Phenotypic Dissection of Bone Mineral Density Reveals Skeletal Site Specificity and Facilitates the Identification of Novel Loci in the Genetic Regulation of Bone Mass Attainment. Kemp, J., P., Medina-Gomez, C., Estrada, K., St Pourcain, B., Heppe, D., H., M., Warrington, N., M., Oei, L., Ring, S., M., Kruithof, C., J., Timpson, N., J., Wolber, L., E., Reppe, S., Gautvik, K., Grundberg, E., Ge, B., van der Eerden, B., van de Peppel, J., Hibbs, M., A., Ackert-Bicknell, C., L., Choi, K., Koller, D., L., Econs, M., J., Williams, F., M., K., Foroud, T., Carola Zillikens, M., Ohlsson, C., Hofman, A., Uitterlinden, A., G., Davey Smith, G., Jaddoe, V., W., V., Tobias, J., H., Rivadeneira, F., & Evans, D., M. PLoS Genetics, 10(6):e1004423, Public Library of Science, 6, 2014.
Paper
Website abstract bibtex Heritability of bone mineral density (BMD) varies across skeletal sites, reflecting different relative contributions of genetic and environmental influences. To quantify the degree to which common genetic variants tag and environmental factors influence BMD, at different sites, we estimated the genetic (rg) and residual (re) correlations between BMD measured at the upper limbs (UL-BMD), lower limbs (LL-BMD) and skull (SK-BMD), using total-body DXA scans of ~4,890 participants recruited by the Avon Longitudinal Study of Parents and their Children (ALSPAC). Point estimates of rg indicated that appendicular sites have a greater proportion of shared genetic architecture (LL-/UL-BMD rg = 0.78) between them, than with the skull (UL-/SK-BMD rg = 0.58 and LL-/SK-BMD rg = 0.43). Likewise, the residual correlation between BMD at appendicular sites (re = 0.55) was higher than the residual correlation between SK-BMD and BMD at appendicular sites (re = 0.20-0.24). To explore the basis for the observed differences in rg and re, genome-wide association meta-analyses were performed (n~9,395), combining data from ALSPAC and the Generation R Study identifying 15 independent signals from 13 loci associated at genome-wide significant level across different skeletal regions. Results suggested that previously identified BMD-associated variants may exert site-specific effects (i.e. differ in the strength of their association and magnitude of effect across different skeletal sites). In particular, variants at CPED1 exerted a larger influence on SK-BMD and UL-BMD when compared to LL-BMD (P = 2.01×10-37), whilst variants at WNT16 influenced UL-BMD to a greater degree when compared to SK- and LL-BMD (P = 2.31×10-14). In addition, we report a novel association between RIN3 (previously associated with Paget's disease) and LL-BMD (rs754388: β = 0.13, SE = 0.02, P = 1.4×10-10). Our results suggest that BMD at different skeletal sites is under a mixture of shared and specific genetic and environmental influences. Allowing for these differences by performing genome-wide association at different skeletal sites may help uncover new genetic influences on BMD. © 2014 Kemp et al.
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title = {Phenotypic Dissection of Bone Mineral Density Reveals Skeletal Site Specificity and Facilitates the Identification of Novel Loci in the Genetic Regulation of Bone Mass Attainment},
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abstract = {Heritability of bone mineral density (BMD) varies across skeletal sites, reflecting different relative contributions of genetic and environmental influences. To quantify the degree to which common genetic variants tag and environmental factors influence BMD, at different sites, we estimated the genetic (rg) and residual (re) correlations between BMD measured at the upper limbs (UL-BMD), lower limbs (LL-BMD) and skull (SK-BMD), using total-body DXA scans of ~4,890 participants recruited by the Avon Longitudinal Study of Parents and their Children (ALSPAC). Point estimates of rg indicated that appendicular sites have a greater proportion of shared genetic architecture (LL-/UL-BMD rg = 0.78) between them, than with the skull (UL-/SK-BMD rg = 0.58 and LL-/SK-BMD rg = 0.43). Likewise, the residual correlation between BMD at appendicular sites (re = 0.55) was higher than the residual correlation between SK-BMD and BMD at appendicular sites (re = 0.20-0.24). To explore the basis for the observed differences in rg and re, genome-wide association meta-analyses were performed (n~9,395), combining data from ALSPAC and the Generation R Study identifying 15 independent signals from 13 loci associated at genome-wide significant level across different skeletal regions. Results suggested that previously identified BMD-associated variants may exert site-specific effects (i.e. differ in the strength of their association and magnitude of effect across different skeletal sites). In particular, variants at CPED1 exerted a larger influence on SK-BMD and UL-BMD when compared to LL-BMD (P = 2.01×10-37), whilst variants at WNT16 influenced UL-BMD to a greater degree when compared to SK- and LL-BMD (P = 2.31×10-14). In addition, we report a novel association between RIN3 (previously associated with Paget's disease) and LL-BMD (rs754388: β = 0.13, SE = 0.02, P = 1.4×10-10). Our results suggest that BMD at different skeletal sites is under a mixture of shared and specific genetic and environmental influences. Allowing for these differences by performing genome-wide association at different skeletal sites may help uncover new genetic influences on BMD. © 2014 Kemp et al.},
bibtype = {article},
author = {Kemp, John P. and Medina-Gomez, Carolina and Estrada, Karol and St Pourcain, Beate and Heppe, Denise H. M. and Warrington, Nicole M. and Oei, Ling and Ring, Susan M. and Kruithof, Claudia J. and Timpson, Nicholas J. and Wolber, Lisa E. and Reppe, Sjur and Gautvik, Kaare and Grundberg, Elin and Ge, Bing and van der Eerden, Bram and van de Peppel, Jeroen and Hibbs, Matthew A. and Ackert-Bicknell, Cheryl L. and Choi, Kwangbom and Koller, Daniel L. and Econs, Michael J. and Williams, Frances M. K. and Foroud, Tatiana and Carola Zillikens, M. and Ohlsson, Claes and Hofman, Albert and Uitterlinden, André G. and Davey Smith, George and Jaddoe, Vincent W. V. and Tobias, Jonathan H. and Rivadeneira, Fernando and Evans, David M.},
journal = {PLoS Genetics},
number = {6}
}
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