Vitamin D receptor gene polymorphisms in relation to Vitamin D related disease states

The role in skeletal metabolism of the steroid hormone Vitamin D and its nuclear receptor (VDR) is well known. In addition, however, Vitamin D is also involved in a wide variety of other biological processes including modulation of the immune response and regulation of cell proliferation and differentiation. Variations in the Vitamin D endocrine system have thus been linked to several diseases, including osteoarthritis, diabetes, cancer, cardiovascular disease and tuberculosis. Evidence to support this pleiotropic character of Vitamin D has included epidemiological studies on circulating Vitamin D hormone levels, but also genetic epidemiological studies. Genetic studies provide excellent opportunities to link molecular insights with epidemiological data and have therefore gained much interest. DNA sequence variations which occur frequently in the population are referred to as "polymorphisms" and are usually suspected of having only modest and subtle effects. Recent studies have indicated many polymorphisms to exist in the VDR gene, but the influence of VDR gene polymorphisms on VDR protein function are largely unknown. Sofar, three adjacent restriction fragment length polymorphisms (RFLP) for BsmI, ApaI and TaqI, respectively, at the 3′ end of the VDR gene have been the most frequently studied sofar. But because these polymorphisms are probably non-functional, linkage disequilibrium (LD) with one or more truly functional polymorphisms elsewhere in the VDR gene is assumed to explain the associations observed. Research is therefore focussed on documenting additional polymorphisms across the VDR gene to verify this hypothesis, and on trying to understand the functional consequences of the variations. Substantial progress has been made including the discovery of novel polymorphisms in the large promoter region of the VDR gene. Eventually, results of this research will deepen our understanding of variability in the Vitamin D endocrine system and might find applications in risk-assessment of disease and in predicting response-to-treatment.

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