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Here, we discuss the immunoproteomics technologies used for the discovery of autoantigens in autoimmune diseases where immune system dysregulation plays a central role in disease onset and progression. These autoantigens and associated autoantibodies can be used as potential biomarkers for disease diagnostics, prognostics and predicting\/monitoring drug responsiveness (theranostics). Here, we compare a variety of methods such as mass spectrometry (MS)-based [serological proteome analysis (SERPA), antibody mediated identification of antigens (AMIDA), circulating immune complexome (CIC) analysis, surface enhanced laser desorption\/ionization-time of flight (SELDI-TOF)], nucleic acid based serological analysis of antigens by recombinant cDNA expression cloning (SEREX), phage immunoprecipitation sequencing (PhIP-seq) and array-based immunoscreening (proteomic microarrays), luciferase immunoprecipitation systems (LIPS), nucleic acid programmable protein array (NAPPA) methods. We also review the relevance of immunoproteomic data generated in the last 10 years, with a focus on the aforementioned MS based methods.<\/jats:p>","DOI":"10.1515\/bmc-2016-0007","type":"journal-article","created":{"date-parts":[[2016,4,26]],"date-time":"2016-04-26T06:04:55Z","timestamp":1461650695000},"page":"133-143","source":"Crossref","is-referenced-by-count":19,"title":["Immunoproteomics technologies in the discovery of autoantigens in autoimmune diseases"],"prefix":"10.1515","volume":"7","author":[{"given":"Vinitha","family":"Ganesan","sequence":"first","affiliation":[{"name":"Department of Biological Sciences , Carnegie Mellon University , 4400 Fifth Avenue, Pittsburgh, PA 15213, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dana P.","family":"Ascherman","sequence":"additional","affiliation":[{"name":"Division of Rheumatology, Department of Medicine , University of Miami Miller School of Medicine , 1600 Northwest 10th Avenue, Miami, FL 33136, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jonathan S.","family":"Minden","sequence":"additional","affiliation":[{"name":"Department of Biological Sciences , Carnegie Mellon University , 4400 Fifth Avenue, Pittsburgh, PA 15213, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2016,4,26]]},"reference":[{"key":"2025120518245593092_j_bmc-2016-0007_ref_001_w2aab3b7c26b1b6b1ab2b2b1Aa","doi-asserted-by":"crossref","unstructured":"Purcell AW, Gorman JJ. Immunoproteomics: mass spectrometry-based methods to study the targets of the immune response. Mol Cell Proteomics 2004; 3: 193\u2013208.","DOI":"10.1074\/mcp.R300013-MCP200"},{"key":"2025120518245593092_j_bmc-2016-0007_ref_002_w2aab3b7c26b1b6b1ab2b2b2Aa","unstructured":"Tassinari OW, Caiazzo RJ, Jr., Ehrlich JR, Liu BC. Identifying autoantigens as theranostic targets: antigen arrays and immunoproteomics approaches. Curr Opin Mol Ther 2008; 10: 107\u201315."},{"key":"2025120518245593092_j_bmc-2016-0007_ref_003_w2aab3b7c26b1b6b1ab2b2b3Aa","doi-asserted-by":"crossref","unstructured":"Kohler K, Seitz H. Validation processes of protein biomarkers in serum \u2013 a cross platform comparison. Sensors 2012; 12: 12710\u201328.","DOI":"10.3390\/s120912710"},{"key":"2025120518245593092_j_bmc-2016-0007_ref_004_w2aab3b7c26b1b6b1ab2b2b4Aa","doi-asserted-by":"crossref","unstructured":"Klade CS, Voss T, Krystek E, Ahorn H, Zatloukal K, Pummer K, Pummer K, Adolf GR. 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