Screening of osteoarthritis diagnostic markers based on immune-related genes and immune infiltration

Abstract Osteoarthritis (OA) is a chronic degenerative disease of the bone and joints. Immune-related genes and immune cell infiltration are important in OA development. We analyzed immune-related genes and immune infiltrates to identify OA diagnostic markers. The datasets GSE51588, GSE55235, GSE554...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Wen-Hua Yuan, Qi-Qi Xie, Ke-Ping Wang, Wei Shen, Xiao-Fei Feng, Zheng Liu, Jin-Tao Shi, Xiao-Bo Zhang, Kai Zhang, Ya-Jun Deng, Hai-Yu Zhou
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/086cea24440a4b17ac1002a105dc661e
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:086cea24440a4b17ac1002a105dc661e
record_format	dspace
spelling	oai:doaj.org-article:086cea24440a4b17ac1002a105dc661e2021-12-02T18:18:06ZScreening of osteoarthritis diagnostic markers based on immune-related genes and immune infiltration10.1038/s41598-021-86319-72045-2322https://doaj.org/article/086cea24440a4b17ac1002a105dc661e2021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-86319-7https://doaj.org/toc/2045-2322Abstract Osteoarthritis (OA) is a chronic degenerative disease of the bone and joints. Immune-related genes and immune cell infiltration are important in OA development. We analyzed immune-related genes and immune infiltrates to identify OA diagnostic markers. The datasets GSE51588, GSE55235, GSE55457, GSE82107, and GSE114007 were downloaded from the Gene Expression Omnibus database. First, R software was used to identify differentially expressed genes (DEGs) and differentially expressed immune-related genes (DEIRGs), and functional correlation analysis was conducted. Second, CIBERSORT was used to evaluate infiltration of immune cells in OA tissue. Finally, the least absolute shrinkage and selection operator logistic regression algorithm and support vector machine-recurrent feature elimination algorithm were used to screen and verify diagnostic markers of OA. A total of 711 DEGs and 270 DEIRGs were identified in this study. Functional enrichment analysis showed that the DEGs and DEIRGs are closely related to cellular calcium ion homeostasis, ion channel complexes, chemokine signaling pathways, and JAK-STAT signaling pathways. Differential analysis of immune cell infiltration showed that M1 macrophage infiltration was increased but that mast cell and neutrophil infiltration were decreased in OA samples. The machine learning algorithm cross-identified 15 biomarkers (BTC, PSMD8, TLR3, IL7, APOD, CIITA, IFIH1, CDC42, FGF9, TNFAIP3, CX3CR1, ERAP2, SEMA3D, MPO, and plasma cells). According to pass validation, all 15 biomarkers had high diagnostic efficacy (AUC > 0.7), and the diagnostic efficiency was higher when the 15 biomarkers were fitted into one variable (AUC = 0.758). We developed 15 biomarkers for OA diagnosis. The findings provide a new understanding of the molecular mechanism of OA from the perspective of immunology.Wen-Hua YuanQi-Qi XieKe-Ping WangWei ShenXiao-Fei FengZheng LiuJin-Tao ShiXiao-Bo ZhangKai ZhangYa-Jun DengHai-Yu ZhouNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Wen-Hua Yuan Qi-Qi Xie Ke-Ping Wang Wei Shen Xiao-Fei Feng Zheng Liu Jin-Tao Shi Xiao-Bo Zhang Kai Zhang Ya-Jun Deng Hai-Yu Zhou Screening of osteoarthritis diagnostic markers based on immune-related genes and immune infiltration
description	Abstract Osteoarthritis (OA) is a chronic degenerative disease of the bone and joints. Immune-related genes and immune cell infiltration are important in OA development. We analyzed immune-related genes and immune infiltrates to identify OA diagnostic markers. The datasets GSE51588, GSE55235, GSE55457, GSE82107, and GSE114007 were downloaded from the Gene Expression Omnibus database. First, R software was used to identify differentially expressed genes (DEGs) and differentially expressed immune-related genes (DEIRGs), and functional correlation analysis was conducted. Second, CIBERSORT was used to evaluate infiltration of immune cells in OA tissue. Finally, the least absolute shrinkage and selection operator logistic regression algorithm and support vector machine-recurrent feature elimination algorithm were used to screen and verify diagnostic markers of OA. A total of 711 DEGs and 270 DEIRGs were identified in this study. Functional enrichment analysis showed that the DEGs and DEIRGs are closely related to cellular calcium ion homeostasis, ion channel complexes, chemokine signaling pathways, and JAK-STAT signaling pathways. Differential analysis of immune cell infiltration showed that M1 macrophage infiltration was increased but that mast cell and neutrophil infiltration were decreased in OA samples. The machine learning algorithm cross-identified 15 biomarkers (BTC, PSMD8, TLR3, IL7, APOD, CIITA, IFIH1, CDC42, FGF9, TNFAIP3, CX3CR1, ERAP2, SEMA3D, MPO, and plasma cells). According to pass validation, all 15 biomarkers had high diagnostic efficacy (AUC > 0.7), and the diagnostic efficiency was higher when the 15 biomarkers were fitted into one variable (AUC = 0.758). We developed 15 biomarkers for OA diagnosis. The findings provide a new understanding of the molecular mechanism of OA from the perspective of immunology.
format	article
author	Wen-Hua Yuan Qi-Qi Xie Ke-Ping Wang Wei Shen Xiao-Fei Feng Zheng Liu Jin-Tao Shi Xiao-Bo Zhang Kai Zhang Ya-Jun Deng Hai-Yu Zhou
author_facet	Wen-Hua Yuan Qi-Qi Xie Ke-Ping Wang Wei Shen Xiao-Fei Feng Zheng Liu Jin-Tao Shi Xiao-Bo Zhang Kai Zhang Ya-Jun Deng Hai-Yu Zhou
author_sort	Wen-Hua Yuan
title	Screening of osteoarthritis diagnostic markers based on immune-related genes and immune infiltration
title_short	Screening of osteoarthritis diagnostic markers based on immune-related genes and immune infiltration
title_full	Screening of osteoarthritis diagnostic markers based on immune-related genes and immune infiltration
title_fullStr	Screening of osteoarthritis diagnostic markers based on immune-related genes and immune infiltration
title_full_unstemmed	Screening of osteoarthritis diagnostic markers based on immune-related genes and immune infiltration
title_sort	screening of osteoarthritis diagnostic markers based on immune-related genes and immune infiltration
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/086cea24440a4b17ac1002a105dc661e
work_keys_str_mv	AT wenhuayuan screeningofosteoarthritisdiagnosticmarkersbasedonimmunerelatedgenesandimmuneinfiltration AT qiqixie screeningofosteoarthritisdiagnosticmarkersbasedonimmunerelatedgenesandimmuneinfiltration AT kepingwang screeningofosteoarthritisdiagnosticmarkersbasedonimmunerelatedgenesandimmuneinfiltration AT weishen screeningofosteoarthritisdiagnosticmarkersbasedonimmunerelatedgenesandimmuneinfiltration AT xiaofeifeng screeningofosteoarthritisdiagnosticmarkersbasedonimmunerelatedgenesandimmuneinfiltration AT zhengliu screeningofosteoarthritisdiagnosticmarkersbasedonimmunerelatedgenesandimmuneinfiltration AT jintaoshi screeningofosteoarthritisdiagnosticmarkersbasedonimmunerelatedgenesandimmuneinfiltration AT xiaobozhang screeningofosteoarthritisdiagnosticmarkersbasedonimmunerelatedgenesandimmuneinfiltration AT kaizhang screeningofosteoarthritisdiagnosticmarkersbasedonimmunerelatedgenesandimmuneinfiltration AT yajundeng screeningofosteoarthritisdiagnosticmarkersbasedonimmunerelatedgenesandimmuneinfiltration AT haiyuzhou screeningofosteoarthritisdiagnosticmarkersbasedonimmunerelatedgenesandimmuneinfiltration
_version_	1718378256301817856

Screening of osteoarthritis diagnostic markers based on immune-related genes and immune infiltration

Ejemplares similares