Comparison of the serum whole molecular composition with the serum metabolome to acquire the pathophysiological state

Bibliographic Details
Main Author: Correia, Inês
Publication Date: 2024
Other Authors: Henrique Fonseca, Tiago Alexandre, Pataco, Jéssica, Oliveira, Mafalda, Caldeira, Viviana, Domingues, N., Von Rekowski, Cristiana, Araújo, Rúben Alexandre Dinis, Bento, Luís, Calado, Cecília
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.21/21760
Summary: Omics Sciences serve as an essential tool to advance precision medicine. Since conventional omics sciences rely on laborious, complex and time-consuming analytical processes, this study evaluated whether the serum molecular fingerprint, captured by FTIR spectroscopy, could predict mortality risk in critically ill patients. Both the whole serum and the serum metabolome (i.e., serum after removal of macromolecules) were analyzed. PCA-LDA models demonstrated strong performance in predicting patients’ pathophysiological state. A significantly more accurate model for predicting the patients’ pathophysiological state was achieved using the serum metabolome (94%) compared to the whole serum (81%). This is consistent with metabolomics, which provides a more direct view of the systems’ functionality. These promising results highlight the importance of FTIR spectroscopy analysis of the serum metabolome, offering a rapid, cost-effective, and high-throughput method for assessing patients' pathophysiological state.
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spelling Comparison of the serum whole molecular composition with the serum metabolome to acquire the pathophysiological stateBiomarkersFTIR spectroscopyMetabolomeIntensive care unitOmics Sciences serve as an essential tool to advance precision medicine. Since conventional omics sciences rely on laborious, complex and time-consuming analytical processes, this study evaluated whether the serum molecular fingerprint, captured by FTIR spectroscopy, could predict mortality risk in critically ill patients. Both the whole serum and the serum metabolome (i.e., serum after removal of macromolecules) were analyzed. PCA-LDA models demonstrated strong performance in predicting patients’ pathophysiological state. A significantly more accurate model for predicting the patients’ pathophysiological state was achieved using the serum metabolome (94%) compared to the whole serum (81%). This is consistent with metabolomics, which provides a more direct view of the systems’ functionality. These promising results highlight the importance of FTIR spectroscopy analysis of the serum metabolome, offering a rapid, cost-effective, and high-throughput method for assessing patients' pathophysiological state.EARETDomingues, NunoTomar, Rajesh SinghMahamud, TosapornRCIPLCorreia, InêsHenrique Fonseca, Tiago AlexandrePataco, JéssicaOliveira, MafaldaCaldeira, VivianaDomingues, N.Von Rekowski, CristianaAraújo, Rúben Alexandre DinisBento, LuísCalado, Cecília2025-04-07T07:18:32Z2024-122024-12-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10400.21/21760eng978-989-9121-43-010.17758/EARES19info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-04-09T02:16:19Zoai:repositorio.ipl.pt:10400.21/21760Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T06:21:25.390773Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Comparison of the serum whole molecular composition with the serum metabolome to acquire the pathophysiological state
title Comparison of the serum whole molecular composition with the serum metabolome to acquire the pathophysiological state
spellingShingle Comparison of the serum whole molecular composition with the serum metabolome to acquire the pathophysiological state
Correia, Inês
Biomarkers
FTIR spectroscopy
Metabolome
Intensive care unit
title_short Comparison of the serum whole molecular composition with the serum metabolome to acquire the pathophysiological state
title_full Comparison of the serum whole molecular composition with the serum metabolome to acquire the pathophysiological state
title_fullStr Comparison of the serum whole molecular composition with the serum metabolome to acquire the pathophysiological state
title_full_unstemmed Comparison of the serum whole molecular composition with the serum metabolome to acquire the pathophysiological state
title_sort Comparison of the serum whole molecular composition with the serum metabolome to acquire the pathophysiological state
author Correia, Inês
author_facet Correia, Inês
Henrique Fonseca, Tiago Alexandre
Pataco, Jéssica
Oliveira, Mafalda
Caldeira, Viviana
Domingues, N.
Von Rekowski, Cristiana
Araújo, Rúben Alexandre Dinis
Bento, Luís
Calado, Cecília
author_role author
author2 Henrique Fonseca, Tiago Alexandre
Pataco, Jéssica
Oliveira, Mafalda
Caldeira, Viviana
Domingues, N.
Von Rekowski, Cristiana
Araújo, Rúben Alexandre Dinis
Bento, Luís
Calado, Cecília
author2_role author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Domingues, Nuno
Tomar, Rajesh Singh
Mahamud, Tosaporn
RCIPL
dc.contributor.author.fl_str_mv Correia, Inês
Henrique Fonseca, Tiago Alexandre
Pataco, Jéssica
Oliveira, Mafalda
Caldeira, Viviana
Domingues, N.
Von Rekowski, Cristiana
Araújo, Rúben Alexandre Dinis
Bento, Luís
Calado, Cecília
dc.subject.por.fl_str_mv Biomarkers
FTIR spectroscopy
Metabolome
Intensive care unit
topic Biomarkers
FTIR spectroscopy
Metabolome
Intensive care unit
description Omics Sciences serve as an essential tool to advance precision medicine. Since conventional omics sciences rely on laborious, complex and time-consuming analytical processes, this study evaluated whether the serum molecular fingerprint, captured by FTIR spectroscopy, could predict mortality risk in critically ill patients. Both the whole serum and the serum metabolome (i.e., serum after removal of macromolecules) were analyzed. PCA-LDA models demonstrated strong performance in predicting patients’ pathophysiological state. A significantly more accurate model for predicting the patients’ pathophysiological state was achieved using the serum metabolome (94%) compared to the whole serum (81%). This is consistent with metabolomics, which provides a more direct view of the systems’ functionality. These promising results highlight the importance of FTIR spectroscopy analysis of the serum metabolome, offering a rapid, cost-effective, and high-throughput method for assessing patients' pathophysiological state.
publishDate 2024
dc.date.none.fl_str_mv 2024-12
2024-12-01T00:00:00Z
2025-04-07T07:18:32Z
dc.type.driver.fl_str_mv conference paper
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.21/21760
url http://hdl.handle.net/10400.21/21760
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 978-989-9121-43-0
10.17758/EARES19
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eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv EARET
publisher.none.fl_str_mv EARET
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collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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