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Integrating the characteristic genes of macrophage pseudotime analysis in single-cell RNA-seq to construct a prediction model of atherosclerosis
Background: Macrophages play an important role in the occurrence and development of atherosclerosis. However, few existing studies have deliberately analyzed the changes in characteristic genes in the process of macrophage phenotype transformation. Method: Carotid atherosclerotic plaque single-cell...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10373969/ https://www.ncbi.nlm.nih.gov/pubmed/37421595 http://dx.doi.org/10.18632/aging.204856 |
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author | Tian, Zemin Yang, Shize |
author_facet | Tian, Zemin Yang, Shize |
author_sort | Tian, Zemin |
collection | PubMed |
description | Background: Macrophages play an important role in the occurrence and development of atherosclerosis. However, few existing studies have deliberately analyzed the changes in characteristic genes in the process of macrophage phenotype transformation. Method: Carotid atherosclerotic plaque single-cell RNA (scRNA) sequencing data were analyzed to define the cells involved and determine their transcriptomic characteristics. KEGG enrichment analysis, CIBERSORT, ESTIMATE, support vector machine (SVM), random forest (RF), and weighted correlation network analysis (WGCNA) were applied to bulk sequencing data. All data were downloaded from Gene Expression Omnibus (GEO). Result: Nine cell clusters were identified. M1 macrophages, M2 macrophages, and M2/M1 macrophages were identified as three clusters within the macrophages. According to pseudotime analysis, M2/M1 macrophages and M2 macrophages can be transformed into M1 macrophages. The ROC curve values of the six genes in the test group were statistically significant (AUC (IL1RN): 0.899, 95% CI: 0.764-0.990; AUC (NRP1): 0.817, 95% CI: 0.620-0.971; AUC (TAGLN): 0.846, 95% CI: 0.678-0.971; AUC (SPARCL1): 0.825, 95% CI: 0.620-0.988; AUC (EMP2): 0.808, 95% CI: 0.630-0.947; AUC (ACTA2): 0.784, 95% CI: 0.591-0.938). The atherosclerosis prediction model showed significant statistical significance in both the train group (AUC: 0.909, 95% CI: 0.842-0.967) and the test group (AUC: 0.812, 95% CI: 0.630-0.966). Conclusions: IL1RN(High) M1, NRP1(High) M2, ACTA2(High) M2/M1, EMP2(High) M1/M1, SPACL1(High) M2/M1 and TAGLN(High) M2/M1 macrophages play key roles in the occurrence and development of arterial atherosclerosis. These marker genes of macrophage phenotypic transformation can also be used to establish a model to predict the occurrence of atherosclerosis. |
format | Online Article Text |
id | pubmed-10373969 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
spelling | pubmed-103739692023-07-28 Integrating the characteristic genes of macrophage pseudotime analysis in single-cell RNA-seq to construct a prediction model of atherosclerosis Tian, Zemin Yang, Shize Aging (Albany NY) Research Paper Background: Macrophages play an important role in the occurrence and development of atherosclerosis. However, few existing studies have deliberately analyzed the changes in characteristic genes in the process of macrophage phenotype transformation. Method: Carotid atherosclerotic plaque single-cell RNA (scRNA) sequencing data were analyzed to define the cells involved and determine their transcriptomic characteristics. KEGG enrichment analysis, CIBERSORT, ESTIMATE, support vector machine (SVM), random forest (RF), and weighted correlation network analysis (WGCNA) were applied to bulk sequencing data. All data were downloaded from Gene Expression Omnibus (GEO). Result: Nine cell clusters were identified. M1 macrophages, M2 macrophages, and M2/M1 macrophages were identified as three clusters within the macrophages. According to pseudotime analysis, M2/M1 macrophages and M2 macrophages can be transformed into M1 macrophages. The ROC curve values of the six genes in the test group were statistically significant (AUC (IL1RN): 0.899, 95% CI: 0.764-0.990; AUC (NRP1): 0.817, 95% CI: 0.620-0.971; AUC (TAGLN): 0.846, 95% CI: 0.678-0.971; AUC (SPARCL1): 0.825, 95% CI: 0.620-0.988; AUC (EMP2): 0.808, 95% CI: 0.630-0.947; AUC (ACTA2): 0.784, 95% CI: 0.591-0.938). The atherosclerosis prediction model showed significant statistical significance in both the train group (AUC: 0.909, 95% CI: 0.842-0.967) and the test group (AUC: 0.812, 95% CI: 0.630-0.966). Conclusions: IL1RN(High) M1, NRP1(High) M2, ACTA2(High) M2/M1, EMP2(High) M1/M1, SPACL1(High) M2/M1 and TAGLN(High) M2/M1 macrophages play key roles in the occurrence and development of arterial atherosclerosis. These marker genes of macrophage phenotypic transformation can also be used to establish a model to predict the occurrence of atherosclerosis. Impact Journals 2023-07-08 /pmc/articles/PMC10373969/ /pubmed/37421595 http://dx.doi.org/10.18632/aging.204856 Text en Copyright: © 2023 Tian and Yang. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Tian, Zemin Yang, Shize Integrating the characteristic genes of macrophage pseudotime analysis in single-cell RNA-seq to construct a prediction model of atherosclerosis |
title | Integrating the characteristic genes of macrophage pseudotime analysis in single-cell RNA-seq to construct a prediction model of atherosclerosis |
title_full | Integrating the characteristic genes of macrophage pseudotime analysis in single-cell RNA-seq to construct a prediction model of atherosclerosis |
title_fullStr | Integrating the characteristic genes of macrophage pseudotime analysis in single-cell RNA-seq to construct a prediction model of atherosclerosis |
title_full_unstemmed | Integrating the characteristic genes of macrophage pseudotime analysis in single-cell RNA-seq to construct a prediction model of atherosclerosis |
title_short | Integrating the characteristic genes of macrophage pseudotime analysis in single-cell RNA-seq to construct a prediction model of atherosclerosis |
title_sort | integrating the characteristic genes of macrophage pseudotime analysis in single-cell rna-seq to construct a prediction model of atherosclerosis |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10373969/ https://www.ncbi.nlm.nih.gov/pubmed/37421595 http://dx.doi.org/10.18632/aging.204856 |
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