AUTHOR=Jiang Mingyang , Liu Kaicheng , Lu Shenyi , Qiu Yue , Zou Xiaochong , Zhang Ke , Chen Chuanliang , Jike Yiji , Xie Mingjing , Dai Yongheng , Bo Zhandong 

TITLE=Verification of cuproptosis-related diagnostic model associated with immune infiltration in rheumatoid arthritis

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2023.1204926

DOI=10.3389/fendo.2023.1204926

ISSN=1664-2392

ABSTRACT=Background: Rheumatoid arthritis (RA) is a chronic autoimmune disease closely related to inflammation. Cuproptosis is a newly discovered unique type of cell death, and it has been found that it may play an essential role in the occurrence and development of RA. Therefore, we intend to explore the potential association between cuproptosis-related genes (CRGs) and RA to provide a new target for the treatment and prognosis of RA.
Methods: Download GSE93777 and GSE40888 datasets from the GEO database. Variance analysis was performed on the CRGs that had been reported. Then, the random forest (RF) model and nomogram of differentially expressed CRGs were constructed, and the ROC curve was used to evaluate the accuracy of the diagnostic model. Next, RA patients were subtyped by consensus clustering, and immune infiltration was performed in each subgroup to confirm the abundance of CRGs and immune cells. The expression levels of CRGs were verified by qRT-PCR.
Results: Eight differentially expressed CRGs (DLST, DLD, PDHB, PDHA1, ATP7A, CDKN2A, LIAS, DLAT) were screened out by differential analysis to construct an RF model. The ROC curve proved that this model had good diagnostic accuracy. Based on the above 8 significant CRGs, a nomogram model was built to predict effective and high-precision results. The consensus clustering method identified two CRG patterns. Most of the immune cells were enriched in cluster A, indicating that cluster A may be related to the development of RA. Finally, qRT-PCR verified the expression of 8 key genes, further confirming our findings.
Conclusions: The diagnosis model of RA based on the above 8 CRGs has excellent diagnostic potential. Based on these, patients can be divided into two different molecular subtypes; it is expected to develop a new treatment strategy for RA.