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Epidemiology and Population Health

Four pleiotropic loci associated with fat mass and lean mass

International Journal of Obesity volume 44, pages 2113–2123 (2020)Cite this article

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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.

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Fig. 1: Logarithmic quantile–quantile (QQ) plot of the discovery GWAS results.
Fig. 2: Manhattan plot of the GWAS meta-analysis for LFM and LLM.
Fig. 3: Age dependent effect at the identified loci.
Fig. 4: Regional plot of rs4976033.
Fig. 5: Protein–protein interaction network for PIK3R1.

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Acknowledgements

We appreciate all the volunteers who participated into this study. The Framingham Heart Study is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with Boston University (Contract No. N01-HC-25195). This manuscript was not prepared in collaboration with investigators of the Framingham Heart Study and does not necessarily reflect the opinions or views of the Framingham Heart Study, Boston University, or NHLBI. Funding for SHARe Affymetrix genotyping was provided by NHLBI Contract N02-HL-64278. SHARe Illumina genotyping was provided under an agreement between Illumina and Boston University. Funding support for the Framingham Whole Body and Regional Dual X-ray Absorptiometry (DXA) dataset was provided by NIH grants R01 AR/AG 41398. 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 phs000342.v14.p 10. The WHI program is funded by the National Heart, Lung, and Blood Institute, National 20 Institutes of Health, U.S. 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.p 3.

Funding

YFP and LZ were partially supported by the funding from National Natural Science Foundation of China (31771417 and 31571291). HWD was partially supported by the National Institutes of Health (R01 AR069055, U19 AG055373, R01 MH104680, R01 AR059781 and P20 GM109036), the Franklin D. Dickson/Missouri Endowment and the Edward G. Schlieder Endowment. This study was also benefited from a project funded by the Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions. The numerical calculations in this paper have been done on the supercomputing system of the National Supercomputing Center in Changsha. The funders had no role in study design, data collection and analysis, results interpretation, or preparation of the manuscript.

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Author notes

  1. These authors contributed equally: Yu Liu, Shu Ran, Yong Lin

  2. These authors jointly supervised this study: Hong-Wen Deng, Lei Zhang, Yu-Fang Pei

Authors and Affiliations

  1. Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Jiangsu, PR China

    Yu Liu, Xiao-Lin Yang, Hong Zhang & Lei Zhang

  2. School of Medical Instruments and Food Engineering, University of Shanghai for Science and Technology, Shanghai, PR China

    Yu Liu, Shu Ran, Yong Lin, Yu-Xue Zhang, Zi-Xuan Jiang & Xiao He

  3. Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Jiangsu, PR China

    Xiao-Lin Yang, Xin-Tong Wei, Hong Zhang, Gui-Juan Feng, Lei Zhang & Yu-Fang Pei

  4. Department of Epidemiology and Health Statistics, Medical College of Soochow University, Jiangsu, PR China

    Xin-Tong Wei, Gui-Juan Feng & Yu-Fang Pei

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

    Hui Shen, Qing Tian & Hong-Wen Deng

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Liu, Y., Ran, S., Lin, Y. et al. Four pleiotropic loci associated with fat mass and lean mass. Int J Obes 44, 2113–2123 (2020). https://doi.org/10.1038/s41366-020-0645-0

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