL for insulin), and sensitive (LLMI of 0.04 to 0.10 ng/mL for C-peptide and 0.03 ng/mL for insulin). Median imprecision across the 3 laboratories was 13.4% (inter-quartile range [IQR] 11.6%) for C-peptide and 22.2% (IQR 20.9%) for insulin using individual measurements, and 10.8% (IQR 8.7%) and 15.3% (IQR 14.9%) for C-peptide and insulin, respectively, when replicate measurements were averaged. Method comparison with the University of Missouri reference method for C-peptide demonstrated a robust linear correlation with a slope of 1.044 and r2 = 0.99.
CONCLUSIONS CONCLUSIONS
Our results suggest that combined LC-MS/MS measurements of C-peptide and insulin are robust and adaptable and that standardization with a reference measurement procedure could allow accurate and precise measurements across sites, which could be important to diabetes research and help patient care in the future.

Identifiants

pubmed: 38549041
pii: 7637206
doi: 10.1093/clinchem/hvae034
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Published by Oxford University Press on behalf of Association for Diagnostics & Laboratory Medicine 2024.

Auteurs

Annie Moradian (A)

Precision Biomarker Laboratories, Cedars-Sinai Medical Center, Los Angeles, CA, United States.

Elisha Goonatilleke (E)

Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States.

Tai-Tu Lin (TT)

Integrative Omics, Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States.

Maya Hatten-Beck (M)

Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States.

Michelle Emrick (M)

Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States.

Athena A Schepmoes (AA)

Integrative Omics, Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States.

Thomas L Fillmore (TL)

Integrative Omics, Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States.

Michael J MacCoss (MJ)

Department of Genome Sciences, University of Washington, Seattle, WA, United States.

Salvatore Sechi (S)

Division of Diabetes, Endocrinology, & Metabolic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, United States.

Kimia Sobhani (K)

Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States.

Randie Little (R)

Department of Pathology and Anatomical Sciences, University of Missouri School of Medicine, Columbia, MO, United States.

Kuanysh Kabytaev (K)

Department of Pathology and Anatomical Sciences, University of Missouri School of Medicine, Columbia, MO, United States.

Jennifer E van Eyk (JE)

Precision Biomarker Laboratories, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Advanced Clinical Biosystems Research Institute, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States.

Wei-Jun Qian (WJ)

Integrative Omics, Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States.

Andrew N Hoofnagle (AN)

Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States.
Department of Medicine, Kidney Research Institute, University of Washington, Seattle, WA, United States.

Classifications MeSH