Comprehensive and Reproducible Untargeted Lipidomic Workflow Using LC-QTOF Validated for Human Plasma Analysis

The goal of this work was to develop a label-free, comprehensive, and reproducible high-resolution liquid chromatography–mass spectrometry (LC-MS)-based untargeted lipidomic workflow using a single instrument, which could be applied to biomarker discovery in both basic and clinical studies. For this...

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Published inJournal of proteome research Vol. 17; no. 11; pp. 3657 - 3670
Main Authors Forest, Anik, Ruiz, Matthieu, Bouchard, Bertrand, Boucher, Gabrielle, Gingras, Olivier, Daneault, Caroline, Robillard Frayne, Isabelle, Rhainds, David, Tardif, Jean-Claude, Rioux, John D, Des Rosiers, Christine
Format Journal Article
LanguageEnglish
Published United States American Chemical Society 02.11.2018
Subjects
bioinformatics
biomarkers
Chromatography, Liquid - instrumentation
Chromatography, Liquid - methods
clinical trials
Computational Biology - methods
data collection
Healthy Volunteers
Humans
isomers
lipids
Lipids - blood
Lipids - chemistry
Lipids - classification
Lipids - isolation & purification
liquid chromatography
Metabolome - physiology
Molecular Sequence Annotation
Principal Component Analysis
proteome
Reproducibility of Results
tandem mass spectrometry
Tandem Mass Spectrometry - instrumentation
Tandem Mass Spectrometry - methods
coverage
annotation
lipid isomers
lipids
workflow
reproducibility
mass spectrometry
untargeted
WGCNA
lipidomics
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Summary:The goal of this work was to develop a label-free, comprehensive, and reproducible high-resolution liquid chromatography–mass spectrometry (LC-MS)-based untargeted lipidomic workflow using a single instrument, which could be applied to biomarker discovery in both basic and clinical studies. For this, we have (i) optimized lipid extraction and elution to enhance coverage of polar and nonpolar lipids as well as resolution of their isomers, (ii) ensured MS signal reproducibility and linearity, and (iii) developed a bioinformatic pipeline to correct remaining biases. Workflow validation is reported for 48 replicates of a single human plasma sample: 1124 reproducible LC-MS signals were extracted (median signal intensity RSD = 10%), 50% of which are redundant due to adducts, dimers, in-source fragmentation, contaminations, or positive and negative ion duplicates. From the resulting 578 unique compounds, 428 lipids were identified by MS/MS, including acyl chain composition, of which 394 had RSD < 30% inside their linear intensity range, thereby enabling robust semiquantitation. MS signal intensity spanned 4 orders of magnitude, covering 16 lipid subclasses. Finally, the power of our workflow is illustrated by a proof-of-concept study in which 100 samples from healthy human subjects were analyzed and the data set was investigated using three different statistical testing strategies in order to compare their capacity in identifying the impact of sex and age on circulating lipids.
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The iGenoMed Consortium
1Robert Wood Johnson Medical School (RWJMS), Rutgers University, New Brunswick, NJ, USA; 2Icahn School of Medicine at Mount Sinai, NY, NY, USA; 3University of Pittsburgh, Pittsburgh, PA, USA; 4Cedars Sinai Medical Center, Los Angeles, CA, USA; 5Institut de cardiologie de Montréal, Université de Montréal, Montreal, Qc, Canada; 6 University of Toronto, Samuel Lunenfeld Research Institute, Mount Sinai Hosphital, Toronto, ON, Canada.
At the time of the study, the principal investigators were, in alphabetical order: Alain Bitton1, Christine Des Rosiers2,3, Lawrence Joseph6, Jean Lachaine3, Sylvie Lesage3,7, Megan Levings4,5, John D. Rioux2,3, Sachdev Sidhu8, Sophie Veilleux9, Brian White-Guay3, and Ramnik Xavier2,3
At the time of the study, the principal investigators were, in alphabetical order: Steven R. Brant1, Judy Cho2, Richard H. Duerr3, Dermot B. P. McGoverm4, John D. Rioux5, and Mark S. Silverberg6
The NIDDK IBD Genetics Consortium
Author Contributions
AF and CDR contributed to the design of all experiments. AF performed the optimization of the LC-MS. BB, CRD and IRF contributed to optimization of sample preparation. OG, GB and AF created the data processing pipeline. AF with the help of CD and IRF carried out the data analysis for the workflow validation. JDR, The iGenoMed Consortium and The NIDDK IBD Genetics Consortium have contributed samples for the proof-of-concept study. AF and GB performed the data analysis of the proof of concept. AF, CDR and MR wrote the manuscript, with contributions from all authors.
1McGill University Health Centre, Montreal, Qc, Canada; 2Institut de cardiologie de Montréal, 3Université de Montréal, Montreal, Qc, Canada, 4Child & Family Research Institute, 5University of British Columbia, Vancouver, BC, Canada; 6McGill University, Montreal, Qc, Canada; 7Hôpital Maisonneuve Rosemont, 8University of Toronto, Toronto, ON, Canada; 9Université Laval, Quebec, Qc, Canada.
ISSN:1535-3893
1535-3907
1535-3907
DOI:10.1021/acs.jproteome.8b00270