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Metabolites
Volume 14
Issue 6
10.3390/metabo14060313
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Article

Utilising a Clinical Metabolomics LC-MS Study to Determine the Integrity of Biological Samples for Statistical Modelling after Long Term −80 °C Storage: A TOFI_Asia Sub-Study

by
Aidan Joblin-Mills
1,2,*,
Zhanxuan E. Wu
1,2,3,
Ivana R. Sequeira-Bisson
2,4,
Jennifer L. Miles-Chan
2,4,
Sally D. Poppitt
2,4,5 and
Karl Fraser
1,2
1
Food Chemistry & Structure Team, AgResearch, Palmerston North 4410, New Zealand
2
High-Value Nutrition National Science Challenge, Auckland 1145, New Zealand
3
School of Food and Nutrition, Massey University, Palmerston North 4410, New Zealand
4
Human Nutrition Unit, School of Biological Sciences, University of Auckland, Auckland 1024, New Zealand
5
Department of Medicine, University of Auckland, Auckland 1145, New Zealand
*
Author to whom correspondence should be addressed.
Metabolites 2024, 14(6), 313; https://doi.org/10.3390/metabo14060313
Submission received: 16 April 2024 / Revised: 20 May 2024 / Accepted: 27 May 2024 / Published: 29 May 2024
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Abstract

Biological samples of lipids and metabolites degrade after extensive years in −80 °C storage. We aimed to determine if associated multivariate models are also impacted. Prior TOFI_Asia metabolomics studies from our laboratory established multivariate models of metabolic risks associated with ethnic diversity. Therefore, to compare multivariate modelling degradation after years of −80 °C storage, we selected a subset of aged (≥5-years) plasma samples from the TOFI_Asia study to re-analyze via untargeted LC-MS metabolomics. Samples from European Caucasian (n = 28) and Asian Chinese (n = 28) participants were evaluated for ethnic discrimination by partial least squares discriminative analysis (PLS–DA) of lipids and polar metabolites. Both showed a strong discernment between participants ethnicity by features, before (Initial) and after (Aged) 5-years of −80 °C storage. With receiver operator characteristic curves, sparse PLS–DA derived confusion matrix and prediction error rates, a considerable reduction in model integrity was apparent with the Aged polar metabolite model relative to Initial modelling. Ethnicity modelling with lipids maintained predictive integrity in Aged plasma samples, while equivalent polar metabolite models reduced in integrity. Our results indicate that researchers re-evaluating samples for multivariate modelling should consider time at −80 °C when producing predictive metrics from polar metabolites, more so than lipids.
Keywords: frozen; −80 °C storage; lipidomics; metabolomics; multivariate modelling; predictions; ethnicity; comparison; confusion matrices frozen; −80 °C storage; lipidomics; metabolomics; multivariate modelling; predictions; ethnicity; comparison; confusion matrices

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MDPI and ACS Style

Joblin-Mills, A.; Wu, Z.E.; Sequeira-Bisson, I.R.; Miles-Chan, J.L.; Poppitt, S.D.; Fraser, K. Utilising a Clinical Metabolomics LC-MS Study to Determine the Integrity of Biological Samples for Statistical Modelling after Long Term −80 °C Storage: A TOFI_Asia Sub-Study. Metabolites 2024, 14, 313. https://doi.org/10.3390/metabo14060313

AMA Style

Joblin-Mills A, Wu ZE, Sequeira-Bisson IR, Miles-Chan JL, Poppitt SD, Fraser K. Utilising a Clinical Metabolomics LC-MS Study to Determine the Integrity of Biological Samples for Statistical Modelling after Long Term −80 °C Storage: A TOFI_Asia Sub-Study. Metabolites. 2024; 14(6):313. https://doi.org/10.3390/metabo14060313

Chicago/Turabian Style

Joblin-Mills, Aidan, Zhanxuan E. Wu, Ivana R. Sequeira-Bisson, Jennifer L. Miles-Chan, Sally D. Poppitt, and Karl Fraser. 2024. "Utilising a Clinical Metabolomics LC-MS Study to Determine the Integrity of Biological Samples for Statistical Modelling after Long Term −80 °C Storage: A TOFI_Asia Sub-Study" Metabolites 14, no. 6: 313. https://doi.org/10.3390/metabo14060313

APA Style

Joblin-Mills, A., Wu, Z. E., Sequeira-Bisson, I. R., Miles-Chan, J. L., Poppitt, S. D., & Fraser, K. (2024). Utilising a Clinical Metabolomics LC-MS Study to Determine the Integrity of Biological Samples for Statistical Modelling after Long Term −80 °C Storage: A TOFI_Asia Sub-Study. Metabolites, 14(6), 313. https://doi.org/10.3390/metabo14060313

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