Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring

Mohan Ghorasaini; Yassene Mohammed; Jerzy Adamski; Lisa Bettcher; John A. Bowden; Matias Cabruja; Kévin Contrepois; Mathew Ellenberger; Bharat Gajera; Mark Haid; Daniel Hornburg; Christie Hunter; Christina M. Jones; Theo Klein; Oleg Mayboroda; Mina Mirzaian; Ruin Moaddel; Luigi Ferrucci; Jacqueline Lovett; Kenneth Nazir; Mackenzie Pearson; Baljit K. Ubhi; Daniel Raftery; Fabien Riols; Rebekah Sayers; Eric J.G. Sijbrands; Michael P. Snyder; Baolong Su; Vidya Velagapudi; Kevin J. Williams; Yolanda B. De Rijke; Martin Giera

doi:10.1021/acs.analchem.1c02826

Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring

Mohan Ghorasaini, Yassene Mohammed, Jerzy Adamski, Lisa Bettcher, John A. Bowden, Matias Cabruja, Kévin Contrepois, Mathew Ellenberger, Bharat Gajera, Mark Haid, Daniel Hornburg, Christie Hunter, Christina M. Jones, Theo Klein, Oleg Mayboroda, Mina Mirzaian, Ruin Moaddel, Luigi Ferrucci, Jacqueline Lovett, Kenneth NazirMackenzie Pearson, Baljit K. Ubhi, Daniel Raftery, Fabien Riols, Rebekah Sayers, Eric J.G. Sijbrands, Michael P. Snyder, Baolong Su, Vidya Velagapudi, Kevin J. Williams, Yolanda B. De Rijke, Martin Giera^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

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Abstract

Modern biomarker and translational research as well as personalized health care studies rely heavily on powerful omics' technologies, including metabolomics and lipidomics. However, to translate metabolomics and lipidomics discoveries into a high-throughput clinical setting, standardization is of utmost importance. Here, we compared and benchmarked a quantitative lipidomics platform. The employed Lipidyzer platform is based on lipid class separation by means of differential mobility spectrometry with subsequent multiple reaction monitoring. Quantitation is achieved by the use of 54 deuterated internal standards and an automated informatics approach. We investigated the platform performance across nine laboratories using NIST SRM 1950-Metabolites in Frozen Human Plasma, and three NIST Candidate Reference Materials 8231-Frozen Human Plasma Suite for Metabolomics (high triglyceride, diabetic, and African-American plasma). In addition, we comparatively analyzed 59 plasma samples from individuals with familial hypercholesterolemia from a clinical cohort study. We provide evidence that the more practical methyl-tert-butyl ether extraction outperforms the classic Bligh and Dyer approach and compare our results with two previously published ring trials. In summary, we present standardized lipidomics protocols, allowing for the highly reproducible analysis of several hundred human plasma lipids, and present detailed molecular information for potentially disease relevant and ethnicity-related materials.

Original language	English
Pages (from-to)	16369-16378
Number of pages	10
Journal	Analytical Chemistry
Volume	93
Issue number	49
DOIs	https://doi.org/10.1021/acs.analchem.1c02826
Publication status	Published - 14 Dec 2021

Bibliographical note

Funding Information:
The authors would like to acknowledge Tracy Schock, Dan Bearden, and Yamil Simón-Manso for their help with material design and procurement. Niek Blomberg is acknowledged for assistance with Lipidyzer analysis. Part of the TOC graphic was created with BioRender.com . D.R. thanks the NIH (grants P30CA015704 and S10OD021562) for financial support. Mohan Ghorasaini (M.G.) is an early-stage researcher supported by the H2020 ITN consortium ArthritisHeal (#812890). Martin Giera (M.G.) was partially supported by the NWO XOmics project #184.034.019. This research was supported in part by the Intramural Research Program of the National Institute on Aging, NIH. This research was supported in part by NIH grants 5U54HG010426-03 (M.P.S.) and 1U2CCA233311-01 (M.P.S.). The FIMM Metabolomics Unit was supported by HiLIFE and Biocenter Finland.

Publisher Copyright:
© 2021 The Authors. Published by American Chemical Society.

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Ghorasaini, M., Mohammed, Y., Adamski, J., Bettcher, L., Bowden, J. A., Cabruja, M., Contrepois, K., Ellenberger, M., Gajera, B., Haid, M., Hornburg, D., Hunter, C., Jones, C. M., Klein, T., Mayboroda, O., Mirzaian, M., Moaddel, R., Ferrucci, L., Lovett, J., ... Giera, M. (2021). Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring. Analytical Chemistry, 93(49), 16369-16378. https://doi.org/10.1021/acs.analchem.1c02826

@article{11c2337b866b4653acea8bea4d06d1b4,

title = "Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring",

abstract = "Modern biomarker and translational research as well as personalized health care studies rely heavily on powerful omics' technologies, including metabolomics and lipidomics. However, to translate metabolomics and lipidomics discoveries into a high-throughput clinical setting, standardization is of utmost importance. Here, we compared and benchmarked a quantitative lipidomics platform. The employed Lipidyzer platform is based on lipid class separation by means of differential mobility spectrometry with subsequent multiple reaction monitoring. Quantitation is achieved by the use of 54 deuterated internal standards and an automated informatics approach. We investigated the platform performance across nine laboratories using NIST SRM 1950-Metabolites in Frozen Human Plasma, and three NIST Candidate Reference Materials 8231-Frozen Human Plasma Suite for Metabolomics (high triglyceride, diabetic, and African-American plasma). In addition, we comparatively analyzed 59 plasma samples from individuals with familial hypercholesterolemia from a clinical cohort study. We provide evidence that the more practical methyl-tert-butyl ether extraction outperforms the classic Bligh and Dyer approach and compare our results with two previously published ring trials. In summary, we present standardized lipidomics protocols, allowing for the highly reproducible analysis of several hundred human plasma lipids, and present detailed molecular information for potentially disease relevant and ethnicity-related materials. ",

author = "Mohan Ghorasaini and Yassene Mohammed and Jerzy Adamski and Lisa Bettcher and Bowden, {John A.} and Matias Cabruja and K{\'e}vin Contrepois and Mathew Ellenberger and Bharat Gajera and Mark Haid and Daniel Hornburg and Christie Hunter and Jones, {Christina M.} and Theo Klein and Oleg Mayboroda and Mina Mirzaian and Ruin Moaddel and Luigi Ferrucci and Jacqueline Lovett and Kenneth Nazir and Mackenzie Pearson and Ubhi, {Baljit K.} and Daniel Raftery and Fabien Riols and Rebekah Sayers and Sijbrands, {Eric J.G.} and Snyder, {Michael P.} and Baolong Su and Vidya Velagapudi and Williams, {Kevin J.} and {De Rijke}, {Yolanda B.} and Martin Giera",

note = "Funding Information: The authors would like to acknowledge Tracy Schock, Dan Bearden, and Yamil Sim{\'o}n-Manso for their help with material design and procurement. Niek Blomberg is acknowledged for assistance with Lipidyzer analysis. Part of the TOC graphic was created with BioRender.com . D.R. thanks the NIH (grants P30CA015704 and S10OD021562) for financial support. Mohan Ghorasaini (M.G.) is an early-stage researcher supported by the H2020 ITN consortium ArthritisHeal (#812890). Martin Giera (M.G.) was partially supported by the NWO XOmics project #184.034.019. This research was supported in part by the Intramural Research Program of the National Institute on Aging, NIH. This research was supported in part by NIH grants 5U54HG010426-03 (M.P.S.) and 1U2CCA233311-01 (M.P.S.). The FIMM Metabolomics Unit was supported by HiLIFE and Biocenter Finland. Publisher Copyright: {\textcopyright} 2021 The Authors. Published by American Chemical Society.",

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language = "English",

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Ghorasaini, M, Mohammed, Y, Adamski, J, Bettcher, L, Bowden, JA, Cabruja, M, Contrepois, K, Ellenberger, M, Gajera, B, Haid, M, Hornburg, D, Hunter, C, Jones, CM, Klein, T, Mayboroda, O, Mirzaian, M, Moaddel, R, Ferrucci, L, Lovett, J, Nazir, K, Pearson, M, Ubhi, BK, Raftery, D, Riols, F, Sayers, R, Sijbrands, EJG, Snyder, MP, Su, B, Velagapudi, V, Williams, KJ, De Rijke, YB & Giera, M 2021, 'Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring', Analytical Chemistry, vol. 93, no. 49, pp. 16369-16378. https://doi.org/10.1021/acs.analchem.1c02826

TY - JOUR

T1 - Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring

AU - Ghorasaini, Mohan

AU - Mohammed, Yassene

AU - Adamski, Jerzy

AU - Bettcher, Lisa

AU - Bowden, John A.

AU - Cabruja, Matias

AU - Contrepois, Kévin

AU - Ellenberger, Mathew

AU - Gajera, Bharat

AU - Haid, Mark

AU - Hornburg, Daniel

AU - Hunter, Christie

AU - Jones, Christina M.

AU - Klein, Theo

AU - Mayboroda, Oleg

AU - Mirzaian, Mina

AU - Moaddel, Ruin

AU - Ferrucci, Luigi

AU - Lovett, Jacqueline

AU - Nazir, Kenneth

AU - Pearson, Mackenzie

AU - Ubhi, Baljit K.

AU - Raftery, Daniel

AU - Riols, Fabien

AU - Sayers, Rebekah

AU - Sijbrands, Eric J.G.

AU - Snyder, Michael P.

AU - Su, Baolong

AU - Velagapudi, Vidya

AU - Williams, Kevin J.

AU - De Rijke, Yolanda B.

AU - Giera, Martin

N1 - Funding Information: The authors would like to acknowledge Tracy Schock, Dan Bearden, and Yamil Simón-Manso for their help with material design and procurement. Niek Blomberg is acknowledged for assistance with Lipidyzer analysis. Part of the TOC graphic was created with BioRender.com . D.R. thanks the NIH (grants P30CA015704 and S10OD021562) for financial support. Mohan Ghorasaini (M.G.) is an early-stage researcher supported by the H2020 ITN consortium ArthritisHeal (#812890). Martin Giera (M.G.) was partially supported by the NWO XOmics project #184.034.019. This research was supported in part by the Intramural Research Program of the National Institute on Aging, NIH. This research was supported in part by NIH grants 5U54HG010426-03 (M.P.S.) and 1U2CCA233311-01 (M.P.S.). The FIMM Metabolomics Unit was supported by HiLIFE and Biocenter Finland. Publisher Copyright: © 2021 The Authors. Published by American Chemical Society.

PY - 2021/12/14

Y1 - 2021/12/14

N2 - Modern biomarker and translational research as well as personalized health care studies rely heavily on powerful omics' technologies, including metabolomics and lipidomics. However, to translate metabolomics and lipidomics discoveries into a high-throughput clinical setting, standardization is of utmost importance. Here, we compared and benchmarked a quantitative lipidomics platform. The employed Lipidyzer platform is based on lipid class separation by means of differential mobility spectrometry with subsequent multiple reaction monitoring. Quantitation is achieved by the use of 54 deuterated internal standards and an automated informatics approach. We investigated the platform performance across nine laboratories using NIST SRM 1950-Metabolites in Frozen Human Plasma, and three NIST Candidate Reference Materials 8231-Frozen Human Plasma Suite for Metabolomics (high triglyceride, diabetic, and African-American plasma). In addition, we comparatively analyzed 59 plasma samples from individuals with familial hypercholesterolemia from a clinical cohort study. We provide evidence that the more practical methyl-tert-butyl ether extraction outperforms the classic Bligh and Dyer approach and compare our results with two previously published ring trials. In summary, we present standardized lipidomics protocols, allowing for the highly reproducible analysis of several hundred human plasma lipids, and present detailed molecular information for potentially disease relevant and ethnicity-related materials.

AB - Modern biomarker and translational research as well as personalized health care studies rely heavily on powerful omics' technologies, including metabolomics and lipidomics. However, to translate metabolomics and lipidomics discoveries into a high-throughput clinical setting, standardization is of utmost importance. Here, we compared and benchmarked a quantitative lipidomics platform. The employed Lipidyzer platform is based on lipid class separation by means of differential mobility spectrometry with subsequent multiple reaction monitoring. Quantitation is achieved by the use of 54 deuterated internal standards and an automated informatics approach. We investigated the platform performance across nine laboratories using NIST SRM 1950-Metabolites in Frozen Human Plasma, and three NIST Candidate Reference Materials 8231-Frozen Human Plasma Suite for Metabolomics (high triglyceride, diabetic, and African-American plasma). In addition, we comparatively analyzed 59 plasma samples from individuals with familial hypercholesterolemia from a clinical cohort study. We provide evidence that the more practical methyl-tert-butyl ether extraction outperforms the classic Bligh and Dyer approach and compare our results with two previously published ring trials. In summary, we present standardized lipidomics protocols, allowing for the highly reproducible analysis of several hundred human plasma lipids, and present detailed molecular information for potentially disease relevant and ethnicity-related materials.

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U2 - 10.1021/acs.analchem.1c02826

DO - 10.1021/acs.analchem.1c02826

M3 - Article

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SN - 0003-2700

VL - 93

SP - 16369

EP - 16378

JO - Analytical Chemistry

JF - Analytical Chemistry

IS - 49

ER -

Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring

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Bibliographical note

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