{"title":"鉴定和验证新的脂肪酸代谢相关机制和勃起功能障碍生物标志物。","authors":"Yanfeng He, Changyi Liu, Zhongjie Zheng, Rui Gao, Haocheng Lin, Huiliang Zhou","doi":"10.1093/sexmed/qfae011","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Erectile dysfunction (ED) is a common condition affecting middle-aged and elderly men.</p><p><strong>Aim: </strong>The study sought to investigate differentially expressed fatty acid metabolism-related genes and the molecular mechanisms of ED.</p><p><strong>Methods: </strong>The expression profiles of GSE2457 and GSE31247 were downloaded from the Gene Expression Omnibus database and merged. Differentially expressed genes (DEGs) between ED and normal samples were obtained using the R package limma. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses of DEGs were conducted using the R package clusterProfiler. Fatty acid metabolism-related DEGs (FAMDEGs) were further identified and analyzed. Machine learning algorithms, including Lasso (least absolute shrinkage and selection operator), support vector machine, and random forest algorithms, were utilized to identify hub FAMDEGs with the ability to predict ED occurrence. Coexpression analysis and gene set enrichment analysis of hub FAMDEGs were performed.</p><p><strong>Outcome: </strong>Fatty acid metabolism-related functions (such as fatty acid metabolism and degradation) may play a vital role in ED.</p><p><strong>Results: </strong>In total, 5 hub FAMDEGs (<i>Aldh2</i>, <i>Eci2</i>, <i>Acat1</i>, <i>Acadl</i>, and <i>Hadha</i>) were identified and found to be differentially expressed between ED and normal samples. Gene set enrichment analysis identified key pathways associated with these genes. The area under the curve values of the 5 hub FAMDEGs for predicting ED occurrence were all >0.8.</p><p><strong>Clinical translation: </strong>Our results suggest that these 5 key FAMDEGs may serve as biomarkers for the diagnosis and treatment of ED.</p><p><strong>Strengths and limitations: </strong>The strengths of our study include the use of multiple datasets and machine learning algorithms to identify key FAMDEGs. However, limitations include the lack of validation in animal models and human tissues, as well as research on the mechanisms of these FAMDEGs.</p><p><strong>Conclusion: </strong>Five hub FAMDEGs were identified as potential biomarkers for ED progression. Our work may prove that fatty acid metabolism-related genes are worth further investigation in ED.</p>","PeriodicalId":21782,"journal":{"name":"Sexual Medicine","volume":"12 1","pages":"qfae011"},"PeriodicalIF":2.6000,"publicationDate":"2024-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10960936/pdf/","citationCount":"0","resultStr":"{\"title\":\"Identification and validation of new fatty acid metabolism-related mechanisms and biomarkers for erectile dysfunction.\",\"authors\":\"Yanfeng He, Changyi Liu, Zhongjie Zheng, Rui Gao, Haocheng Lin, Huiliang Zhou\",\"doi\":\"10.1093/sexmed/qfae011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Erectile dysfunction (ED) is a common condition affecting middle-aged and elderly men.</p><p><strong>Aim: </strong>The study sought to investigate differentially expressed fatty acid metabolism-related genes and the molecular mechanisms of ED.</p><p><strong>Methods: </strong>The expression profiles of GSE2457 and GSE31247 were downloaded from the Gene Expression Omnibus database and merged. Differentially expressed genes (DEGs) between ED and normal samples were obtained using the R package limma. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses of DEGs were conducted using the R package clusterProfiler. Fatty acid metabolism-related DEGs (FAMDEGs) were further identified and analyzed. Machine learning algorithms, including Lasso (least absolute shrinkage and selection operator), support vector machine, and random forest algorithms, were utilized to identify hub FAMDEGs with the ability to predict ED occurrence. Coexpression analysis and gene set enrichment analysis of hub FAMDEGs were performed.</p><p><strong>Outcome: </strong>Fatty acid metabolism-related functions (such as fatty acid metabolism and degradation) may play a vital role in ED.</p><p><strong>Results: </strong>In total, 5 hub FAMDEGs (<i>Aldh2</i>, <i>Eci2</i>, <i>Acat1</i>, <i>Acadl</i>, and <i>Hadha</i>) were identified and found to be differentially expressed between ED and normal samples. Gene set enrichment analysis identified key pathways associated with these genes. The area under the curve values of the 5 hub FAMDEGs for predicting ED occurrence were all >0.8.</p><p><strong>Clinical translation: </strong>Our results suggest that these 5 key FAMDEGs may serve as biomarkers for the diagnosis and treatment of ED.</p><p><strong>Strengths and limitations: </strong>The strengths of our study include the use of multiple datasets and machine learning algorithms to identify key FAMDEGs. However, limitations include the lack of validation in animal models and human tissues, as well as research on the mechanisms of these FAMDEGs.</p><p><strong>Conclusion: </strong>Five hub FAMDEGs were identified as potential biomarkers for ED progression. Our work may prove that fatty acid metabolism-related genes are worth further investigation in ED.</p>\",\"PeriodicalId\":21782,\"journal\":{\"name\":\"Sexual Medicine\",\"volume\":\"12 1\",\"pages\":\"qfae011\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-03-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10960936/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sexual Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/sexmed/qfae011\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/2/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sexual Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/sexmed/qfae011","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/2/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0
摘要
背景：勃起功能障碍（ED）是影响中老年男性的常见疾病：目的：本研究旨在探讨脂肪酸代谢相关基因的差异表达及ED的分子机制：方法：从基因表达总库（Gene Expression Omnibus）数据库下载 GSE2457 和 GSE31247 的表达谱并进行合并。使用R软件包limma获得ED与正常样本之间的差异表达基因（DEGs）。使用 R 软件包 clusterProfiler 对 DEGs 进行基因本体和京都基因组百科全书富集分析。脂肪酸代谢相关 DEGs（FAMDEGs）被进一步鉴定和分析。利用机器学习算法，包括 Lasso（最小绝对收缩和选择算子）、支持向量机和随机森林算法，确定了具有预测 ED 发生能力的枢纽 FAMDEGs。对枢纽 FAMDEGs 进行了共表达分析和基因组富集分析：结果：脂肪酸代谢相关功能（如脂肪酸代谢和降解）可能在 ED 中发挥重要作用：结果：共鉴定出5个中枢FAMDEGs（Aldh2、Eci2、Acat1、Acadl和Hadha），发现它们在ED和正常样本之间存在差异表达。基因组富集分析确定了与这些基因相关的关键通路。预测 ED 发生的 5 个关键 FAMDEG 的曲线下面积值均大于 0.8：我们的研究结果表明，这5个关键FAMDEG可作为诊断和治疗ED的生物标志物：我们研究的优点包括使用多个数据集和机器学习算法来识别关键 FAMDEGs。然而，局限性包括缺乏动物模型和人体组织的验证，以及对这些FAMDEGs机制的研究：结论：五个枢纽 FAMDEGs 被确定为 ED 进展的潜在生物标志物。我们的工作可能会证明脂肪酸代谢相关基因在 ED 中值得进一步研究。
Identification and validation of new fatty acid metabolism-related mechanisms and biomarkers for erectile dysfunction.
Background: Erectile dysfunction (ED) is a common condition affecting middle-aged and elderly men.
Aim: The study sought to investigate differentially expressed fatty acid metabolism-related genes and the molecular mechanisms of ED.
Methods: The expression profiles of GSE2457 and GSE31247 were downloaded from the Gene Expression Omnibus database and merged. Differentially expressed genes (DEGs) between ED and normal samples were obtained using the R package limma. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses of DEGs were conducted using the R package clusterProfiler. Fatty acid metabolism-related DEGs (FAMDEGs) were further identified and analyzed. Machine learning algorithms, including Lasso (least absolute shrinkage and selection operator), support vector machine, and random forest algorithms, were utilized to identify hub FAMDEGs with the ability to predict ED occurrence. Coexpression analysis and gene set enrichment analysis of hub FAMDEGs were performed.
Outcome: Fatty acid metabolism-related functions (such as fatty acid metabolism and degradation) may play a vital role in ED.
Results: In total, 5 hub FAMDEGs (Aldh2, Eci2, Acat1, Acadl, and Hadha) were identified and found to be differentially expressed between ED and normal samples. Gene set enrichment analysis identified key pathways associated with these genes. The area under the curve values of the 5 hub FAMDEGs for predicting ED occurrence were all >0.8.
Clinical translation: Our results suggest that these 5 key FAMDEGs may serve as biomarkers for the diagnosis and treatment of ED.
Strengths and limitations: The strengths of our study include the use of multiple datasets and machine learning algorithms to identify key FAMDEGs. However, limitations include the lack of validation in animal models and human tissues, as well as research on the mechanisms of these FAMDEGs.
Conclusion: Five hub FAMDEGs were identified as potential biomarkers for ED progression. Our work may prove that fatty acid metabolism-related genes are worth further investigation in ED.
期刊介绍：
Sexual Medicine is an official publication of the International Society for Sexual Medicine, and serves the field as the peer-reviewed, open access journal for rapid dissemination of multidisciplinary clinical and basic research in all areas of global sexual medicine, and particularly acts as a venue for topics of regional or sub-specialty interest. The journal is focused on issues in clinical medicine and epidemiology but also publishes basic science papers with particular relevance to specific populations. Sexual Medicine offers clinicians and researchers a rapid route to publication and the opportunity to publish in a broadly distributed and highly visible global forum. The journal publishes high quality articles from all over the world and actively seeks submissions from countries with expanding sexual medicine communities. Sexual Medicine relies on the same expert panel of editors and reviewers as The Journal of Sexual Medicine and Sexual Medicine Reviews.
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