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BMC oral health
01 02, 2023;23 (1): 2.

Identification of key module and hub genes in pulpitis using weighted gene co-expression network analysis.

Denghui Zhang, Chen Zheng, Tianer Zhu, Fan Yang, Yiqun Zhou
Author Information
  1. Denghui Zhang: Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310006, China.
  2. Chen Zheng: Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310006, China.
  3. Tianer Zhu: Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310006, China.
  4. Fan Yang: Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310006, China.
  5. Yiqun Zhou: Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310006, China. 7306002@zju.edu.cn.
PMID: 36593446 DOI: 10.1186/s12903-022-02638-9

Abstract

BACKGROUND: Pulpitis is a common disease mainly caused by bacteria. Conventional approaches of diagnosing the state of dental pulp are mainly based on clinical symptoms, thereby harbor deficiencies. The accurate and rapid diagnosis of pulpitis is important for choosing the suitable therapy. The study aimed to identify pulpits related key genes by integrating micro-array data analysis and systems biology network-based methods such as weighted gene co-expression network analysis (WGCNA).
METHODS: The micro-array data of 13 inflamed pulp and 11 normal pulp were acquired from Gene Expression Omnibus (GEO). WGCNA was utilized to establish a genetic network and categorize genes into diverse modules. Hub genes in the most associated module to pulpitis were screened out using high module group members (MM) methods. Pulpitis model in rat was constructed and iRoot BP plus was applied to cap pulp. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used for validation of hub genes.
RESULTS: WGCNA was established and genes were categorized into 22 modules. The darkgrey module had the highest correlation with pulpitis among them. A total of 5 hub genes (HMOX1, LOX, ACTG1, STAT3, GNB5) were identified. RT-qPCR proved the differences in expression levels of HMOX1, LOX, ACTG1, STAT3, GNB5 in inflamed dental pulp. Pulp capping reversed the expression level of HMOX1, LOX, ACTG1.
CONCLUSION: The study was the first to produce a holistic view of pulpitis, screen out and validate hub genes involved in pulpitis using WGCNA method. Pulp capping using iRoot BP plus could reverse partial hub genes.

Keywords

Bioinfomatics Hub genes Pulp capping Pulpitis Weighted gene co-expression network analysis

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Grants

  1. WKJ-ZJ-2034/Major Science and Technology Project of Medical and Health of Zhejiang Province of China

MeSH Term

Animals
Rats
Dental Pulp Capping
Gene Expression Profiling
Gene Regulatory Networks
Pulpitis

Chemicals

iRoot BP Plus
Journal Article Research Support, Non-U.S. Gov't

Word Cloud

Created with Highcharts 10.0.0genespulpitispulphubanalysisnetworkWGCNAmoduleusingPulpitisgeneco-expressionHMOX1LOXACTG1Pulpcappingmainlydentalstudykeymicro-arraydatamethodsweightedinflamedmodulesHubiRootBPplusRT-qPCRSTAT3GNB5expressionBACKGROUND:commondiseasecausedbacteriaConventionalapproachesdiagnosingstatebasedclinicalsymptomstherebyharbordeficienciesaccuraterapiddiagnosisimportantchoosingsuitabletherapyaimedidentifypulpitsrelatedintegratingsystemsbiologynetwork-basedMETHODS:1311normalacquiredGeneExpressionOmnibusGEOutilizedestablishgeneticcategorizediverseassociatedscreenedhighgroupmembersMMmodelratconstructedappliedcapReversetranscription-quantitativepolymerasechainreactionusedvalidationRESULTS:establishedcategorized22darkgreyhighestcorrelationamongtotal5identifiedproveddifferenceslevelsreversedlevelCONCLUSION:firstproduceholisticviewscreenvalidateinvolvedmethodreversepartialIdentificationBioinfomaticsWeighted

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