Identification of copper death-associated molecular clusters and immunological profiles in rheumatoid arthritis

Frontiers in Immunology

Immunology

Wenlong Su¹  Jinhua Hu¹  Wentao Guo¹  Yu Zhou²  Songchuan Su³  Liqi Ng⁴  Chaozong Liu⁴  Jinghong Zhong⁵  Xin Li⁵  Qing Zhao⁶ 

[1] College of Pharmacy, Changchun University of Chinese Medicine, Changchun, China;College of Traditional Chinese Medicine, Changchun University of Chinese Medicine, Changchun, China;Foot & Ankle Surgery, Chongqing Orthopedic Hospital of Traditional Chinese Medicine, Chongqing, China;Foot & Ankle Surgery, Chongqing Orthopedic Hospital of Traditional Chinese Medicine, Chongqing, China;Institute of Orthopaedic and Musculoskeletal Science, University College London, Royal National Orthopaedic Hospital, London, United Kingdom;Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun, China;School of Health Management, Tianjin University of Chinese Medicine, Tianjin, China;

关键词: rheumatoid arthritis;    copper death;    machine learning;    immune infiltration;    predictive models;   

DOI  :  10.3389/fimmu.2023.1103509

 received in 2022-11-20, accepted in 2023-01-30,  发布年份 2023

来源: Frontiers

【 摘 要 】

ObjectiveAn analysis of the relationship between rheumatoid arthritis (RA) and copper death-related genes (CRG) was explored based on the GEO dataset.MethodsBased on the differential gene expression profiles in the GSE93272 dataset, their relationship to CRG and immune signature were analysed. Using 232 RA samples, molecular clusters with CRG were delineated and analysed for expression and immune infiltration. Genes specific to the CRGcluster were identified by the WGCNA algorithm. Four machine learning models were then built and validated after selecting the optimal model to obtain the significant predicted genes, and validated by constructing RA rat models.ResultsThe location of the 13 CRGs on the chromosome was determined and, except for GCSH. LIPT1, FDX1, DLD, DBT, LIAS and ATP7A were expressed at significantly higher levels in RA samples than in non-RA, and DLST was significantly lower. RA samples were significantly expressed in immune cells such as B cells memory and differentially expressed genes such as LIPT1 were also strongly associated with the presence of immune infiltration. Two copper death-related molecular clusters were identified in RA samples. A higher level of immune infiltration and expression of CRGcluster C2 was found in the RA population. There were 314 crossover genes between the 2 molecular clusters, which were further divided into two molecular clusters. A significant difference in immune infiltration and expression levels was found between the two. Based on the five genes obtained from the RF model (AUC = 0.843), the Nomogram model, calibration curve and DCA also demonstrated their accuracy in predicting RA subtypes. The expression levels of the five genes were significantly higher in RA samples than in non-RA, and the ROC curves demonstrated their better predictive effect. Identification of predictive genes by RA animal model experiments was also confirmed.ConclusionThis study provides some insight into the correlation between rheumatoid arthritis and copper mortality, as well as a predictive model that is expected to support the development of targeted treatment options in the future.

【 授权许可】

Unknown   
Copyright © 2023 Zhou, Li, Ng, Zhao, Guo, Hu, Zhong, Su, Liu and Su