Genetic variants of VDR and CYP2R1 affect BMI independently of serum vitamin D concentrations

BACKGROUND: Vitamin D metabolism and obesity have been linked by several studies, however the reason for this association is unclear. Our objective was to investigate potential correlations between genetic variants in key enzymes of vitamin D metabolism and the body mass index on a representative and random sample of Hungarian adults. METHODS: Altogether 462 severely vitamin D deficient individuals were studied at the end of winter in order to decrease environmental and maximize any relevant genetic effect. Furthermore, participants with lifestyle factors known to affect vitamin D homeostasis were also excluded. We selected 23 target SNPs in five genes that encode key proteins of vitamin D metabolism (NADSYN1, GC, CYP24A1, CYP2R1, VDR). RESULTS: Variants in 2 genetic polymorphisms; rs2853564 (VDR) and rs11023374 (CYP2R1) showed a significant association with participants' BMI. These associations survived further adjustment for total-, free-, or bioactive-25(OH) vitamin D levels, although the variance explained by these 2 SNPS in BMI heterogeneity was only 3.2%. CONCLUSION: Our results show two novel examples of the relationship between genetics of vitamin D and BMI, highlighting the potential role of vitamin D hormone in the physiology of obesity

Impact of genetic influence on serum total-and free 25-hydroxyvitamin-D in humans

Serum 25-hydroxyvitamin D /25OHD/ levels in humans are determined primarily by environmental factors such as UV-B radiation and diet, including vitamin D intake. Although some genetic determinants of 25OHD levels have been shown, the magnitude of this association has not yet been clarified. The present study evaluates the genetic contribution to total- /t-25OHD/ and free-25OHD /f-25OHD/ in a representative sample of the Hungarian population (n = 462). The study was performed at the end of winter to minimize the effect of sunlight, which is a major determinant of serum vitamin D levels. Single nucleotide polymorphisms (SNPs) of five genes playing major roles in vitamin D metabolism were investigated (NADSYN1, DHCR7, GC, CYP2R1 and CYP24A1). The selected SNPs account for 13.1% of the variance of t-25OHD levels. More than half of the genetic effect on t-25OHD levels was explained by two polymorphisms (rs7935125 in NADSYN1 and rs2762941 in CYP24A1), which had not previously been investigated with respect to vitamin D metabolism. No SNPs exhibited association with f-25OHD levels. Unexpectedly, SNPs that showed univariate associations with vitamin D binding protein (DBP) levels were not associated with f-25OHD levels questioning the biological significance of these polymorphisms. The present study shows that t-25OHD levels are significantly influenced by genetic factors, however, the clinical significance of this observation remains to be defined, as variation in f-25OHD levels are marginally explained by genetic effects

Different gene expression patterns in bone tissue of aging postmenopausal osteoporotic and non-osteoporotic women.

Purpose To identify genes that are differently expressed in osteoporotic and non-osteoporotic human bone and to describe the relationships between these genes using multivariate data analysis. Methods Seven bone tissue samples from postmenopausal osteoporotic patients and 10 bone tissue samples from postmenopausal non-osteoporotic women were examined in our study. Messenger RNA was prepared from each sample and reverse transcribed to cDNA. The expression differences of 87 selected genes were analyzed in a Taqman probe-based quantitative real-time RT-PCR system. Results A Mann-Whitney U-test indicated significant differences in the expression of nine genes (p <= 0.05). Seven of these nine genes-ALPL, COL1A1, MMP2, MMP13, MMP9, PDGFA, NFKB1-were significantly downregulated in the bone tissue of osteoporotic women, while CD36 and TWIST2 were significantly upregulated in osteoporotic patients. Principal components analysis was used to evaluate data structure and the relationship between osteoporotic and non-osteoporotic phenotypes based on the multiple mRNA expression profiles of 78 genes. Canonical variates analysis demonstrated further that osteoporotic and non-osteoporotic tissues can be distinguished by expression analysis of genes coding growth factors/non-collagen matrix molecules, and genes belonging to the canonical TGFB pathway. Conclusion Significant differences observed in gene expression profiles of osteoporotic and non-osteoporotic human bone tissues provide further insight into the pathogenesis of this disease. Characterization of the differences between osteoporotic and non-osteoporotic bones by expression profiling will contribute to the development of diagnostic tools in the future