1. Computational and Systems Biology
  2. Genetics and Genomics

Predicting mechanisms of action at genetic loci associated with discordant effects on type 2 diabetes and abdominal fat accumulation

  1. Yonathan Tamrat Aberra  Is a corresponding author
  2. Lijiang Ma
  3. Johan LM Björkegren
  4. Mete Civelek  Is a corresponding author
  1. University of Virginia, United States
  2. Icahn School of Medicine at Mount Sinai, United States
https://doi.org/10.7554/eLife.79834
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  1. Yonathan Tamrat Aberra
  2. Lijiang Ma
  3. Johan LM Björkegren
  4. Mete Civelek
(2023)
Predicting mechanisms of action at genetic loci associated with discordant effects on type 2 diabetes and abdominal fat accumulation
eLife 12:e79834.
https://doi.org/10.7554/eLife.79834
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Abstract

Metabolic syndrome (MetSyn) is a cluster of dysregulated metabolic conditions that occur together to increase the risk for cardiometabolic disorders such as type 2 diabetes (T2D). One key condition associated with MetSyn, abdominal obesity, is measured by computing the ratio of waist-to-hip circumference adjusted for the body-mass index (WHRadjBMI). WHRadjBMI and T2D are complex traits with genetic and environmental components, which has enabled genome-wide association studies (GWAS) to identify hundreds of loci associated with both. Statistical genetics analyses of these GWAS have predicted that WHRadjBMI is a strong causal risk factor of T2D and that these traits share genetic architecture at many loci. To date, no variants have been described that are simultaneously associated with protection from T2D but with increased abdominal obesity. Here, we used colocalization analysis to identify genetic variants with a shared association for T2D and abdominal obesity. This analysis revealed the presence of five loci associated with discordant effects on T2D and abdominal obesity. The alleles of the lead genetic variants in these loci that were protective against T2D were also associated with increased abdominal obesity. We further used publicly available expression, epigenomic, and genetic regulatory data to predict the effector genes (eGenes) and functional tissues at the 2p21, 5q21.1, and 19q13.11 loci. We also computed the correlation between the subcutaneous adipose tissue (SAT) expression of predicted effector genes (eGenes) with metabolic phenotypes and adipogenesis. We proposed a model to resolve the discordant effects at the 5q21.1 locus. We find that eGenes gypsy retrotransposon integrase 1 (GIN1), diphosphoinositol pentakisphosphate kinase 2 (PPIP5K2), and peptidylglycine alpha-amidating monooxygenase (PAM) represent the likely causal eGenes at the 5q21.1 locus. Taken together, these results are the first to describe a potential mechanism through which a genetic variant can confer increased abdominal obesity but protection from T2D risk. Understanding precisely how and which genetic variants confer increased risk for MetSyn will develop the basic science needed to design novel therapeutics for metabolic syndrome.

Data availability

The current manuscript is a computational investigation using publicly available data, so no data have been generated for this manuscript. All publicly obtained data sets are included in Supplementary Table 1. All analysis and figure-generating code uploaded to the following Github repository: https://github.com/aberrations/predicting-functional-mechanisms-discordant-loci.

The following previously published data sets were used
    1. Raulerson CK
    2. Ko A
    3. Kidd JC
    4. et al.
    (2019) METSIM eQTL
    FTP, https://doi.org/10.1016/j.ajhg.2019.09.001.
    https://mohlke.web.unc.edu/data/

Article and author information

Author details

  1. Yonathan Tamrat Aberra

    Department of Biomedical Engineering, University of Virginia, Charlottesville, United States
    For correspondence
    ya8eb@virginia.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6055-2291

  2. Lijiang Ma

    Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, United States
    Competing interests
    The authors declare that no competing interests exist.

  3. Johan LM Björkegren

    Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, United States
    Competing interests
    The authors declare that no competing interests exist.

  4. Mete Civelek

    Department of Biomedical Engineering, University of Virginia, Charlottesville, United States
    For correspondence
    mete@virginia.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8141-0284

Funding

National Heart, Lung, and Blood Institute (2T32HL007284-46)

  • Yonathan Tamrat Aberra

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2023, Aberra et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Yonathan Tamrat Aberra
  2. Lijiang Ma
  3. Johan LM Björkegren
  4. Mete Civelek
(2023)
Predicting mechanisms of action at genetic loci associated with discordant effects on type 2 diabetes and abdominal fat accumulation
eLife 12:e79834.
https://doi.org/10.7554/eLife.79834

Share this article

https://doi.org/10.7554/eLife.79834

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