Evidence map›Paper›PMID 24664114›Full record

Trial reportPloS one2014

Parallel workflow for high-throughput (>1,000 samples/day) quantitative analysis of human insulin-like growth factor 1 using mass spectrometric immunoassay.

Paul E Oran, Olgica Trenchevska, Dobrin Nedelkov, Chad R Borges, Matthew R Schaab, Douglas S Rehder, Jason W Jarvis, Nisha D Sherma, Luhui Shen, Bryan Krastins and 3 more

Erratum issuedOpen access · goldAbstract readClinical Trial
In one paragraph

Trial report in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
5.8field-weighted citation impact, top 3% 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

16 citing papers in PubMed, 52 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Prospective on Imaging Mass Spectrometry in Clinical Diagnostics.Molecular & cellular proteomics : MCP · 2023
    Review
  5. Article
  6. Article
  7. MALDI-MS: Emerging roles in pathology and laboratory medicine.Clinical mass spectrometry (Del Mar, Calif.) · 2019
    Review
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Review
  14. Review
  15. Article
  16. Article
4 · The record

Corrections and comments

  • Erratum issued
    Lopez, Mary F [removed]
5 · Who and what money

Authors and funding

13 authors at 3 institutions in 1 country.

Paul E OranMolecular Biomarkers Laboratory, Biodesign Institute, Arizona State University, Tempe, Arizona, United States of America.
Olgica TrenchevskaMolecular Biomarkers Laboratory, Biodesign Institute, Arizona State University, Tempe, Arizona, United States of America.
Dobrin NedelkovMolecular Biomarkers Laboratory, Biodesign Institute, Arizona State University, Tempe, Arizona, United States of America.
Chad R BorgesMolecular Biomarkers Laboratory, Biodesign Institute, Arizona State University, Tempe, Arizona, United States of America.
Matthew R SchaabMolecular Biomarkers Laboratory, Biodesign Institute, Arizona State University, Tempe, Arizona, United States of America.
Douglas S RehderMolecular Biomarkers Laboratory, Biodesign Institute, Arizona State University, Tempe, Arizona, United States of America.
Jason W JarvisMolecular Biomarkers Laboratory, Biodesign Institute, Arizona State University, Tempe, Arizona, United States of America.
Nisha D ShermaMolecular Biomarkers Laboratory, Biodesign Institute, Arizona State University, Tempe, Arizona, United States of America.
Luhui ShenCenter for Innovations in Medicine, Biodesign Institute, Arizona State University, Tempe, Arizona, United States of America.
Bryan KrastinsThermo Fisher Scientific, The Biomarkers Research Initiatives in Mass Spectrometry Center, Cambridge, Massachusetts, United States of America.
Dawn C SchwenkePhoenix VA Health Care System, Phoenix, Arizona, United States of America; College of Nursing & Health Innovation, Arizona State University, Phoenix, Arizona, United States of America.
Peter D ReavenPhoenix VA Health Care System, Phoenix, Arizona, United States of America.
Randall W NelsonMolecular Biomarkers Laboratory, Biodesign Institute, Arizona State University, Tempe, Arizona, United States of America.
Arizona State University · USThermo Fisher Scientific (United States) · USPhoenix VA Health Care System · US

Funding

Team Approach to Translate Novel Biomarkers for DiabetesR24DK090958 · NIDDK · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI NELSON, RANDALL W, PEARSON, JAMES DAVID · 2011 to 2014
$4.5M
Population-Based Proteomic Investigation of Type 2 Diabetes MellitusR01DK082542 · NIDDK · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI NELSON, RANDALL W · 2010 to 2014
$3.0M
NIDDK NIH HHS R01 DK082542NIDDK NIH HHS R01DK082542NIDDK NIH HHS R24 DK090958NIDDK NIH HHS R24DK090958
6 · The paper itself

Abstract

Insulin-like growth factor 1 (IGF1) is an important biomarker for the management of growth hormone disorders. Recently there has been rising interest in deploying mass spectrometric (MS) methods of detection for measuring IGF1. However, widespread clinical adoption of any MS-based IGF1 assay will require increased throughput and speed to justify the costs of analyses, and robust industrial platforms that are reproducible across laboratories. Presented here is an MS-based quantitative IGF1 assay with performance rating of >1,000 samples/day, and a capability of quantifying IGF1 point mutations and posttranslational modifications. The throughput of the IGF1 mass spectrometric immunoassay (MSIA) benefited from a simplified sample preparation step, IGF1 immunocapture in a tip format, and high-throughput MALDI-TOF MS analysis. The Limit of Detection and Limit of Quantification of the resulting assay were 1.5 μg/L and 5 μg/L, respectively, with intra- and inter-assay precision CVs of less than 10%, and good linearity and recovery characteristics. The IGF1 MSIA was benchmarked against commercially available IGF1 ELISA via Bland-Altman method comparison test, resulting in a slight positive bias of 16%. The IGF1 MSIA was employed in an optimized parallel workflow utilizing two pipetting robots and MALDI-TOF-MS instruments synced into one-hour phases of sample preparation, extraction and MSIA pipette tip elution, MS data collection, and data processing. Using this workflow, high-throughput IGF1 quantification of 1,054 human samples was achieved in approximately 9 hours. This rate of assaying is a significant improvement over existing MS-based IGF1 assays, and is on par with that of the enzyme-based immunoassays. Furthermore, a mutation was detected in ∼1% of the samples (SNP: rs17884626, creating an A→T substitution at position 67 of the IGF1), demonstrating the capability of IGF1 MSIA to detect point mutations and posttranslational modifications.

Indexed as

Point MutationFemaleHumansImmunoassayInsulin-Like Growth Factor IMaleSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationTime FactorsIGF1 protein, humanInsulin-Like Growth Factor I

Identifiers

PMID24664114
PMCPMC3963945
OpenAlexW2051516411

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.