[Dataset] Cohort-based strategies as an in-house tool to evaluate and improve phenotyping robustness of LC-MS/MS lipidomics platforms

In recent years, instrumental improvements have enabled the spread of mass spectrometry-based lipidomics platforms in biomedical research. In mass spectrometry, the reliability of generated data varies for each compound, contingent on, among other factors, the availability of labeled internal standa...

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Detalles Bibliográficos
Autores: Zöhrer, Benedikt, Gómez, Cristina, Jaumot, Joaquim, Idborg, Helena, Torekov, Signe S., Wheelock, Åsa M., Wheelock, Craig E., Checa, Antonio
Tipo de recurso: conjunto de datos
Fecha de publicación:2024
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/383735
Acceso en línea:http://hdl.handle.net/10261/383735
https://digital.csic.es/handle/10261/363846
Access Level:acceso abierto
Palabra clave:Sphingolipids
Bioanalytical methods
LC-MS/MS
Lipidomics
http://metadata.un.org/sdg/3
http://metadata.un.org/sdg/6
Ensure healthy lives and promote well-being for all at all ages
Ensure availability and sustainable management of water and sanitation for all
Ensure sustainable consumption and production patterns
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spelling [Dataset] Cohort-based strategies as an in-house tool to evaluate and improve phenotyping robustness of LC-MS/MS lipidomics platformsZöhrer, BenediktGómez, CristinaJaumot, JoaquimIdborg, HelenaTorekov, Signe S.Wheelock, Åsa M.Wheelock, Craig E.Checa, AntonioSphingolipidsBioanalytical methodsLC-MS/MSLipidomicshttp://metadata.un.org/sdg/3http://metadata.un.org/sdg/6Ensure healthy lives and promote well-being for all at all agesEnsure availability and sustainable management of water and sanitation for allEnsure sustainable consumption and production patternsIn recent years, instrumental improvements have enabled the spread of mass spectrometry-based lipidomics platforms in biomedical research. In mass spectrometry, the reliability of generated data varies for each compound, contingent on, among other factors, the availability of labeled internal standards. It is challenging to evaluate the data for lipids without specific labeled internal standards, especially when dozens to hundreds of lipids are measured simultaneously. Thus, evaluation of the performance of these platforms at the individual lipid level in interlaboratory studies is generally not feasible in a time-effective manner. Herein, using a focused subset of sphingolipids, we present an in-house validation methodology for individual lipid reliability assessment, tailored to the statistical analysis to be applied. Moreover, this approach enables the evaluation of various methodological aspects, including discerning coelutions sharing identical selected reaction monitoring transitions, pinpointing optimal labeled internal standards and their concentrations, and evaluating different extraction techniques. While the full validation according to analytical guidelines for all lipids included in a lipidomics method is currently not possible, this process shows areas to focus on for subsequent method development iterations as well as the robustness of data generated across diverse methodologies.Open access funding provided by Karolinska Institute. CEW received support from the Swedish Heart and Lung Foundation (HLF 20230463 and HLF 20210519) and the Swedish Research Council (2022-00796). BZ is supported by the H2020 ITN consortium ArthritisHeal (#812890), the Konung Gustaf V:s 80-årsfond (FAI-2020-0732), and the Swedish Heart and Lung Foundation (HLF20230363). AW received support from the Swedish Heart and Lung Foundation (HLF 20190017) and the Swedish Research Council (2018-00520). JJ received support from the Spanish Ministry of Science and Innovation MCIU/AEI/10.13039/501100011033 and Severo Ochoa Excelencia Grant CEX2018-000794-S.Peer reviewedSpringer NatureEuropean Commission0000-0002-0674-3329Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202520252024info:eu-repo/semantics/datasethttp://purl.org/coar/resource_type/c_ddb1http://hdl.handle.net/10261/383735https://digital.csic.es/handle/10261/363846reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/EC/H2020/812890Analytical and bioanalytical chemistryCohort-based strategies as an in-house tool to evaluate and improve phenotyping robustness of LC–MS/MS lipidomics platformsSíinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/3837352026-05-22T06:33:51Z
dc.title.none.fl_str_mv [Dataset] Cohort-based strategies as an in-house tool to evaluate and improve phenotyping robustness of LC-MS/MS lipidomics platforms
title [Dataset] Cohort-based strategies as an in-house tool to evaluate and improve phenotyping robustness of LC-MS/MS lipidomics platforms
spellingShingle [Dataset] Cohort-based strategies as an in-house tool to evaluate and improve phenotyping robustness of LC-MS/MS lipidomics platforms
Zöhrer, Benedikt
Sphingolipids
Bioanalytical methods
LC-MS/MS
Lipidomics
http://metadata.un.org/sdg/3
http://metadata.un.org/sdg/6
Ensure healthy lives and promote well-being for all at all ages
Ensure availability and sustainable management of water and sanitation for all
Ensure sustainable consumption and production patterns
title_short [Dataset] Cohort-based strategies as an in-house tool to evaluate and improve phenotyping robustness of LC-MS/MS lipidomics platforms
title_full [Dataset] Cohort-based strategies as an in-house tool to evaluate and improve phenotyping robustness of LC-MS/MS lipidomics platforms
title_fullStr [Dataset] Cohort-based strategies as an in-house tool to evaluate and improve phenotyping robustness of LC-MS/MS lipidomics platforms
title_full_unstemmed [Dataset] Cohort-based strategies as an in-house tool to evaluate and improve phenotyping robustness of LC-MS/MS lipidomics platforms
title_sort [Dataset] Cohort-based strategies as an in-house tool to evaluate and improve phenotyping robustness of LC-MS/MS lipidomics platforms
dc.creator.none.fl_str_mv Zöhrer, Benedikt
Gómez, Cristina
Jaumot, Joaquim
Idborg, Helena
Torekov, Signe S.
Wheelock, Åsa M.
Wheelock, Craig E.
Checa, Antonio
author Zöhrer, Benedikt
author_facet Zöhrer, Benedikt
Gómez, Cristina
Jaumot, Joaquim
Idborg, Helena
Torekov, Signe S.
Wheelock, Åsa M.
Wheelock, Craig E.
Checa, Antonio
author_role author
author2 Gómez, Cristina
Jaumot, Joaquim
Idborg, Helena
Torekov, Signe S.
Wheelock, Åsa M.
Wheelock, Craig E.
Checa, Antonio
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv European Commission
0000-0002-0674-3329
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Sphingolipids
Bioanalytical methods
LC-MS/MS
Lipidomics
http://metadata.un.org/sdg/3
http://metadata.un.org/sdg/6
Ensure healthy lives and promote well-being for all at all ages
Ensure availability and sustainable management of water and sanitation for all
Ensure sustainable consumption and production patterns
topic Sphingolipids
Bioanalytical methods
LC-MS/MS
Lipidomics
http://metadata.un.org/sdg/3
http://metadata.un.org/sdg/6
Ensure healthy lives and promote well-being for all at all ages
Ensure availability and sustainable management of water and sanitation for all
Ensure sustainable consumption and production patterns
description In recent years, instrumental improvements have enabled the spread of mass spectrometry-based lipidomics platforms in biomedical research. In mass spectrometry, the reliability of generated data varies for each compound, contingent on, among other factors, the availability of labeled internal standards. It is challenging to evaluate the data for lipids without specific labeled internal standards, especially when dozens to hundreds of lipids are measured simultaneously. Thus, evaluation of the performance of these platforms at the individual lipid level in interlaboratory studies is generally not feasible in a time-effective manner. Herein, using a focused subset of sphingolipids, we present an in-house validation methodology for individual lipid reliability assessment, tailored to the statistical analysis to be applied. Moreover, this approach enables the evaluation of various methodological aspects, including discerning coelutions sharing identical selected reaction monitoring transitions, pinpointing optimal labeled internal standards and their concentrations, and evaluating different extraction techniques. While the full validation according to analytical guidelines for all lipids included in a lipidomics method is currently not possible, this process shows areas to focus on for subsequent method development iterations as well as the robustness of data generated across diverse methodologies.
publishDate 2024
dc.date.none.fl_str_mv 2024
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/dataset
http://purl.org/coar/resource_type/c_ddb1
format dataset
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/383735
https://digital.csic.es/handle/10261/363846
url http://hdl.handle.net/10261/383735
https://digital.csic.es/handle/10261/363846
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/EC/H2020/812890
Analytical and bioanalytical chemistry
Cohort-based strategies as an in-house tool to evaluate and improve phenotyping robustness of LC–MS/MS lipidomics platforms
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Springer Nature
publisher.none.fl_str_mv Springer Nature
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869414817071104000
score 15.811543

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