Objective: Production of pathogenic autoantibodies by self-reactive plasma cells (PC) is a hallmark of autoimmune diseases. Investigating the prevalence of PC in autoimmune disease and their relationship with known pathogenic pathways may increase our understanding of the role of PC in disease progression and treatment response. Methods: We developed a sensitive gene expression based method to overcome the challenges of measuring PC using flow cytometry. Whole genome microarray analysis of sorted cellular fractions identified a panel of genes, IGHA, IGJ, IGKC, IGKV, and TNFRSF17, expressed predominantly in PC. The sensitivity of the PC signature score created from the combined expression levels of these genes was assessed through ex vivo experiments with sorted cells. This PC gene expression signature was used for monitoring changes in PC levels following anti-CD19 therapy; evaluating the relationship between PC and other autoimmune disease-related genes; and estimating PC levels in affected blood and tissue from multiple autoimmune diseases. Results: The PC signature was highly sensitive and capable of detecting as few as 300 PCs. The PC signature was reduced over 90% in scleroderma patients following anti-CD19 treatment and this reduction was highly correlated (r = 0.77) with inhibition of collagen gene expression. Evaluation of multiple autoimmune diseases revealed 30-35% of lupus, rheumatoid arthritis, and scleroderma patients with increased PC levels. Conclusion: This newly developed PC signature provides a robust and accurate method to measure PC levels in the clinic. Our results highlight subsets of patients across multiple autoimmune diseases that may benefit from PC depleting therapy.