TY - JOUR

T1 - Multi-omics to predict changes during cold pressor test

AU - Kogelman, Lisette J.A.

AU - Ernst, Madeleine

AU - Falkenberg, Katrine

AU - Mazzoni, Gianluca

AU - Courraud, Julie

AU - Lundgren, Li Peng

AU - Laursen, Susan Svane

AU - Cohen, Arieh

AU - Olesen, Jes

AU - Hansen, Thomas Folkmann

N1 - Publisher Copyright: © 2022, The Author(s).

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

KW - Cold pressor test

KW - Data integration

KW - Metabolomics

KW - Multi-omics

KW - PCA

KW - PLS

KW - Systems biology

KW - Transcriptomics

U2 - 10.1186/s12864-022-08981-z

DO - 10.1186/s12864-022-08981-z

M3 - Journal article

C2 - 36402977

AN - SCOPUS:85142263302

VL - 23

JO - BMC Genomics

JF - BMC Genomics

SN - 1471-2164

M1 - 759

ER -