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The Ratio of Macronutrients, Not Caloric Intake, Dictates Cardiometabolic Health, Aging, and Longevity in Ad Libitum-Fed Mice
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The fundamental questions of what represents a macronutritionally balanced diet and how this maintains health and longevity remain unanswered. Here, the Geometric Framework, a state-space nutritional modeling method, was used to measure interactive effects of dietary energy, protein, fat, and carbohydrate on food intake, cardiometabolic phenotype, and longevity in mice fed one of 25 diets ad libitum. Food intake was regulated primarily by protein and carbohydrate content. Longevity and health were optimized when protein was replaced with carbohydrate to limit compensatory feeding for protein and suppress protein intake. These consequences are associated with hepatic mammalian target of rapamycin (mTOR) activation and mitochondrial function and, in turn, related to circulating branched-chain amino acids and glucose. Calorie restriction achieved by high-protein diets or dietary dilution had no beneficial effects on lifespan. The results suggest that longevity can be extended in ad libitum-fed animals by manipulating the ratio of macronutrients to inhibit mTOR activation.
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“Although density is only a rough proxy for fitness, our results are consistent with laboratory experiments, which demonstrated that generalists pay the cost of relying on unbalanced diets, suffering either high mortality rates and disease risk52,53 or low reproductive outputs12.”
From Nutritional ecology of a prototypical generalist predator, the red fox (Vulpes vulpes) (2024) · cites this paper as [53]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
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“Several studies have shown that restriction of protein or specific restriction of either methionine or one or more of the branched-chain amino acids (BCAAs; leucine, isoleucine, and valine) reduces mTORC1 activity and extends lifespan in preclinical species 24,150–152.”
From Targeting the biology of aging with mTOR inhibitors (2023) · cites this paper as [24]
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“For example, Solon-Biet and colleagues [30] explored the contribution of 25 different diets to the overall health and longevity of over 800 mice.”
From Multi-omics approaches to disease (2017) · cites this paper as [30]
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“The ratio of protein to carbohydrate in the diet was shown to have profound effects on health parameters later in life, offering mechanistic insight into how this is achieved.”
From Multi-omics approaches to disease (2017) · cites this paper as [30]
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“The observation that protein is prioritized and regulated to a specific target suggests that small changes in the proportion of dietary protein can induce large changes in total food and energy intake, a concept termed protein leveraging”
From FGF21 and the physiological regulation of macronutrient preference (2020) · cites this paper as [106]
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Cites
Generalized Additive Models: An Introduction with R
Wood, S. N. (2017) · doi:10.1201/9781315370279 · Cited by 13,852
Data Analysis Using Regression and Multilevel/Hierarchical Models
Gelman, A., & Hill, J. (2006) · doi:10.1017/cbo9780511790942 · Cited by 13,597
Modeling Survival Data: Extending the Cox Model
Therneau, T. M., & Grambsch, P. M. (2000) · Statistics for Biology and Health · doi:10.1007/978-1-4757-3294-8 · Cited by 8,674
Effects of the obese Gene Product on Body Weight Regulation in ob / ob Mice
Pelleymounter, M. A., Cullen, M. J., Baker, M. B., Hecht, R., Winters, D., Boone, T., & Collins, F. (1995) · Science · doi:10.1126/science.7624776 · Cited by 4,017
Rapamycin fed late in life extends lifespan in genetically heterogeneous mice
Harrison, D. E., Strong, R., Sharp, Z. D., Nelson, J. F., Astle, C. M., Flurkey, K., Nadon, N. L., Wilkinson, J. E., Frenkel, K., Carter, C. S., et al. (2009) · Nature · doi:10.1038/nature08221 · Cited by 3,766
Extending Healthy Life Span—From Yeast to Humans
Fontana, L., Partridge, L., & Longo, V. D. (2010) · Science · doi:10.1126/science.1172539 · Cited by 3,023
Wood, S. (2003) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/1467-9868.00374 · Cited by 2,580
Generalized Additive Models: An Introduction With R
Anderson‐Cook, C. M. (2007) · Journal of the American Statistical Association · doi:10.1198/jasa.2007.s188 · Cited by 1,632
Biomarkers of mitochondrial content in skeletal muscle of healthy young human subjects
Larsen, S., Nielsen, J., Hansen, C. N., Nielsen, L. B., Wibrand, F., Stride, N., Schroder, H. D., Boushel, R., Helge, J. W., Dela, F., et al. (2012) · The Journal of Physiology · doi:10.1113/jphysiol.2012.230185 · Cited by 1,180 · cited 2×
“…Metabolism 19, 418–430, March 4, 2014 ª2014 Elsevier Inc. 423 synthase activity (which is a gold-standard marker of mitochondrial number; Larsen et al., 2012) (Figure S4) while negatively associated with state III and IVo mitochondrial respiration and hydrogen peroxide production,…”
BackgroundLifespan and reproduction in Drosophila : New insights from nutritional geometry
Lee, K. P., Simpson, S. J., Clissold, F. J., Brooks, R., Ballard, J. W. O., Taylor, P. W., Soran, N., & Raubenheimer, D. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0710787105 · Cited by 1,032
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Srivastava, A., Lu, J., Gadalla, D. S., Hendrich, O., Grönke, S., & Partridge, L. (2022) · Frontiers in Aging · doi:10.3389/fragi.2022.944466 · Cited by 21
Almutairi, A. W., Abomohra, A., & Elsayed, M. (2023) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2023.137236 · Cited by 22
Ersoy, U., Kanakis, I., Alameddine, M., Pedraza-Vázquez, G., Ozanne, S. E., Peffers, M. J., Jackson, M. J., Goljanek‐Whysall, K., & Vasilaki, A. (2023) · Redox Biology · doi:10.1016/j.redox.2023.102980 · Cited by 26
Preoperative Protein or Methionine Restriction Preserves Wound Healing and Reduces Hyperglycemia
Trocha, K. M., Kip, P., MacArthur, M. R., Mitchell, S. J., Longchamp, A., Trevino-Villarreal, J. H., Tao, M., Bredella, M. A., Bernstein, K. D. A., Mitchell, J. R., et al. (2018) · Journal of Surgical Research · doi:10.1016/j.jss.2018.09.071 · Cited by 22
The immune-nutrition interplay in aging – facts and controversies
Alam, I., Almajwal, A. M., Alam, W., Alam, I., Ullah, N., Abulmeaaty, M., Razak, S., Khan, S., Pawelec, G., & Paracha, P. I. (2019) · Nutrition and Healthy Aging · doi:10.3233/nha-170034 · Cited by 22
Santos, J., Leitão-Correia, F., Sousa, M. J., & Leão, C. (2014) · Oncotarget · doi:10.18632/oncotarget.2989 · Cited by 20
Aging and energetics’ ‘Top 40’ future research opportunities 2010-2013
Allison, D. B., Antoine, L. H., Ballinger, S. W., Bamman, M. M., Biga, P. R., Darley-Usmar, V. M., Fisher, G., Gohlke, J. M., Halade, G. V., Hartman, J. L., et al. (2014) · F1000Research · doi:10.12688/f1000research.5212.1 · Cited by 21
Panthi, S., Aryal, A., & Coogan, S. C. P. (2019) · Ecology and Evolution · doi:10.1002/ece3.4926 · Cited by 20
Sex‐specific metabolic responses to 6 hours of fasting during the active phase in young mice
Freire, T., Senior, A. M., Perks, R., Pulpitel, T., Clark, X., Brandon, A. E., Wahl, D., Hatchwell, L., Couteur, D. G. L., Cooney, G. J., et al. (2020) · The Journal of Physiology · doi:10.1113/jp278806 · Cited by 23
Self-citationDietary restriction and lifespan: adaptive reallocation or somatic sacrifice?
Piper, M. D. W., Zanco, B., Sgrò, C. M., Adler, M. I., Mirth, C. K., & Bonduriansky, R. (2022) · FEBS Journal · doi:10.1111/febs.16463 · Cited by 21
Xu, M., Qin, H., Zheng, Y., Chen, J., Liang, X., Huang, J., Luo, W., Yang, R., & Guan, Y. (2022) · Colloids and Surfaces B Biointerfaces · doi:10.1016/j.colsurfb.2022.112858 · Cited by 22
Chowing down: diet considerations in rodent models of metabolic disease
Klatt, K. C., Bass, K. N., Speakman, J. R., & Hall, K. D. (2023) · Life Metabolism · doi:10.1093/lifemeta/load013 · Cited by 21
Long term methionine restriction: Influence on gut microbiome and metabolic characteristics
Nagarajan, A., Lasher, A. T., Morrow, C. D., & Sun, L. Y. (2024) · Aging Cell · doi:10.1111/acel.14051 · Cited by 21
Crean, A. J., Senior, A. M., Freire, T., Clark, T. D., Mackay, F., Austin, G., Pulpitel, T., Nóbrega, M. A., Barrès, R., & Simpson, S. J. (2024) · Nature Communications · doi:10.1038/s41467-024-46782-y · Cited by 23
Self-citationBabygirija, R., Sonsalla, M. M., Mill, J., James, I., Han, J. H., Green, C. L., Calubag, M. F., Wade, G., Tobon, A., Michael, J., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-49589-z · Cited by 22
Nutrient‐dependent increased dendritic arborization of somatosensory neurons
Watanabe, K., Furumizo, Y., Usui, T., Hattori, Y., & Uemura, T. (2016) · Genes to Cells · doi:10.1111/gtc.12451 · Cited by 21
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Späth, M. R., Koehler, F. C., Hoyer-Allo, K. J. R., Grundmann, F., Burst, V. R., & Müller, R. (2020) · F1000Research · doi:10.12688/f1000research.21406.1 · Cited by 20
Haghighat, N., Ashtary‐Larky, D., Bagheri, R., Wong, A., Cheraghloo, N., Moradpour, G., Nordvall, M., Asbaghi, O., Moeinvaziri, N., Amini, M., et al. (2021) · Nutrients · doi:10.3390/nu13072266 · Cited by 22
Eberhard, J., Ruiz, K., Tan, J., Jayasinghe, T. N., Khan, S., Eroglu, E. I., Adler, C. J., Simpson, S. J., Couteur, D. G. L., Raubenheimer, D., et al. (2021) · Journal Of Clinical Periodontology · doi:10.1111/jcpe.13587 · Cited by 20
Self-citationEffects of early-life protein starvation on longevity and sexual performance of male medfly
Papanastasiou, S. A., Carey, J. R., & Papadopoulos, N. T. (2019) · PLoS ONE · doi:10.1371/journal.pone.0219518 · Cited by 20
Rallis, C., Mülleder, M., Smith, G. C., Au, Y. Z., Ralser, M., & Bähler, J. (2020) · The Journals of Gerontology Series A · doi:10.1093/gerona/glaa246 · Cited by 19
Mousavi, S. M., Jayedi, A., Jalilpiran, Y., Hajishafiee, M., Aminianfar, A., & Esmaillzadeh, A. (2020) · Critical Reviews in Food Science and Nutrition · doi:10.1080/10408398.2020.1841730 · Cited by 23
FGF21 prevents low-protein diet-induced renal inflammation in aged mice
Fang, H., Ghosh, S., Sims, L. C., Stone, K. P., Hill, C. M., Spires, D. R., Ilatovskaya, D. V., Morrison, C. D., Gettys, T. W., & Stadler, K. (2021) · American Journal of Physiology-Renal Physiology · doi:10.1152/ajprenal.00107.2021 · Cited by 20
The road ahead of dietary restriction on anti-aging: focusing on personalized nutrition
Duan, H., Li, J., Yu, L., & Fan, L. (2022) · Critical Reviews in Food Science and Nutrition · doi:10.1080/10408398.2022.2110034 · Cited by 20
Coleman, C. R., Pallos, J., Arreola-Bustos, A., Wang, L., Raftery, D., Promislow, D., & Martin, I. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2403450121 · Cited by 20
Jensen, K., Coby Schal, A., & Silverman, J. (2015) · Journal of Evolutionary Biology · doi:10.1111/jeb.12617 · Cited by 21
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Poissonnier, L., Arganda, S., Simpson, S. J., Dussutour, A., & Buhl, C. (2018) · Functional Ecology · doi:10.1111/1365-2435.13200 · Cited by 20
Self-citationWolters, M., Joslowski, G., Plachta‐Danielzik, S., Standl, M., Müller, M. J., Ahrens, W., & Buyken, A. E. (2018) · Nutrients · doi:10.3390/nu10101442 · Cited by 23
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Hosking, C., Raubenheimer, D., Charleston, M., Simpson, S. J., & Senior, A. M. (2019) · Journal of The Royal Society Interface · doi:10.1098/rsif.2018.0733 · Cited by 20
Self-citationKitada, M., Ogura, Y., Monno, I., Xu, J., & Koya, D. (2019) · Aging · doi:10.18632/aging.102902 · Cited by 20
Takahashi, M. Q., Rothman, J. M., Raubenheimer, D., & Cords, M. (2020) · Behavioral Ecology · doi:10.1093/beheco/araa120 · Cited by 20
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Sedej, S. (2017) · Cardiovascular Research · doi:10.1093/cvr/cvx218 · Cited by 20
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Liang, Y., & Wang, Z. (2018) · Advances in experimental medicine and biology · doi:10.1007/978-981-13-1117-8_17 · Cited by 23
Bar, S., Wilson, K. A., Hilsabeck, T. A. U., Alderfer, S. A., Dammer, E. B., Burton, J. B., Shah, S., Holtz, A. N., Carrera, E. M., Beck, J. N., et al. (2025) · Nature Metabolism · doi:10.1038/s42255-025-01314-w · Cited by 20
Nychyk, O., Barton, W., Rudolf, A. M., Boscaini, S., Walsh, A. M., Bastiaanssen, T. F. S., Giblin, L., Cormican, P., Chen, L., Piotrowicz, Y., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109093 · Cited by 25
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Koundouros, N., & Blenis, J. (2022) · Endocrinology · doi:10.1210/endocr/bqac041 · Cited by 22
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Li, K., Wang, C., Wang, Y., Fu, L., & Zhang, N. (2023) · Journal of Future Foods · doi:10.1016/j.jfutfo.2022.12.001 · Cited by 20
Mu, C., Yang, Y., Luo, Z., & Zhu, W. (2015) · Amino Acids · doi:10.1007/s00726-015-1949-6 · Cited by 19
Analytes and Metabolites Associated with Muscle Quality in Young, Healthy Adults
Lustgarten, M. S., Price, L. L., & Fielding, R. A. (2014) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0000000000000578 · Cited by 19
Dietary composition affects the development of cognitive deficits in WT and Tg AD model mice
Kadish, I., Kumar, A., Beitnere, U., Jennings, E., McGilberry, W., & van Groen, T. (2016) · Experimental Gerontology · doi:10.1016/j.exger.2016.05.003 · Cited by 20
Kosakamoto, H., Sakuma, C., Okada, R., Miura, M., & Obata, F. (2024) · Science Advances · doi:10.1126/sciadv.adn7167 · Cited by 16
Cai, S., Xue, B., Li, S., Wang, X., Zeng, X., Zhu, Z., Fan, X., Zou, Y., Yu, H., Qiao, S., et al. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.115291 · Cited by 18
Santos, J., Leitão-Correia, F., Sousa, M. J., & Leão, C. (2016) · Oncotarget · doi:10.18632/oncotarget.8656 · Cited by 18
Wahl, D., & LaRocca, T. J. (2021) · Frontiers in Nutrition · doi:10.3389/fnut.2021.712129 · Cited by 18
Metabolic Alterations at the Crossroad of Aging and Oncogenesis
Raffaghello, L., & Longo, V. D. (2017) · International review of cytology · doi:10.1016/bs.ircmb.2017.01.003 · Cited by 19
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Rau, C. D., Lusis, A. J., & Wang, Y. (2020) · Circulation Research · doi:10.1161/circresaha.119.315863 · Cited by 19
Poggiogalle, E., Rossignon, F., Carayon, A., Capel, F., Rigaudière, J., Vincent, S. D. S., Bacquer, O. L., Salles, J., Giraudet, C., Patrac, V., et al. (2022) · Frontiers in Physiology · doi:10.3389/fphys.2021.749049 · Cited by 18
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Kizirian, N. V., Markovic, T., Muirhead, R., Brodie, S., Garnett, S. P., Louie, J. C. Y., Petocz, P., Ross, G. P., & Brand-Miller, J. C. (2016) · Nutrients · doi:10.3390/nu8050270 · Cited by 20
Bajracharya, R., Bustamante, S., & Ballard, J. W. O. (2017) · The Journals of Gerontology Series A · doi:10.1093/gerona/glx246 · Cited by 18
Self-citationLaeger, T., Castaño-Martinez, T., Werno, M. W., Japtok, L., Baumeier, C., Jonas, W., Kleuser, B., & Schürmann, A. (2018) · Diabetologia · doi:10.1007/s00125-018-4595-1 · Cited by 17
Temporal Dynamics of the Intestinal Microbiome Following Short-Term Dietary Restriction
Anderson, E. M., Rozowsky, J. M., Fazzone, B. J., Schmidt, E., Stevens, B. R., O’Malley, K. A., Scali, S. T., & Berceli, S. A. (2022) · Nutrients · doi:10.3390/nu14142785 · Cited by 18
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Strilbytska, O. M., Semaniuk, U. V., Bubalo, V., Storey, K. B., & Lushchak, O. V. (2022) · Biomolecules · doi:10.3390/biom12091201 · Cited by 17
Osterholt, T., Gloistein, C., Todorova, P., Becker, I., Arenskrieger, K., Melka, R., Koehler, F. C., Faust, M., Wahlers, T., Benzing, T. R., et al. (2022) · Journal of the American Heart Association · doi:10.1161/jaha.121.025229 · Cited by 20
Sonar, S. A., Watanabe, M., & Nikolich‐Žugich, J. (2023) · Seminars in Immunology · doi:10.1016/j.smim.2023.101835 · Cited by 19
Semerciöz, A. S., Mitchell, S. E., Özilgen, M., Yılmaz, B., & Speakman, J. R. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2300624120 · Cited by 17
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Farris, K. M., Senior, A. M., Sobreira, D. R., Mitchell, R. M., Weber, Z., Ingerslev, L. R., Barrès, R., Simpson, S. J., Crean, A. J., & Nóbrega, M. A. (2024) · Communications Biology · doi:10.1038/s42003-024-05876-5 · Cited by 18
Self-citationNeuroprotective Effects of Intermittent Fasting in the Aging Brain
Dong, H., Wang, S., Hu, C., Wang, M., Zhou, T., & Zhou, Y. (2024) · Annals of Nutrition and Metabolism · doi:10.1159/000538782 · Cited by 20
Morimoto, J., Senior, A. M., Ruiz, K., Wali, J. A., Pulpitel, T., Solon‐Biet, S. M., Cogger, V. C., Raubenheimer, D., Couteur, D. G. L., Simpson, S. J., et al. (2019) · PLoS ONE · doi:10.1371/journal.pone.0212796 · Cited by 18
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Shim, H. S., & Longo, V. D. (2015) · Cell · doi:10.1016/j.cell.2014.12.027 · Cited by 17
Ng, S. H., Simpson, S. J., & Simmons, L. W. (2019) · Journal of Evolutionary Biology · doi:10.1111/jeb.13513 · Cited by 17
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Kim, S. Q., Spann, R. A., Hill, C. M., Berryman, C. E., Berthoud, H., McDougal, D. H., He, Y., Münzberg, H., Yu, S., & Morrison, C. D. (2025) · Annual Review of Nutrition · doi:10.1146/annurev-nutr-121624-114918 · Cited by 17
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Schmauck‐Medina, T., Lautrup, S., Francesco, A. D., Mitchell, S. J., Clemmensen, C., Partridge, L., Roth, G. S., Anderson, R. M., Mattison, J. A., de Cabo, R., et al. (2026) · Nature Aging · doi:10.1038/s43587-026-01091-5 · Cited by 18
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MacArthur, M. R., Mitchell, S. J., Chadaideh, K. S., Trevino-Villarreal, J. H., Jung, J., Kalafut, K. C., Reynolds, J. S., Mann, C. G., Trocha, K. M., Tao, M., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111187 · Cited by 16
Obata, F., & Miura, M. (2024) · Annual Review of Genetics · doi:10.1146/annurev-genet-111523-102042 · Cited by 18
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Zhang, X., Gao, Y., Zhang, S., Wang, Y., Du, Y., Hao, S., & Ni, T. (2025) · Biomolecules · doi:10.3390/biom15030448 · Cited by 17
Epigenetic mechanisms of dietary restriction induced aging in Drosophila
Lian, T., Gaur, U., Yang, D., Li, D., Li, Y., & Yang, M. (2015) · Experimental Gerontology · doi:10.1016/j.exger.2015.08.015 · Cited by 17
The Effects of Dietary Macronutrient Balance on Skin Structure in Aging Male and Female Mice
Hew, J. J., Solon‐Biet, S. M., McMahon, A. C., Ruohonen, K., Raubenheimer, D., Ballard, J. W. O., Couteur, D. G. L., Nicholls, C. M., Li, Z., Maitz, P., et al. (2016) · PLoS ONE · doi:10.1371/journal.pone.0166175 · Cited by 16
Self-citationZheng, T., Ni, Y., Li, J., Chow, B., & Panagiotou, G. (2017) · Frontiers in Physiology · doi:10.3389/fphys.2017.00753 · Cited by 16
Shahar, S., Mohamed, H. J. B. J., Reyes, F. D. L., & Amarra, M. S. (2018) · Nutrients · doi:10.3390/nu10111584 · Cited by 16
Transgenerational Obesity and Healthy Aging in Drosophila
Camilleri-Carter, T.-L., Dowling, D. K., Robker, R. L., & Piper, M. D. W. (2019) · The Journals of Gerontology Series A · doi:10.1093/gerona/glz154 · Cited by 17
He, C., Wu, Q., Hayashi, N., Nakano, F., Nakatsukasa, E., & Tsuduki, T. (2019) · The Journal of Nutritional Biochemistry · doi:10.1016/j.jnutbio.2019.108326 · Cited by 17
Revealing metabolic pathways relevant to prediabetes based on metabolomics profiling analysis
Ouyang, Y., Jin, Y., Zhao, X., Chen, M., Yang, P., Zheng, X., Zeng, L., Chen, L., & Tian, Z. (2020) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2020.09.016 · Cited by 16
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Matos, M. S., Platt, B., & Delibegović, M. (2020) · Proceedings of The Nutrition Society · doi:10.1017/s0029665120007910 · Cited by 16
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Koemel, N. A., Senior, A. M., Dissanayake, H. U., Ross, J. P., McMullan, R. L., Kong, Y., Phang, M., Hyett, J. A., Raubenheimer, D., Gordon, A., et al. (2021) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/nqab318 · Cited by 18
Self-citationWei, S., Li, C., Luo, X., Yang, L., Yu, L., Wang, Q., Meng, Z., Wang, T., & Chen, Y. (2021) · 中国科学通报:英文版 · doi:10.1016/j.scib.2021.12.024 · Cited by 16
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Hawley, J., Simpson, S. J., & Wilder, S. M. (2015) · Behavioral Ecology · doi:10.1093/beheco/arv151 · Cited by 17
Self-citationFaiman, R., Solon‐Biet, S. M., Sullivan, M., Huestis, D. L., & Lehmann, T. (2017) · Parasites & Vectors · doi:10.1186/s13071-017-2088-6 · Cited by 17
Self-citationGarcia‐Caraballo, S., Comhair, T. M., Dejong, C. H. C., Lamers, W. H., & Köhler, E. (2017) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2017.04.022 · Cited by 16
Spring, S., Singh, A., Zapata, R. C., Chelikani, P. K., & Pezeshki, A. (2019) · Nutrients · doi:10.3390/nu11030707 · Cited by 16
Role of peptide hormones in the adaptation to altered dietary protein intake
Rose, A. J. (2019) · Nutrients · doi:10.3390/nu11091990 · Cited by 15
“Expectedly, leptin levels track with body fat changes in mice chronically exposed to diets of varying macronutrient compositions [58,60], with no linear relationship between dietary protein and leptin owing to an inverted U shaped curve effect on fatness mediated by dietary protein intake [58].”
BackgroundAssociation between dietary diversity and healthy aging: a systematic review
Molani‐Gol, R., Rafraf, M., & Alipour, B. (2025) · BMC Nutrition · doi:10.1186/s40795-025-01085-3 · Cited by 17
Protein restriction reprograms the multi-organ proteomic landscape of mouse aging
Lu, T., Xie, Y., Wang, Y., Lin, X., Cai, X., Zhang, Y., Nie, Z., Su, C., Gou, W., Zhang, H., et al. (2025) · Cell · doi:10.1016/j.cell.2025.10.004 · Cited by 19
Fang, H., Stone, K. P., Ghosh, S., Forney, L. A., & Gettys, T. W. (2021) · Nutrients · doi:10.3390/nu13082609 · Cited by 15
Comprehensive evaluation of caloric restriction-induced changes in the metabolome profile of mice
Xie, D., Huang, J., Zhang, Q., Zhao, S., Xue, H., Yu, Q., Sun, Z., Li, J., Yang, X., Shao, M., et al. (2022) · Nutrition & Metabolism · doi:10.1186/s12986-022-00674-4 · Cited by 15
Crean, A. J., Afrin, S., Niranjan, H. N., Pulpitel, T., Ahmad, G., Senior, A. M., Freire, T., Mackay, F., Nóbrega, M. A., Barrès, R., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-38314-x · Cited by 19
Self-citationSugar Promotes Feeding in Flies via the Serine Protease Homolog scarface
Prasad, N., & Hens, K. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.08.059 · Cited by 15
Neuronal Mechanisms that Drive Organismal Aging Through the Lens of Perception
Gendron, C. M., Chakraborty, T. S., Chung, B. Y., Harvanek, Z. M., Holme, K. J., Johnson, J. C., Lyu, Y., Munneke, A. S., & Pletcher, S. D. (2019) · Annual Review of Physiology · doi:10.1146/annurev-physiol-021119-034440 · Cited by 17
Ren, H., Liu, T. C., Lu, Y., Zhang, K., Xu, Y., Zhou, P., & Xue Ming, T. A. N. G. (2021) · Food & Function · doi:10.1039/d0fo01960g · Cited by 15
Rodent diet aids and the fallacy of caloric restriction
Wolf, A. M. (2021) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2021.111584 · Cited by 15
Davidson, K. H., Starzomski, B. M., El‐Sabaawi, R. W., Hocking, M. D., Reynolds, J. D., Wickham, S. B., & Darimont, C. T. (2021) · Ecology and Evolution · doi:10.1002/ece3.8225 · Cited by 14
Shon, J., Han, Y., & Park, Y. J. (2022) · Nutrients · doi:10.3390/nu14030478 · Cited by 15
Wang, H., Wang, B., Yin, H., Zhang, G., Yu, L., Kong, X.-M., Yuan, H., Fang, X., Liu, Q., Liu, C., et al. (2016) · Metabolic Brain Disease · doi:10.1007/s11011-016-9905-z · Cited by 15
Emerging Molecular Pathways Governing Dietary Regulation of Neural Stem Cells during Aging
de Lucia, C., Murphy, T., & Thuret, S. (2017) · Frontiers in Physiology · doi:10.3389/fphys.2017.00017 · Cited by 15
Xenotopic synthetic biology: Prospective tools for delaying aging and age-related diseases
Parkhitko, A. A., & Cracan, V. (2025) · Science Advances · doi:10.1126/sciadv.adu1710 · Cited by 15
A high-fiber diet mimics aging-related signatures of caloric restriction in mammals
Hu, F., Yu, L., Tu, X., Huang, R., Yan, X., Wang, L., Wei, X., Wei, X., & Wu, Z. (2025) · Nature Communications · doi:10.1038/s41467-025-61046-z · Cited by 15
Effects of lifespan-extending interventions on cognitive healthspan
Čulig, L., Sahbaz, B. D., & Bohr, V. A. (2022) · Expert Reviews in Molecular Medicine · doi:10.1017/erm.2022.36 · Cited by 14
Insulin sensitivity is preserved in mice made obese by feeding a high starch diet
Brandon, A. E., Small, L., Nguyen, T.-V., Suryana, E., Gong, H., Yassmin, C., Hancock, S. E., Pulpitel, T., Stonehouse, S., Prescott, L. A., et al. (2022) · eLife · doi:10.7554/elife.79250 · Cited by 14
Self-citationThe serotonin receptor 5-HT2A modulates lifespan and protein feeding in Drosophila melanogaster
Munneke, A. S., Chakraborty, T. S., Porter, S. S., Gendron, C. M., & Pletcher, S. D. (2022) · Frontiers in Aging · doi:10.3389/fragi.2022.1068455 · Cited by 14
Geroprotective interventions in the 3xTg mouse model of Alzheimer’s disease
Sonsalla, M. M., & Lamming, D. W. (2023) · GeroScience · doi:10.1007/s11357-023-00782-w · Cited by 17
Metadata
- Authors
- Solon-Biet, S. M., McMahon, A. C., Ballard, J. W. O., Ruohonen, K., Wu, L. E., Cogger, V. C., Warren, A., Huang, X., Pichaud, N., Melvin, R. G., Gokarn, R., Khalil, M., Turner, N., Cooney, G. J., Sinclair, D. A., Raubenheimer, D., Le Couteur, D. G., & Simpson, S. J.
- Affiliations
- The University of Sydney (AU)
- UNSW Sydney (AU)
- Ewos Innovation (Norway) (NO)
- University of Helsinki (FI)
- Garvan Institute of Medical Research (AU)
- Harvard University (US)
- Corresponding author
- Simpson, Stephen J.
- ORCID
- Venue
- Cell Metabolism
- Publisher
- Elsevier BV
- Published
- 2014-03
- Volume
- 19
- Issue
- 3
- Pages
- 418-430
- ISSN
- 1550-4131 (ISSN-L)
- PMC
- PMC5087279
- OpenAlex
- W2042438674
- Cited by
- 904
- References
- 39
- Citations by year
- 2026: 37 · 2025: 47 · 2024: 71 · 2023: 75 · 2022: 82 · 2021: 86 · 2020: 101 · 2019: 86 · 2018: 76 · 2017: 74 · 2016: 68 · 2015: 68 · 2014: 31
- FWCI
- 27.47
- Type
- journal article
- Language
- en
- Update notices
- erratum (2020-03-03)
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell Metabolism (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Research Centre
- Cancer Institute NSW
- Australian Research Council
- National Health and Medical Research Council
- National Medical Research Council
- National Institute on Aging (DP1AG058605, R37AG028730, R01AG028730, R01AG019719)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK100263)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Health Sciences › Medicine › Physiology (medical) › Dietary Effects on Health
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diet, Metabolism, and Disease
- Keywords
- macronutrient ratio, dietary protein, dietary carbohydrates, dietary fat, ad libitum feeding, longevity, cardiometabolic health, aging, compensatory feeding, mTOR signaling, mitochondrial function, branched-chain amino acids, glucose, food intake regulation, caloric restriction, dietary dilution, geometric framework, mice
- MeSH terms
- Aging, Amino Acids, Branched-Chain, Animals, Blood Pressure, Body Composition, Energy Intake, Cardiovascular Physiological Phenomena, Diet, Glucose, Insulin, Liver, Longevity, Male, Mice, Inbred C57BL, Phosphorylation, Glucose Intolerance, Leptin, Mice, Kaplan-Meier Estimate, TOR Serine-Threonine Kinases
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