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Multi-omics to predict changes during cold pressor test
BACKGROUND: The cold pressor test (CPT) is a widely used pain provocation test to investigate both pain tolerance and cardiovascular responses. We hypothesize, that performing multi-omic analyses during CPT gives the opportunity to home in on molecular mechanisms involved. Twenty-two females were ph...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9675059/ https://www.ncbi.nlm.nih.gov/pubmed/36402977 http://dx.doi.org/10.1186/s12864-022-08981-z |
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author | Kogelman, Lisette J. A. Ernst, Madeleine Falkenberg, Katrine Mazzoni, Gianluca Courraud, Julie Lundgren, Li Peng Laursen, Susan Svane Cohen, Arieh Olesen, Jes Hansen, Thomas Folkmann |
author_facet | Kogelman, Lisette J. A. Ernst, Madeleine Falkenberg, Katrine Mazzoni, Gianluca Courraud, Julie Lundgren, Li Peng Laursen, Susan Svane Cohen, Arieh Olesen, Jes Hansen, Thomas Folkmann |
author_sort | Kogelman, Lisette J. A. |
collection | PubMed |
description | BACKGROUND: The cold pressor test (CPT) is a widely used pain provocation test to investigate both pain tolerance and cardiovascular responses. We hypothesize, that performing multi-omic analyses during CPT gives the opportunity to home in on molecular mechanisms involved. Twenty-two females were phenotypically assessed before and after a CPT, and blood samples were taken. RNA-Sequencing, steroid profiling and untargeted metabolomics were performed. Each ‘omic level was analyzed separately at both single-feature and systems-level (principal component [PCA] and partial least squares [PLS] regression analysis) and all ‘omic levels were combined using an integrative multi-omics approach, all using the paired-sample design. RESULTS: We showed that PCA was not able to discriminate time points, while PLS did significantly distinguish time points using metabolomics and/or transcriptomic data, but not using conventional physiological measures. Transcriptomic and metabolomic data revealed at feature-, systems- and integrative- level biologically relevant processes involved during CPT, e.g. lipid metabolism and stress response. CONCLUSION: Multi-omics strategies have a great potential in pain research, both at feature- and systems- level. Therefore, they should be exploited in intervention studies, such as pain provocation tests, to gain knowledge on the biological mechanisms involved in complex traits. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-022-08981-z. |
format | Online Article Text |
id | pubmed-9675059 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-96750592022-11-20 Multi-omics to predict changes during cold pressor test Kogelman, Lisette J. A. Ernst, Madeleine Falkenberg, Katrine Mazzoni, Gianluca Courraud, Julie Lundgren, Li Peng Laursen, Susan Svane Cohen, Arieh Olesen, Jes Hansen, Thomas Folkmann BMC Genomics Research BACKGROUND: The cold pressor test (CPT) is a widely used pain provocation test to investigate both pain tolerance and cardiovascular responses. We hypothesize, that performing multi-omic analyses during CPT gives the opportunity to home in on molecular mechanisms involved. Twenty-two females were phenotypically assessed before and after a CPT, and blood samples were taken. RNA-Sequencing, steroid profiling and untargeted metabolomics were performed. Each ‘omic level was analyzed separately at both single-feature and systems-level (principal component [PCA] and partial least squares [PLS] regression analysis) and all ‘omic levels were combined using an integrative multi-omics approach, all using the paired-sample design. RESULTS: We showed that PCA was not able to discriminate time points, while PLS did significantly distinguish time points using metabolomics and/or transcriptomic data, but not using conventional physiological measures. Transcriptomic and metabolomic data revealed at feature-, systems- and integrative- level biologically relevant processes involved during CPT, e.g. lipid metabolism and stress response. CONCLUSION: Multi-omics strategies have a great potential in pain research, both at feature- and systems- level. Therefore, they should be exploited in intervention studies, such as pain provocation tests, to gain knowledge on the biological mechanisms involved in complex traits. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-022-08981-z. BioMed Central 2022-11-19 /pmc/articles/PMC9675059/ /pubmed/36402977 http://dx.doi.org/10.1186/s12864-022-08981-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Kogelman, Lisette J. A. Ernst, Madeleine Falkenberg, Katrine Mazzoni, Gianluca Courraud, Julie Lundgren, Li Peng Laursen, Susan Svane Cohen, Arieh Olesen, Jes Hansen, Thomas Folkmann Multi-omics to predict changes during cold pressor test |
title | Multi-omics to predict changes during cold pressor test |
title_full | Multi-omics to predict changes during cold pressor test |
title_fullStr | Multi-omics to predict changes during cold pressor test |
title_full_unstemmed | Multi-omics to predict changes during cold pressor test |
title_short | Multi-omics to predict changes during cold pressor test |
title_sort | multi-omics to predict changes during cold pressor test |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9675059/ https://www.ncbi.nlm.nih.gov/pubmed/36402977 http://dx.doi.org/10.1186/s12864-022-08981-z |
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