H Zhang1,2, L Liu1,2,3, J-J Ni1,2, X-T Wei2,4, G-J Feng2,4, X-L Yang1,2, Q Xu2,4, Z-J Zhang5, R Hai5, Q Tian6, H Shen6, H-W Deng7,8, Y-F Pei9,10, L Zhang11,12. 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. 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. 3. Kunshan Hospital of Traditional Chinese Medicine, SuZhou, Jiangsu, People's Republic of China. 4. Department of Epidemiology and Health Statistics, School of Public Health, Medical College of Soochow University, SuZhou, Jiangsu, People's Republic of China. 5. People's Hospital of Inner Mongolia Autonomous Region, Hohhot, Inner Mongolia, People's Republic of China. 6. Department of Biostatistics and Bioinformatics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA. 7. Department of Biostatistics and Bioinformatics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA. hdeng2@tulane.edu. 8. Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal St., Suite 2001, New Orleans, LA, 70112, USA. hdeng2@tulane.edu. 9. 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. ypei@suda.edu.cn. 10. Department of Epidemiology and Health Statistics, School of Public Health, Medical College of Soochow University, SuZhou, Jiangsu, People's Republic of China. ypei@suda.edu.cn. 11. 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. lzhang6@suda.edu.cn. 12. 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. lzhang6@suda.edu.cn.
Abstract
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.
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.
Entities:
Keywords:
2q37.1; 6q26; Bivariate GWAS; Hip bone mineral density; Hip bone size
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