Evidence map›Paper›PMID 34859676›Full record

ArticleAnalytical chemistry2021

Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring.

Mohan Ghorasaini, Yassene Mohammed, Jerzy Adamski, Lisa Bettcher, John A Bowden, Matias Cabruja, Kévin Contrepois, Mathew Ellenberger, Bharat Gajera, Mark Haid and 22 more

Open access · bronzeAbstract read
In one paragraph

Article in Analytical chemistry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed
5.1field-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

50 citing papers in PubMed, 94 citations in OpenAlex.

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  17. Perturbation ofJournal of virology · 2025
    Article
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  19. (Pre)Clinical Metabolomics Analysis.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  20. 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

32 authors at 12 institutions in 7 countries.

Mohan GhorasainiCenter for Proteomics and Metabolomics, Leiden University Medical Center, Albinusdreef 2, Leiden 2333ZA, The Netherlands.
Yassene MohammedCenter for Proteomics and Metabolomics, Leiden University Medical Center, Albinusdreef 2, Leiden 2333ZA, The Netherlands.ORCID 0000-0003-3265-3332
Jerzy AdamskiInstitute of Experimental Genetics, German Research Center for Environmental Health, Helmholtz Zentrum München, Ingolstaedter Landstr. 1, Neuherberg 85764, Germany.ORCID 0000-0001-9259-0199
Lisa BettcherNorthwest Metabolomics Research Center, Department of Anesthesiology, University of Washington, Seattle, Washington 98109, United States.
John A BowdenDepartment of Physiological Sciences, College of Veterinary Medicine, University of Florida, 1333 Center Drive, Gainesville, Florida 32610, United States.
Matias CabrujaDepartment of Genetics, School of Medicine, Stanford University, 300 Pasteur Drive, Stanford, California 94305, United States.
Kévin ContrepoisDepartment of Genetics, School of Medicine, Stanford University, 300 Pasteur Drive, Stanford, California 94305, United States.ORCID 0000-0001-9678-5161
Mathew EllenbergerDepartment of Genetics, School of Medicine, Stanford University, 300 Pasteur Drive, Stanford, California 94305, United States.
Bharat GajeraMetabolomics Unit, Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Tukholmankatu 8, Biomedicum 2U, Helsinki 00014, Finland.
Mark HaidMetabolomics and Proteomics Core, German Research Center for Environmental Health, Helmholtz Zentrum München, Ingolstaedter Landstr. 1, Neuherberg 85764, Germany.ORCID 0000-0001-6118-1333
Daniel HornburgDepartment of Genetics, School of Medicine, Stanford University, 300 Pasteur Drive, Stanford, California 94305, United States.
Christie HunterSCIEX, 1201 Radio Rd, Redwood City, California 94065, USA.
Christina M JonesMaterial Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland 20899, United States.ORCID 0000-0001-7571-3062
Theo KleinDepartment of Clinical Chemistry, University Medical Center, Erasmus MC, Rotterdam, 3000CA, The Netherlands.ORCID 0000-0001-8061-9353
Oleg MayborodaCenter for Proteomics and Metabolomics, Leiden University Medical Center, Albinusdreef 2, Leiden 2333ZA, The Netherlands.ORCID 0000-0001-8739-9875
Mina MirzaianDepartment of Clinical Chemistry, University Medical Center, Erasmus MC, Rotterdam, 3000CA, The Netherlands.
Ruin MoaddelNational Institute on Aging, National Institutes of Health, Baltimore, Maryland 21224, United States.
Luigi FerrucciNational Institute on Aging, National Institutes of Health, Baltimore, Maryland 21224, United States.
Jacqueline LovettNational Institute on Aging, National Institutes of Health, Baltimore, Maryland 21224, United States.
Kenneth NazirMetabolomics Unit, Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Tukholmankatu 8, Biomedicum 2U, Helsinki 00014, Finland.
Mackenzie PearsonSCIEX, Framingham, Massachusetts 01701, United States.
Baljit K UbhiSCIEX, Framingham, Massachusetts 01701, United States.
Daniel RafteryNorthwest Metabolomics Research Center, Department of Anesthesiology, University of Washington, Seattle, Washington 98109, United States.ORCID 0000-0003-2467-8118
Fabien RiolsMetabolomics and Proteomics Core, German Research Center for Environmental Health, Helmholtz Zentrum München, Ingolstaedter Landstr. 1, Neuherberg 85764, Germany.
Rebekah SayersSCIEX, Macclesfield SK10 4TG, United Kingdom.
Eric J G SijbrandsDepartment of Internal Medicine, University Medical Center, Erasmus MC, Rotterdam 3000CA, The Netherlands.
Michael P SnyderDepartment of Genetics, School of Medicine, Stanford University, 300 Pasteur Drive, Stanford, California 94305, United States.
Baolong SuDepartment of Biological Chemistry, University of California, Los Angeles, California 90095, United States.
Vidya VelagapudiMetabolomics Unit, Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Tukholmankatu 8, Biomedicum 2U, Helsinki 00014, Finland.
Kevin J WilliamsDepartment of Biological Chemistry, University of California, Los Angeles, California 90095, United States.ORCID 0000-0001-8091-7924
Yolanda B de RijkeDepartment of Clinical Chemistry, University Medical Center, Erasmus MC, Rotterdam, 3000CA, The Netherlands.
Martin GieraCenter for Proteomics and Metabolomics, Leiden University Medical Center, Albinusdreef 2, Leiden 2333ZA, The Netherlands.ORCID 0000-0003-1684-1894
Stanford University · USErasmus MC · NLLeiden University Medical Center · NLNational Institutes of Health · USUniversity of Helsinki · FIHelmholtz Zentrum München · DEUniversity of California, Los Angeles · USUniversity of Washington · USNational Institute of Standards and Technology · USUniversity of Florida · USUniversity of Ljubljana · SIUniversity of Victoria · CA

Funding

Translational Bioimaging Core Shared ResourceP30CA015704 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Eric Collisson · 1985 to 2026
$296.4M
PreCancer Atlas of Familial Adenomatous PolyposisU2CCA233311 · NCI · STANFORD UNIVERSITY · PI SNYDER, MICHAEL P. · 2018 to 2023
$11.6M
Stanford Tissue Mapping CenterU54HG010426 · NHGRI · STANFORD UNIVERSITY · PI SNYDER, MICHAEL P. · 2018 to 2021
$5.1M
Multiplexed UPLC-MS/MS System for Advanced Target MetabolomicsS10OD021562 · OD · UNIVERSITY OF WASHINGTON · PI RAFTERY, DANIEL · 2016 to 2016
$596k
NCI NIH HHS P30 CA015704NCI NIH HHS U2C CA233311NHGRI NIH HHS U54 HG010426NIH HHS S10 OD021562
6 · The paper itself

Abstract

Modern biomarker and translational research as well as personalized health care studies rely heavily on powerful omics' technologies, including metabolomics and lipidomics. However, to translate metabolomics and lipidomics discoveries into a high-throughput clinical setting, standardization is of utmost importance. Here, we compared and benchmarked a quantitative lipidomics platform. The employed Lipidyzer platform is based on lipid class separation by means of differential mobility spectrometry with subsequent multiple reaction monitoring. Quantitation is achieved by the use of 54 deuterated internal standards and an automated informatics approach. We investigated the platform performance across nine laboratories using NIST SRM 1950-Metabolites in Frozen Human Plasma, and three NIST Candidate Reference Materials 8231-Frozen Human Plasma Suite for Metabolomics (high triglyceride, diabetic, and African-American plasma). In addition, we comparatively analyzed 59 plasma samples from individuals with familial hypercholesterolemia from a clinical cohort study. We provide evidence that the more practical methyl-tert-butyl ether extraction outperforms the classic Bligh and Dyer approach and compare our results with two previously published ring trials. In summary, we present standardized lipidomics protocols, allowing for the highly reproducible analysis of several hundred human plasma lipids, and present detailed molecular information for potentially disease relevant and ethnicity-related materials.

Indexed as

LaboratoriesLipidomicsCohort StudiesHumansReference StandardsSpectrum Analysis

Identifiers

PMID34859676
PMCPMC8674878
OpenAlexW3216809113

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.