Evidence map›Paper›PMID 39075446›Full record

ArticleBMC biology2024

Hierarchical lncRNA regulatory network in early-onset severe preeclampsia.

Haihua Liu, Zhijian Wang, Yanjun Li, Qian Chen, Sijia Jiang, Yue Gao, Jing Wang, Yali Chi, Jie Liu, Xiaoli Wu and 5 more

Abstract read
In one paragraph

Article in BMC biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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. Article
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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

15 authors.

Haihua Liu *Center for Genetics and Developmental Systems Biology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Zhijian Wang *Center for Genetics and Developmental Systems Biology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Yanjun Li *Center for Genetics and Developmental Systems Biology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Qian ChenDepartment of Obstetrics & Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Sijia JiangDepartment of Obstetrics & Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Yue GaoCenter for Genetics and Developmental Systems Biology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Jing WangCenter for Genetics and Developmental Systems Biology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Yali ChiCenter for Genetics and Developmental Systems Biology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Jie LiuDepartment of Obstetrics & Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Xiaoli WuDepartment of Obstetrics & Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Qiong ChenDepartment of Obstetrics & Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Chaoqun XiaoDepartment of Obstetrics & Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Mei ZhongDepartment of Obstetrics & Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Chunlin ChenDepartment of Obstetrics & Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China. ccl1@smu.edu.cn.
Xinping YangCenter for Genetics and Developmental Systems Biology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China. xpyang1@smu.edu.cn.ORCID http://orcid.org/0000-0003-4086-4180

Funding

Basic and Applied Basic Research Foundation of Guangdong Province 2019B1515120080National Natural Science Foundation of China 31771434National Natural Science Foundation of China 81671466Natural Science Foundation of Guangdong Province 2016A030308020Science and Technology Planning Project of Guangdong Province 2017B020227010
6 · The paper itself

Abstract

backgroundRecent studies have shown that several long non-coding RNAs (lncRNAs) in the placenta are associated with preeclampsia (PE). However, the extent to which lncRNAs may contribute to the pathological progression of PE is unclear.

resultsHere, we report a hierarchical regulatory network involved in early-onset severe PE (EOSPE). We have carried out transcriptome sequencing on the placentae from patients and normal subjects to identify the differentially expressed genes (DEGs), including some lncRNAs (DElncRNAs). We then constructed a high-quality hierarchical regulatory network of lncRNAs, transcription factors (TFs), and target DEGs, containing 1851 lncRNA-TF interactions and 6901 TF-promoter interactions. The lncRNA-to-target regulatory interactions were further validated by the triplex structures between the DElncRNAs and the promoters of the target DEGs. The DElncRNAs in the regulatory network were clustered into 3 clusters, one containing DElncRNAs correlated with the blood pressure, including FLNB-AS1 with targeting 27.89% (869/3116) DEGs in EOSPE. We further demonstrated that FLNB-AS1 could bind the transcription factor JUNB to regulate a series members of the HIF-1 signaling pathway in trophoblast cells.

conclusionsOur results suggest that the differential expression of lncRNAs may perturb the lncRNA-TF-DEG hierarchical regulatory network, leading to the dysregulation of many genes involved in EOSPE. Our study provides a new strategy and a valuable resource for studying the mechanism underlying gene dysregulation in EOSPE patients.

Indexed as

Gene Regulatory NetworksPre-EclampsiaRNA, Long NoncodingFemaleHumansPlacentaPregnancyRNA, Long NoncodingFLNB-AS1Hierarchical regulatory networkHIF-1 signaling pathwayLong non-coding RNAPreeclampsia

Identifiers

PMID39075446
PMCPMC11287949

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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.