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Identification of the Immune Status of Hypertrophic Cardiomyopathy by Integrated Analysis of Bulk- and Single-Cell RNA Sequencing Data

OBJECTIVES: Hypertrophic cardiomyopathy (HCM) is the most common hereditary cardiomyopathy and immune infiltration is considered an indispensable factor involved in its pathogenesis. In this study, we attempted to combine bulk sequencing and single-cell sequencing to map the immune infiltration-rela...

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Autores principales: Zhao, Wei, Wu, Tianyu, Zhan, Jian, Dong, Zishuang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9553329/
https://www.ncbi.nlm.nih.gov/pubmed/36238494
http://dx.doi.org/10.1155/2022/7153491
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author Zhao, Wei
Wu, Tianyu
Zhan, Jian
Dong, Zishuang
author_facet Zhao, Wei
Wu, Tianyu
Zhan, Jian
Dong, Zishuang
author_sort Zhao, Wei
collection PubMed
description OBJECTIVES: Hypertrophic cardiomyopathy (HCM) is the most common hereditary cardiomyopathy and immune infiltration is considered an indispensable factor involved in its pathogenesis. In this study, we attempted to combine bulk sequencing and single-cell sequencing to map the immune infiltration-related genes in hypertrophic cardiomyopathy. METHODS: The GSE36961, GSE160997, and GSE122930 datasets were obtained from the Gene Expression Omnibus database. The compositional patterns of the 18 types of immune cell fraction and pathway enrichment score in control and HCM patients were estimated based on the GSE36961 cohort using xCell algorithm. The Weighted Gene Coexpression Network Analysis (WGCNA) was performed to identify genes associated with immune infiltration for hypertrophic cardiomyopathy. The area under the curve (AUC) value was obtained and used to evaluate the discriminatory ability of common immune-related DEGs. “NetworkAnalyst” platform was used to identify TF-gene and TF-miRNA interaction with identified common genes. Heat map was used to determine the association between common DEGs and various immune cells. RESULTS: Immune infiltration analysis by the xCell algorithm showed a higher level of CD8+ naive T cells, CD8+ T cells, as well as a lower level of activated dendritic cells (aDC), dendritic cells (DC), immature dendritic cells (iDC), conventional dendritic cells (cDC), macrophages, M1 macrophages, monocytes, and NKT cell in HCM compared with the control group in GSE36961 dataset. aDC, macrophages, and M1 macrophages were the top three discriminators between HCM and control groups with the area under the curve (AUC) of 0.907, 0.867, and 0.941. WGCNA analysis showed that 1258 immune-related genes were included in four different modules. Of these modules, the turquoise module showed a pivotal correlation with HCM. 13 common immune-related DEGs were found by intersecting common DEGs in GSE36961 and GSE160997 datasets with genes from the genes in turquoise module. 5 hub immune-related genes (S100A9, TYROBP, FCER1G, CD14, and S100A8) were identified by protein interaction network. Through analysis of single-cell sequencing data, S100a9, TYROBP, FCER1G, and S100a8 were mainly expressed by infiltrated M1 proinflammatory cells, especially Ccr2-M1 proinflammatory macrophage cells in the heart immune microenvironment while Cd14 was expressed by infiltrated M1 proinflammatory macrophage cells and M2 macrophages in transverse aortic constriction (TAC) mice at 1 week. Higher M2 macrophage and M1 proinflammatory macrophage infiltration as well as lower Ccr2-M1 proinflammatory macrophage and dendritic cells were shown in TAC 1week mice compared with sham mice. CONCLUSIONS: There was a difference in immune infiltration between HCM patients and normal groups. aDC, macrophages, and M1 macrophages were the top three discriminator immune cell subsets between HCM and control groups. S100A9, TYROBP, FCER1G, CD14, and S100A8 were identified as potential biomarkers to discriminate HCM from the control group. S100a9, TYROBP, FCER1G, and S100a8 were mainly expressed by infiltrated M1 proinflammatory cells, especially Ccr2-M1 proinflammatory cells in the heart immune microenvironment while Cd14 was expressed by M2 macrophages in transverse aortic constriction (TAC) mice at 1 week.
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spelling pubmed-95533292022-10-12 Identification of the Immune Status of Hypertrophic Cardiomyopathy by Integrated Analysis of Bulk- and Single-Cell RNA Sequencing Data Zhao, Wei Wu, Tianyu Zhan, Jian Dong, Zishuang Comput Math Methods Med Research Article OBJECTIVES: Hypertrophic cardiomyopathy (HCM) is the most common hereditary cardiomyopathy and immune infiltration is considered an indispensable factor involved in its pathogenesis. In this study, we attempted to combine bulk sequencing and single-cell sequencing to map the immune infiltration-related genes in hypertrophic cardiomyopathy. METHODS: The GSE36961, GSE160997, and GSE122930 datasets were obtained from the Gene Expression Omnibus database. The compositional patterns of the 18 types of immune cell fraction and pathway enrichment score in control and HCM patients were estimated based on the GSE36961 cohort using xCell algorithm. The Weighted Gene Coexpression Network Analysis (WGCNA) was performed to identify genes associated with immune infiltration for hypertrophic cardiomyopathy. The area under the curve (AUC) value was obtained and used to evaluate the discriminatory ability of common immune-related DEGs. “NetworkAnalyst” platform was used to identify TF-gene and TF-miRNA interaction with identified common genes. Heat map was used to determine the association between common DEGs and various immune cells. RESULTS: Immune infiltration analysis by the xCell algorithm showed a higher level of CD8+ naive T cells, CD8+ T cells, as well as a lower level of activated dendritic cells (aDC), dendritic cells (DC), immature dendritic cells (iDC), conventional dendritic cells (cDC), macrophages, M1 macrophages, monocytes, and NKT cell in HCM compared with the control group in GSE36961 dataset. aDC, macrophages, and M1 macrophages were the top three discriminators between HCM and control groups with the area under the curve (AUC) of 0.907, 0.867, and 0.941. WGCNA analysis showed that 1258 immune-related genes were included in four different modules. Of these modules, the turquoise module showed a pivotal correlation with HCM. 13 common immune-related DEGs were found by intersecting common DEGs in GSE36961 and GSE160997 datasets with genes from the genes in turquoise module. 5 hub immune-related genes (S100A9, TYROBP, FCER1G, CD14, and S100A8) were identified by protein interaction network. Through analysis of single-cell sequencing data, S100a9, TYROBP, FCER1G, and S100a8 were mainly expressed by infiltrated M1 proinflammatory cells, especially Ccr2-M1 proinflammatory macrophage cells in the heart immune microenvironment while Cd14 was expressed by infiltrated M1 proinflammatory macrophage cells and M2 macrophages in transverse aortic constriction (TAC) mice at 1 week. Higher M2 macrophage and M1 proinflammatory macrophage infiltration as well as lower Ccr2-M1 proinflammatory macrophage and dendritic cells were shown in TAC 1week mice compared with sham mice. CONCLUSIONS: There was a difference in immune infiltration between HCM patients and normal groups. aDC, macrophages, and M1 macrophages were the top three discriminator immune cell subsets between HCM and control groups. S100A9, TYROBP, FCER1G, CD14, and S100A8 were identified as potential biomarkers to discriminate HCM from the control group. S100a9, TYROBP, FCER1G, and S100a8 were mainly expressed by infiltrated M1 proinflammatory cells, especially Ccr2-M1 proinflammatory cells in the heart immune microenvironment while Cd14 was expressed by M2 macrophages in transverse aortic constriction (TAC) mice at 1 week. Hindawi 2022-10-04 /pmc/articles/PMC9553329/ /pubmed/36238494 http://dx.doi.org/10.1155/2022/7153491 Text en Copyright © 2022 Wei Zhao et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zhao, Wei
Wu, Tianyu
Zhan, Jian
Dong, Zishuang
Identification of the Immune Status of Hypertrophic Cardiomyopathy by Integrated Analysis of Bulk- and Single-Cell RNA Sequencing Data
title Identification of the Immune Status of Hypertrophic Cardiomyopathy by Integrated Analysis of Bulk- and Single-Cell RNA Sequencing Data
title_full Identification of the Immune Status of Hypertrophic Cardiomyopathy by Integrated Analysis of Bulk- and Single-Cell RNA Sequencing Data
title_fullStr Identification of the Immune Status of Hypertrophic Cardiomyopathy by Integrated Analysis of Bulk- and Single-Cell RNA Sequencing Data
title_full_unstemmed Identification of the Immune Status of Hypertrophic Cardiomyopathy by Integrated Analysis of Bulk- and Single-Cell RNA Sequencing Data
title_short Identification of the Immune Status of Hypertrophic Cardiomyopathy by Integrated Analysis of Bulk- and Single-Cell RNA Sequencing Data
title_sort identification of the immune status of hypertrophic cardiomyopathy by integrated analysis of bulk- and single-cell rna sequencing data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9553329/
https://www.ncbi.nlm.nih.gov/pubmed/36238494
http://dx.doi.org/10.1155/2022/7153491
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