@article {8538,
	title = {{Life-Course Genome-wide Association Study Meta-analysis of Total Body BMD and Assessment of Age-Specific Effects},
	journal = {Am J Hum Genet},
	volume = {102},
	year = {2018},
	month = {01},
	pages = {88{\textendash}102},
	abstract = {Bone mineral density (BMD) assessed by DXA is used to evaluate bone health. In children, total body (TB) measurements are commonly used; in older individuals, BMD at the lumbar spine (LS) and femoral neck (FN) is used to diagnose osteoporosis. To date, genetic variants in more than 60 loci have been identified as associated with BMD. To investigate the genetic determinants of TB-BMD variation along the life course and test for age-specific effects, we performed a meta-analysis of 30 genome-wide association studies (GWASs) of TB-BMD including 66,628 individuals overall and divided across five age strata, each spanning 15 years. We identified variants associated with TB-BMD at 80 loci, of which 36 have not been previously identified; overall, they explain approximately 10\% of the TB-BMD variance when combining all age groups and influence the risk of fracture. Pathway and enrichment analysis of the association signals showed clustering within gene sets implicated in the regulation of cell growth and SMAD proteins, overexpressed in the musculoskeletal system, and enriched in enhancer and promoter regions. These findings reveal TB-BMD as a relevant trait for genetic studies of osteoporosis, enabling the identification of variants and pathways influencing different bone compartments. Only variants in ESR1 and close proximity to RANKL showed a clear effect dependency on age. This most likely indicates that the majority of genetic variants identified influence BMD early in life and that their effect can be captured throughout the life course.},
	author = {Medina-Gomez, C. and Kemp, J. P. and Trajanoska, K. and Luan, J. and Chesi, A. and Ahluwalia, T. S. and Mook-Kanamori, D. O. and Ham, A. and Hartwig, F. P. and Evans, D. S. and Joro, R. and Nedeljkovic, I. and Zheng, H. F. and Zhu, K. and Atalay, M. and Liu, C. T. and Nethander, M. and Broer, L. and Porleifsson, G. and Mullin, B. H. and Handelman, S. K. and Nalls, M. A. and Jessen, L. E. and Heppe, D. H. M. and Richards, J. B. and Wang, C. and Chawes, B. and Schraut, K. E. and Amin, N. and Wareham, N. and Karasik, D. and Van der Velde, N. and Ikram, M. A. and Zemel, B. S. and Zhou, Y. and Carlsson, C. J. and Liu, Y. and McGuigan, F. E. and Boer, C. G. and B?nnelykke, K. and Ralston, S. H. and Robbins, J. A. and Walsh, J. P. and Zillikens, M. C. and Langenberg, C. and Li-Gao, R. and Williams, F. M. K. and Harris, T. B. and Akesson, K. and Jackson, R. D. and Sigurdsson, G. and den Heijer, M. and van der Eerden, B. C. J. and van de Peppel, J. and Spector, T. D. and Pennell, C. and Horta, B. L. and Felix, J. F. and Zhao, J. H. and Wilson, S. G. and de Mutsert, R. and Bisgaard, H. and Styrk?rsd?ttir, U. and Jaddoe, V. W. and Orwoll, E. and Lakka, T. A. and Scott, R. and Grant, S. F. A. and Lorentzon, M. and van Duijn, C. M. and Wilson, J. F. and Stefansson, K. and Psaty, B. M. and Kiel, D. P. and Ohlsson, C. and Ntzani, E. and van Wijnen, A. J. and Forgetta, V. and Ghanbari, M. and Logan, J. G. and Williams, G. R. and Bassett, J. H. D. and Croucher, P. I. and Evangelou, E. and Uitterlinden, A. G. and Ackert-Bicknell, C. L. and Tobias, J. H. and Evans, D. M. and Rivadeneira, F.}
}
@article {8517,
	title = {{Meta-Analysis of Genomewide Association Studies Reveals Genetic Variants for Hip Bone Geometry},
	journal = {J Bone Miner Res},
	volume = {34},
	year = {2019},
	month = {07},
	pages = {1284{\textendash}1296},
	abstract = {Hip geometry is an important predictor of fracture. We performed a meta-analysis of GWAS studies in adults to identify genetic variants that are associated with proximal femur geometry phenotypes. We analyzed four phenotypes: (i) femoral neck length; (ii) neck-shaft angle; (iii) femoral neck width, and (iv) femoral neck section modulus, estimated from DXA scans using algorithms of hip structure analysis. In the Discovery stage, 10 cohort studies were included in the fixed-effect meta-analysis, with up to 18,719 men and women ages 16 to 93 years. Association analyses were performed with {\^a}{\textasciicircum}{\textonequarter}2.5 million polymorphisms under an additive model adjusted for age, body mass index, and height. Replication analyses of meta-GWAS significant loci (at adjusted genomewide significance [GWS], threshold p {\^a}{\textperthousand}¤ 2.6 {\~A}{\textemdash} 10-8 ) were performed in seven additional cohorts in silico. We looked up SNPs associated in our analysis, for association with height, bone mineral density (BMD), and fracture. In meta-analysis (combined Discovery and Replication stages), GWS associations were found at 5p15 (IRX1 and ADAMTS16); 5q35 near FGFR4; at 12p11 (in CCDC91); 11q13 (near LRP5 and PPP6R3 (rs7102273)). Several hip geometry signals overlapped with BMD, including LRP5 (chr. 11). Chr. 11 SNP rs7102273 was associated with any-type fracture (p = 7.5 {\~A}{\textemdash} 10-5 ). We used bone transcriptome data and discovered several significant eQTLs, including rs7102273 and PPP6R3 expression (p = 0.0007), and rs6556301 (intergenic, chr.5 near FGFR4) and PDLIM7 expression (p = 0.005). In conclusion, we found associations between several genes and hip geometry measures that explained 12\% to 22\% of heritability at different sites. The results provide a defined set of genes related to biological pathways relevant to BMD and etiology of bone fragility. {\^A}{\textcopyright} 2019 American Society for Bone and Mineral Research.},
	author = {Hsu, Y. H. and Estrada, K. and Evangelou, E. and Ackert-Bicknell, C. and Akesson, K. and Beck, T. and Brown, S. J. and Capellini, T. and Carbone, L. and Cauley, J. and Cheung, C. L. and Cummings, S. R. and Czerwinski, S. and Demissie, S. and Econs, M. and Evans, D. and Farber, C. and Gautvik, K. and Harris, T. and Kammerer, C. and Kemp, J. and Koller, D. L. and Kung, A. and Lawlor, D. and Lee, M. and Lorentzon, M. and McGuigan, F. and Medina-Gomez, C. and Mitchell, B. and Newman, A. and Nielson, C. and Ohlsson, C. and Peacock, M. and Reppe, S. and Richards, J. B. and Robbins, J. and Sigurdsson, G. and Spector, T. D. and Stefansson, K. and Streeten, E. and Styrkarsdottir, U. and Tobias, J. and Trajanoska, K. and Uitterlinden, A. and Vandenput, L. and Wilson, S. G. and Yerges-Armstrong, L. and Young, M. and Zillikens, M. C. and Rivadeneira, F. and Kiel, D. P. and Karasik, D.}
}
@article {9618,
	title = {{Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications},
	journal = {Nat Commun},
	volume = {15},
	year = {2024},
	month = {Jan},
	pages = {888},
	abstract = {T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases.},
	author = {Sterenborg, R. B. T. M. and Steinbrenner, I. and Li, Y. and Bujnis, M. N. and Naito, T. and Marouli, E. and Galesloot, T. E. and Babajide, O. and Andreasen, L. and Astrup, A. and svold, B. O. and Bandinelli, S. and Beekman, M. and Beilby, J. P. and Bork-Jensen, J. and Boutin, T. and Brody, J. A. and Brown, S. J. and Brumpton, B. and Campbell, P. J. and Cappola, A. R. and Ceresini, G. and Chaker, L. and Chasman, D. I. and Concas, M. P. and Coutinho de Almeida, R. and Cross, S. M. and Cucca, F. and Deary, I. J. and Kjaergaard, A. D. and Echouffo Tcheugui, J. B. and Ellervik, C. and Eriksson, J. G. and Ferrucci, L. and Freudenberg, J. and Fuchsberger, C. and Gieger, C. and Giulianini, F. and gele, M. and Graham, S. E. and Grarup, N. and {\"a}, I. and Hansen, T. and Harding, B. N. and Harris, S. E. and {\o}, S. and Hayward, C. and Hui, J. and Ittermann, T. and Jukema, J. W. and Kajantie, E. and Kanters, J. K. and rhus, L. L. and Kiemeney, L. A. L. M. and Kloppenburg, M. and hnel, B. and Lahti, J. and Langenberg, C. and Lapauw, B. and Leese, G. and Li, S. and Liewald, D. C. M. and Linneberg, A. and Lominchar, J. V. T. and Luan, J. and Martin, N. G. and Matana, A. and Meima, M. E. and Meitinger, T. and Meulenbelt, I. and Mitchell, B. D. and llehave, L. T. and Mora, S. and Naitza, S. and Nauck, M. and Netea-Maier, R. T. and Noordam, R. and Nursyifa, C. and Okada, Y. and Onano, S. and Papadopoulou, A. and Palmer, C. N. A. and Pattaro, C. and Pedersen, O. and Peters, A. and Pietzner, M. and ek, O. and Pramstaller, P. P. and Psaty, B. M. and Punda, A. and Ray, D. and Redmond, P. and Richards, J. B. and Ridker, P. M. and Russ, T. C. and Ryan, K. A. and Olesen, M. S. and Schultheiss, U. T. and Selvin, E. and Siddiqui, M. K. and Sidore, C. and Slagboom, P. E. and rensen, T. I. A. and Soto-Pedre, E. and Spector, T. D. and Spedicati, B. and Srinivasan, S. and Starr, J. M. and Stott, D. J. and Tanaka, T. and Torlak, V. and Trompet, S. and Tuhkanen, J. and Uitterlinden, A. G. and van den Akker, E. B. and van den Eynde, T. and van der Klauw, M. M. and van Heemst, D. and Verroken, C. and Visser, W. E. and Vojinovic, D. and lzke, H. and Waldenberger, M. and Walsh, J. P. and Wareham, N. J. and Weiss, S. and Willer, C. J. and Wilson, S. G. and Wolffenbuttel, B. H. R. and Wouters, H. J. C. M. and Wright, M. J. and Yang, Q. and Zemunik, T. and Zhou, W. and Zhu, G. and llner, S. and Smit, J. W. A. and Peeters, R. P. and ttgen, A. and Teumer, A. and Medici, M.}
}
