{"title":"基于机器学习算法的糖尿病肾病关键免疫相关基因鉴定和免疫浸润","authors":"Yue Sun, Weiran Dai, Wenwen He","doi":"10.1049/syb2.12061","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Diabetic nephropathy (DN) is a complication of diabetes. This study aimed to identify potential diagnostic markers of DN and explore the significance of immune cell infiltration in this pathology.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>The GSE30528, GSE96804, and GSE1009 datasets were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified by merging the GSE30528 and GSE96804 datasets. Enrichment analyses of the DEGs were performed. A LASSO regression model, support vector machine recursive feature elimination analysis and random forest analysis methods were performed to identify candidate biomarkers. The CIBERSORT algorithm was utilised to compare immune infiltration between DN and normal controls.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>In total, 115 DEGs were obtained. The enrichment analysis showed that the DEGs were prominent in immune and inflammatory responses. The DEGs were closely related to kidney disease, urinary system disease, kidney cancer etc. CXCR2, DUSP1, and LPL were recognised as diagnostic markers of DN. The immune cell infiltration analysis indicated that DN patients contained a higher ratio of memory B cells, gamma delta T cells, M1 macrophages, M2 macrophages etc. cells than normal people.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>Immune cell infiltration is important for the occurrence of DN. CXCR2, DUSP1, and LPL may become novel diagnostic markers of DN.</p>\n </section>\n </div>","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":null,"pages":null},"PeriodicalIF":16.4000,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/ba/25/SYB2-17-95.PMC10280611.pdf","citationCount":"1","resultStr":"{\"title\":\"Identification of key immune-related genes and immune infiltration in diabetic nephropathy based on machine learning algorithms\",\"authors\":\"Yue Sun, Weiran Dai, Wenwen He\",\"doi\":\"10.1049/syb2.12061\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>Diabetic nephropathy (DN) is a complication of diabetes. This study aimed to identify potential diagnostic markers of DN and explore the significance of immune cell infiltration in this pathology.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>The GSE30528, GSE96804, and GSE1009 datasets were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified by merging the GSE30528 and GSE96804 datasets. Enrichment analyses of the DEGs were performed. A LASSO regression model, support vector machine recursive feature elimination analysis and random forest analysis methods were performed to identify candidate biomarkers. The CIBERSORT algorithm was utilised to compare immune infiltration between DN and normal controls.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>In total, 115 DEGs were obtained. The enrichment analysis showed that the DEGs were prominent in immune and inflammatory responses. The DEGs were closely related to kidney disease, urinary system disease, kidney cancer etc. CXCR2, DUSP1, and LPL were recognised as diagnostic markers of DN. The immune cell infiltration analysis indicated that DN patients contained a higher ratio of memory B cells, gamma delta T cells, M1 macrophages, M2 macrophages etc. cells than normal people.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusion</h3>\\n \\n <p>Immune cell infiltration is important for the occurrence of DN. CXCR2, DUSP1, and LPL may become novel diagnostic markers of DN.</p>\\n </section>\\n </div>\",\"PeriodicalId\":1,\"journal\":{\"name\":\"Accounts of Chemical Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":16.4000,\"publicationDate\":\"2023-03-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/ba/25/SYB2-17-95.PMC10280611.pdf\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Accounts of Chemical Research\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/syb2.12061\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"99","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/syb2.12061","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Identification of key immune-related genes and immune infiltration in diabetic nephropathy based on machine learning algorithms
Background
Diabetic nephropathy (DN) is a complication of diabetes. This study aimed to identify potential diagnostic markers of DN and explore the significance of immune cell infiltration in this pathology.
Methods
The GSE30528, GSE96804, and GSE1009 datasets were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified by merging the GSE30528 and GSE96804 datasets. Enrichment analyses of the DEGs were performed. A LASSO regression model, support vector machine recursive feature elimination analysis and random forest analysis methods were performed to identify candidate biomarkers. The CIBERSORT algorithm was utilised to compare immune infiltration between DN and normal controls.
Results
In total, 115 DEGs were obtained. The enrichment analysis showed that the DEGs were prominent in immune and inflammatory responses. The DEGs were closely related to kidney disease, urinary system disease, kidney cancer etc. CXCR2, DUSP1, and LPL were recognised as diagnostic markers of DN. The immune cell infiltration analysis indicated that DN patients contained a higher ratio of memory B cells, gamma delta T cells, M1 macrophages, M2 macrophages etc. cells than normal people.
Conclusion
Immune cell infiltration is important for the occurrence of DN. CXCR2, DUSP1, and LPL may become novel diagnostic markers of DN.
期刊介绍：
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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