Evidence map›Paper›PMID 38549041›Full record

ArticleClinical chemistry2024

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

Annie Moradian, Elisha Goonatilleke, Tai-Tu Lin, Maya Hatten-Beck, Michelle Emrick, Athena A Schepmoes, Thomas L Fillmore, Michael J MacCoss, Salvatore Sechi, Kimia Sobhani and 5 more

Open access · hybridAbstract readComparative Study
In one paragraph

Article in Clinical chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
4.4field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. MRM-based LC-MS method for accurate C-peptide quantitation.Journal of mass spectrometry and advances in the clinical lab · 2025
    Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 5 institutions in 1 country.

Annie MoradianPrecision Biomarker Laboratories, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Elisha GoonatillekeDepartment of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States.
Tai-Tu LinIntegrative Omics, Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States.
Maya Hatten-BeckDepartment of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States.
Michelle EmrickDepartment of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States.
Athena A SchepmoesIntegrative Omics, Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States.
Thomas L FillmoreIntegrative Omics, Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States.
Michael J MacCossDepartment of Genome Sciences, University of Washington, Seattle, WA, United States.
Salvatore SechiDivision of Diabetes, Endocrinology, & Metabolic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, United States.
Kimia SobhaniDepartment of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Randie LittleDepartment of Pathology and Anatomical Sciences, University of Missouri School of Medicine, Columbia, MO, United States.
Kuanysh KabytaevDepartment of Pathology and Anatomical Sciences, University of Missouri School of Medicine, Columbia, MO, United States.
Jennifer E van EykPrecision Biomarker Laboratories, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Wei-Jun QianIntegrative Omics, Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States.ORCID 0000-0002-5393-2827
Andrew N HoofnagleDepartment of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States.ORCID 0000-0002-6449-0243
University of Washington · USPacific Northwest National Laboratory · USCedars-Sinai Medical Center · USUniversity of Missouri · USNational Institutes of Health · US

Funding

Vector and Transgenic Mouse CoreP30DK017047 · NIDDK · UNIVERSITY OF WASHINGTON · PI Karin E Bornfeldt · 1986 to 2026
$41.4M
PILOT STUDY--CLINICAL NUTRITION RESEARCHP30DK035816 · NIDDK · UNIVERSITY OF WASHINGTON · PI Ellen A Schur · 1986 to 2026
$30.4M
Quantifying proteins in plasma do democratize personalized medicine for patients with type 1 diabetesU01DK137097 · NIDDK · UNIVERSITY OF WASHINGTON · PI ANDREW N HOOFNAGLE, Michael MacCoss · 2023 to 2026
$3.4M
Multiplex Mass Spectrometric Protein Assays for Precise Monitoring of the Pathophysiology of ObesityU01DK124020 · NIDDK · BATTELLE PACIFIC NORTHWEST LABORATORIES · PI QIAN, WEI-JUN · 2019 to 2022
$3.3M
Design and Validation of Easy-to-Adopt Mass Spectrometry Assays of Importance to ObesityU01DK124019 · NIDDK · CEDARS-SINAI MEDICAL CENTER · PI SOBHANI, KIMIA, VAN EYK, JENNIFER E · 2019 to 2022
$3.1M
Standardization of C-Peptide and HbA1C Measurements ProgramU01DK133106 · NIDDK · UNIVERSITY OF MISSOURI-COLUMBIA · PI Kuanysh Kabytaev · 2022 to 2026
$2.3M
Quantifying proteins in plasma to democratize personalized medicine for patients with type 1 diabetesU01DK121289 · NIDDK · UNIVERSITY OF WASHINGTON · PI HOOFNAGLE, ANDREW N · 2019 to 2021
$1.9M
NIDDK NIH HHS P30 DK017047NIDDK NIH HHS P30 DK035816NIDDK NIH HHS U01 DK121289NIDDK NIH HHS U01 DK124019NIDDK NIH HHS U01 DK124020NIDDK NIH HHS U01 DK133106NIDDK NIH HHS U01 DK137097
6 · The paper itself

Abstract

backgroundThe 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.

methodsThe 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.

resultsDuring 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.

conclusionsOur 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.

Indexed as

C-PeptideInsulinTandem Mass SpectrometryChromatography, LiquidHumansLaboratoriesLiquid Chromatography-Mass SpectrometryReproducibility of ResultsC-PeptideInsulin

Identifiers

PMID38549041
PMCPMC12052497
OpenAlexW4393315560

What OpenQuestion holds

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Registered trials

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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.