Abdulla Watad MD, Shana G. Neumann BA, Alessandra Soriano MD, Howard Amital MD and Yehuda Shoenfeld MD FRCP MaCR
There is growing interest in the contribution of vitamin D deficiency to autoimmunity. Several studies have shown an association between low levels of vitamin D and autoimmune disorders, including multiple sclerosis, rheumatoid arthritis, type 1 diabetes, autoimmune thyroid diseases, celiac disease, and systemic lupus erythematosus (SLE). Vitamin D receptor ligands can mediate immunosuppressive effects. It has been suggested that low levels of this hormone contribute to the immune activation in lupus and other autoimmune diseases. This review updates and summarizes the literature on the association between vitamin D and SLE, and discusses the various correlations between vitamin D and SLE activity, clinical expressions, serology, and gene polymorphisms of vitamin D receptors.
Howard Amital MD MHA
The increasing use of computerized medical records has made the clinical data of the entire population available for epidemiological research. The resultant accessibility to this information mandates careful adaptions of ethical guidelines regarding the handling of clinical data. At the same time it grants a unique opportunity to explore the clinical nature of health and disease in large populations across all of society’s strata, socioeconomic levels, ethnicities, and geographic locations regardless of their vicinity or distance to tertiary care centers. Analysis of large databases allows us to learn the public‘s behavior towards medical services and to investigate how medical interventions affect outcomes over time. Moreover, interaction between different co-morbidities can also be better understood by large population studies. The huge numbers of patients involved in these studies provide a good model of multivariate analysis, a statistical tool that by following proper population adjustments underlines the true independent associations between different conditions. Nevertheless, the limitations of these studies should be borne in mind, such as in-built imprecision of diagnoses, incompleteness of the medical data, and the fact that these databases were initially planned for clinical and not investigational use.