{"title":"生物信息学方法研究牙周炎在动脉粥样硬化进展中的免疫炎症机制。","authors":"Wenling Yang, Jianhua Xie, Xing Zhao, Xuelian Li, Qingyi Liu, Jinpeng Sun, Ruiyu Zhang, Yumiao Wei, Boyuan Wang","doi":"10.3390/cimb47030197","DOIUrl":null,"url":null,"abstract":"<p><p>Unstable atherosclerotic plaques are a major cause of acute cardiovascular events and ischemic stroke. Clinical studies have suggested a link between periodontitis and atherosclerotic plaque progression, but the underlying mechanisms remain unclear. To investigate this, transcriptomic datasets related to periodontitis and atherosclerosis were downloaded from Gene Expression Omnibus. A weighted gene co-expression network analysis was used to identify gene modules associated with periodontitis, and the Limma R package identified differentially expressed genes (DEGs) between unstable and stable plaques. Overlapping genes were defined as periodontitis-related DEGs, followed by functional enrichment analysis and protein-protein interaction network construction. Machine learning methods were used to identify biomarkers for unstable plaques related to periodontitis, which were validated using external datasets. Immune infiltration and single-cell analyses were performed to explore the relationship between biomarkers and immune cells. A total of 161 periodontitis-related DEGs were identified, with the pathway analysis showing associations with immune regulation and collagen matrix degradation. <i>HCK</i>, <i>NCKAP1L</i>, and <i>WAS</i> were identified as biomarkers for unstable plaques, demonstrating a high diagnostic value (AUC: 0.9884, 95% CI: 0.9641-1). Immune infiltration analysis revealed an increase in macrophages within unstable plaques. Single-cell analysis showed <i>HCK</i> expression in macrophages and dendritic cells, while <i>NCKAP1L</i> and <i>WAS</i> were expressed in macrophages, dendritic cells, NK cells, and T cells. Consensus clustering identified three expression patterns within unstable plaques. Our findings were validated in atherosclerotic mouse models with periodontitis. This study provides insights into how periodontitis contributes to plaque instability, supporting diagnosis and intervention in patients with periodontitis.</p>","PeriodicalId":10839,"journal":{"name":"Current Issues in Molecular Biology","volume":"47 3","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11941604/pdf/","citationCount":"0","resultStr":"{\"title\":\"Bioinformatics Approach to Investigating the Immuno-Inflammatory Mechanisms of Periodontitis in the Progression of Atherosclerosis.\",\"authors\":\"Wenling Yang, Jianhua Xie, Xing Zhao, Xuelian Li, Qingyi Liu, Jinpeng Sun, Ruiyu Zhang, Yumiao Wei, Boyuan Wang\",\"doi\":\"10.3390/cimb47030197\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Unstable atherosclerotic plaques are a major cause of acute cardiovascular events and ischemic stroke. Clinical studies have suggested a link between periodontitis and atherosclerotic plaque progression, but the underlying mechanisms remain unclear. To investigate this, transcriptomic datasets related to periodontitis and atherosclerosis were downloaded from Gene Expression Omnibus. A weighted gene co-expression network analysis was used to identify gene modules associated with periodontitis, and the Limma R package identified differentially expressed genes (DEGs) between unstable and stable plaques. Overlapping genes were defined as periodontitis-related DEGs, followed by functional enrichment analysis and protein-protein interaction network construction. Machine learning methods were used to identify biomarkers for unstable plaques related to periodontitis, which were validated using external datasets. Immune infiltration and single-cell analyses were performed to explore the relationship between biomarkers and immune cells. A total of 161 periodontitis-related DEGs were identified, with the pathway analysis showing associations with immune regulation and collagen matrix degradation. <i>HCK</i>, <i>NCKAP1L</i>, and <i>WAS</i> were identified as biomarkers for unstable plaques, demonstrating a high diagnostic value (AUC: 0.9884, 95% CI: 0.9641-1). Immune infiltration analysis revealed an increase in macrophages within unstable plaques. Single-cell analysis showed <i>HCK</i> expression in macrophages and dendritic cells, while <i>NCKAP1L</i> and <i>WAS</i> were expressed in macrophages, dendritic cells, NK cells, and T cells. Consensus clustering identified three expression patterns within unstable plaques. Our findings were validated in atherosclerotic mouse models with periodontitis. This study provides insights into how periodontitis contributes to plaque instability, supporting diagnosis and intervention in patients with periodontitis.</p>\",\"PeriodicalId\":10839,\"journal\":{\"name\":\"Current Issues in Molecular Biology\",\"volume\":\"47 3\",\"pages\":\"\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2025-03-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11941604/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Issues in Molecular Biology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.3390/cimb47030197\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Issues in Molecular Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.3390/cimb47030197","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Bioinformatics Approach to Investigating the Immuno-Inflammatory Mechanisms of Periodontitis in the Progression of Atherosclerosis.
Unstable atherosclerotic plaques are a major cause of acute cardiovascular events and ischemic stroke. Clinical studies have suggested a link between periodontitis and atherosclerotic plaque progression, but the underlying mechanisms remain unclear. To investigate this, transcriptomic datasets related to periodontitis and atherosclerosis were downloaded from Gene Expression Omnibus. A weighted gene co-expression network analysis was used to identify gene modules associated with periodontitis, and the Limma R package identified differentially expressed genes (DEGs) between unstable and stable plaques. Overlapping genes were defined as periodontitis-related DEGs, followed by functional enrichment analysis and protein-protein interaction network construction. Machine learning methods were used to identify biomarkers for unstable plaques related to periodontitis, which were validated using external datasets. Immune infiltration and single-cell analyses were performed to explore the relationship between biomarkers and immune cells. A total of 161 periodontitis-related DEGs were identified, with the pathway analysis showing associations with immune regulation and collagen matrix degradation. HCK, NCKAP1L, and WAS were identified as biomarkers for unstable plaques, demonstrating a high diagnostic value (AUC: 0.9884, 95% CI: 0.9641-1). Immune infiltration analysis revealed an increase in macrophages within unstable plaques. Single-cell analysis showed HCK expression in macrophages and dendritic cells, while NCKAP1L and WAS were expressed in macrophages, dendritic cells, NK cells, and T cells. Consensus clustering identified three expression patterns within unstable plaques. Our findings were validated in atherosclerotic mouse models with periodontitis. This study provides insights into how periodontitis contributes to plaque instability, supporting diagnosis and intervention in patients with periodontitis.
期刊介绍:
Current Issues in Molecular Biology (CIMB) is a peer-reviewed journal publishing review articles and minireviews in all areas of molecular biology and microbiology. Submitted articles are subject to an Article Processing Charge (APC) and are open access immediately upon publication. All manuscripts undergo a peer-review process.