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Genetics of sexually dimorphic adipose distribution in humans

Nature Genetics volume 55, pages 461–470 (2023)Cite this article

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Abstract

Obesity-associated morbidity is exacerbated by abdominal obesity, which can be measured as the waist-to-hip ratio adjusted for the body mass index (WHRadjBMI). Here we identify genes associated with obesity and WHRadjBMI and characterize allele-sensitive enhancers that are predicted to regulate WHRadjBMI genes in women. We found that several waist-to-hip ratio-associated variants map within primate-specific Alu retrotransposons harboring a DNA motif associated with adipocyte differentiation. This suggests that a genetic component of adipose distribution in humans may involve co-option of retrotransposons as adipose enhancers. We evaluated the role of the strongest female WHRadjBMI-associated gene, SNX10, in adipose biology. We determined that it is required for human adipocyte differentiation and function and participates in diet-induced adipose expansion in female mice, but not males. Our data identify genes and regulatory mechanisms that underlie female-specific adipose distribution and mediate metabolic dysfunction in women.

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Fig. 1: Characteristics of obesity and WHRadjBMI genetic risk.
Fig. 2: Genes identified by TWAS.
Fig. 3: Regulatory network of female WHRadjBMI.
Fig. 4: Effects of the rs1534696 allele on human primary adipocytes.
Fig. 5: SNX10-mediated inhibition of adipogenesis.

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Data availability

Previously published gene expression and GWAS data that were used in this study can be accessed via the GTEx Consortium (https://gtexportal.org/home/biobank), CommonMind consortium (https://www.nimhgenetics.org/resources/commonmind), UKBB (https://pan.ukbb.broadinstitute.org/downloads) and GIANT Consortium (https://portals.broadinstitute.org/collaboration/giant/index.php/GIANT_consortium_data_files). 15-state chromHMM data from adipose nuclei were obtained at https://egg2.wustl.edu/roadmap/data/byFileType/chromhmmSegmentations/ChmmModels/coreMarks/jointModel/final/E063_15_coreMarks_dense.bed.gz. Other data include RepeatMasker hg38 repeat data, hg38 phastCons conservation and the GRCh38 and GRCh37 genome assemblies (https://hgdownload.soe.ucsc.edu/downloads.html#human). Baseline annotations used for calculating LDSC-SEG tissue-specific gene enrichment can be found at https://github.com/bulik/ldsc. Comparison MPRA data from Ulirsch et al.25 can be obtained on request from the Sankaran lab. Comparison data from Khetan et al.49 can be found at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE145643. Sequencing data generated in this study can be found in the NCBI Sequence Read Archive via the BioProject accession code PRJNA847334. Tables that contain data generated in this study, including LDSC-SEG enrichment for obesity and WHR, xCell cell type proportion estimations, obesity and WHRadjBMI-associated genes identified in the paper, variants tested in the MPRA, with enhancer activity levels and significance status, transcription factor motif enrichment data, significant LipocyteProfiler features, SNX10 shRNA knockdown and SNX10 mouse data, have been uploaded to the Open Science Framework in a repository entitled ‘Genetics of sexually dimorphic adipose distribution in humans’ (https://osf.io/cesvr/).

Code availability

Unless otherwise specified in Methods, all code used to generate the figures and data included in this study are available at https://github.com/grace-hansen/.

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Acknowledgements

This work was supported by the Novo Nordisk Foundation (challenge grant NNF18OC0033754 to M.A.N.), Novo Nordisk Foundation grant NNF21SA0072102 to M.C., the National Institutes of Health (grants R01HL128075, P30DK020595 and R01HL119577 to M.A.N., grant R01AR064793 to R.A.B., grant UM1126185 to M.C. and training grant T32HL007381 to A.C.J) and the American Heart Association (grant 20PRE35210899 to G.T.H.). We thank A. Candles for support with the paper.

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Author notes

  1. These authors contributed equally: Grace T. Hansen, Débora R. Sobreira.

Authors and Affiliations

  1. Department of Human Genetics, University of Chicago, Chicago, IL, USA

    Grace T. Hansen, Débora R. Sobreira, Zachary T. Weber, Alexis G. Thornburg, Ivy Aneas, Li Zhang, Noboru J. Sakabe, Amelia C. Joslin, Gabriela A. Haddad, Yang I. Li & Marcelo A. Nóbrega

  2. Pritzker School of Medicine, University of Chicago, Chicago, IL, USA

    Grace T. Hansen

  3. Broad Institute of MIT and Harvard, Boston, MA, USA

    Sophie M. Strobel, Samantha Laber & Melina Claussnitzer

  4. Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany

    Sophie M. Strobel

  5. Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK

    Samantha Laber

  6. Department of Rehabilitation Medicine, University of Minnesota, Minneapolis, MN, USA

    Farhath Sultana, Faezeh Sahebdel, Kohinoor Khan, Liang Ye & Ricardo A. Battaglino

  7. Department of Genetic Medicine, University of Chicago, Chicago, IL, USA

    Yang I. Li

  8. Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, MA, USA

    Melina Claussnitzer

  9. Massachussetts General Hospital, Harvard Medical School, Boston, MA, USA

    Melina Claussnitzer

  10. Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA

    Melina Claussnitzer

  11. Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA

    Melina Claussnitzer

  12. Department of Medicine, Harvard Medical School, Boston, MA, USA

    Melina Claussnitzer

  13. Novo Nordisk Foundation Center for Genomic Mechanisms of Disease at the Broad Institute of MIT and Harvard, Boston, MA, USA

    Melina Claussnitzer

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  1. Grace T. Hansen
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Contributions

G.T.H., M.A.N. and Y.I.L. conceived of the initial TWAS approach to finding genes associated with obesity and WHRadjBMI. Y.I.L. supervised the genetic correlation, LDSC-SEG and TWAS analyses. A.C.J. and G.A.H. performed the MPRA with assistance and direction from D.R.S. L.Y. performed the mmΔSnx10Adipoq mouse generation, HFD administration and DEXA scanning with supervision from R.A.B., L.Y., F. Sahebdel and K.K. F. Sultana and K.K. performed the SNX10 shRNA experiments with supervision and training from R.A.B. A.G.T. and D.R.S. performed the luciferase assays to confirm the regulatory activity of Alu elements. I.A., Z.T.W., L.Z. and D.R.S. performed the CRISPR-mediated deletion of Alu elements. Z.T.W. and N.J.S. analyzed the CRISPR data. S.M.S. and S.L. performed the ABC and LipocyteProfiler analyses with supervision from M.C. G.T.H. performed the genetic correlation, LDSC-SEG, TWAS, MPRA and motif analyses. G.T.H. drafted the manuscript and figures with editorial assistance from M.A.N.

Corresponding authors

Correspondence to Grace T. Hansen, Liang Ye, Ricardo A. Battaglino or Marcelo A. Nóbrega.

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Extended data

Extended Data Fig. 1 UKBB GWAS summary statistics at SNX10 locus, triglycerides.

Plots represent UK biobank GWAS summary statistics for quantile-binned blood triglyceride levels, separated by sex. x- axis represents genomic position; y axis represents -log10(p) for association with trait. Color of points represents linkage with rs1534696. Female N = 315,133, male N = 315,133.

Extended Data Fig. 2 UKBB GWAS summary statistics at SNX10 locus, HDL cholesterol.

Plots represent UK biobank GWAS summary statistics for quantile-binned HDL cholesterol levels, separated by sex. x- axis represents genomic position; y axis represents -log10(p) for association with trait. Color of points represents linkage with rs1534696. Female N = 315,133, male N = 315,133.

Extended Data Fig. 3 Enhancer-modulating variants by allele.

Normalized activity level of all 58 enhancer-modulating variants. y axis represents normalized activity level; x axis represents allele. enhancer-modulating variants are labeled by rsid and by female WHRadjBMI TWAS gene from which they were identified (see MPRA methods). Data are colored by expression (darker=more highly expressed allele).

Extended Data Fig. 4 Enrichment of significant MPRA enhancers in active adipose chromHMM marks.

y axis represents number of rsids per adipose nuclei chromHMM category; x axis represents chromHMM category; grouping represents MPRA variant type (significant/nonsignificant). p-values represents chi-square testing of observed values to values expected by chance.

Extended Data Fig. 5 Functional validation of MPRA variants.

This plot shows luciferase activity (luciferase/Renilla) averages in 3T3-L1 preadipocytes for four technical replicates (n = 4) and average ± SEM of these four technical replicates for the control and each variant construct. Significant increase in luciferase activity between each construct and control was measured using a one-tailed paired t-test. * p < 0.05, ** p < 0.01, *** p < 0.001. Exact p-values are reported in the luciferase data available in the repository. Data are colored by MPRA significance status.

Extended Data Fig. 6 CRISPR/cas9-mediated deletion of Alu-associated MPRA enhancers.

These plots show significantly down- and up-regulated genes subsequent to deletion of MPRA-identified enhancers (rs4955430 and rs6446275) contained within an Alu element, and a nonsignificant MPRA variant also located within an Alu element. Genomic deletions ranged from 585 to 1,300 bp (see Supplementary table 7), and each deletion was assessed in triplicate. Significance is derived from edgeR modeling and FDR correction, and defined astwo-sided p < 0.05 and q < 0.05. Box plot whiskers represent minimum (1st percentile) and maximum (99th percentile) expression, box bounds represent first quartile (25th percentile and 75th percentile), and center line represents median of data (50th percentile). Exact p-values are reported in the CRISPR data available in the repository. Data are colored by rs1534696 genotype.

Extended Data Fig. 7 Correlation of SNX10 expression with adipocyte markers.

Numbers represent Pearson’s r values. Genes included are mature adipocyte markers PLIN1, LEP, FABP4, and ADIPOQ, adipocyte progenitor marker ICAM1, and multipotent progenitor marker DPP4. Samples are all those included in GTEx v8 subcutaneous adipose (n = 581).

Extended Data Fig. 8 Metabolic and anthropometric attributes of mmΔSnx10Adipoq mice and control littermates.

* indicates p < 0.01. All statistical tests are two-sided Student’s t-tests between sex-genotype groups. F-control n = 12 mice, F-KO n = 5, M-control n = 34 M-KO n = 6 in all tests. Box plot whiskers represent minimum (1st percentile) and maximum (99th percentile) of data, box bounds represent first quartile (25th percentile and 75th percentile), and center line represents median of data (50th percentile). a) Mass of body fat of mmΔSnx10Adipoq mice and littermate controls by sex. b) Femur length of mmΔSnx10Adipoq mice and littermate controls by sex. c) Lean mass of mmΔSnx10Adipoq mice and littermate controls by sex. d) Lean percent of mmΔSnx10Adipoq mice and littermate controls by sex. Data are colored by sex and SNX10 genotype. Fat weight:Mean FC = 19.6, mean FKO = 7.50, mean MC = 19.0, mean MKO = 20.9. FKO vs MKOt=5.90, df=4, CI = 7.33-19.5. Lean weight:Mean FC = 20.3, mean FKO = 17.8, mean MC = 25.4, mean MKO = 26.5. FKO vs MKO t = 8.48,df=4,CI = -5.45-11.1. Lean body fat percent:Mean FC = 49.7, mean FKO = 72.2, mean MC = 56.3, mean MKO = 55.0. FKO vs MKO) t = -6.27,df=4,CI = -24.1–10.4. Femur length:Mean FC = 1.6, mean FKO = 1.5, mean MC = 1.7, mean MKO = 1.7. FKO vs MKO t = 1.75,df=4,CI = -0.0810-0.436.

Extended Data Fig. 9 DEXA scans of mmΔSnx10Adipoq mice and control littermates.

DEXA composition scans of all mice after high-fat diet. Scans are organized by genotype status and sex. F-control N = 6, F-KO N = 5, M-control N = 3, M-KO N = 6.

Extended Data Fig. 10 Identification of enriched adipogenesis motif in Khetan et al.

Figure is made from Khetan et al-identified motifs in the same mannrs as Fig. 3e of this article. Enrichment of a partial DR1 motif at ~55 bp from the start of Alu elements, seen in our MPRA of female WHRadjBMI-associated loci, is also seen in their MPRA identifying enhancers associated with type 2 diabetes in pancreatic beta cells.

Supplementary information

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Supplementary Figs. 1–9.

Reporting Summary

Supplementary Tables

Supplementary tables, including primers and guides for the CRISPR, luciferase and SNX10 experiments.

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Hansen, G.T., Sobreira, D.R., Weber, Z.T. et al. Genetics of sexually dimorphic adipose distribution in humans. Nat Genet 55, 461–470 (2023). https://doi.org/10.1038/s41588-023-01306-0

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