Identification of clinical characteristics biomarkers for rheumatoid arthritis through targeted DNA methylation sequencing.

OBJECTIVES: Rheumatoid arthritis (RA) is a complex disease with a challenging diagnosis, especially in seronegative patients. The aim of this study is to investigate whether the methylation sites associated with the overall immune response in RA can assist in clinical diagnosis, using targeted methylation sequencing technology on peripheral venous blood samples. METHODS: The study enrolled 241 RA patients, 30 osteoarthritis patients (OA), and 30 healthy volunteers control (HC). Fifty significant cytosine guanine (CG) sites between undifferentiated arthritis and RA were selected and analyzed using targeted DNA methylation sequencing. Logistic regression models were used to establish diagnostic models for different clinical features of RA, and six machine learning methods (logit model, random forest, support vector machine, adaboost, naive bayes, and learning vector quantization) were used to construct clinical diagnostic models for different subtypes of RA. Least absolute shrinkage and selection operator regression and detrended correspondence analysis were utilized to screen for important CGs. Spearman correlation was used to calculate the correlation coefficient. RESULTS: The study identified 16 important CG sites, including tumor necrosis factort receptor associated factor 5 (TRAF5) (chr1:211500151), mothers against decapentaplegic homolog 3 (SMAD3) (chr15:67357339), tumor endothelial marker 1 (CD248) (chr11:66083766), lysosomal trafficking regulator (LYST) (chr1:235998714), PR domain zinc finger protein 16 (PRDM16) (chr1:3307069), A-kinase anchoring protein 10 (AKAP10) (chr17:19850460), G protein subunit gamma 7 (GNG7) (chr19:2546620), yes1 associated transcriptional regulator (YAP1) (chr11:101980632), PRDM16 (chr1:3163969), histone deacetylase complex subunit sin3a (SIN3A) (chr15:75747445), prenylated rab acceptor protein 2 (ARL6IP5) (chr3:69134502), mitogen-activated protein kinase kinase kinase 4 (MAP3K4) (chr6:161412392), wnt family member 7A (WNT7A) (chr3:13895991), inhibin subunit beta B (INHBB) (chr2:121107018), deoxyribonucleic acid replication helicase/nuclease 2 (DNA2) (chr10:70231628) and chromosome 14 open reading frame 180 (C14orf180) (chr14:105055171). Seven CG sites showed abnormal changes between the three groups (P < 0.05), and 16 CG sites were significantly correlated with common clinical indicators (P < 0.05). Diagnostic models constructed using different CG sites had an area under the receiver operating characteristic curve (AUC) range of 0.64-0.78 for high-level clinical indicators of high clinical value, with specificity ranging from 0.42 to 0.77 and sensitivity ranging from 0.57 to 0.88. The AUC range for low-level clinical indicators of high clinical value was 0.63-0.72, with specificity ranging from 0.48 to 0.74 and sensitivity ranging from 0.72 to 0.88. Diagnostic models constructed using different CG sites showed good overall diagnostic accuracy for the four subtypes of RA, with an accuracy range of 0.61-0.96, a balanced accuracy range of 0.46-0.94, and an AUC range of 0.46-0.94. CONCLUSIONS: This study identified potential clinical diagnostic biomarkers for RA and provided novel insights into the diagnosis and subtyping of RA. The use of targeted deoxyribonucleic acid (DNA) methylation sequencing and machine learning methods for establishing diagnostic models for different clinical features and subtypes of RA is innovative and can improve the accuracy and efficiency of RA diagnosis.

Circulating methylation level of HTR2A is associated with inflammation and disease activity in rheumatoid arthritis.

Objectives: HTR2A is previously identified as a susceptibility gene for rheumatoid arthritis (RA). In this study, we performed the association analysis between DNA methylation of HTR2A with RA within peripheral blood samples. Methods: We enrolled peripheral blood samples from 235 patients with RA, 30 osteoarthritis (OA) patients, and 30 healthy controls. The DNA methylation levels of about 218 bp from chr13: 46898190 to chr13: 46897973 (GRCh38/hg38) around HTR2A cg15692052 from patients were analyzed by targeted methylation sequencing. Results: We measured methylation status for 7 CpGs in the promoter region of HTR2A and obseved overall methylation status are signficantly increased in RA compared with normal inviduals (FDR= 9.05 x 10-5). The average cg15692052 methylation levels (methylation score) showed a positive correlation with CRP (r=0.15, P=0.023). Compared with the OA group or HC group, the proportion of haplotypes CCCCCCC (FDR=0.02 and 2.81 x 10-6) is signficantly increased while TTTTTCC (FDR =0.01) and TTTTTTT(FDR =6.92 x 10-3) are significantly decreased in RA. We find methylation haplotypes combining with RF and CCP could signficantly enhance the performance of the diagnosing RA and its comorbidities (hypertension, interstitial lung disease, and osteoporosis), especially in interstitial lung disease. Conclusions: In our study, we found signficant hypermethylation of promoter region of HTR2A which indicates the potential clinical diagnostic role in rheumatoid arthritis.