Osteoarthritis　(OA)　is　a　kind　of　chronic　osteoarthropathy　and　degenerative　joint　disease.　Epigenetic　regulation　in　the　gene　expression　dynamics　has　become　increasingly　important　in　OA.　We　performed　a combined　analysis　of　two　types　of　microarray　datasets　(gene　expression　and　DNA　methylation)　to　identify　methylation-based　key　biomarkers　to　provide　a　better　understanding　of　molecular　biological　mechanisms　of　OA.We　obtained　two　expression　profiling　datasets　(GSE55235,　GSE55457)　and　one　DNA　methylation　profiling　data　set　(GSE63695)　from　the　Gene　Expression　Omnibus.　First,　differentially　expressed　genes　(DEGs)　between　patients　with　OA　and　controls　were　identified　using　the　Limma　package　in　R(v3.4.4).　Then,　function　enrichment　analysis　of　DEGs　was　performed　using　a DAVID　database.　For　DNA　methylation　datasets,　ChAMP　methylation　analysis　package　was　used　to　identify　differential　methylation　genes　(DMGs).　Finally,　a　comprehensive　analysis　of　DEGs　and　DMGs　was　conducted　to　identify　genes　that　exhibited　differential　expression　and　methylation　simultaneously.We　identified　112　DEGs　and　2,896　DMGs　in　patients　with　OA　compared　with　controls.　Functional　analysis　of　DEGs　obtained　that　inflammatory　responses,　immune　responses,　and　positive　regulation　of　apoptosis,　tumor　necrosis　factor　(TNF)　signaling　pathway,　and　osteoclast　differentiation　may　be　involved　in　the　pathogenesis　of　OA.　Cross-analysis　revealed　26　genes　that　exhibited　differential　expression　and　methylation　in　OA.　Among　them,　ADAMTS9,　FKBP5,　and　PFKBF3　were　identified　as　valuable　methylation-based　biomarkers　for　OA.In　summary,　our　study　identified　different　molecular　features　between　patients　with OA　and　controls.　This　may　provide　new　clues　for　clarifying　the　pathogenetic　mechanisms　of　OA.