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Metabolic phenotyping of BMI to characterize cardiometabolic risk: evidence from large population-based cohorts

Author

Listed:
  • Habtamu B. Beyene

    (Baker Heart and Diabetes Institute
    Monash University
    La Trobe University
    Melbourne University)

  • Corey Giles

    (Baker Heart and Diabetes Institute
    La Trobe University
    Melbourne University)

  • Kevin Huynh

    (Baker Heart and Diabetes Institute
    La Trobe University
    Melbourne University)

  • Tingting Wang

    (Baker Heart and Diabetes Institute
    La Trobe University
    Melbourne University)

  • Michelle Cinel

    (Baker Heart and Diabetes Institute)

  • Natalie A. Mellett

    (Baker Heart and Diabetes Institute)

  • Gavriel Olshansky

    (Baker Heart and Diabetes Institute)

  • Thomas G. Meikle

    (Baker Heart and Diabetes Institute
    La Trobe University)

  • Gerald F. Watts

    (University of Western Australia
    Royal Perth Hospital)

  • Joseph Hung

    (University of Western Australia)

  • Jennie Hui

    (PathWest Laboratory Medicine of Western Australia
    University of Western Australia
    University of Western Australia)

  • Gemma Cadby

    (University of Western Australia)

  • John Beilby

    (University of Western Australia)

  • John Blangero

    (The University of Texas Rio Grande Valley)

  • Eric K. Moses

    (University of Western Australia
    University of Tasmania)

  • Jonathan E. Shaw

    (Baker Heart and Diabetes Institute
    Monash University)

  • Dianna J. Magliano

    (Baker Heart and Diabetes Institute
    Monash University)

  • Peter J. Meikle

    (Baker Heart and Diabetes Institute
    Monash University
    La Trobe University
    Melbourne University)

Abstract

Obesity is a risk factor for type 2 diabetes and cardiovascular disease. However, a substantial proportion of patients with these conditions have a seemingly normal body mass index (BMI). Conversely, not all obese individuals present with metabolic disorders giving rise to the concept of “metabolically healthy obese”. We use lipidomic-based models for BMI to calculate a metabolic BMI score (mBMI) as a measure of metabolic dysregulation associated with obesity. Using the difference between mBMI and BMI (mBMIΔ), we identify individuals with a similar BMI but differing in their metabolic health and disease risk profiles. Exercise and diet associate with mBMIΔ suggesting the ability to modify mBMI with lifestyle intervention. Our findings show that, the mBMI score captures information on metabolic dysregulation that is independent of the measured BMI and so provides an opportunity to assess metabolic health to identify “at risk” individuals for targeted intervention and monitoring.

Suggested Citation

  • Habtamu B. Beyene & Corey Giles & Kevin Huynh & Tingting Wang & Michelle Cinel & Natalie A. Mellett & Gavriel Olshansky & Thomas G. Meikle & Gerald F. Watts & Joseph Hung & Jennie Hui & Gemma Cadby & , 2023. "Metabolic phenotyping of BMI to characterize cardiometabolic risk: evidence from large population-based cohorts," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-41963-7
    DOI: 10.1038/s41467-023-41963-7
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    References listed on IDEAS

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    1. Adam E. Locke & Bratati Kahali & Sonja I. Berndt & Anne E. Justice & Tune H. Pers & Felix R. Day & Corey Powell & Sailaja Vedantam & Martin L. Buchkovich & Jian Yang & Damien C. Croteau-Chonka & Tonu , 2015. "Genetic studies of body mass index yield new insights for obesity biology," Nature, Nature, vol. 518(7538), pages 197-206, February.
    2. Virginia W Chang & Kenneth M Langa & David Weir & Theodore J Iwashyna, 2017. "The obesity paradox and incident cardiovascular disease: A population-based study," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-12, December.
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    Cited by:

    1. Nikos Stratakis & Augusto Anguita-Ruiz & Lorenzo Fabbri & Léa Maitre & Juan R. González & Sandra Andrusaityte & Xavier Basagaña & Eva Borràs & Hector C. Keun & Lida Chatzi & David V. Conti & Jesse Goo, 2025. "Multi-omics architecture of childhood obesity and metabolic dysfunction uncovers biological pathways and prenatal determinants," Nature Communications, Nature, vol. 16(1), pages 1-15, December.

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