The Interplay between Pathophysiological Pathways in Early-Onset Severe Preeclampsia Unveiled by Metabolomics

dc.contributor.author
Youssef, Lina
dc.contributor.author
Crovetto, Francesca
dc.contributor.author
Vasco Simoes, Rui
dc.contributor.author
Miranda, Jezid
dc.contributor.author
Paules, Cristina
dc.contributor.author
Blasco, Miquel
dc.contributor.author
Palomo, Marta
dc.contributor.author
García Calderó, Héctor
dc.contributor.author
Tura-Ceide, Olga
dc.contributor.author
Dantas, Ana Paula
dc.contributor.author
Hernandez Gea, Virginia
dc.contributor.author
Herrero, Pol
dc.contributor.author
Canela i Canela, Núria
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Campistol Plana, Josep M.
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García Pagán, Juan Carlos
dc.contributor.author
Diaz Ricart, M. Isabel
dc.contributor.author
Gratacós Freixas, Eduardo
dc.contributor.author
Crispi Brillas, Fàtima
dc.date.issued
2022-06-20T10:45:30Z
dc.date.issued
2022-06-20T10:45:30Z
dc.date.issued
2022-01-07
dc.date.issued
2022-06-20T10:45:30Z
dc.identifier
2075-1729
dc.identifier
https://hdl.handle.net/2445/186808
dc.identifier
717733
dc.identifier
9296731
dc.identifier
35054479
dc.description.abstract
Introduction: Preeclampsia is a multi-system disorder unique to pregnancy responsible for a great part of maternal and perinatal morbidity and mortality. The precise pathogenesis of this complex disorder is still unrevealed. Methods: We examined the pathophysiological pathways involved in early-onset preeclampsia, a specific subgroup representing its most severe presentation, using LC-MS/MS metabolomic analysis based on multi-level extraction of lipids and small metabolites from maternal blood samples, collected at the time of diagnosis from 14 preeclamptic and six matched healthy pregnancies. Statistical analysis comprised multivariate and univariate approaches with the application of over representation analysis to identify differential pathways. Results: A clear difference between preeclamptic and control pregnancies was observed in principal component analysis. Supervised multivariate analysis using orthogonal partial least square discriminant analysis provided a robust model with goodness of fit (R2X = 0.91, p = 0.002) and predictive ability (Q2Y = 0.72, p < 0.001). Finally, univariate analysis followed by 5% false discovery rate correction indicated 82 metabolites significantly altered, corresponding to six overrepresented pathways: (1) aminoacyl-tRNA biosynthesis; (2) arginine biosynthesis; (3) alanine, aspartate and glutamate metabolism; (4) D-glutamine and D-glutamate metabolism; (5) arginine and proline metabolism; and (6) histidine metabolism. Conclusion: Metabolomic analysis focusing specifically on the early-onset severe form of preeclampsia reveals the interplay between pathophysiological pathways involved in this form. Future studies are required to explore new therapeutic approaches targeting these altered metabolic pathways in early-onset preeclampsia
dc.format
21 p.
dc.format
application/pdf
dc.language
eng
dc.publisher
MDPI
dc.relation
Reproducció del document publicat a: https://doi.org/10.3390/life12010086
dc.relation
Life, 2022, vol. 12, num. 1, p. 86
dc.relation
https://doi.org/10.3390/life12010086
dc.rights
cc-by (c) Youssef, Lina et al., 2022
dc.rights
https://creativecommons.org/licenses/by/4.0/
dc.rights
info:eu-repo/semantics/openAccess
dc.source
Articles publicats en revistes (Medicina)
dc.subject
Preeclàmpsia
dc.subject
Metabolòmica
dc.subject
Creixement fetal
dc.subject
Preeclampsia
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Metabolomics
dc.subject
Fetal growth
dc.title
The Interplay between Pathophysiological Pathways in Early-Onset Severe Preeclampsia Unveiled by Metabolomics
dc.type
info:eu-repo/semantics/article
dc.type
info:eu-repo/semantics/publishedVersion


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