Autoimmune disease affects 3% of the US population, and likely a similar percentage of the population of the industrialized world (1). Although remarkable progress toward understanding immune function has been made over the last 4 decades in terms of the role of the major histocompatibility complex and the nature of lymphocyte antigen receptors that confer specificity to autoimmune responses, understanding of the underlying dysregulation and autoimmune response specificity remains limited. For certain autoimmune diseases, including Sjögren’s syndrome and systemic lupus erythematosus (SLE), candidate autoantigens have been identified but their exact roles in the initiation, perpetuation, and pathophysiology are not well understood. For other autoimmune diseases, including rheumatoid arthritis (RA) and psoriasis, the targeted autoantigens remain unidentified despite extensive experimental efforts. Array and other multiplex screening technologies represent powerful tools for studying the pathophysiology and specificity of autoimmune responses. The advent of DNA microarray technology during the last decade has led to an explosion of studies aimed at identifying novel messenger RNA (mRNA) transcripts, or patterns of transcripts, that are transcriptionally up-or down-regulated in association with a particular disease or phenotype. As the availability and costs of such “DNA chips” improve, it is anticipated that transcriptional profiling will gain even greater prominence in autoimmune disease research.“Spotted” DNA microarrays are now available at many university and industry laboratories and are providing a wealth of information regarding the underlying pathophysiology of autoimmune disease (2). However, use of RNA transcriptional profiling has important limitations and is likely unable to provide the comprehensive understanding of autoimmune processes that would be necessary to develop next-generation therapies. RNA transcriptional profiling alone is an inadequate method for studying human autoimmune disease, for several reasons. First, diseases manifest not at the level of RNA transcription, but rather at the level of the protein. Second, there is a frequently nonpredictive correlation between RNA expression and protein expression and function (3, 4). Messenger RNA undergoes a variety of processing events that can profoundly affect cell phenotype yet are not revealed in current transcriptional profiles. For example, mRNA encoding certain apoptosis-regulatory molecules exists in 2 or more alternative splice forms encoding proteins with opposing functions (eg, proapoptotic isoforms such as Bcl-xS and protective isoforms such as Bcl-xL)(5). Translation of mRNA into protein is also regulated by translational regulatory elements such as 3 mRNA AU–rich elements and by addition of poly (A) tails of various lengths (6–8). Third, protein function can be regulated by posttranslational modifications by enzymes such as kinases or proteases. Finally, autoimmune responses are regulated by autoantigen-specific T and B lymphocytes expressing distinct and heterogeneous antigen receptors that are not easily examined by transcriptional profiling. Many of these limitations can be circumvented by direct study of the expression and function of proteins encoded by these RNA transcripts. The large-scale study of the expression, function, and interactions of proteins expressed in a tissue or organism is termed “proteomics”(9). With our entrance into the “post-genomics era,” it is essential to develop novel tools with which protein