New technologies for studying the complexity of oral diseases

Abstract

Several new technologies are providing useful diagnostic tools and new information related to the pathogenesis of certain oral diseases. In this review, we describe several of these technologies including gene and microRNA arrays, proteomics, and antigen arrays as they relate to the study of Sjögren's syndrome and head and neck cancer. A common theme is the systematic analysis of large-scale inventories of RNAs, proteins, and autoantibody biomarkers revealing information not previously recognized. We also discuss metagenomic approaches that characterize the many different microorganisms present in the oral cavity that may impact oral and human health. Lastly, we describe applications of a new type of antibody-profiling technology termed Luciferase Immunoprecipitation Systems (LIPS), which has a wide dynamic range of detection of both linear and conformational epitopes needed for optimum diagnostics and biomarker discovery. We propose that the information offered by these technologies will enhance our ability to diagnose, treat, and further understand the pathogenesis of multiple oral diseases.

Figure 1

LIPS provides a facile and robust technology for measuring autoantibodies in SjS. In these studies, antibodies in serum are incubated in solution with Renilla luciferase (Ruc)-tagged antigens (Ag). IgG immunoglobulins are then captured with protein A/G beads and following washing, antigen-specific antibody titers are measured by luciferase-catalyzed light production. Due to the wide dynamic range of antibody detection and the ability to profile many different target antigens, LIPS data can often be best visualized with a heatmap of color-coded antibody titers. In this heatmap, the antigen-antibody measurement greater than the control mean plus 3 standard deviations was color-coded to signify a titer above these cut-off values. Colors on the heatmap signify the relative number of standard deviations further above the control mean plus 3 standard deviations. Each row of the heatmap represents one patient's antibody profile against 7 different autoantigens including La, Ro52, Ro60, thyroid peroxidase (TPO), gastric ATPase (ATPase), aquaporin-4 (AQP-4), and transglutaminase (TGM). Although many of the SjS patients showed high titer and heterogeneous autoantibody responses, four of the SjS patients at the bottom of the heatmap did not show statistical response to any of the autoantigens tested.