Identification and validation of hub m7G-related genes and infiltrating immune cells in osteoarthritis based on integrated computational and bioinformatics analysis

Abstract Background Osteoarthritis (OA) is a joint disease closely associated with synovial tissue inflammation, with the severity of synovitis impacting disease progression. m7G RNA methylation is critical in RNA processing, metabolism, and function, but its role in OA synovial tissue is not well u...

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Main Authors: Zhenhui Huo, Chongyi Fan, Kehan Li, Chenyue Xu, Yingzhen Niu, Fei Wang
Format: Article
Language:English
Published: BMC 2025-04-01
Series:BMC Musculoskeletal Disorders
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Online Access:https://doi.org/10.1186/s12891-025-08539-6
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author Zhenhui Huo
Chongyi Fan
Kehan Li
Chenyue Xu
Yingzhen Niu
Fei Wang
author_facet Zhenhui Huo
Chongyi Fan
Kehan Li
Chenyue Xu
Yingzhen Niu
Fei Wang
author_sort Zhenhui Huo
collection DOAJ
description Abstract Background Osteoarthritis (OA) is a joint disease closely associated with synovial tissue inflammation, with the severity of synovitis impacting disease progression. m7G RNA methylation is critical in RNA processing, metabolism, and function, but its role in OA synovial tissue is not well understood. This study explores the relationship between m7G methylation and immune infiltration in OA. Methods Data were obtained from the GEO database. Hub genes related to m7G were identified using differential expression and LASSO-Cox regression analysis, and a diagnostic model was developed. Functional enrichment, drug target prediction, and target gene-related miRNA prediction were performed for these genes. Immune cell infiltration was analyzed using the CIBERSORT algorithm, and unsupervised clustering analysis was conducted to examine immune infiltration patterns. RT-qPCR was used to validate hub gene expression. Results Seven m7G hub genes (SNUPN, RNMT, NUDT1, LSM1, LARP1, CYFIP2, and CYFIP1) were identified and used to develop a nomogram for OA risk prediction. Functional enrichment indicated involvement in mRNA metabolism and RNA transport. Differences in macrophage and T-cell infiltration were observed between OA and normal groups. Two distinct m7G immune infiltration patterns were identified, with significant microenvironment differences between clusters. RT-qPCR confirmed differential hub gene expression. Conclusion A diagnostic model based on seven m7G hub genes was developed, highlighting these genes as potential biomarkers and significant players in OA pathogenesis.
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spelling doaj-art-a4d90f9eb1574885ad5a975580646a492025-08-20T01:52:55ZengBMCBMC Musculoskeletal Disorders1471-24742025-04-0126111810.1186/s12891-025-08539-6Identification and validation of hub m7G-related genes and infiltrating immune cells in osteoarthritis based on integrated computational and bioinformatics analysisZhenhui Huo0Chongyi Fan1Kehan Li2Chenyue Xu3Yingzhen Niu4Fei Wang5Department of Orthopaedic Surgery, Third Hospital of Hebei Medical UniversityDepartment of Orthopedics, Aerospace Central HospitalDepartment of Orthopaedic Surgery, Third Hospital of Hebei Medical UniversityDepartment of Orthopaedic Surgery, Third Hospital of Hebei Medical UniversityDepartment of Orthopaedic Surgery, Third Hospital of Hebei Medical UniversityDepartment of Orthopaedic Surgery, Third Hospital of Hebei Medical UniversityAbstract Background Osteoarthritis (OA) is a joint disease closely associated with synovial tissue inflammation, with the severity of synovitis impacting disease progression. m7G RNA methylation is critical in RNA processing, metabolism, and function, but its role in OA synovial tissue is not well understood. This study explores the relationship between m7G methylation and immune infiltration in OA. Methods Data were obtained from the GEO database. Hub genes related to m7G were identified using differential expression and LASSO-Cox regression analysis, and a diagnostic model was developed. Functional enrichment, drug target prediction, and target gene-related miRNA prediction were performed for these genes. Immune cell infiltration was analyzed using the CIBERSORT algorithm, and unsupervised clustering analysis was conducted to examine immune infiltration patterns. RT-qPCR was used to validate hub gene expression. Results Seven m7G hub genes (SNUPN, RNMT, NUDT1, LSM1, LARP1, CYFIP2, and CYFIP1) were identified and used to develop a nomogram for OA risk prediction. Functional enrichment indicated involvement in mRNA metabolism and RNA transport. Differences in macrophage and T-cell infiltration were observed between OA and normal groups. Two distinct m7G immune infiltration patterns were identified, with significant microenvironment differences between clusters. RT-qPCR confirmed differential hub gene expression. Conclusion A diagnostic model based on seven m7G hub genes was developed, highlighting these genes as potential biomarkers and significant players in OA pathogenesis.https://doi.org/10.1186/s12891-025-08539-6OsteoarthritisBioinformaticsM7GImmune cell infiltrationDifferentially expressed genes
spellingShingle Zhenhui Huo
Chongyi Fan
Kehan Li
Chenyue Xu
Yingzhen Niu
Fei Wang
Identification and validation of hub m7G-related genes and infiltrating immune cells in osteoarthritis based on integrated computational and bioinformatics analysis
BMC Musculoskeletal Disorders
Osteoarthritis
Bioinformatics
M7G
Immune cell infiltration
Differentially expressed genes
title Identification and validation of hub m7G-related genes and infiltrating immune cells in osteoarthritis based on integrated computational and bioinformatics analysis
title_full Identification and validation of hub m7G-related genes and infiltrating immune cells in osteoarthritis based on integrated computational and bioinformatics analysis
title_fullStr Identification and validation of hub m7G-related genes and infiltrating immune cells in osteoarthritis based on integrated computational and bioinformatics analysis
title_full_unstemmed Identification and validation of hub m7G-related genes and infiltrating immune cells in osteoarthritis based on integrated computational and bioinformatics analysis
title_short Identification and validation of hub m7G-related genes and infiltrating immune cells in osteoarthritis based on integrated computational and bioinformatics analysis
title_sort identification and validation of hub m7g related genes and infiltrating immune cells in osteoarthritis based on integrated computational and bioinformatics analysis
topic Osteoarthritis
Bioinformatics
M7G
Immune cell infiltration
Differentially expressed genes
url https://doi.org/10.1186/s12891-025-08539-6
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AT kehanli identificationandvalidationofhubm7grelatedgenesandinfiltratingimmunecellsinosteoarthritisbasedonintegratedcomputationalandbioinformaticsanalysis
AT chenyuexu identificationandvalidationofhubm7grelatedgenesandinfiltratingimmunecellsinosteoarthritisbasedonintegratedcomputationalandbioinformaticsanalysis
AT yingzhenniu identificationandvalidationofhubm7grelatedgenesandinfiltratingimmunecellsinosteoarthritisbasedonintegratedcomputationalandbioinformaticsanalysis
AT feiwang identificationandvalidationofhubm7grelatedgenesandinfiltratingimmunecellsinosteoarthritisbasedonintegratedcomputationalandbioinformaticsanalysis