Project description:Osteoporosis is a complex disease with developmental origins. It is therefore important to understand the genetic contribution to pediatric areal bone mineral density (aBMD). Individual skeletal site phenotyping has been primarily used to identify pediatric aBMD loci. However, this approach is limited because there is a degree of aBMD discordance across skeletal sites. We therefore applied a novel multidimensional phenotyping approach to further understand the genetic regulation of pediatric aBMD. Our sample comprised a prospective, longitudinal cohort of 1293 children of European ancestry (52% female; up to seven annual measurements). Principal components analysis was applied to dual-energy X-ray absorptiometry-derived aBMD Z-scores for total hip, femoral neck, spine, and distal radius to generate multidimensional aBMD phenotypes (ie, principal component scores). We tested the association between a genetic score (percentage of bone lowering alleles at 63 loci) and each principal component. We also performed a genomewide association study (GWAS) using the multiethnic baseline data (n?=?1885) to identify novel loci associated with these principal components. The first component (PC1) reflected a concordant phenotypic model of the skeleton (eg, higher loading score?=?higher BMD across all sites). In contrast, PC2 was discordant for distal radius versus spine and hip aBMD, and PC3 was discordant for spine versus distal radius and hip aBMD. The genetic score was associated with PC1 (beta?=?-0.05, p?=?3.9?×?10-10 ), but was not associated with discordant PC2 or PC3. Our GWAS discovered variation near CPED1 that associated with PC2 (rs67991850, p?=?2.5?×?10-11 ) and near RAB11FIP5 (rs58649746, p?=?4.8?×?10-9 ) that associated with PC3. In conclusion, an established bone fragility genetic summary score was associated with a concordant skeletal phenotype, but not discordant skeletal phenotypes. Novel associations were observed for the discordant multidimensional skeletal phenotypes that provide new biological insights into the developing skeleton. © 2017 American Society for Bone and Mineral Research.

Project description:Introduction Mammographic density (MD), as assessed from film screen mammograms, is determined by the relative content of adipose, connective and epithelial tissue in the female breast. In epidemiological studies, a high percentage of MD confers a four to six fold risk elevation of developing breast cancer, even after adjustment for other known breast cancer risk factors. However, the biologic correlates of density are little known. Methods Gene expression analysis using whole genome arrays was performed on breast biopsies from 143 women; 79 women with no malignancy (healthy women) and 64 newly diagnosed breast cancer patients, both included from mammographic centres. Percent MD was determined using a previously validated, computerized method on scanned mammograms. Significance analysis of microarrays (SAM) was performed to identify genes influencing MD and generalized regression models were used to assess the independent contribution from different variables to MD. Results SAM-analysis identified 24 genes differentially expressed between samples from breasts with high and low MD. These genes included three uridine 5'-diphospho-glucuronosyltransferase (UGT) genes and the oestrogen receptor gene (ESR1). These genes were down-regulated in samples with high MD compared to those with low MD. The UGT gene products, which are known to inactivate oestrogen metabolites, were also down-regulated in tumour samples compared to samples from healthy individuals. Several single nucleotide polymorphisms (SNPs) in the UGT genes associated with the expression of UGT and other genes in their vicinity were identified. Conclusions Three UGT enzymes were lower expressed both in breast tissue biopsies from healthy women with high MD and in biopsies from newly diagnosed breast cancers. The association was strongest among young women and women using hormonal therapy. UGT2B10 predicts MD independently of age, hormone therapy and parity. Our results indicate that down-regulation of UGT genes in women exposed to female sex hormones is associated with high MD and might increase the risk of breast cancer.

Project description:Introduction Mammographic density (MD), as assessed from film screen mammograms, is determined by the relative content of adipose, connective and epithelial tissue in the female breast. In epidemiological studies, a high percentage of MD confers a four to six fold risk elevation of developing breast cancer, even after adjustment for other known breast cancer risk factors. However, the biologic correlates of density are little known. Methods Gene expression analysis using whole genome arrays was performed on breast biopsies from 143 women; 79 women with no malignancy (healthy women) and 64 newly diagnosed breast cancer patients, both included from mammographic centres. Percent MD was determined using a previously validated, computerized method on scanned mammograms. Significance analysis of microarrays (SAM) was performed to identify genes influencing MD and generalized regression models were used to assess the independent contribution from different variables to MD. Results SAM-analysis identified 24 genes differentially expressed between samples from breasts with high and low MD. These genes included three uridine 5'-diphospho-glucuronosyltransferase (UGT) genes and the oestrogen receptor gene (ESR1). These genes were down-regulated in samples with high MD compared to those with low MD. The UGT gene products, which are known to inactivate oestrogen metabolites, were also down-regulated in tumour samples compared to samples from healthy individuals. Several single nucleotide polymorphisms (SNPs) in the UGT genes associated with the expression of UGT and other genes in their vicinity were identified. Conclusions Three UGT enzymes were lower expressed both in breast tissue biopsies from healthy women with high MD and in biopsies from newly diagnosed breast cancers. The association was strongest among young women and women using hormonal therapy. UGT2B10 predicts MD independently of age, hormone therapy and parity. Our results indicate that down-regulation of UGT genes in women exposed to female sex hormones is associated with high MD and might increase the risk of breast cancer. Gene expression analysis of breast biopsies from 143 women, 79 non-cancer (healthy women with no cancer who had a mammogram taken) and 64 breast cancer.

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Nursing Genetic Research: New Insights Linking Breast Cancer Genetics and Bone Density.

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Nursing Genetic Research: New Insights Linking Breast Cancer Genetics and Bone Density.

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