Development of a new parallelized, optical biosensor platform for label-free detection of autoimmunity-related antibodies Multiplex Platforms in Diagnostics and Bioanalytics

Oliver Bleher, Aline Schindler, Meng Xin Yin, Andrew B. Holmes, Peter B. Luppa, Günter Gauglitz, Günther Proll

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

Autoimmune diseases are characterized by the presence of autoantibodies in serum of affected patients. The heterogeneity of autoimmune relevant antigens creates a variety of different antibodies, which requires a simultaneous detection mode. For this reason, we developed a tool for parallelized, label-free, optical detection that accomplishes the characterization of multiple antigen-antibody interactions within a single measurement on a timescale of minutes. Using 11-aminoundecyltrimethoxysilane, we were able to immobilize proteinogenic antigens as well as an amino-functionalized cardiolipin on a glass surface. Assay conditions were optimized for serum measurements with a single spot antigen chip on a single spot 1-λ detection system. Minimized background signal allows a differentiation between patients and healthy controls with a good sensitivity and specificity. Applying polarized imaging reflectometric interference spectroscopy, we evaluated samples from three APS patients and three control subjects for this proof-of-principle and already obtained good results for β2-glycoprotein I and cardiolipin.

Original languageEnglish
Pages (from-to)3305-3314
Number of pages10
JournalAnalytical and Bioanalytical Chemistry
Volume406
Issue number14
DOIs
StatePublished - May 2014

Keywords

  • Antiphospholipid syndrome
  • Label-free detection
  • Microarray
  • Optical sensors
  • Reflectometric interference spectroscopy
  • β2-Glycoprotein I

Fingerprint

Dive into the research topics of 'Development of a new parallelized, optical biosensor platform for label-free detection of autoimmunity-related antibodies Multiplex Platforms in Diagnostics and Bioanalytics'. Together they form a unique fingerprint.

Cite this