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RATIONALE Studies have shown elevated inflammatory biomarkers in OSA, but data following CPAP treatment are inconsistent. OBJECTIVES We used the Olink® proteomics panel to identify unique OSA clusters based on inflammatory protein expression, and assess the impact of CPAP therapy. METHODS Adults with newly-diagnosed OSA had blood drawn at baseline, and three to four months after CPAP. Samples were analyzed using the Olink® proteomics platform which measures 92 pre-specified inflammatory proteins using proximity extension assay (PEA). Linear mixed-effects models were used to model changes in protein expression during the period of CPAP use, adjusting for batch, age and sex. Unsupervised hierarchical clustering was performed to identify unique inflammatory OSA clusters based on inflammatory biomarkers. Within-cluster impact of CPAP was assessed on inflammatory protein expression. RESULTS Among 46 patients, mean age was 46±12 years (22% female), mean BMI 31±5 kg/m2, and mean respiratory disturbance index (RDI) was 33±17 events/hour. Unsupervised cluster/heatmap analysis revealed three unique proteomic clusters, with low[n=21], intermediate[n=19] and high[n=6] inflammatory protein expression. Following CPAP, there were significant within-cluster differences in protein expression. The low inflammatory cluster had a significant increase in protein expression (16%, p=0.02), and the high inflammatory cluster had a significant decrease in protein expression (-20%, p=0.003), more significant among those compliant with CPAP in the low (25%, p=0.04) and high (-22%, p=0.01) clusters. CONCLUSION We identified three unique inflammatory clusters in OSA patients using plasma proteomics, with a differential response to CPAP by cluster. Our results are hypothesis-generating and require further investigation in larger longitudinal studies for enhanced cardiovascular risk-profiling in OSA.