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Journal article
Analytical quality control in targeted lipidomics: Evaluating the performance of commercial plasma as a surrogate for pooled study samples
Analytica chimica acta, Vol.1365, 344225
2025
Appears in Open Access via Read & Publish Agreements
Abstract
Pooled quality control (PQC) samples are the gold standard for data quality monitoring in metabolic phenotyping studies. Typically composed of equal parts from all study samples, PQCs can be challenging to generate in large cohorts or when sample volumes are low. As an alternative, externally sourced matrix-matched surrogate QCs (sQC) have been proposed. This study evaluates the performance of sQCs against PQCs for assessing analytical variation, data pre-processing, and downstream data analysis in a targeted lipidomics workflow.
Plasma samples (n = 701) from the Microbiome Understanding in Maternity Study, along with PQC (n = 80) and sQC (n = 80) samples, were analyzed using a lipidomics assay targeting 1162 lipids. QC samples were injected throughout acquisition, and data pre-processing was performed using each strategy. For simplicity, a subset (n = 381) of the study samples was used to assess differences in downstream statistical analyses.
Both QC approaches demonstrated high analytical repeatability. While PQC and sQC compositions differed, use of PQCs retained less than 4 % more lipid species during pre-processing. Univariate analysis identified more statistically significant lipids with PQC-based pre-processing, but multivariate model performance was similar between datasets.
This study provides a comprehensive comparison of QC strategies and emphasizes the importance of careful QC workflow selection. While PQCs offer advantages, sQCs serve as a suitable alternative for quality assessment and pre-processing. Their commercial availability also supports use as intra- and inter-laboratory long-term references, aiding data harmonization across studies and laboratories.
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•Comparison of two quality control workflows; pooled study and surrogate QC samples.•In-depth assessment of lipid composition, precision, and filtering.•OPLS-DA model predictive power maintained with both QC pre-processing strategies.•Surrogate QC samples are a robust alternative to a pooled QC in targeted lipidomics.
Details
- Title
- Analytical quality control in targeted lipidomics: Evaluating the performance of commercial plasma as a surrogate for pooled study samples
- Authors/Creators
- Alanah Grant-St James - Australian National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Murdoch, WA 6150, AustraliaAude-Claire Lee - Australian National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Murdoch, WA 6150, AustraliaAlex J. Lee - Murdoch University, Centre for Computational and Systems MedicineJulien Wist - Murdoch University, Centre for Computational and Systems MedicineFerdous Sohel - Murdoch University, Centre for Crop and Food InnovationKok Wai Wong - Murdoch UniversityBu B. Yeap - Fiona Stanley HospitalRuey Leng Loo - Murdoch University, Centre for Computational and Systems MedicineAmanda Henry - St George HospitalDaniella Susic - Sutherland HospitalEmad El-Omar - Sutherland HospitalJeremy K. Nicholson - University of LondonElaine Holmes - Murdoch University, Centre for Computational and Systems MedicineLuke Whiley - Murdoch University, Centre for Computational and Systems MedicineNicola Gray - Murdoch University, Centre for Computational and Systems Medicine
- Publication Details
- Analytica chimica acta, Vol.1365, 344225
- Publisher
- Elsevier B.V.
- Number of pages
- 11
- Identifiers
- 991005782832907891
- Copyright
- © 2025 The Authors.
- Murdoch Affiliation
- Centre for Crop and Food Innovation; School of Information Technology; Centre for Computational and Systems Medicine
- Language
- English
- Resource Type
- Journal article
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- Citation topics
- 2 Chemistry
- 2.211 Mass Spectrometry
- 2.211.990 Metabolomics
- Web Of Science research areas
- Chemistry, Analytical
- ESI research areas
- Chemistry