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Integrated multi-omics analysis to investigate the pathogenesis of intrauterine adhesion
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Abstract
Background
Intrauterine adhesion (IUA) represents a prevalent cause of infertility and reproductive dysfunction; however, the underlying molecular mechanisms contributing to the development of IUA remain inadequately characterized. Consequently, this study aimed to elucidate key genes implicated in IUA through comprehensive multi-omics analyses.
Methods
Transcriptome data from 6 IUA and 6 control endometrial tissue samples, microbiome (16S rRNA gene sequencing) data from 6 IUA and 6 control uterine lavage samples, and metabolome data from 21 IUA and 21 control uterine lavage samples were utilized. Initially, differential analyses were performed separately on transcriptome, microbiome, and metabolome data to identify genes, microbes, and metabolites of interest, respectively. Subsequently, multi-omics integration through Spearman correlation analysis identified key genes, microbes, and metabolites. Additionally, functional annotation, regulatory network construction, and drug prediction analyses were performed to further clarify the molecular mechanisms associated with the identified key genes.
Results
In this study, 46 genes, 4 microbes, and 11 metabolites of interest were identified. Through comprehensive multi-omics analyses, 7 key genes (DUSP2, IL1A, POF1B, ICAM4, CX3CL1, HTR2C, and SIX1), 2 key microbes (g__Clostridium_sensu_stricto_1 and g__Acidisoma), and 2 key metabolites (Pe(18:3(6Z,9Z,12Z)/18:1(9Z)) and 1,3,6-trihydroxy-2-(3-methylbut-2-enyl)xanthen-9-one) were pinpointed, all showing strong intercorrelations. Moreover, functional pathways were involved in various biological processes, including ribosome function, fatty acid metabolism, cell cycle regulation, DNA replication, and cytokine signaling. The regulatory networks revealed complex interactions, such as NEAT1-hsa-miR-185-5p-SIX1 and hsa_circ_0013870-hsa-miR-4498-CX3CL1. Additionally, olanzapine was predicted as a potential therapeutic drug based on its predicted targeting of two key genes (IL1A and HTR2C) through drug-gene interaction analysis.
Conclusion
This research identified seven key genes, two key microbes, and two key metabolites associated with IUA, offering novel insights into its molecular mechanisms and underscoring potential therapeutic targets for subsequent investigation.
Title: Integrated multi-omics analysis to investigate the pathogenesis of intrauterine adhesion
Description:
Abstract
Background
Intrauterine adhesion (IUA) represents a prevalent cause of infertility and reproductive dysfunction; however, the underlying molecular mechanisms contributing to the development of IUA remain inadequately characterized.
Consequently, this study aimed to elucidate key genes implicated in IUA through comprehensive multi-omics analyses.
Methods
Transcriptome data from 6 IUA and 6 control endometrial tissue samples, microbiome (16S rRNA gene sequencing) data from 6 IUA and 6 control uterine lavage samples, and metabolome data from 21 IUA and 21 control uterine lavage samples were utilized.
Initially, differential analyses were performed separately on transcriptome, microbiome, and metabolome data to identify genes, microbes, and metabolites of interest, respectively.
Subsequently, multi-omics integration through Spearman correlation analysis identified key genes, microbes, and metabolites.
Additionally, functional annotation, regulatory network construction, and drug prediction analyses were performed to further clarify the molecular mechanisms associated with the identified key genes.
Results
In this study, 46 genes, 4 microbes, and 11 metabolites of interest were identified.
Through comprehensive multi-omics analyses, 7 key genes (DUSP2, IL1A, POF1B, ICAM4, CX3CL1, HTR2C, and SIX1), 2 key microbes (g__Clostridium_sensu_stricto_1 and g__Acidisoma), and 2 key metabolites (Pe(18:3(6Z,9Z,12Z)/18:1(9Z)) and 1,3,6-trihydroxy-2-(3-methylbut-2-enyl)xanthen-9-one) were pinpointed, all showing strong intercorrelations.
Moreover, functional pathways were involved in various biological processes, including ribosome function, fatty acid metabolism, cell cycle regulation, DNA replication, and cytokine signaling.
The regulatory networks revealed complex interactions, such as NEAT1-hsa-miR-185-5p-SIX1 and hsa_circ_0013870-hsa-miR-4498-CX3CL1.
Additionally, olanzapine was predicted as a potential therapeutic drug based on its predicted targeting of two key genes (IL1A and HTR2C) through drug-gene interaction analysis.
Conclusion
This research identified seven key genes, two key microbes, and two key metabolites associated with IUA, offering novel insights into its molecular mechanisms and underscoring potential therapeutic targets for subsequent investigation.
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