Overactive bladder (OAB) is a common debilitating bladder condition with unknown etiology and limited diagnostic modalities. Here, we explored a novel high throughput, and unbiased multiplex approach with cellular and molecular components in a well characterized patient cohort to identify biomarkers that could be reliably used to distinguish OAB from controls or provide insights into underlying etiology. As a secondary analysis, we determined if this method could discriminate between OAB and other chronic bladder conditions. We analyzed plasma samples from healthy volunteers (n=19) and patients diagnosed with OAB, IC/BPS, or urinary tract infections (UTI) (n= 51) for pro-inflammatory, chemokine, cytokine, angiogenesis, and vascular injury factors using Meso Scale Discovery (MSD) analysis and urinary cytological analysis. Wilcoxon rank-sum tests were used to perform univariate and multivariate comparisons between patient groups (controls, OAB, IC/BPS, and UTI). Multivariate logistic regression models were fit for each MSD analyte on 1) OAB patients and controls, 2) OAB and IC/BPS patients, and 3) OAB and UTI patients. Age, race, and sex were included as independent variables in all multivariate analysis. Receiver operating characteristic (ROC) curves were generated to determine the diagnostic potential of a given analyte. Our findings demonstrate that five analytes, interleukin 4, tumor necrosis factor alpha, macrophage inflammatory protein-1β, serum amyloid A, and Tie-2 can reliably differentiate OAB relative to controls and can be used to distinguish OAB from the other conditions. Together, our pilot study suggests a molecular imbalance in inflammatory proteins may contributes to OAB pathogenesis.