Evidence map›Paper›PMID 35489416›Full record

ArticleJournal of lipid research2022

Validation of a multiplexed and targeted lipidomics assay for accurate quantification of lipidomes.

Nanyan Rena Zhang, Nathan G Hatcher, Kim Ekroos, Komal Kedia, Monika Kandebo, Jacob N Marcus, Sean M Smith, Kevin P Bateman, Daniel S Spellman

Open access · goldAbstract read
In one paragraph

Article in Journal of lipid research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

5 citing papers in PubMed, 18 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Nanyan Rena ZhangDepartment of Discovery, Preclinical and Translational Medicine, Merck & Co., Inc., West Point, PA, USA. Electronic address: rena_zhang@merck.com.
Nathan G HatcherDepartment of Neuroscience, Merck & Co., Inc., West Point, PA, USA. Electronic address: Nathan_hatcher@merck.com.
Kim EkroosLipidomics Consulting Ltd, Esbo, Finland.
Komal KediaDepartment of Discovery, Preclinical and Translational Medicine, Merck & Co., Inc., West Point, PA, USA.
Monika KandeboDepartment of Neuroscience, Merck & Co., Inc., West Point, PA, USA.
Jacob N MarcusDepartment of Neuroscience, Merck & Co., Inc., West Point, PA, USA.
Sean M SmithDepartment of Neuroscience, Merck & Co., Inc., West Point, PA, USA.
Kevin P BatemanDepartment of Discovery, Preclinical and Translational Medicine, Merck & Co., Inc., West Point, PA, USA.
Daniel S SpellmanDepartment of Discovery, Preclinical and Translational Medicine, Merck & Co., Inc., West Point, PA, USA.
United States Military Academy · USMerck & Co., Inc., Rahway, NJ, USA (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A major challenge of lipidomics is to determine and quantify the precise content of complex lipidomes to the exact lipid molecular species. Often, multiple methods are needed to achieve sufficient lipidomic coverage to make these determinations. Multiplexed targeted assays offer a practical alternative to enable quantitative lipidomics amenable to quality control standards within a scalable platform. Herein, we developed a multiplexed normal phase liquid chromatography-hydrophilic interaction chromatography multiple reaction monitoring method that quantifies lipid molecular species across over 20 lipid classes spanning wide polarities in a single 20-min run. Analytical challenges such as in-source fragmentation, isomer separations, and concentration dynamics were addressed to ensure confidence in selectivity, quantification, and reproducibility. Utilizing multiple MS/MS product ions per lipid species not only improved the confidence of lipid identification but also enabled the determination of relative abundances of positional isomers in samples. Lipid class-based calibration curves were applied to interpolate lipid concentrations and guide sample dilution. Analytical validation was performed following FDA Bioanalytical Method Validation Guidance for Industry. We report repeatable and robust quantitation of 900 lipid species measured in NIST-SRM-1950 plasma, with over 700 lipids achieving inter-assay variability below 25%. To demonstrate proof of concept for biomarker discovery, we analyzed plasma from mice treated with a glucosylceramide synthase inhibitor, benzoxazole 1. We observed expected reductions in glucosylceramide levels in treated animals but, more notably, identified novel lipid biomarker candidates from the plasma lipidome. These data highlight the utility of this qualified lipidomic platform for enabling biological discovery.

Indexed as

LipidomicsTandem Mass SpectrometryAnimalsChromatography, LiquidLipidsMiceReproducibility of ResultsLipidsBenzoxazole 1FDA bioanalytical method validation guidance for industryglucosylceramide synthaseglycosphingolipid metabolismhydrophilic interaction chromatography (HILIC)normal phase liquid chromatography (NPLC)quantitative lipidomicsscheduled MRMtargeted lipidomicstriple quadrupole mass spectrometry

Identifiers

PMID35489416
PMCPMC9168725
OpenAlexW4225278833

What OpenQuestion holds

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LicenceCC BY
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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.