title: Prediction and prevention of autoimmune disease: a personal perspective.
abstract: Biomarkers, represented by genetically determined traits or biologic changes predictive of disease onset or outcome, are increasingly employed by academic and industrial investigators. They can identify unusually susceptible populations or individuals, facilitate prognosis, forecast the outcome of therapy in clinical trials, or aid in developing improved treatments or preventative measures. All of these applications have been applied to the autoimmune diseases. As a case in point, we have through the years used biomarkers to predict susceptibility and the longer-range outcome of thyroid autoimmunity employing, a number of different approaches. They have taught us valuable lessons for future broader applications of biomarkers. The clues for susceptibility include major histocompatibility complex (MHC) and non-MHC genes combined with the fine specificity of thyroid autoantibodies in siblings of patients with juvenile thyroid disease. Together these biomarkers are highly predictive of later thyroid autoimmunity and subclinical thyroid dysfunction. For example, the progression from benign autoimmunity to clinical thyroid disease is marked by the appearance of autoantibodies to species-restricted epitopes on thyroglobulin. Thus, predictive biomarkers aid in identifying individuals with inordinate risk of disease and provide opportunities for earlier interventions to arrest the disease process.
authors.affiliation: Department of Pathology, Johns Hopkins Center for Autoimmune Disease Research, Johns Hopkins University, Baltimore, Maryland 21205, USA. nrrose@jhsph.edu
authors.forename: Noel R
authors.initials: NR
authors.lastname: Rose
mesh_terms: D000818:Animals; D001327:Autoimmune Diseases / Q000276:immunology* / Q000517:prevention & control*; D006801:Humans; D012307:Risk Factors