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Pleiotropic loci underlying bone mineral density and bone size identified by a bivariate genome-wide association analysis

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Abstract

Summary

Aiming to identify pleiotropic genomic loci for bone mineral density and bone size, we performed a bivariate GWAS in five discovery samples and replicated in two large-scale samples. We identified 2 novel loci at 2q37.1 and 6q26. Our findings provide insight into common genetic architecture underlying both traits.

Introduction

Bone mineral density (BMD) and bone size (BS) are two important factors that contribute to the development of osteoporosis and osteoporotic fracture. Both BMD and BS are highly heritable and they are genetically correlated. In this study, we aim to identify pleiotropic loci associated with BMD and BS.

Methods

We conducted a bivariate genome-wide association (GWA) analysis of hip BMD and hip BS in 6180 participants from 5 samples, followed by in silico replication in the UK Biobank study of BMD (N = 426,824) and the deCODE study of BS (N = 28,954), respectively.

Results

SNPs from 2 genomic loci were significant at the genome-wide significance (GWS) level (p lt; 5 × 10−8) in the discovery samples and were successfully replicated in the replication samples (2q37.1, lead SNP rs7575512, discovery p = 1.49 × 10−10, replication p = 0.05; 6q26, lead SNP rs1040724, discovery p = 1.95 × 10−8, replication p = 0.03). Functional annotations suggested functional relevance of the identified variants to bone development.

Conclusion

Our findings provide insight into the common genetic architecture underlying BMD and BS, and enhance our understanding of the potential mechanism of osteoporosis fracture.

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Acknowledgments

We appreciate all the volunteers who participated into this study. We are grateful to both GEFOS consortia and the deCODE study for releasing large-scale GWAS summary results for replication analysis.

Funding

LZ and YFP are partially supported by the National Natural Science Foundation of China (31571291, 31771417, and 31501026) and a project of the Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions. RH is partially supported by the Inner Mongolia Autonomous Region Medical Health Science & Technology Research Program (201702180). HS and HWD are partially supported by the National Institutes of Health (R01AR059781, P20GM109036, R01MH107354, R01MH104680, R01GM109068, R01AR069055, U19AG055373, R01DK115679), the Edward G. Schlieder Endowment and the Drs. W. C. Tsai and P. T. Kung Professorship in Biostatistics from Tulane University. The numerical calculations in this paper have been done on the supercomputing system of the National Supercomputing Center in Changsha. The WHI program is funded by the National Heart, Lung, and Blood Institute, National 20 Institutes of Health, US Department of Health and Human Services through contracts N01WH22110, 24152, 32100-2, 32105-6, 32108-9, 32111-13, 32115, 32118-32119, 32122, 42107-26, 42129-32, and 44221. This manuscript was not prepared in collaboration with investigators of the WHI, has not been reviewed and/or approved by the Women’s Health Initiative (WHI), and does not necessarily reflect the opinions of the WHI investigators or the NHLBI. Funding for WHI SHARe genotyping was provided by NHLBI Contract N02-HL-64278. The datasets used for the analyses described in this manuscript were obtained from dbGaP at http://www.ncbi.nlm.nih.gov/sites/entrez?db=gap through dbGaP accession phs000200.v10.p3.

Author information

Author notes

  1. Hong-Zhang and Lu-Liu contributed equally to this work.

Authors and Affiliations

  1. Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, 199 Ren-ai Rd., SuZhou City, 215123, Jiangsu Province, People’s Republic of China

    H. Zhang, L. Liu, J.-J. Ni, X.-L. Yang & L. Zhang

  2. Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, 199 Ren-ai Rd., SuZhou City, 215123, Jiangsu Province, People’s Republic of China

    H. Zhang, L. Liu, J.-J. Ni, X.-T. Wei, G.-J. Feng, X.-L. Yang, Q. Xu, Y.-F. Pei & L. Zhang

  3. Kunshan Hospital of Traditional Chinese Medicine, SuZhou, Jiangsu, People’s Republic of China

    L. Liu

  4. Department of Epidemiology and Health Statistics, School of Public Health, Medical College of Soochow University, SuZhou, Jiangsu, People’s Republic of China

    X.-T. Wei, G.-J. Feng, Q. Xu & Y.-F. Pei

  5. People’s Hospital of Inner Mongolia Autonomous Region, Hohhot, Inner Mongolia, People’s Republic of China

    Z.-J. Zhang & R. Hai

  6. Department of Biostatistics and Bioinformatics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA

    Q. Tian, H. Shen & H.-W. Deng

  7. Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal St., Suite 2001, New Orleans, LA, 70112, USA

    H.-W. Deng

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  1. H. Zhang
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  2. L. Liu
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  8. Z.-J. Zhang
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  11. H. Shen
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  12. H.-W. Deng
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Corresponding authors

Correspondence to H.-W. Deng, Y.-F. Pei or L. Zhang.

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Zhang, H., Liu, L., Ni, JJ. et al. Pleiotropic loci underlying bone mineral density and bone size identified by a bivariate genome-wide association analysis. Osteoporos Int 31, 1691–1701 (2020). https://doi.org/10.1007/s00198-020-05389-x

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