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Nutritional redundancy in the human diet and its application in phenotype association studies

Author

Listed:
  • Xu-Wen Wang

    (Brigham and Women’s Hospital and Harvard Medical School)

  • Yang Hu

    (Harvard T.H. Chan School of Public Health)

  • Giulia Menichetti

    (Brigham and Women’s Hospital and Harvard Medical School
    Northeastern University)

  • Francine Grodstein

    (Rush University)

  • Shilpa N. Bhupathiraju

    (Brigham and Women’s Hospital and Harvard Medical School
    Harvard T.H. Chan School of Public Health)

  • Qi Sun

    (Brigham and Women’s Hospital and Harvard Medical School
    Harvard T.H. Chan School of Public Health
    Harvard T.H. Chan School of Public Health)

  • Xuehong Zhang

    (Brigham and Women’s Hospital and Harvard Medical School
    Harvard T.H. Chan School of Public Health)

  • Frank B. Hu

    (Brigham and Women’s Hospital and Harvard Medical School
    Harvard T.H. Chan School of Public Health
    Harvard T.H. Chan School of Public Health)

  • Scott T. Weiss

    (Brigham and Women’s Hospital and Harvard Medical School)

  • Yang-Yu Liu

    (Brigham and Women’s Hospital and Harvard Medical School
    University of Illinois at Urbana-Champaign)

Abstract

Studying human dietary intake may help us identify effective measures to treat or prevent many chronic diseases whose natural histories are influenced by nutritional factors. Here, by examining five cohorts with dietary intake data collected on different time scales, we show that the food intake profile varies substantially across individuals and over time, while the nutritional intake profile appears fairly stable. We refer to this phenomenon as ‘nutritional redundancy’ and attribute it to the nested structure of the food-nutrient network. This network enables us to quantify the level of nutritional redundancy for each diet assessment of any individual. Interestingly, this nutritional redundancy measure does not strongly correlate with any classical healthy diet scores, but its performance in predicting healthy aging shows comparable strength. Moreover, after adjusting for age, we find that a high nutritional redundancy is associated with lower risks of cardiovascular disease and type 2 diabetes.

Suggested Citation

  • Xu-Wen Wang & Yang Hu & Giulia Menichetti & Francine Grodstein & Shilpa N. Bhupathiraju & Qi Sun & Xuehong Zhang & Frank B. Hu & Scott T. Weiss & Yang-Yu Liu, 2023. "Nutritional redundancy in the human diet and its application in phenotype association studies," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-39836-0
    DOI: 10.1038/s41467-023-39836-0
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    References listed on IDEAS

    as
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    2. Soodabeh Milanlouei & Giulia Menichetti & Yanping Li & Joseph Loscalzo & Walter C. Willett & Albert-László Barabási, 2020. "A systematic comprehensive longitudinal evaluation of dietary factors associated with acute myocardial infarction and fatal coronary heart disease," Nature Communications, Nature, vol. 11(1), pages 1-14, December.
    3. Liang Tian & Xu-Wen Wang & Ang-Kun Wu & Yuhang Fan & Jonathan Friedman & Amber Dahlin & Matthew K. Waldor & George M. Weinstock & Scott T. Weiss & Yang-Yu Liu, 2020. "Deciphering functional redundancy in the human microbiome," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
    4. Giulia Menichetti & Babak Ravandi & Dariush Mozaffarian & Albert-László Barabási, 2023. "Machine learning prediction of the degree of food processing," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
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