CD3D, GZMK, and KLRB1 Are Potential Markers for Early Diagnosis of Rheumatoid Arthritis, Especially in Anti-Citrullinated Protein Antibody-Negative Patients.

Junqin Lu,Jian Zhou,Shi Huipeng,Yihui Bi,Yapeng Zhu,Wenxiu Duan

doi:10.3389/fphar.2021.726529

Abstract

Early diagnosis and monitoring of rheumatoid arthritis (RA) progress are critical for effective treatment. In clinic, the detection of rheumatoid factor (RF) and anti-citrullinated protein antibodies (ACPA) are usually combined to diagnose early RA. However, the poor specificity of RF and high heterogeneity of ACPA make the early diagnosis of RA still challenging. Bioinformatics analysis based on high-throughput omics is an emerging method to identify novel and effective biomarkers, which has been widely used in many diseases. Herein, utilizing an integrated strategy based on expression correlation analysis and weighted gene coexpression network analysis (WGCNA), we identified 76 RA-trait different expression genes (DEGs). Combined with protein-protein interaction (PPI) network construction and clustering, new hub genes associated in RA synovia, CD3D, GZMK, and KLRB1, were identified. We verified the specificity of these genes in the synovium of RA patients through three external datasets. We also observed high sensitivity and specificity of them for ACPA-negative patients. CD3D, GZMK, and KLRB1 are potentially key mediators of RA pathogenesis and markers for RA diagnosis.

Highlights

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by chronic inflammation in the synovium tissue of joints (McInnes and Schett, 2011; Gibofsky, 2014; Malmstrom et al, 2017; Smolen et al, 2018)
Followed by protein-protein interaction (PPI) network construction and hub genes selection, we identified CD3D, GZMK, and KLRB1 as three novel hub genes with rheumatoid arthritis (RA) characteristics
Multivariate Principal component analysis (PCA) showed that when classified according to the sample type, the integrated dataset was staggered with poor discrimination (Figure 1B)

Summary

Introduction

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by chronic inflammation in the synovium tissue of joints (McInnes and Schett, 2011; Gibofsky, 2014; Malmstrom et al, 2017; Smolen et al, 2018). A variety of immune cells and cytokines are involved in synovial inflammation, which leads to the destruction of soft tissues, cartilage, and bones around the joints (Zhang et al, 2019). RA clearly begins months to years when autoimmune response persists and is seronegative before it becomes a manifest polyarthritis and this is known as “preclinical RA.”. The treatment of RA is usually only effective in the early stage, and many patients gradually lose their drug response as the disease progresses (Guo et al, 2018). Some serum biomarkers like rheumatoid factor (RF) (MacGregor et al, 2000; Onuora, 2012), anti-citrullinated protein antibody (ACPA) (Padyukov et al, 2011; Stahl et al, 2012), anti-cyclic citrullinated peptide (anti-CCP) antibody (Zendman et al, 2006), C-reactive protein

Methods

Results

Conclusion