Evidence map›Paper›PMID 38041082›Full record

ArticleBMC medical genomics2023

Integrated analysis of microRNA and mRNA expression profiles in Preeclampsia.

Zepeng Ping, Ying Feng, Ying Lu, Ling Ai, Huling Jiang

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.8field-weighted citation impact, top 14% of its field
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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Machine learning: a new era for cardiovascular pregnancy physiology and cardio-obstetrics research.American journal of physiology. Heart and circulatory physiology · 2024
    Review
  5. Circulating miRNAs and Preeclampsia: From Implantation to Epigenetics.International journal of molecular sciences · 2024
    Review
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

5 authors at 2 institutions in 1 country.

Zepeng Ping *Department of Obstetrics, Maternity and Child Health Care Affiliated Hospital, Jiaxing University, 2468 Central South Road, Jiaxing, 314000, China.
Ying Feng *Department of Obstetrics, Maternity and Child Health Care Affiliated Hospital, Jiaxing University, 2468 Central South Road, Jiaxing, 314000, China.
Ying LuDepartment of Obstetrics, Maternity and Child Health Care Affiliated Hospital, Jiaxing University, 2468 Central South Road, Jiaxing, 314000, China.
Ling AiDepartment of Obstetrics, Maternity and Child Health Care Affiliated Hospital, Jiaxing University, 2468 Central South Road, Jiaxing, 314000, China. ailing@zjxu.edu.cn.
Huling JiangDepartment of Obstetrics, Maternity and Child Health Care Affiliated Hospital, Jiaxing University, 2468 Central South Road, Jiaxing, 314000, China. jianghuling@zju.edu.cn.
Jiaxing University · CNFirst Hospital of Jiaxing · CN

Funding

Jiaxing Municipal Public Welfare Research Plan 2021AD30129Medical Health Science and Technology Project of Zhejiang Provincial Health Commission 2022KY389, 2022KY1261
6 · The paper itself

Abstract

backgroundPreeclampsia (PE), a pregnancy specific syndrome, is one kind of common gestational hypertension disease, which can cause maternal and perinatal mortality and morbidity. This study was conducted to identify key microRNAs (miRNAs), mRNAs and related signaling pathways in the pathogenesis of PE.

methodsWhole transcriptome sequencing and small RNA sequencing of the peripheral blood from 3 PE patients and 3 normal pregnant women were performed. Differential expressed (DE) miRNAs were identified using the DEseq2 package. Target genes of the selected upregulated and downregulated DE miRNAs were predicted. Based on the hypergeometric distribution of DE miRNA target genes, we analyzed GO enrichment and KEGG pathway enrichment using R.

resultsTotal 1291 and 1281 novel RNAs were obtained from the preeclampsia patients and healthy individuals. 70 miRNAs were screened out with significant levels with 51 significantly upregulated and 19 significantly downregulated. 44,306 genes were predicted as the targets of these miRNAs. Besides, KEGG pathway analysis revealed that the upregulated miRNAs were enriched in Glycosaminoglycan biosynthesis-chondroitin sulfate / dermatan sulfate, Base excision repair and the downregulated miRNAs were enriched in Tuberculosis, Phagosome.

conclusionWe constructed regulatory networks of miRNAs and target genes, there were 2208 negative miRNA-mRNA interactions in total. The network and pathway information illustrate the potential functions of mRNAs and miRNAs in PE pathogenesis.

Indexed as

MicroRNAsPre-EclampsiaFemaleGene Regulatory NetworksHumansPregnancyRNA, MessengerSignal TransductionMicroRNAsRNA, MessengermiRNAsmRNAsPreeclampsiaSignaling pathways

Identifiers

PMID38041082
PMCPMC10691005
OpenAlexW4389242399

What OpenQuestion holds

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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.