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Branched-chain amino acids impact health and lifespan indirectly via amino acid balance and appetite control

Nature Metabolism volume 1, pages 532–545 (2019)Cite this article

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Abstract

Elevated branched-chain amino acids (BCAAs) are associated with obesity and insulin resistance. How long-term dietary BCAAs impact late-life health and lifespan is unknown. Here, we show that when dietary BCAAs are varied against a fixed, isocaloric macronutrient background, long-term exposure to high BCAA diets leads to hyperphagia, obesity and reduced lifespan. These effects are not due to elevated BCAA per se or hepatic mammalian target of rapamycin activation, but instead are due to a shift in the relative quantity of dietary BCAAs and other amino acids, notably tryptophan and threonine. Increasing the ratio of BCAAs to these amino acids results in hyperphagia and is associated with central serotonin depletion. Preventing hyperphagia by calorie restriction or pair-feeding averts the health costs of a high-BCAA diet. Our data highlight a role for amino acid quality in energy balance and show that health costs of chronic high BCAA intakes need not be due to intrinsic toxicity but instead are a consequence of hyperphagia driven by amino acid imbalance.

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Fig. 1: Dietary BCAA imbalance drives hyperphagia and obesity, and shortens lifespan.
Fig. 2: Trp and Thr supplementation prevents hyperphagia.
Fig. 3: Hyperphagia in BCAA200 mice is linked to Trp-mediated serotonin (5-HT) depletion.
Fig. 4: The ratio of dietary BCAA to non-BCAA influences hypothalamic gene expression.
Fig. 5: Dietary BCAA imbalance promotes hepatosteatosis and de novo lipogenesis.
Fig. 6: Dietary amino acid imbalance alters whole-body metabolism.
Fig. 7: Preventing hyperphagia on high BCAA diets averts metabolic and lifespan costs.

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Data availability

RNA-seq data have been deposited with the Gene Expression Omnibus and are accessible through accession number GSE114855. The data that support the plots within this article and other findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

We thank F. Held and P. Telleria Teixeira for their technical and administrative support. We thank the Laboratory Animal Services at the University of Sydney, N. Sunn of Sydney Imaging, W. Potts from Specialty Feeds, L. McQuade from the Australian Proteome Analysis Facility and the Diagnostic Pathology Unit at Concord Hospital. This work is supported by a National Health and Medical Research Council (NHMRC) project grant (GNT1084267 to D.R., D.L.C. and S.J.S.), the Ageing and Alzheimers Institute and the Sydney Food and Nutrition Network. S.S.B. is supported by the NHMRC Peter Doherty Biomedical Fellowship (no. GNT1110098) and the University of Sydney SOAR fellowship. A.M.S. was supported by a Discovery Early Career Researcher Award from the Australian Research Council (DE180101520). V.C.C. is supported by a University of Sydney Equity Fellowship. L.P. and P.J. were supported by the Max Planck Society and acknowledge funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7, 2007–2013)/ERC grant agreement no. 268739 and the Wellcome Trust (098565/Z/12/).

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Authors and Affiliations

  1. Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia

    Samantha M. Solon-Biet, Victoria C. Cogger, Tamara Pulpitel, Devin Wahl, Ximonie Clark, Elena E. Bagley, Gabrielle C. Gregoriou, Alistair M. Senior, Qiao-Ping Wang, Amanda E. Brandon, Ruth Perks, John O’Sullivan, Yen Chin Koay, Kim Bell-Anderson, Melkam Kebede, Belinda Yau, Clare Atkinson, Tim Dodgson, Jibran A. Wali, David Raubenheimer, Gregory J. Cooney, David G. Le Couteur & Stephen J. Simpson

  2. School of Life and Environmental Sciences, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia

    Samantha M. Solon-Biet, Ximonie Clark, Alistair M. Senior, Qiao-Ping Wang, Kim Bell-Anderson, Melkam Kebede, Belinda Yau, Clare Atkinson, Tim Dodgson, Jibran A. Wali, David Raubenheimer & Stephen J. Simpson

  3. Sydney Medical School, Faculty of Health and Medicine, The University of Sydney, Sydney, New South Wales, Australia

    Victoria C. Cogger, Tamara Pulpitel, Devin Wahl, Amanda E. Brandon, Gregory J. Cooney & David G. Le Couteur

  4. Ageing and Alzheimers Institute and Centre for Education and Research on Ageing, Concord Hospital, Sydney, New South Wales, Australia

    Victoria C. Cogger, Devin Wahl & David G. Le Couteur

  5. ANZAC Research Institute, The University of Sydney, Sydney, New South Wales, Australia

    Victoria C. Cogger & David G. Le Couteur

  6. School of Medical Sciences, Faculty of Health and Medicine, The University of Sydney, Sydney, New South Wales, Australia

    Elena E. Bagley & Gabrielle C. Gregoriou

  7. School of Pharmaceutical Sciences (Shenzhen), Sun Yat-Sen University, Guangzhou, China

    Qiao-Ping Wang

  8. Heart Research Institute, The University of Sydney, Sydney, New South Wales, Australia

    John O’Sullivan & Yen Chin Koay

  9. Department of Medical Biology, The Arctic University of Tromsø, Tromsø, Norway

    Gunbjorg Svineng

  10. School of Biological Sciences, Monash University Clayton Campus, Melbourne, Victoria, Australia

    Matthew D. W. Piper

  11. Max Planck Institute for Biology of Ageing, Cologne, Germany

    Paula Juricic & Linda Partridge

  12. Monash Biomedicine Discovery Institute, Monash University Clayton Campus, Melbourne, Victoria, Australia

    Adam J. Rose

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Contributions

D.L.C., S.J.S. and L.P. conceived the study. S.S.B., S.J.S. and D.L.C. wrote the manuscript. D.R., L.P. and A.J.R. reviewed and assisted in writing the manuscript. S.S.B., V.C.C. and T.P. ran the study. G.J.C., D.W., X.C., A.E.B., E.B., G.C.G., R.P., J.O.S., Y.C.K., M.K., B.Y., C.A., G.S., T.D., J.A.W. and P.J. ran the experiments. S.S.B., A.M.S., Q.-P.W., K.B.A., M.D.W.P. and P.J. analysed the data.

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Correspondence to Samantha M. Solon-Biet or Stephen J. Simpson.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–6, Supplementary Tables 1–4 and Supplementary Table 6

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Supplementary Table 5

Statistical summary for the effects of diet, sex or diet–sex interaction

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Solon-Biet, S.M., Cogger, V.C., Pulpitel, T. et al. Branched-chain amino acids impact health and lifespan indirectly via amino acid balance and appetite control. Nat Metab 1, 532–545 (2019). https://doi.org/10.1038/s42255-019-0059-2

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