Yu Liu1,2, Shu Ran2, Yong Lin2, Yu-Xue Zhang2, Xiao-Lin Yang1,3, Xin-Tong Wei3,4, Zi-Xuan Jiang2, Xiao He2, Hong Zhang1,3, Gui-Juan Feng3,4, Hui Shen5, Qing Tian5, Hong-Wen Deng6, Lei Zhang7,8, Yu-Fang Pei9,10. 1. Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Jiangsu, PR China. 2. School of Medical Instruments and Food Engineering, University of Shanghai for Science and Technology, Shanghai, PR China. 3. Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Jiangsu, PR China. 4. Department of Epidemiology and Health Statistics, Medical College of Soochow University, Jiangsu, PR China. 5. Department of Biostatistics and Bioinformatics, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA. 6. Department of Biostatistics and Bioinformatics, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA. hdeng2@tulane.edu. 7. Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Jiangsu, PR China. lzhang6@suda.edu.cn. 8. Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Jiangsu, PR China. lzhang6@suda.edu.cn. 9. Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Jiangsu, PR China. ypei@suda.edu.cn. 10. Department of Epidemiology and Health Statistics, Medical College of Soochow University, Jiangsu, PR China. ypei@suda.edu.cn.
Abstract
BACKGROUND: Fat mass and lean mass are two biggest components of body mass. Both fat mass and lean mass are under strong genetic determinants and are correlated. METHODS: We performed a bivariate genome-wide association meta-analysis of (lean adjusted) leg fat mass and (fat adjusted) leg lean mass in 12,517 subjects from 6 samples, and followed by in silico replication in large-scale UK biobank cohort sample (N = 370 097). RESULTS: We identified four loci that were significant at the genome-wide significance (GWS, α = 5.0 × 10-8) level at the discovery meta-analysis, and successfully replicated in the replication sample: 2q36.3 (rs1024137, pdiscovery = 3.32 × 10-8, preplication = 4.07 × 10-13), 5q13.1 (rs4976033, pdiscovery = 1.93 × 10-9, preplication = 6.35 × 10-7), 12q24.31 (rs4765528, pdiscovery = 7.19 × 10-12, preplication = 1.88 × 10-11) and 18q21.32 (rs371326986, pdiscovery = 9.04 × 10-9, preplication = 2.35 × 10-95). The above four pleiotropic loci may play a pleiotropic role for fat mass and lean mass development. CONCLUSIONS: Our findings further enhance the understanding of the genetic association between fat mass and lean mass and provide a new theoretical basis for their understanding.
BACKGROUND: Fat mass and lean mass are two biggest components of body mass. Both fat mass and lean mass are under strong genetic determinants and are correlated. METHODS: We performed a bivariate genome-wide association meta-analysis of (lean adjusted) leg fat mass and (fat adjusted) leg lean mass in 12,517 subjects from 6 samples, and followed by in silico replication in large-scale UK biobank cohort sample (N = 370 097). RESULTS: We identified four loci that were significant at the genome-wide significance (GWS, α = 5.0 × 10-8) level at the discovery meta-analysis, and successfully replicated in the replication sample: 2q36.3 (rs1024137, pdiscovery = 3.32 × 10-8, preplication = 4.07 × 10-13), 5q13.1 (rs4976033, pdiscovery = 1.93 × 10-9, preplication = 6.35 × 10-7), 12q24.31 (rs4765528, pdiscovery = 7.19 × 10-12, preplication = 1.88 × 10-11) and 18q21.32 (rs371326986, pdiscovery = 9.04 × 10-9, preplication = 2.35 × 10-95). The above four pleiotropic loci may play a pleiotropic role for fat mass and lean mass development. CONCLUSIONS: Our findings further enhance the understanding of the genetic association between fat mass and lean mass and provide a new theoretical basis for their understanding.
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