Evidence mapPaperPMID 33224973Full record

ArticleBioMed research international2020

Identification of Crucial lncRNAs, miRNAs, mRNAs, and Potential Therapeutic Compounds for Polycystic Ovary Syndrome by Bioinformatics Analysis.

Zhi Zeng, Xia Lin, Tingting Xia, Wenxiu Liu, Xiaohui Tian, Manchao Li

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.7field-weighted citation impact, top 35% 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

10 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. State of the Art of Genomic Technology in Toxicology: A Review.International journal of molecular sciences · 2023
    Review
  5. Article
  6. 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

6 authors at 2 institutions in 1 country.

Zhi Zeng *Center of Reproductive Medicine, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China.
Xia Lin *Department of Gynecology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China.
Tingting XiaCenter for Reproductive Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China.
Wenxiu LiuDepartment of Gynecology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510407, China.
Xiaohui TianDepartment of Obstetrics and Gynecology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, China.ORCID https://orcid.org/0000-0002-7999-6108
Manchao LiCenter of Reproductive Medicine, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China.ORCID https://orcid.org/0000-0001-5405-0116
Sun Yat-sen University · CNFirst Affiliated Hospital of Guangzhou University of Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study was aimed at mining crucial long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) for the development of polycystic ovary syndrome (PCOS) based on the coexpression and the competitive endogenous RNA (ceRNA) theories and investigating the underlying therapeutic drugs that may function by reversing the expression of lncRNAs, miRNAs, and mRNAs.

methodsRNA (GSE106724, GSE114419, GSE137684, and GSE138518) or miRNA (GSE84376 and GSE138572) expression profile datasets of PCOS patients were downloaded from the Gene Expression Omnibus database. The weighted gene coexpression network analysis (WGCNA) using four RNA datasets was conducted to construct the lncRNA-mRNA coexpression networks, while the common differentially expressed miRNAs in two miRNA datasets and module RNAs were used to establish the ceRNA network. A protein-protein interaction (PPI) network was created to explore the potential interactions between genes. Gene Ontology and KEGG pathway enrichment analyses were performed to explore the functions of genes in networks. Connectivity Map (CMap) and Comparative Toxicogenomics Database (CTD) analyses were performed to identify potential therapeutic agents for PCOS.

resultsThree modules (black, magenta, and yellow) were identified to be PCOS-related after WGCNA analysis, in which KLF3-AS1-PLCG2, MAPKAPK5-AS1-MAP3K14, and WWC2-AS2-TXNIP were important coexpression relationship pairs. WWC2-AS2-hsa-miR-382-PLCG2 was a crucial ceRNA loop in the ceRNA network. The PPI network showed that MAP3K14 and TXNIP could interact with hub genes PLK1 (degree = 21) and TLR1 (degree = 18), respectively. These genes were enriched into mitosis (PLK1), immune response (PLCG2 and TLR1), and cell cycle (TXNIP and PLK1) biological processes. Ten small molecule drugs (especially quercetin) were considered to be therapeutical for PCOS.

conclusionOur study may provide a novel insight into the mechanisms and therapy for PCOS.

Indexed as

Cell Cycle ProteinsComputational BiologyDatabases, PharmaceuticalFemaleGene Expression RegulationGene Regulatory NetworksGenetic MarkersHigh-Throughput Nucleotide SequencingHumansMicroRNAsPolo-Like Kinase 1Polycystic Ovary SyndromeProtein Interaction MapsProtein Serine-Threonine KinasesProto-Oncogene ProteinsQuercetinCell Cycle ProteinsGenetic MarkersMicroRNAsPolo-Like Kinase 1Protein Serine-Threonine KinasesProto-Oncogene ProteinsQuercetinRNA, Long NoncodingRNA, MessengerSmall Molecule Libraries

Identifiers

PMID33224973
PMCPMC7666708
OpenAlexW3096543863

What Socratic 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 Socratic graph.