Life-Course Genome-wide Association Study Meta-analysis of Total Body BMD and Assessment of Age-Specific Effects

Carolina Medina-Gomez; John P. Kemp; Katerina Trajanoska; Jian'an Luan; Alessandra Chesi; Tarunveer S. Ahluwalia; Dennis O. Mook-Kanamori; Annelies Ham; Fernando P. Hartwig; Daniel S. Evans; Raimo Joro; Ivana Nedeljkovic; Hou-Feng Zheng; Kun Zhu; Mustafa Atalay; Ching-Ti Liu; Maria Nethander; Linda Broer; Gudmar Porleifsson; Benjamin H. Mullin; Samuel K. Handelman; Mike A. Nalls; Leon Eyrich Jessen; Denise H. M. Heppe; J. Brent Richards; Carol Wang; Bo Chawes; Katharina E. Schraut; Najaf Amin; Nick Wareham; David Karasik; Nathalie Van der Velde; M. Arfan Ikram; Babette S. Zemel; Yanhua Zhou; Christian J. Carlsson; Yongmei Liu; Fiona E. McGuigan; Cindy G. Boer; Klaus Bønnelykke; Stuart H. Ralston; John A. Robbins; John P. Walsh; M. Carola Zillikens; Claudia Langenberg; Ruifang Li-Gao; Frances M. K. Williams; Tamara B. Harris; Kristina Akesson; Rebecca D. Jackson; Gunnar Sigurdsson; Martin den Heijer; Bram C. J. van der Eerden; Jeroen van de Peppel; Timothy D. Spector; Craig Pennell; Bernardo L. Horta; Janine F. Felix; Jing Hua Zhao; Scott G. Wilson; Renée de Mutsert; Hans Bisgaard; Unnur Styrkársdóttir; Vincent W. Jaddoe; Eric Orwoll; Timo A. Lakka; Robert Scott; Struan F. A. Grant; Mattias Lorentzon; Cornelia M. van Duijn; James F. Wilson; Kari Stefansson; Bruce M. Psaty; Douglas P. Kiel; Claes Ohlsson; Evangelia Ntzani; Andre J. van Wijnen; Vincenzo Forgetta; Mohsen Ghanbari; John G. Logan; Graham R. Williams; J. H. Duncan Bassett; Peter I. Croucher; Evangelos Evangelou; Andre G. Uitterlinden; Cheryl L. Ackert-Bicknell; Jonathan H. Tobias; David M. Evans; Fernando Rivadeneira

doi:10.1016/j.ajhg.2017.12.005

Life-Course Genome-wide Association Study Meta-analysis of Total Body BMD and Assessment of Age-Specific Effects

Carolina Medina-Gomez, John P. Kemp, Katerina Trajanoska, Jian'an Luan, Alessandra Chesi, Tarunveer S. Ahluwalia, Dennis O. Mook-Kanamori, Annelies Ham, Fernando P. Hartwig, Daniel S. Evans, Raimo Joro, Ivana Nedeljkovic, Hou-Feng Zheng, Kun Zhu, Mustafa Atalay, Ching-Ti Liu, Maria Nethander, Linda Broer, Gudmar Porleifsson, Benjamin H. MullinSamuel K. Handelman, Mike A. Nalls, Leon Eyrich Jessen, Denise H. M. Heppe, J. Brent Richards, Carol Wang, Bo Chawes, Katharina E. Schraut, Najaf Amin, Nick Wareham, David Karasik, Nathalie Van der Velde, M. Arfan Ikram, Babette S. Zemel, Yanhua Zhou, Christian J. Carlsson, Yongmei Liu, Fiona E. McGuigan, Cindy G. Boer, Klaus Bønnelykke, Stuart H. Ralston, John A. Robbins, John P. Walsh, M. Carola Zillikens, Claudia Langenberg, Ruifang Li-Gao, Frances M. K. Williams, Tamara B. Harris, Kristina Akesson, Rebecca D. Jackson, Gunnar Sigurdsson, Martin den Heijer, Bram C. J. van der Eerden, Jeroen van de Peppel, Timothy D. Spector, Craig Pennell, Bernardo L. Horta, Janine F. Felix, Jing Hua Zhao, Scott G. Wilson, Renée de Mutsert, Hans Bisgaard, Unnur Styrkársdóttir, Vincent W. Jaddoe, Eric Orwoll, Timo A. Lakka, Robert Scott, Struan F. A. Grant, Mattias Lorentzon, Cornelia M. van Duijn, James F. Wilson, Kari Stefansson, Bruce M. Psaty, Douglas P. Kiel, Claes Ohlsson, Evangelia Ntzani, Andre J. van Wijnen, Vincenzo Forgetta, Mohsen Ghanbari, John G. Logan, Graham R. Williams, J. H. Duncan Bassett, Peter I. Croucher, Evangelos Evangelou, Andre G. Uitterlinden, Cheryl L. Ackert-Bicknell, Jonathan H. Tobias, David M. Evans, Fernando Rivadeneira^*

^*Corresponding author for this work

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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.

Original language	English
Journal	American Journal of Human Genetics
Volume	102
Issue number	1
Pages (from-to)	88-102
ISSN	0002-9297
DOIs	https://doi.org/10.1016/j.ajhg.2017.12.005
Publication status	Published - 2018

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Medina-Gomez, C., Kemp, J. P., Trajanoska, K., Luan, J., Chesi, A., Ahluwalia, T. S., Mook-Kanamori, D. O., Ham, A., Hartwig, F. P., Evans, D. S., Joro, R., Nedeljkovic, I., Zheng, H.-F., Zhu, K., Atalay, M., Liu, C.-T., Nethander, M., Broer, L., Porleifsson, G., ... Rivadeneira, F. (2018). Life-Course Genome-wide Association Study Meta-analysis of Total Body BMD and Assessment of Age-Specific Effects. American Journal of Human Genetics, 102(1), 88-102. https://doi.org/10.1016/j.ajhg.2017.12.005

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title = "Life-Course Genome-wide Association Study Meta-analysis of Total Body BMD and Assessment of Age-Specific Effects",

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 = "Carolina Medina-Gomez and Kemp, {John P.} and Katerina Trajanoska and Jian'an Luan and Alessandra Chesi and Ahluwalia, {Tarunveer S.} and Mook-Kanamori, {Dennis O.} and Annelies Ham and Hartwig, {Fernando P.} and Evans, {Daniel S.} and Raimo Joro and Ivana Nedeljkovic and Hou-Feng Zheng and Kun Zhu and Mustafa Atalay and Ching-Ti Liu and Maria Nethander and Linda Broer and Gudmar Porleifsson and Mullin, {Benjamin H.} and Handelman, {Samuel K.} and Nalls, {Mike A.} and Jessen, {Leon Eyrich} and Heppe, {Denise H. M.} and Richards, {J. Brent} and Carol Wang and Bo Chawes and Schraut, {Katharina E.} and Najaf Amin and Nick Wareham and David Karasik and {Van der Velde}, Nathalie and Ikram, {M. Arfan} and Zemel, {Babette S.} and Yanhua Zhou and Carlsson, {Christian J.} and Yongmei Liu and McGuigan, {Fiona E.} and Boer, {Cindy G.} and Klaus B{\o}nnelykke and Ralston, {Stuart H.} and Robbins, {John A.} and Walsh, {John P.} and Zillikens, {M. Carola} and Claudia Langenberg and Ruifang Li-Gao and Williams, {Frances M. K.} and Harris, {Tamara B.} and Kristina Akesson and Jackson, {Rebecca D.} and Gunnar Sigurdsson and {den Heijer}, Martin and {van der Eerden}, {Bram C. J.} and {van de Peppel}, Jeroen and Spector, {Timothy D.} and Craig Pennell and Horta, {Bernardo L.} and Felix, {Janine F.} and Zhao, {Jing Hua} and Wilson, {Scott G.} and {de Mutsert}, Ren{\'e}e and Hans Bisgaard and Unnur Styrk{\'a}rsd{\'o}ttir and Jaddoe, {Vincent W.} and Eric Orwoll and Lakka, {Timo A.} and Robert Scott and Grant, {Struan F. A.} and Mattias Lorentzon and {van Duijn}, {Cornelia M.} and Wilson, {James F.} and Kari Stefansson and Psaty, {Bruce M.} and Kiel, {Douglas P.} and Claes Ohlsson and Evangelia Ntzani and {van Wijnen}, {Andre J.} and Vincenzo Forgetta and Mohsen Ghanbari and Logan, {John G.} and Williams, {Graham R.} and Bassett, {J. H. Duncan} and Croucher, {Peter I.} and Evangelos Evangelou and Uitterlinden, {Andre G.} and Ackert-Bicknell, {Cheryl L.} and Tobias, {Jonathan H.} and Evans, {David M.} and Fernando Rivadeneira",

year = "2018",

doi = "10.1016/j.ajhg.2017.12.005",

language = "English",

volume = "102",

pages = "88--102",

journal = "American Journal of Human Genetics",

issn = "0002-9297",

publisher = "Cell Press",

number = "1",

}

Medina-Gomez, C, Kemp, JP, Trajanoska, K, Luan, J, Chesi, A, Ahluwalia, TS, Mook-Kanamori, DO, Ham, A, Hartwig, FP, Evans, DS, Joro, R, Nedeljkovic, I, Zheng, H-F, Zhu, K, Atalay, M, Liu, C-T, Nethander, M, Broer, L, Porleifsson, G, Mullin, BH, Handelman, SK, Nalls, MA, Jessen, LE, Heppe, DHM, Richards, JB, Wang, C, Chawes, B, Schraut, KE, Amin, N, Wareham, N, Karasik, D, Van der Velde, N, Ikram, MA, Zemel, BS, Zhou, Y, Carlsson, CJ, Liu, Y, McGuigan, FE, Boer, CG, Bønnelykke, K, Ralston, SH, Robbins, JA, Walsh, JP, Zillikens, MC, Langenberg, C, Li-Gao, R, Williams, FMK, Harris, TB, Akesson, K, Jackson, RD, Sigurdsson, G, den Heijer, M, van der Eerden, BCJ, van de Peppel, J, Spector, TD, Pennell, C, Horta, BL, Felix, JF, Zhao, JH, Wilson, SG, de Mutsert, R, Bisgaard, H, Styrkársdóttir, U, Jaddoe, VW, Orwoll, E, Lakka, TA, Scott, R, Grant, SFA, Lorentzon, M, van Duijn, CM, Wilson, JF, Stefansson, K, Psaty, BM, Kiel, DP, Ohlsson, C, Ntzani, E, van Wijnen, AJ, Forgetta, V, Ghanbari, M, Logan, JG, Williams, GR, Bassett, JHD, Croucher, PI, Evangelou, E, Uitterlinden, AG, Ackert-Bicknell, CL, Tobias, JH, Evans, DM & Rivadeneira, F 2018, 'Life-Course Genome-wide Association Study Meta-analysis of Total Body BMD and Assessment of Age-Specific Effects', American Journal of Human Genetics, vol. 102, no. 1, pp. 88-102. https://doi.org/10.1016/j.ajhg.2017.12.005

TY - JOUR

T1 - Life-Course Genome-wide Association Study Meta-analysis of Total Body BMD and Assessment of Age-Specific Effects

AU - Medina-Gomez, Carolina

AU - Kemp, John P.

AU - Trajanoska, Katerina

AU - Luan, Jian'an

AU - Chesi, Alessandra

AU - Ahluwalia, Tarunveer S.

AU - Mook-Kanamori, Dennis O.

AU - Ham, Annelies

AU - Hartwig, Fernando P.

AU - Evans, Daniel S.

AU - Joro, Raimo

AU - Nedeljkovic, Ivana

AU - Zheng, Hou-Feng

AU - Zhu, Kun

AU - Atalay, Mustafa

AU - Liu, Ching-Ti

AU - Nethander, Maria

AU - Broer, Linda

AU - Porleifsson, Gudmar

AU - Mullin, Benjamin H.

AU - Handelman, Samuel K.

AU - Nalls, Mike A.

AU - Jessen, Leon Eyrich

AU - Heppe, Denise H. M.

AU - Richards, J. Brent

AU - Wang, Carol

AU - Chawes, Bo

AU - Schraut, Katharina E.

AU - Amin, Najaf

AU - Wareham, Nick

AU - Karasik, David

AU - Van der Velde, Nathalie

AU - Ikram, M. Arfan

AU - Zemel, Babette S.

AU - Zhou, Yanhua

AU - Carlsson, Christian J.

AU - Liu, Yongmei

AU - McGuigan, Fiona E.

AU - Boer, Cindy G.

AU - Bønnelykke, Klaus

AU - Ralston, Stuart H.

AU - Robbins, John A.

AU - Walsh, John P.

AU - Zillikens, M. Carola

AU - Langenberg, Claudia

AU - Li-Gao, Ruifang

AU - Williams, Frances M. K.

AU - Harris, Tamara B.

AU - Akesson, Kristina

AU - Jackson, Rebecca D.

AU - Sigurdsson, Gunnar

AU - den Heijer, Martin

AU - van der Eerden, Bram C. J.

AU - van de Peppel, Jeroen

AU - Spector, Timothy D.

AU - Pennell, Craig

AU - Horta, Bernardo L.

AU - Felix, Janine F.

AU - Zhao, Jing Hua

AU - Wilson, Scott G.

AU - de Mutsert, Renée

AU - Bisgaard, Hans

AU - Styrkársdóttir, Unnur

AU - Jaddoe, Vincent W.

AU - Orwoll, Eric

AU - Lakka, Timo A.

AU - Scott, Robert

AU - Grant, Struan F. A.

AU - Lorentzon, Mattias

AU - van Duijn, Cornelia M.

AU - Wilson, James F.

AU - Stefansson, Kari

AU - Psaty, Bruce M.

AU - Kiel, Douglas P.

AU - Ohlsson, Claes

AU - Ntzani, Evangelia

AU - van Wijnen, Andre J.

AU - Forgetta, Vincenzo

AU - Ghanbari, Mohsen

AU - Logan, John G.

AU - Williams, Graham R.

AU - Bassett, J. H. Duncan

AU - Croucher, Peter I.

AU - Evangelou, Evangelos

AU - Uitterlinden, Andre G.

AU - Ackert-Bicknell, Cheryl L.

AU - Tobias, Jonathan H.

AU - Evans, David M.

AU - Rivadeneira, Fernando

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

U2 - 10.1016/j.ajhg.2017.12.005

DO - 10.1016/j.ajhg.2017.12.005

M3 - Journal article

C2 - 29304378

SN - 0002-9297

VL - 102

SP - 88

EP - 102

JO - American Journal of Human Genetics

JF - American Journal of Human Genetics

IS - 1

ER -

Life-Course Genome-wide Association Study Meta-analysis of Total Body BMD and Assessment of Age-Specific Effects

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