AUTHOR=Yu Rongguo , Zhang Jiayu , Zhuo Youguang , Hong Xu , Ye Jie , Tang Susu , Zhang Yiyuan 

TITLE=Identification of Diagnostic Signatures and Immune Cell Infiltration Characteristics in Rheumatoid Arthritis by Integrating Bioinformatic Analysis and Machine-Learning Strategies

JOURNAL=Frontiers in Immunology

VOLUME=Volume 12 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2021.724934

DOI=10.3389/fimmu.2021.724934

ISSN=1664-3224

ABSTRACT=Abstract
Background
Rheumatoid arthritis (RA) refers to an autoimmune rheumatic disease carrying great pressure on patient and society. Early RA diagnosis critically improves the prevention of disease progression and the selection of optimal therapeutic strategies. In the present study, the aim was at exploring RA’s diagnostic signature and the effect exerted by infiltration of immune cells in this pathology.

Methods
GEO database provided 3 gene expressions datasets. Firstly, this study adopted R software for identifying genes with differential expression and conducting functional correlation analyses. Subsequently, we integrated bioinformatic analysis and machine-learning strategies for screening and determining RA’s diagnostic signature and further verify by qRT-PCR. The diagnostic values were assessed through receiver operating characteristic (ROC) curves. Moreover, this study employed CIBERSORT website for assessing the inflammatory state of RA, and an investigation was conducted on the relationship of diagnostic signature and infiltrating immune cells.

Results
On the whole, 54 robust DEGs received the recognition. LSP1, GNLY and MEOX2 (AUC = 0.955) were regarded as RA’s diagnostic markers and showed their statistically significant difference by qRT-PCR. As indicated from the immune cell infiltration analysis, resting NK cells, neutrophils, activated NK cells, T cells CD8, memory B cells and M0 macrophages may be involved in the development of RA. Additionally, all diagnostic signatures were different degrees of correlation with immune cells.

Conclusions
In conclusion, LSP1, GNLY and MEOX2 are likely to be available in terms of diagnosing and treating RA, and the infiltration of immune cells critically impacts RA development and occurrence.