DNA methylation markers in peripheral blood for psoriatic arthritis.

BACKGROUND

The clinical manifestations of psoriatic arthritis (PsA) are highly heterogeneous and no reliable diagnostic biomarkers exist.

OBJECTIVE

We explored the role of DNA methylation CpG markers in the diagnosis of PsA.

METHODS

DNA methylation array was used to screen for differentially methylated sites (DMSs) in the discovery phase (PsA, n = 25; healthy controls [HCs], n = 19; psoriasis vulgaris [PsV], n = 20). In the validation phase, pyrosequencing was used to identify the DMSs in an expanded cohort (PsA, n = 60; HCs, n = 91; PsV, n = 48; rheumatoid arthritis [RA], n = 60). Logistic regression prediction models were established based on the identified DMSs for the diagnosis of PsA.

RESULTS

A total of 17 DMSs differentiating PsA and HCs as well as 11 DMSs differentiating PsA and PsV were screened in the discovery phase. A total of six DMSs (chr14: cg07940072, chr14: 38061320, chr9: cg15734589, chr6: cg12800266, chr3: cg12992827, chr6: cg24500972) differentiating PsA and HCs and two DMSs (chr12: cg16459382, chr2: cg16348668) differentiating PsA and PsV were identified using pyrosequencing. Three logistic regression prediction models were established based on the identified DMSs, which distinguished PsA, RA, PsV, and HCs (P < 0.001). The models performed well in differentiating PsA from HCs, RA, and PsV (AUC: 0.858, 0.851, and 0.976, respectively).

CONCLUSIONS

The models based on methylated CpG sites are useful for distinguishing patients with PsA from HCs and those with RA or PsV and are a highly sensitive and specific diagnostic biomarker for PsA.