Summary of study ST000986

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR000672. The data can be accessed directly via it's Project DOI: 10.21228/M8T68F This work is supported by NIH grant, U2C- DK119886.

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Study IDST000986
Study TitleValidating Quantitative Untargeted Lipidomics Across Nine Liquid Chromatography−High-Resolution Mass Spectrometry Platforms (part IV)
Study SummaryLiquid chromatography−mass spectrometry (LC−MS) methods are most often used for untargeted metabolomics and lipidomics. However, methods have not been standardized as accepted “best practice” documents, and reports lack harmonization with respect to quantitative data that enable interstudy comparisons. Researchers use a wide variety of high-resolution mass spectrometers under different operating conditions, and it is unclear if results would yield different biological conclusions depending on the instrument performance. To this end, we used 126 identical human plasma samples and 29 quality control samples from a nutritional intervention study. We investigated lipidomic data acquisitions across nine different MS instruments (1 single TOF, 1 Q/orbital ion trap, and 7 QTOF instruments). Sample preparations, chromatography conditions, and data processing methods were kept identical. Single-point internal standard calibrations were used to estimate absolute concentrations for 307 unique lipids identified by accurate mass, MS/MS spectral match, and retention times. Quantitative results were highly comparable between the LC−MS platforms tested. Using partial least-squares discriminant analysis (PLS-DA) to compare results between platforms, a 92% overlap for the most discriminating lipids based on variable importance in projection (VIP) scores was achieved for all lipids that were detected by at least two instrument platforms. Importantly, even the relative positions of individual samples on the PLS-DA projections were identical. The key for success in harmonizing results was to avoid ion saturation by carefully evaluating linear dynamic ranges using serial dilutions and adjusting the resuspension volume and/or injection volume before running actual study samples.
Institute
University of California, Davis
DepartmentGenome and Biomedical Sciences Facility
LaboratoryWCMC Metabolomics Core
Last NameFiehn
First NameOliver
Address1315 Genome and Biomedical Sciences Facility, 451 Health Sciences Drive, Davis, CA 95616
Emailofiehn@ucdavis.edu
Phone(530) 754-8258
Submit Date2018-06-21
PublicationsDOI: 10.1021/acs.analchem.7b03404
Raw Data AvailableYes
Raw Data File Type(s).d,.m
Analysis Type DetailLC-MS
Release Date2018-07-17
Release Version1
Oliver Fiehn Oliver Fiehn
https://dx.doi.org/10.21228/M8T68F
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Project:

Project ID:PR000672
Project DOI:doi: 10.21228/M8T68F
Project Title:Validating Quantitative Untargeted Lipidomics Across Nine Liquid Chromatography−High-Resolution Mass Spectrometry Platforms
Project Summary:Liquid chromatography−mass spectrometry (LC−MS) methods are most often used for untargeted metabolomics and lipidomics. However, methods have not been standardized as accepted “best practice” documents, and reports lack harmonization with respect to quantitative data that enable interstudy comparisons. Researchers use a wide variety of high-resolution mass spectrometers under different operating conditions, and it is unclear if results would yield different biological conclusions depending on the instrument performance. To this end, we used 126 identical human plasma samples and 29 quality control samples from a nutritional intervention study. We investigated lipidomic data acquisitions across nine different MS instruments (1 single TOF, 1 Q/orbital ion trap, and 7 QTOF instruments). Sample preparations, chromatography conditions, and data processing methods were kept identical. Single-point internal standard calibrations were used to estimate absolute concentrations for 307 unique lipids identified by accurate mass, MS/MS spectral match, and retention times. Quantitative results were highly comparable between the LC−MS platforms tested. Using partial least-squares discriminant analysis (PLS-DA) to compare results between platforms, a 92% overlap for the most discriminating lipids based on variable importance in projection (VIP) scores was achieved for all lipids that were detected by at least two instrument platforms. Importantly, even the relative positions of individual samples on the PLS-DA projections were identical. The key for success in harmonizing results was to avoid ion saturation by carefully evaluating linear dynamic ranges using serial dilutions and adjusting the resuspension volume and/or injection volume before running actual study samples.
Institute:University of California, Davis
Department:Genome and Biomedical Sciences Facility
Laboratory:WCMC Metabolomics Core
Last Name:Fiehn
First Name:Oliver
Address:1315 Genome and Biomedical Sciences Facility, 451 Health Sciences Drive, Davis, CA 95616
Email:ofiehn@ucdavis.edu
Phone:5307548258
Publications:DOI: 10.1021/acs.analchem.7b03404
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