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Cited by 245Genetic Associations and EpidemiologyGenetics and Physical PerformanceBody Composition Measurement Techniques

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Genome-wide association study of body fat distribution identifies adiposity loci and sex-specific genetic effects

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Rask-Andersen, Mathias, Karlsson, Torgny, Ek, Weronica E., Johansson, Åsa·2019·Nature Communications
DOI 10.1038/s41467-018-08000-4PMC PMC6341104

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Abstract

Body mass and body fat composition are of clinical interest due to their links to cardiovascular- and metabolic diseases. Fat stored in the trunk has been suggested to be more pathogenic compared to fat stored in other compartments. In this study, we perform genome-wide association studies (GWAS) for the proportion of body fat distributed to the arms, legs and trunk estimated from segmental bio-electrical impedance analysis (sBIA) for 362,499 individuals from the UK Biobank. 98 independent associations with body fat distribution are identified, 29 that have not previously been associated with anthropometric traits. A high degree of sex-heterogeneity is observed and the effects of 37 associated variants are stronger in females compared to males. Our findings also implicate that body fat distribution in females involves mesenchyme derived tissues and cell types, female endocrine tissues as well as extracellular matrix maintenance and remodeling.

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Fig. 1 Segmental body impedance analyses. This method uses bio-electrical impedance to estimate body composition: fat mass, muscle mass, etc. In this study, adipose tissue mass was estimated using the Tanita BC-418MA body composition analyzer (a). This machine uses an eight-electrode method, which allows for five measurements of impedance. Electrical current is supplied to the front of both feet and the fingertips of both hands. Voltage is measured on either heel or thenar portion of the palms. Body composition is derived from a regression formula for each body part. The formula is derived from regression analysis using height, weight, age and impedance for each body part as predictors for composition of each body part as assessed by DXA (b). GWAS for AFR, LFR, and TFR were conducted in the UK Biobank cohort and revealed associations with loci that have not previously been associated with standard anthropometric traits. c A manhattan plot with combined results for association studies of body fat ratios in combined and sex-stratified analyses. Overall, 135 independent associations with at least one of the body fat ratios were observed in the discovery analyses. Out of the initial 135 associations, 98 replicated; of which 30 replicated for AFR, 44 for LFR and 66 for TFR. Loci that have not previously been associated with an anthropomorphic trait are highlighted in red (N = 29)
Fig. 1 Segmental body impedance analyses. This method uses bio-electrical impedance to estimate body composition: fat mass, muscle mass, etc. In this study, adipose tissue mass was estimated using the Tanita BC-418MA body composition analyzer (a). This machine uses an eight-electrode method, which allows for five measurements of impedance. Electrical current is supplied to the front of both feet and the fingertips of both hands. Voltage is measured on either heel or thenar portion of the palms. Body composition is derived from a regression formula for each body part. The formula is derived from regression analysis using height, weight, age and impedance for each body part as predictors for composition of each body part as assessed by DXA (b). GWAS for AFR, LFR, and TFR were conducted in the UK Biobank cohort and revealed associations with loci that have not previously been associated with standard anthropometric traits. c A manhattan plot with combined results for association studies of body fat ratios in combined and sex-stratified analyses. Overall, 135 independent associations with at least one of the body fat ratios were observed in the discovery analyses. Out of the initial 135 associations, 98 replicated; of which 30 replicated for AFR, 44 for LFR and 66 for TFR. Loci that have not previously been associated with an anthropomorphic trait are highlighted in red (N = 29)CC BY · PubMed Central
Fig. 2 Overlap and genetic correlation between body fat ratios and other anthropometric traits. a The overlap between AFR-, LFR-, and TFR-associated loci is illustrated as a Venn diagram. The loci are denoted by the nearest gene or by the most likely target gene (see methods section). The loci in bold type and larger font designate loci that have not previously been associated with an anthropometric trait. The total number in each field is illustrated top right. *: Two independent signals were observed within the ADAMTS17 locus: one with an effect on LFR and one on TFR. #: Two independent associations with LFR and TFR were observed within the ACAN locus. b Genetic correlation between body fat ratios within, and between sexes. Genetic correlations were estimated by cross-trait LD-score regression32. The absolute values for each genetic correlation (rg) is included. c Genetic correlations between body fat ratios and standard anthropometric traits. Sex-stratified summary statistics were generated for each trait by GWAS in the discovery cohort. Color scales represent genetic correlation and range from red (−1.0: perfect anticorrelation) to blue (1.0 perfect correlation)
Fig. 2 Overlap and genetic correlation between body fat ratios and other anthropometric traits. a The overlap between AFR-, LFR-, and TFR-associated loci is illustrated as a Venn diagram. The loci are denoted by the nearest gene or by the most likely target gene (see methods section). The loci in bold type and larger font designate loci that have not previously been associated with an anthropometric trait. The total number in each field is illustrated top right. *: Two independent signals were observed within the ADAMTS17 locus: one with an effect on LFR and one on TFR. #: Two independent associations with LFR and TFR were observed within the ACAN locus. b Genetic correlation between body fat ratios within, and between sexes. Genetic correlations were estimated by cross-trait LD-score regression32. The absolute values for each genetic correlation (rg) is included. c Genetic correlations between body fat ratios and standard anthropometric traits. Sex-stratified summary statistics were generated for each trait by GWAS in the discovery cohort. Color scales represent genetic correlation and range from red (−1.0: perfect anticorrelation) to blue (1.0 perfect correlation)CC BY · PubMed Central
Fig. 3 Enrichment analyses of genes at LFR and TFR-associated loci. a Reconstituted gene-sets that were enriched for TFR- and LFR-associated genes (in both males and females) were compared to results from previous GWAS on WHRadjBMI12, BMI9, and height20. Tissue and cell type enrichment of b TFR- and c LFR-associated genes in females. Red bars denote tissues gene sets that were significantly enriched for LFR- and TFR-associated genes at FDR < 0.05/12
Fig. 3 Enrichment analyses of genes at LFR and TFR-associated loci. a Reconstituted gene-sets that were enriched for TFR- and LFR-associated genes (in both males and females) were compared to results from previous GWAS on WHRadjBMI12, BMI9, and height20. Tissue and cell type enrichment of b TFR- and c LFR-associated genes in females. Red bars denote tissues gene sets that were significantly enriched for LFR- and TFR-associated genes at FDR < 0.05/12CC BY · PubMed Central

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Metadata

Authors
Rask-Andersen, M., Karlsson, T., Ek, W. E., & Johansson, Å.
Affiliations
Uppsala University (SE)
Corresponding author
Johansson, Åsa
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2019-01-21
Volume
10
Issue
1
Pages
339-339
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-018-08000-4
PMC
PMC6341104
OpenAlex
W2908665501
Cited by
245
References
56
Citations by year
2026: 17 · 2025: 25 · 2024: 22 · 2023: 37 · 2022: 63 · 2021: 41 · 2020: 29 · 2019: 11
FWCI
21.70
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • KTH Publication Database DiVA (KTH Royal Institute of Technology) (submittedVersion, other-oa)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Åke Wiberg Stiftelse
  • Svenska Sällskapet för Medicinsk Forskning
  • Hjärt-Lungfonden
  • Medical Research Council (MC_PC_17228)
  • Uppsala Multidisciplinary Center for Advanced Computational Science
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Physical Performance
  • Health Sciences › Medicine › Physiology (medical) › Body Composition Measurement Techniques
Keywords
body fat distribution, trunk fat, sex-specific genetic effects, segmental bioelectrical impedance analysis, anthropometric traits, mesenchyme, extracellular matrix remodeling, obesity genetics
MeSH terms
Adipose Tissue, Anthropometry, Arm, Body Weight, Endocrine Glands, Female, Gene Expression Regulation, United Kingdom, Humans, Leg, Male, Obesity, Sex Factors, Body Mass Index, Electric Impedance, Biological Specimen Banks, Genetic Heterogeneity, Polymorphism, Single Nucleotide, Gene Expression Profiling, Waist-Hip Ratio, Body Fat Distribution, Genome-Wide Association Study, Genetic Loci, Torso

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