Review Article | Published:

Body composition-related functions: a problem-oriented approach to phenotyping

European Journal of Clinical Nutrition (2018) | Download Citation

Abstract

Aim

The objective of this study is to generate metabolic phenotypes based on structure–function relationships.

Methods

In 459 healthy adults (54% females, 18 and 40 years old), we analyzed body composition by air-displacement densitometry (to assess fat mass, (FM) and fat-free mass (FFM)) and whole-body magnetic resonance imaging (to assess skeletal muscle mass (SMM) and masses of brain, heart, liver, kidneys, and subcutaneous (SAT) and visceral adipose tissue (VAT)), resting energy expenditure (REE) by indirect calorimetry, and plasma concentrations of insulin (Ins) and leptin (Lep).

Results

Three “functional body composition-derived phenotypes” (FBCPs) were derived: (1) REE on FFM-FBCP, (2) Lep on FM-FBCP, and (3) Ins on VAT-FBCP. Assuming that being within the ± 5% range of the respective regression lines reflects a “normal” structure–function relationship, three “normal” FBCPs were generated with prevalences of 9.0%, 5.1%, and 6.8%, respectively, of the study population. The three “FBCPs” did not overlap and were independent from each other. When compared with the two other FBCPs, the “Lep on FM-FBCP” was leanest, whereas the “REE on FFM-FBCP” had the highest BMI and SAT. Taking into account FFM composition, a hierarchical multi-level model is proposed with brain at level 1, the liver at level 2, and SMM and FM at level 3 with insulin coordinating the interplay between level 1 and 2, whereas variance in plasma insulin levels impacts energy and substrate metabolism in SMM and AT.

Conclusion

Structure–function relationships can be used to generate FBCPs. Different FBCPs reflect different dimensions of normality (or health). This is evidence for the idea that there is no across the board “normal” state.

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Acknowledgements

The study was funded by a grant of the German Ministry of Education and Research (BMBF 0315681), BMBF Competence Network Obesity (CNO; BMBF 01GI1125), and the German Research Foundation (DFG Bo 3296/1–1 and DFG Mü 714/ 8–3).

Author information

Affiliations

  1. Institute of Human Nutrition and Food Science, Christian-Albrechts-Universität, Kiel, Germany

    • Manfred J. Müller
    • , Corinna Geisler
    • , Mark Hübers
    •  & Anja Bosy-Westphal
  2. Department of Geriatric Medicine, Marien Hospital Herne, Ruhr-University Bochum, Bochum, Germany

    • Maryam Pourhassan

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Conflict of interest

The authors declare that they have no conflict of interest.

Corresponding author

Correspondence to Manfred J. Müller.

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DOI

https://doi.org/10.1038/s41430-018-0340-6