{"title":"中枢生物标志物及其在糖代谢紊乱中的临床意义：一种综合的生物信息学和机器学习方法。","authors":"Liping Xiang, Bing Zhou, Yunchen Luo, Hanqi Bi, Yan Lu, Jian Zhou","doi":"10.1097/CM9.0000000000003525","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Gluconeogenesis is a critical metabolic pathway for maintaining glucose homeostasis, and its dysregulation can lead to glycometabolic disorders. This study aimed to identify hub biomarkers of these disorders to provide a theoretical foundation for enhancing diagnosis and treatment.</p><p><strong>Methods: </strong>Gene expression profiles from liver tissues of three well-characterized gluconeogenesis mouse models were analyzed to identify commonly differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA), machine learning techniques, and diagnostic tests on transcriptome data from publicly available datasets of type 2 diabetes mellitus (T2DM) patients were employed to assess the clinical relevance of these DEGs. Subsequently, we identified hub biomarkers associated with gluconeogenesis-related glycometabolic disorders, investigated potential correlations with immune cell types, and validated expression using quantitative Polymerase Chain Reaction in the mouse models.</p><p><strong>Results: </strong>Only a few common DEGs were observed in gluconeogenesis-related glycometabolic disorders across different contributing factors. However, these DEGs were consistently associated with cytokine regulation and oxidative stress (OS). Enrichment analysis highlighted significant alterations in terms related to cytokines and OS. Importantly, osteomodulin (OMD), apolipoprotein A4 (APOA4), and insulin like growth factor binding protein 6 (IGFBP6) were identified with potential clinical significance in T2DM patients. These genes demonstrated robust diagnostic performance in T2DM cohorts and were positively correlated with resting dendritic cells.</p><p><strong>Conclusions: </strong>Gluconeogenesis-related glycometabolic disorders exhibit considerable heterogeneity, yet changes in cytokine regulation and OS are universally present. OMD, APOA4, and IGFBP6 may serve as hub biomarkers for gluconeogenesis-related glycometabolic disorders.</p>","PeriodicalId":10183,"journal":{"name":"Chinese Medical Journal","volume":" ","pages":""},"PeriodicalIF":7.5000,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hub biomarkers and their clinical relevance in glycometabolic disorders: A comprehensive bioinformatics and machine learning approach.\",\"authors\":\"Liping Xiang, Bing Zhou, Yunchen Luo, Hanqi Bi, Yan Lu, Jian Zhou\",\"doi\":\"10.1097/CM9.0000000000003525\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Gluconeogenesis is a critical metabolic pathway for maintaining glucose homeostasis, and its dysregulation can lead to glycometabolic disorders. This study aimed to identify hub biomarkers of these disorders to provide a theoretical foundation for enhancing diagnosis and treatment.</p><p><strong>Methods: </strong>Gene expression profiles from liver tissues of three well-characterized gluconeogenesis mouse models were analyzed to identify commonly differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA), machine learning techniques, and diagnostic tests on transcriptome data from publicly available datasets of type 2 diabetes mellitus (T2DM) patients were employed to assess the clinical relevance of these DEGs. Subsequently, we identified hub biomarkers associated with gluconeogenesis-related glycometabolic disorders, investigated potential correlations with immune cell types, and validated expression using quantitative Polymerase Chain Reaction in the mouse models.</p><p><strong>Results: </strong>Only a few common DEGs were observed in gluconeogenesis-related glycometabolic disorders across different contributing factors. However, these DEGs were consistently associated with cytokine regulation and oxidative stress (OS). Enrichment analysis highlighted significant alterations in terms related to cytokines and OS. Importantly, osteomodulin (OMD), apolipoprotein A4 (APOA4), and insulin like growth factor binding protein 6 (IGFBP6) were identified with potential clinical significance in T2DM patients. These genes demonstrated robust diagnostic performance in T2DM cohorts and were positively correlated with resting dendritic cells.</p><p><strong>Conclusions: </strong>Gluconeogenesis-related glycometabolic disorders exhibit considerable heterogeneity, yet changes in cytokine regulation and OS are universally present. OMD, APOA4, and IGFBP6 may serve as hub biomarkers for gluconeogenesis-related glycometabolic disorders.</p>\",\"PeriodicalId\":10183,\"journal\":{\"name\":\"Chinese Medical Journal\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":7.5000,\"publicationDate\":\"2025-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Chinese Medical Journal\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/CM9.0000000000003525\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chinese Medical Journal","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/CM9.0000000000003525","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
Hub biomarkers and their clinical relevance in glycometabolic disorders: A comprehensive bioinformatics and machine learning approach.
Background: Gluconeogenesis is a critical metabolic pathway for maintaining glucose homeostasis, and its dysregulation can lead to glycometabolic disorders. This study aimed to identify hub biomarkers of these disorders to provide a theoretical foundation for enhancing diagnosis and treatment.
Methods: Gene expression profiles from liver tissues of three well-characterized gluconeogenesis mouse models were analyzed to identify commonly differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA), machine learning techniques, and diagnostic tests on transcriptome data from publicly available datasets of type 2 diabetes mellitus (T2DM) patients were employed to assess the clinical relevance of these DEGs. Subsequently, we identified hub biomarkers associated with gluconeogenesis-related glycometabolic disorders, investigated potential correlations with immune cell types, and validated expression using quantitative Polymerase Chain Reaction in the mouse models.
Results: Only a few common DEGs were observed in gluconeogenesis-related glycometabolic disorders across different contributing factors. However, these DEGs were consistently associated with cytokine regulation and oxidative stress (OS). Enrichment analysis highlighted significant alterations in terms related to cytokines and OS. Importantly, osteomodulin (OMD), apolipoprotein A4 (APOA4), and insulin like growth factor binding protein 6 (IGFBP6) were identified with potential clinical significance in T2DM patients. These genes demonstrated robust diagnostic performance in T2DM cohorts and were positively correlated with resting dendritic cells.
Conclusions: Gluconeogenesis-related glycometabolic disorders exhibit considerable heterogeneity, yet changes in cytokine regulation and OS are universally present. OMD, APOA4, and IGFBP6 may serve as hub biomarkers for gluconeogenesis-related glycometabolic disorders.
期刊介绍：
The Chinese Medical Journal (CMJ) is published semimonthly in English by the Chinese Medical Association, and is a peer reviewed general medical journal for all doctors, researchers, and health workers regardless of their medical specialty or type of employment. Established in 1887, it is the oldest medical periodical in China and is distributed worldwide. The journal functions as a window into China’s medical sciences and reflects the advances and progress in China’s medical sciences and technology. It serves the objective of international academic exchange. The journal includes Original Articles, Editorial, Review Articles, Medical Progress, Brief Reports, Case Reports, Viewpoint, Clinical Exchange, Letter,and News,etc. CMJ is abstracted or indexed in many databases including Biological Abstracts, Chemical Abstracts, Index Medicus/Medline, Science Citation Index (SCI), Current Contents, Cancerlit, Health Plan & Administration, Embase, Social Scisearch, Aidsline, Toxline, Biocommercial Abstracts, Arts and Humanities Search, Nuclear Science Abstracts, Water Resources Abstracts, Cab Abstracts, Occupation Safety & Health, etc. In 2007, the impact factor of the journal by SCI is 0.636, and the total citation is 2315.
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