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

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...
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Autor*in:	Zhang, Denghui [verfasserIn] Zheng, Chen Zhu, Tianer Yang, Fan Zhou, Yiqun

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

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

Anmerkung:	© The Author(s) 2023

Übergeordnetes Werk:	Enthalten in: BMC oral health - London : BioMed Central, 2001, 23(2023), 1 vom: 02. Jan.
Übergeordnetes Werk:	volume:23 ; year:2023 ; number:1 ; day:02 ; month:01

Links:	Volltext

DOI / URN:	10.1186/s12903-022-02638-9

Katalog-ID:	SPR051277298

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520			\|a 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.
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650		4	\|a Weighted gene co-expression network analysis \|7 (dpeaa)DE-He213
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allfields	10.1186/s12903-022-02638-9 doi (DE-627)SPR051277298 (SPR)s12903-022-02638-9-e DE-627 ger DE-627 rakwb eng Zhang, Denghui verfasserin aut Identification of key module and hub genes in pulpitis using weighted gene co-expression network analysis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 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. Pulpitis (dpeaa)DE-He213 Bioinfomatics (dpeaa)DE-He213 Pulp capping (dpeaa)DE-He213 Hub genes (dpeaa)DE-He213 Weighted gene co-expression network analysis (dpeaa)DE-He213 Zheng, Chen aut Zhu, Tianer aut Yang, Fan aut Zhou, Yiqun aut Enthalten in BMC oral health London : BioMed Central, 2001 23(2023), 1 vom: 02. Jan. (DE-627)355500108 (DE-600)2091511-1 1472-6831 nnns volume:23 year:2023 number:1 day:02 month:01 https://dx.doi.org/10.1186/s12903-022-02638-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 23 2023 1 02 01
spelling	10.1186/s12903-022-02638-9 doi (DE-627)SPR051277298 (SPR)s12903-022-02638-9-e DE-627 ger DE-627 rakwb eng Zhang, Denghui verfasserin aut Identification of key module and hub genes in pulpitis using weighted gene co-expression network analysis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 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. Pulpitis (dpeaa)DE-He213 Bioinfomatics (dpeaa)DE-He213 Pulp capping (dpeaa)DE-He213 Hub genes (dpeaa)DE-He213 Weighted gene co-expression network analysis (dpeaa)DE-He213 Zheng, Chen aut Zhu, Tianer aut Yang, Fan aut Zhou, Yiqun aut Enthalten in BMC oral health London : BioMed Central, 2001 23(2023), 1 vom: 02. Jan. (DE-627)355500108 (DE-600)2091511-1 1472-6831 nnns volume:23 year:2023 number:1 day:02 month:01 https://dx.doi.org/10.1186/s12903-022-02638-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 23 2023 1 02 01
allfields_unstemmed	10.1186/s12903-022-02638-9 doi (DE-627)SPR051277298 (SPR)s12903-022-02638-9-e DE-627 ger DE-627 rakwb eng Zhang, Denghui verfasserin aut Identification of key module and hub genes in pulpitis using weighted gene co-expression network analysis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 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. Pulpitis (dpeaa)DE-He213 Bioinfomatics (dpeaa)DE-He213 Pulp capping (dpeaa)DE-He213 Hub genes (dpeaa)DE-He213 Weighted gene co-expression network analysis (dpeaa)DE-He213 Zheng, Chen aut Zhu, Tianer aut Yang, Fan aut Zhou, Yiqun aut Enthalten in BMC oral health London : BioMed Central, 2001 23(2023), 1 vom: 02. Jan. (DE-627)355500108 (DE-600)2091511-1 1472-6831 nnns volume:23 year:2023 number:1 day:02 month:01 https://dx.doi.org/10.1186/s12903-022-02638-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 23 2023 1 02 01
allfieldsGer	10.1186/s12903-022-02638-9 doi (DE-627)SPR051277298 (SPR)s12903-022-02638-9-e DE-627 ger DE-627 rakwb eng Zhang, Denghui verfasserin aut Identification of key module and hub genes in pulpitis using weighted gene co-expression network analysis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 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. Pulpitis (dpeaa)DE-He213 Bioinfomatics (dpeaa)DE-He213 Pulp capping (dpeaa)DE-He213 Hub genes (dpeaa)DE-He213 Weighted gene co-expression network analysis (dpeaa)DE-He213 Zheng, Chen aut Zhu, Tianer aut Yang, Fan aut Zhou, Yiqun aut Enthalten in BMC oral health London : BioMed Central, 2001 23(2023), 1 vom: 02. Jan. (DE-627)355500108 (DE-600)2091511-1 1472-6831 nnns volume:23 year:2023 number:1 day:02 month:01 https://dx.doi.org/10.1186/s12903-022-02638-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 23 2023 1 02 01
allfieldsSound	10.1186/s12903-022-02638-9 doi (DE-627)SPR051277298 (SPR)s12903-022-02638-9-e DE-627 ger DE-627 rakwb eng Zhang, Denghui verfasserin aut Identification of key module and hub genes in pulpitis using weighted gene co-expression network analysis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 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. Pulpitis (dpeaa)DE-He213 Bioinfomatics (dpeaa)DE-He213 Pulp capping (dpeaa)DE-He213 Hub genes (dpeaa)DE-He213 Weighted gene co-expression network analysis (dpeaa)DE-He213 Zheng, Chen aut Zhu, Tianer aut Yang, Fan aut Zhou, Yiqun aut Enthalten in BMC oral health London : BioMed Central, 2001 23(2023), 1 vom: 02. Jan. (DE-627)355500108 (DE-600)2091511-1 1472-6831 nnns volume:23 year:2023 number:1 day:02 month:01 https://dx.doi.org/10.1186/s12903-022-02638-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 23 2023 1 02 01
language	English
source	Enthalten in BMC oral health 23(2023), 1 vom: 02. Jan. volume:23 year:2023 number:1 day:02 month:01
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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. 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author	Zhang, Denghui
spellingShingle	Zhang, Denghui misc Pulpitis misc Bioinfomatics misc Pulp capping misc Hub genes misc Weighted gene co-expression network analysis Identification of key module and hub genes in pulpitis using weighted gene co-expression network analysis
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topic_title	Identification of key module and hub genes in pulpitis using weighted gene co-expression network analysis Pulpitis (dpeaa)DE-He213 Bioinfomatics (dpeaa)DE-He213 Pulp capping (dpeaa)DE-He213 Hub genes (dpeaa)DE-He213 Weighted gene co-expression network analysis (dpeaa)DE-He213
topic	misc Pulpitis misc Bioinfomatics misc Pulp capping misc Hub genes misc Weighted gene co-expression network analysis
topic_unstemmed	misc Pulpitis misc Bioinfomatics misc Pulp capping misc Hub genes misc Weighted gene co-expression network analysis
topic_browse	misc Pulpitis misc Bioinfomatics misc Pulp capping misc Hub genes misc Weighted gene co-expression network analysis
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title	Identification of key module and hub genes in pulpitis using weighted gene co-expression network analysis
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title_full	Identification of key module and hub genes in pulpitis using weighted gene co-expression network analysis
author_sort	Zhang, Denghui
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author_browse	Zhang, Denghui Zheng, Chen Zhu, Tianer Yang, Fan Zhou, Yiqun
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author-letter	Zhang, Denghui
doi_str_mv	10.1186/s12903-022-02638-9
title_sort	identification of key module and hub genes in pulpitis using weighted gene co-expression network analysis
title_auth	Identification of key module and hub genes in pulpitis using weighted gene co-expression network analysis
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. © The Author(s) 2023
abstractGer	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. © The Author(s) 2023
abstract_unstemmed	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. © The Author(s) 2023
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title_short	Identification of key module and hub genes in pulpitis using weighted gene co-expression network analysis
url	https://dx.doi.org/10.1186/s12903-022-02638-9
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author2	Zheng, Chen Zhu, Tianer Yang, Fan Zhou, Yiqun
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up_date	2024-07-03T20:52:32.507Z
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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. 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Identification of key module and hub genes in pulpitis using weighted gene co-expression network analysis

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