Evidence map›Paper›PMID 39591465›Full record

ArticlePloS one2024

Plasma metabolic profile reveals signatures of maternal health during gestational hypertension and preeclampsia without and with severe features.

Julyane N S Kaihara, Fabio Rogerio de Moraes, Priscila Rezeck Nunes, Marco G Alves, Ricardo C Cavalli, Ljubica Tasic, Valeria Cristina Sandrim

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Second-trimester multimetabolite panel for early preeclampsia rule-out.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2026
    Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Julyane N S KaiharaDepartment of Biophysics and Pharmacology, Institute of Biosciences of Botucatu, Sao Paulo State University (UNESP), Botucatu, SP, Brazil.ORCID 0000-0003-4881-8488
Fabio Rogerio de MoraesMultiuser Center for Biomolecular Innovation, Department of Physics, Institute of Biosciences, Languages and Exact Sciences, Sao Paulo State University (UNESP), Sao Jose do Rio Preto, SP, Brazil.
Priscila Rezeck NunesDepartment of Biophysics and Pharmacology, Institute of Biosciences of Botucatu, Sao Paulo State University (UNESP), Botucatu, SP, Brazil.ORCID 0000-0002-8041-5753
Marco G AlvesInstitute of Biomedicine and Department of Medical Science (iBiMED), University of Aveiro, Aveiro, Portugal.ORCID 0000-0001-7635-783X
Ricardo C CavalliDepartment of Gynecology and Obstetrics, Faculty of Medicine of Ribeirao Preto, University of Sao Paulo (USP), Ribeirao Preto, SP, Brazil.
Ljubica TasicDepartment of Organic Chemistry, Institute of Chemistry, State University of Campinas (UNICAMP), Campinas, SP, Brazil.ORCID 0000-0003-2930-7332
Valeria Cristina SandrimDepartment of Biophysics and Pharmacology, Institute of Biosciences of Botucatu, Sao Paulo State University (UNESP), Botucatu, SP, Brazil.ORCID 0000-0002-6168-7470

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Preeclampsia, a pregnancy-specific syndrome, poses substantial risks to maternal and neonatal health, particularly in cases with severe features. Our study focuses on evaluating the impact of low molecular weight metabolites on the intricate mechanisms and pathways involved in the pathophysiology of preeclampsia when severe features are present. We aim to pinpoint the distinct metabolomic profile in maternal plasma during pregnancies affected by hypertensive disorders and to correlate the metabolite levels with the clinical characteristics of the study cohort. A total of 173 plasma samples were collected, comprising 36 healthy pregnant women (HP), 52 patients with gestational hypertension (GH), 43 with preeclampsia without (PE-), and 42 with severe features (PE+). Nuclear magnetic resonance spectroscopy and metabolite identification were conducted to establish the metabolomic profiles. Univariate and chemometric analyses were conducted using MetaboAnalyst, and correlations were performed using GraphPad Prism. Our study unveils distinct metabolomic profiles differentiating HP women, patients featuring GH, and patients with PE-and PE+. Our analysis highlights an increase in acetate, N,N-dimethylglycine, glutamine, alanine, valine, and creatine levels in the PE+ group compared to the HP and GH groups. The PE+ group exhibited higher concentrations of N,N-dimethylglycine, glutamine, alanine, and valine compared to the PE-group. Moreover, elevated levels of specific metabolites, including N,N-dimethylglycine, alanine, and valine, were associated with increased blood pressure, worse obstetric outcomes, and poorer end-organ function, particularly renal and hepatic damage. Metabolomic analysis of PE+ individuals indicates heightened disturbances in nitrogen metabolism, methionine, and urea cycles. Additionally, the exacerbated metabolic disturbance may have disclosed renal impairment and hepatic dysfunction, evidenced by elevated levels of creatine and alanine. These findings not only contribute novel insights but also provide a more comprehensive understanding of the pathophysiological mechanisms at play in cases of PE+.

Indexed as

Hypertension, Pregnancy-InducedMetabolomePre-EclampsiaAdultCase-Control StudiesFemaleHumansMagnetic Resonance SpectroscopyMaternal HealthMetabolomicsPregnancy

Identifiers

PMID39591465
PMCPMC11594399

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.