Prediction of pregnancy-related hypertensive disorders using metabolomics: a systematic review

Detalhes bibliográficos
Autor(a) principal: Jussara de Souza Mayrink Novais
Data de Publicação: 2022
Outros Autores: Debora f Leite, Guilherme m Nobrega, Maria Laura Costa, Jose Guilherme Cecatti
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFMG
Texto Completo: http://hdl.handle.net/1843/60506
Resumo: Objective:To determine the accuracy of metabolomics in predicting hypertensive disorders in pregnancy.Design Systematic review of observational studies.Data sources and study eligibility criteria An electronic literature search was performed in June 2019 and February 2022. Two researchers independently selected studies published between 1998 and 2022 on metabolomic techniques applied to predict the condition; subsequently, they extracted data and performed quality assessment. Discrepancies were dealt with a third reviewer. The primary outcome was pre- eclampsia. Cohort or case–control studies were eligible when maternal samples were taken before diagnosis of the hypertensive disorder.Study appraisal and synthesis methods Data on study design, maternal characteristics, how hypertension was diagnosed, metabolomics details and metabolites, and accuracy were independently extracted by two authors.Results Among 4613 initially identified studies on metabolomics, 68 were read in full text and 32 articles were included. Studies were excluded due to duplicated data, study design or lack of identification of metabolites. Metabolomics was applied mainly in the second trimester; the most common technique was liquid- chromatography coupled to mass spectrometry. Among the 122 different metabolites found, there were 23 amino acids and 21 fatty acids. Most of the metabolites were involved with ammonia recycling; amino acid metabolism; arachidonic acid metabolism; lipid transport, metabolism and peroxidation; fatty acid metabolism; cell signalling; galactose metabolism; nucleotide sugars metabolism; lactose degradation; and glycerolipid metabolism. Only citrate was a common metabolite for prediction of early onset and late- onset pre- eclampsia. Vitamin D was the only metabolite in common for pre- eclampsia and gestational hypertension prediction. Meta- analysis was not performed due to lack of appropriate standardised data.Conclusions and implications: Metabolite signatures may contribute to further insights into the pathogenesis of pre- eclampsia and support screening tests. Nevertheless, it is mandatory to validate such methods in larger studies with a heterogeneous population to ascertain the potential for their use in clinical practice.
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spelling 2023-11-06T20:15:41Z2023-11-06T20:15:41Z202212e05469711910.1136/bmjopen-2021-05469720446055http://hdl.handle.net/1843/60506Objective:To determine the accuracy of metabolomics in predicting hypertensive disorders in pregnancy.Design Systematic review of observational studies.Data sources and study eligibility criteria An electronic literature search was performed in June 2019 and February 2022. Two researchers independently selected studies published between 1998 and 2022 on metabolomic techniques applied to predict the condition; subsequently, they extracted data and performed quality assessment. Discrepancies were dealt with a third reviewer. The primary outcome was pre- eclampsia. Cohort or case–control studies were eligible when maternal samples were taken before diagnosis of the hypertensive disorder.Study appraisal and synthesis methods Data on study design, maternal characteristics, how hypertension was diagnosed, metabolomics details and metabolites, and accuracy were independently extracted by two authors.Results Among 4613 initially identified studies on metabolomics, 68 were read in full text and 32 articles were included. Studies were excluded due to duplicated data, study design or lack of identification of metabolites. Metabolomics was applied mainly in the second trimester; the most common technique was liquid- chromatography coupled to mass spectrometry. Among the 122 different metabolites found, there were 23 amino acids and 21 fatty acids. Most of the metabolites were involved with ammonia recycling; amino acid metabolism; arachidonic acid metabolism; lipid transport, metabolism and peroxidation; fatty acid metabolism; cell signalling; galactose metabolism; nucleotide sugars metabolism; lactose degradation; and glycerolipid metabolism. Only citrate was a common metabolite for prediction of early onset and late- onset pre- eclampsia. Vitamin D was the only metabolite in common for pre- eclampsia and gestational hypertension prediction. Meta- analysis was not performed due to lack of appropriate standardised data.Conclusions and implications: Metabolite signatures may contribute to further insights into the pathogenesis of pre- eclampsia and support screening tests. Nevertheless, it is mandatory to validate such methods in larger studies with a heterogeneous population to ascertain the potential for their use in clinical practice.engUniversidade Federal de Minas GeraisUFMGBrasilMED - DEPARTAMENTO DE GINECOLOGIA OBSTETRÍCIABMJ OpenPregnancyHypertensionMetabolomicsPregnancyhypertensionMetabolomicsPrediction of pregnancy-related hypertensive disorders using metabolomics: a systematic reviewinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttps://pubmed.ncbi.nlm.nih.gov/35470187/Jussara de Souza Mayrink NovaisDebora f LeiteGuilherme m NobregaMaria Laura CostaJose Guilherme Cecattiapplication/pdfinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGLICENSELicense.txtLicense.txttext/plain; charset=utf-82042https://repositorio.ufmg.br/bitstream/1843/60506/1/License.txtfa505098d172de0bc8864fc1287ffe22MD51ORIGINALPrediction of pregnancy-related pdfa.pdfPrediction of pregnancy-related pdfa.pdfapplication/pdf1021957https://repositorio.ufmg.br/bitstream/1843/60506/2/Prediction%20of%20pregnancy-related%20pdfa.pdf8cc2231a54199a823a4146d065eb155eMD521843/605062023-11-06 20:43:28.898oai:repositorio.ufmg.br:1843/60506Repositório de PublicaçõesPUBhttps://repositorio.ufmg.br/oaiopendoar:2023-11-06T23:43:28Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false
dc.title.pt_BR.fl_str_mv Prediction of pregnancy-related hypertensive disorders using metabolomics: a systematic review
title Prediction of pregnancy-related hypertensive disorders using metabolomics: a systematic review
spellingShingle Prediction of pregnancy-related hypertensive disorders using metabolomics: a systematic review
Jussara de Souza Mayrink Novais
Pregnancy
hypertension
Metabolomics
Pregnancy
Hypertension
Metabolomics
title_short Prediction of pregnancy-related hypertensive disorders using metabolomics: a systematic review
title_full Prediction of pregnancy-related hypertensive disorders using metabolomics: a systematic review
title_fullStr Prediction of pregnancy-related hypertensive disorders using metabolomics: a systematic review
title_full_unstemmed Prediction of pregnancy-related hypertensive disorders using metabolomics: a systematic review
title_sort Prediction of pregnancy-related hypertensive disorders using metabolomics: a systematic review
author Jussara de Souza Mayrink Novais
author_facet Jussara de Souza Mayrink Novais
Debora f Leite
Guilherme m Nobrega
Maria Laura Costa
Jose Guilherme Cecatti
author_role author
author2 Debora f Leite
Guilherme m Nobrega
Maria Laura Costa
Jose Guilherme Cecatti
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Jussara de Souza Mayrink Novais
Debora f Leite
Guilherme m Nobrega
Maria Laura Costa
Jose Guilherme Cecatti
dc.subject.por.fl_str_mv Pregnancy
hypertension
Metabolomics
topic Pregnancy
hypertension
Metabolomics
Pregnancy
Hypertension
Metabolomics
dc.subject.other.pt_BR.fl_str_mv Pregnancy
Hypertension
Metabolomics
description Objective:To determine the accuracy of metabolomics in predicting hypertensive disorders in pregnancy.Design Systematic review of observational studies.Data sources and study eligibility criteria An electronic literature search was performed in June 2019 and February 2022. Two researchers independently selected studies published between 1998 and 2022 on metabolomic techniques applied to predict the condition; subsequently, they extracted data and performed quality assessment. Discrepancies were dealt with a third reviewer. The primary outcome was pre- eclampsia. Cohort or case–control studies were eligible when maternal samples were taken before diagnosis of the hypertensive disorder.Study appraisal and synthesis methods Data on study design, maternal characteristics, how hypertension was diagnosed, metabolomics details and metabolites, and accuracy were independently extracted by two authors.Results Among 4613 initially identified studies on metabolomics, 68 were read in full text and 32 articles were included. Studies were excluded due to duplicated data, study design or lack of identification of metabolites. Metabolomics was applied mainly in the second trimester; the most common technique was liquid- chromatography coupled to mass spectrometry. Among the 122 different metabolites found, there were 23 amino acids and 21 fatty acids. Most of the metabolites were involved with ammonia recycling; amino acid metabolism; arachidonic acid metabolism; lipid transport, metabolism and peroxidation; fatty acid metabolism; cell signalling; galactose metabolism; nucleotide sugars metabolism; lactose degradation; and glycerolipid metabolism. Only citrate was a common metabolite for prediction of early onset and late- onset pre- eclampsia. Vitamin D was the only metabolite in common for pre- eclampsia and gestational hypertension prediction. Meta- analysis was not performed due to lack of appropriate standardised data.Conclusions and implications: Metabolite signatures may contribute to further insights into the pathogenesis of pre- eclampsia and support screening tests. Nevertheless, it is mandatory to validate such methods in larger studies with a heterogeneous population to ascertain the potential for their use in clinical practice.
publishDate 2022
dc.date.issued.fl_str_mv 2022
dc.date.accessioned.fl_str_mv 2023-11-06T20:15:41Z
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dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv MED - DEPARTAMENTO DE GINECOLOGIA OBSTETRÍCIA
publisher.none.fl_str_mv Universidade Federal de Minas Gerais
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