{"title":"转录组分类揭示特发性肺纤维化的分子亚群。","authors":"Yuxia Liu, Chang Xu, Wenxin Gao, Huaqiong Liu, Chenglong Li, Mingwei Chen","doi":"10.1155/2022/7448481","DOIUrl":null,"url":null,"abstract":"<p><p>Idiopathic pulmonary fibrosis (IPF) is a disease of progressive lung fibrosis with a high mortality rate. This study aimed to uncover the underlying molecular features for different types of IPF. IPF microarray datasets were retrieved from GEO databases. Weighted gene co-expression analysis (WGCNA) was used and identified subgroup-specific WGCNA modules. Infiltration-level immune cells in different subgroups of microenvironments were analyzed with CIBERSORT algorithms. The result is we classified 173 IPF cases into two subgroups based on gene expression profiles, which were retrieved from the GEO databases. The SGRQ score and age were significantly higher in C2 than in C1. Using WGCNA, five subgroup-specific modules were identified. M4 was mainly enriched by MAPK signaling, which was mainly expressed in C2; M1, M2, and M3 were mainly enriched by metabolic pathways and Chemokine signaling, and the pathway of M5 was phagosome inflammation; M1, M2, M3, and M5 were mainly expressed in C1. Utilizing the CIBERSORT, we showed that the number of M1 macrophage cells, CD8 T cells, regulatory T cells (Tregs), and Plasma cells was significantly different between C1 and C2. We found the molecular subgroups of IPF revealed that cases from different subgroups may have their unique patterns and provide novel information to understand the mechanisms of IPF itself.</p>","PeriodicalId":12778,"journal":{"name":"Genetics research","volume":" ","pages":"7448481"},"PeriodicalIF":1.4000,"publicationDate":"2022-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308534/pdf/","citationCount":"0","resultStr":"{\"title\":\"Transcriptome Classification Reveals Molecular Subgroups in Idiopathic Pulmonary Fibrosis.\",\"authors\":\"Yuxia Liu, Chang Xu, Wenxin Gao, Huaqiong Liu, Chenglong Li, Mingwei Chen\",\"doi\":\"10.1155/2022/7448481\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Idiopathic pulmonary fibrosis (IPF) is a disease of progressive lung fibrosis with a high mortality rate. This study aimed to uncover the underlying molecular features for different types of IPF. IPF microarray datasets were retrieved from GEO databases. Weighted gene co-expression analysis (WGCNA) was used and identified subgroup-specific WGCNA modules. Infiltration-level immune cells in different subgroups of microenvironments were analyzed with CIBERSORT algorithms. The result is we classified 173 IPF cases into two subgroups based on gene expression profiles, which were retrieved from the GEO databases. The SGRQ score and age were significantly higher in C2 than in C1. Using WGCNA, five subgroup-specific modules were identified. M4 was mainly enriched by MAPK signaling, which was mainly expressed in C2; M1, M2, and M3 were mainly enriched by metabolic pathways and Chemokine signaling, and the pathway of M5 was phagosome inflammation; M1, M2, M3, and M5 were mainly expressed in C1. Utilizing the CIBERSORT, we showed that the number of M1 macrophage cells, CD8 T cells, regulatory T cells (Tregs), and Plasma cells was significantly different between C1 and C2. We found the molecular subgroups of IPF revealed that cases from different subgroups may have their unique patterns and provide novel information to understand the mechanisms of IPF itself.</p>\",\"PeriodicalId\":12778,\"journal\":{\"name\":\"Genetics research\",\"volume\":\" \",\"pages\":\"7448481\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2022-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308534/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Genetics research\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1155/2022/7448481\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q4\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genetics research","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1155/2022/7448481","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/1/1 0:00:00","PubModel":"eCollection","JCR":"Q4","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
Transcriptome Classification Reveals Molecular Subgroups in Idiopathic Pulmonary Fibrosis.
Idiopathic pulmonary fibrosis (IPF) is a disease of progressive lung fibrosis with a high mortality rate. This study aimed to uncover the underlying molecular features for different types of IPF. IPF microarray datasets were retrieved from GEO databases. Weighted gene co-expression analysis (WGCNA) was used and identified subgroup-specific WGCNA modules. Infiltration-level immune cells in different subgroups of microenvironments were analyzed with CIBERSORT algorithms. The result is we classified 173 IPF cases into two subgroups based on gene expression profiles, which were retrieved from the GEO databases. The SGRQ score and age were significantly higher in C2 than in C1. Using WGCNA, five subgroup-specific modules were identified. M4 was mainly enriched by MAPK signaling, which was mainly expressed in C2; M1, M2, and M3 were mainly enriched by metabolic pathways and Chemokine signaling, and the pathway of M5 was phagosome inflammation; M1, M2, M3, and M5 were mainly expressed in C1. Utilizing the CIBERSORT, we showed that the number of M1 macrophage cells, CD8 T cells, regulatory T cells (Tregs), and Plasma cells was significantly different between C1 and C2. We found the molecular subgroups of IPF revealed that cases from different subgroups may have their unique patterns and provide novel information to understand the mechanisms of IPF itself.
期刊介绍:
Genetics Research is a key forum for original research on all aspects of human and animal genetics, reporting key findings on genomes, genes, mutations and molecular interactions, extending out to developmental, evolutionary, and population genetics as well as ethical, legal and social aspects. Our aim is to lead to a better understanding of genetic processes in health and disease. The journal focuses on the use of new technologies, such as next generation sequencing together with bioinformatics analysis, to produce increasingly detailed views of how genes function in tissues and how these genes perform, individually or collectively, in normal development and disease aetiology. The journal publishes original work, review articles, short papers, computational studies, and novel methods and techniques in research covering humans and well-established genetic organisms. Key subject areas include medical genetics, genomics, human evolutionary and population genetics, bioinformatics, genetics of complex traits, molecular and developmental genetics, Evo-Devo, quantitative and statistical genetics, behavioural genetics and environmental genetics. The breadth and quality of research make the journal an invaluable resource for medical geneticists, molecular biologists, bioinformaticians and researchers involved in genetic basis of diseases, evolutionary and developmental studies.