Graves’ ophthalmopathy (GO) is an extrathyroidal complication of Graves’ hyperthyroidism. Orbital fibroblast, an important cell in the pathogenesis of GO, is responsible for GO characteristics during active and inactive stages; however, information on the extensive profiles and the mechanistic regulations behind orbital fibroblast phenotypes are currently limited. The aim of this study was to compare the proteome profile of orbital fibroblasts isolated from inactive GO, active GO and healthy control. The proteome profile was further integrated with global DNA methylation data to identify this epigenetics regulation involved in the pathogenesis of GO. Methods Orbital fibroblasts culture isolated from five inactive GO, four active GO and five controls were cultured for total protein and DNA extraction. The labelled and fractionated proteins were analyzed with a liquid chromatography tandem-mass spectrometer (LC-MS/MS). On the other hand, the bisulphite-treated DNA was measured with the Illumina Infinium Human Methylation 450K beadchip. Proteome and methylation data were validated by real-time quantitative (RQ)-PCR. Network, pathway and functional analysis were performed by Ingenuity (Qiagen). Results Orbital fibroblasts from active GO displayed overexpression of proteins typically involved with inflammation, cellular proliferation, hyaluronan synthesis and adipogenesis, while several proteins linked to extracellular matrix (ECM) biology and fibrotic disease were overexpressed in orbital fibroblasts from inactive GO. The DNA methylation patterns were similar in healthy control and inactive GO orbital fibroblasts which were distinct from active GO orbital fibroblasts. In orbital fibroblasts from active GO hypermethylated genes link to inflammation while those genes hypomethylated are involved in adipogenesis and autoimmune-related genes. For the network analysis, overlapped between hypermethylated and hypomethylated genes were observed including NF-B, ERK1/2, Alp, RNA polymerase II, Akt and IFNα. In addition, NF-κB, Akt and IFNα were also identified in networks from the differentially expressed proteins. In general, poor correlation between protein expression, DNA methylation and mRNA expression in our study was observed.