Serological Proteome Analysis (SERPA) as a tool for the identification of new candidate autoantigens in type 1 diabetes

Ornella Massa, Massimo Alessio, Lucia Russo, Giovanni Nardo, Valentina Bonetto, Federico Bertuzzi, Alessandra Paladini, Dario Iafusco, Patrizia Patera, Giorgio Federici, Tarcisio Not, Claudio Tiberti, Riccardo Bonfanti, Fabrizio Barbetti

Research output: Contribution to journalArticlepeer-review


Type 1 diabetes (T1D) is an autoimmune disease characterized by the presence of circulating autoantibodies directed against proteins of islet beta-cell. Autoantibody testing is used for diagnostic purposes; however, up to 2-5% of patients who are clinically diagnosed with T1D are found negative for known antibodies, suggesting that the T1D autoantigen panel is incomplete. With the aim of identifying new T1D autoantigen(s), we used sera from subjects clinically diagnosed with T1D, but who tested negative for the four T1D autoantibodies currently used in clinical practice and for genes responsible for sporadic cases of diabetes.Sera from these patients were challenged by Western blot against the proteome from human pancreatic beta-cells resolved by 2DE. Eleven proteins were identified by MS. A radiobinding assay (RBA) was developed to test the reactivity to Rab GDP dissociation inhibitor beta (GDIβ) of T1D sera using an independent method. Depending on the construct used (open reading frame or COOH-terminus) 22% to 32% of fifty T1D sera showed increased binding to GDIβ by RBA. In addition, 15% of patients with celiac disease had raised binding to the COOH-terminus GDI.

Original languageEnglish
Pages (from-to)263-273
Number of pages11
JournalJournal of Proteomics
Publication statusPublished - Apr 6 2013


  • Autoimmunity
  • Electrophoresis, Two-Dimensional Gel
  • Immunoproteomics
  • Serological Proteome Analysis
  • Serum
  • Type I diabetes

ASJC Scopus subject areas

  • Biochemistry
  • Biophysics


Dive into the research topics of 'Serological Proteome Analysis (SERPA) as a tool for the identification of new candidate autoantigens in type 1 diabetes'. Together they form a unique fingerprint.

Cite this