Xiaomei Lai, Tingting Yang, Chaoping Wei, Shuangbei Zhu, Jianling Li
{"title":"Integrative Analysis of Metabolomic and Transcriptomic Data Reveals Metabolic Signatures and Major Metabolic Pathways in Primary Aldosteronism.","authors":"Xiaomei Lai, Tingting Yang, Chaoping Wei, Shuangbei Zhu, Jianling Li","doi":"10.2174/0118715303361250250119035029","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Primary aldosteronism (PA) is the most common secondary hypertension. In this study, we performed the pathway enrichment analysis based on metabolomics and transcriptomic data to find the metabolic perturbations in PA, which could provide new targets for PA and further understand the biology of PA.</p><p><strong>Methods: </strong>24 PA patients and 24 healthy adults served as the control group in this study. Six participants were chosen from each group to have their peripheral blood and serum samples analyzed for omics investigations. Another eighteen participants' peripheral blood samples were selected for further validation of the RNA-sequencing results.</p><p><strong>Results: </strong>Transcriptomic analyses found 518 differentially expressed genes (DEGs), and 339 remarkably differential metabolites (DMs) were identified by untargeted metabolomics. The pathway enrichment analysis was performed by combining with the omics analysis data. We also focused on analyzing metabolic pathways that repeatedly occur and constructed possible genemetabolic networks. A total of 5 genes and 11 metabolites showed significant changes in altered 3 lipid metabolic pathways. Furthermore, the expressions of these genes were verified by qRT-PCR.</p><p><strong>Conclusion: </strong>The combination of metabolomic and transcriptomic data can give a comprehensive picture of unique illness markers and preliminary knowledge of the molecular abnormalities underpinning PA. These findings may point to viable targets for creating treatments.</p>","PeriodicalId":94316,"journal":{"name":"Endocrine, metabolic & immune disorders drug targets","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Endocrine, metabolic & immune disorders drug targets","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/0118715303361250250119035029","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: Primary aldosteronism (PA) is the most common secondary hypertension. In this study, we performed the pathway enrichment analysis based on metabolomics and transcriptomic data to find the metabolic perturbations in PA, which could provide new targets for PA and further understand the biology of PA.
Methods: 24 PA patients and 24 healthy adults served as the control group in this study. Six participants were chosen from each group to have their peripheral blood and serum samples analyzed for omics investigations. Another eighteen participants' peripheral blood samples were selected for further validation of the RNA-sequencing results.
Results: Transcriptomic analyses found 518 differentially expressed genes (DEGs), and 339 remarkably differential metabolites (DMs) were identified by untargeted metabolomics. The pathway enrichment analysis was performed by combining with the omics analysis data. We also focused on analyzing metabolic pathways that repeatedly occur and constructed possible genemetabolic networks. A total of 5 genes and 11 metabolites showed significant changes in altered 3 lipid metabolic pathways. Furthermore, the expressions of these genes were verified by qRT-PCR.
Conclusion: The combination of metabolomic and transcriptomic data can give a comprehensive picture of unique illness markers and preliminary knowledge of the molecular abnormalities underpinning PA. These findings may point to viable targets for creating treatments.