Evidence map›Paper›PMID 38718074›Full record

ArticlePloS one2024

Identification of hub glutamine metabolism-associated genes and immune characteristics in pre-eclampsia.

Yan Mao, Xinye Li, Rui Ren, Yue Yuan, Li Wang, Xuehong Zhang

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 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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

  1. Pooled it
  2. Cellular and Molecular Network Characteristics ofInternational journal of molecular sciences · 2024
    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

6 authors.

Yan MaoFirst School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China.ORCID 0009-0003-2059-5160
Xinye LiDepartment of Gynecology and Obstetrics, General Hospital of Lanzhou Petrochemical Corporation, Lanzhou, Gansu, China.
Rui RenFirst School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China.
Yue YuanFirst School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China.
Li WangDepartment of Gynecology and Obstetrics, Gansu Provincial Hospital, Lanzhou, Gansu, China.
Xuehong ZhangGansu Key Laboratory for Reproductive Medicine and Embryology, The First Hospital of Lanzhou University, Lanzhou, Gansu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivePreeclampsia (PE) is a severe complication of unclear pathogenesis associated with pregnancy. This research aimed to elucidate the properties of immune cell infiltration and potential biomarkers of PE based on bioinformatics analysis. MATERIALS AND

methodsTwo PE datasets were imported from the Gene ExpressioOmnibus (GEO) and screened to identify differentially expressed genes (DEGs). Significant module genes were identified by weighted gene co-expression network analysis (WGCNA). DEGs that interacted with key module genes (GLu-DEGs) were analyzed further by Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses. The diagnostic value of the genes was assessed using receiver operating characteristic (ROC) curves and protein-protein interaction (PPI) networks were constructed using GeneMANIA, and GSVA analysis was performed using the MSigDB database. Immune cell infiltration was analyzed using the TISIDB database, and StarBase and Cytoscape were used to construct an RBP-mRNA network. The identified hub genes were validated in two independent datasets. For further confirmation, placental tissue from healthy pregnant women and women with PE were collected and analyzed using both RT-qPCR and immunohistochemistry.

resultsA total of seven GLu-DEGs were obtained and were found to be involved in pathways associated with the transport of sulfur compounds, PPAR signaling, and energy metabolism, shown by GO and KEGG analyses. GSVA indicated significant increases in adipocytokine signaling. Furthermore, single-sample Gene Set Enrichment Analysis (ssGSEA) indicated that the levels of activated B cells and T follicular helper cells were significantly increased in the PE group and were negatively correlated with GLu-DEGs, suggesting their potential importance.

conclusionIn summary, the results showed a correlation between glutamine metabolism and immune cells, providing new insights into the understandingPE pathogenesis and furnishing evidence for future advances in the treatment of this disease.

Indexed as

Gene Regulatory NetworksGlutaminePre-EclampsiaProtein Interaction MapsAdultComputational BiologyFemaleGene Expression ProfilingGene OntologyHumansPlacentaPregnancyGlutamine

Identifiers

PMID38718074
PMCPMC11078374

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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.