The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
The Ratio of Macronutrients, Not Caloric Intake, Dictates Cardiometabolic Health, Aging, and Longevity in Ad Libitum-Fed Mice
Open accessAbstract
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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.
In the citing paper
“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]
Experimental — accuracy not yet measuredIn the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
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
Self-citation
Cited by
Sorted by citations
Multi-omics approaches to disease
Hasin, Y., Seldin, M., & Lusis, A. (2017) · Genome Biology · doi:10.1186/s13059-017-1215-1 · Cited by 2,953
Facing up to the global challenges of ageing
Partridge, L., Deelen, J., & Slagboom, P. E. (2018) · Nature · doi:10.1038/s41586-018-0457-8 · Cited by 1,475
Promoting Health and Longevity through Diet: From Model Organisms to Humans
Fontana, L., & Partridge, L. (2015) · Cell · doi:10.1016/j.cell.2015.02.020 · Cited by 1,245
Metabolic Control of Longevity
López-Otín, C., Galluzzi, L., Freije, J. M. P., Madeo, F., & Kroemer, G. (2016) · Cell · doi:10.1016/j.cell.2016.07.031 · Cited by 753
Molecular mechanisms of dietary restriction promoting health and longevity
Green, C. L., Lamming, D. W., & Fontana, L. (2022) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-021-00411-4 · Cited by 714
Association of animal and plant protein intake with all-cause and cause-specific mortality.
Song, M., Fung, T. T., Hu, F. B., Willett, W. C., Longo, V. D., Chan, A. T., & Giovannucci, E. L. (2016) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2016.4182 · Cited by 735
Interventions to slow aging in humans: are we ready?
Longo, V. D., Antebi, A., Bartke, A., Barzilai, N., Brown‐Borg, H. M., Caruso, C., Curiel, T. J., Cabo, R., Franceschi, C., Gems, D., et al. (2015) · Aging Cell · doi:10.1111/acel.12338 · Cited by 592
Self-citationFGF21 is an endocrine signal of protein restriction
Laeger, T., Henagan, T. M., Albarado, D. C., Redman, L. M., Bray, G. A., Noland, R. C., Münzberg, H., Hutson, S. M., Gettys, T. W., Schwartz, M. W., et al. (2014) · Journal of Clinical Investigation · doi:10.1172/jci74915 · Cited by 593
A Ketogenic Diet Extends Longevity and Healthspan in Adult Mice
Roberts, M. N., Wallace, M. A., Tomilov, A. A., Zhou, Z., Marcotte, G. R., Tran, D., Perez, G., Gutierrez-Casado, E., Koike, S., Knotts, T. A., et al. (2017) · Cell Metabolism · doi:10.1016/j.cmet.2017.08.005 · Cited by 514
Francesco, A. D., Germanio, C. D., Bernier, M., & de Cabo, R. (2018) · Science · doi:10.1126/science.aau2095 · Cited by 507
Decreased consumption of branched-chain amino acids improves metabolic health
Fontana, L., Cummings, N. E., Arriola Apelo, S. I., Neuman, J. C., Kasza, I., Schmidt, B. A., Cava, E., Spelta, F., Tosti, V., Syed, F. A., et al. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.05.092 · Cited by 466
mTOR as a central regulator of lifespan and aging
Papadopoli, D. J., Boulay, K., Kazak, L., Pollak, M., Mallette, F. A., Topisirović, I., & Hulea, L. (2019) · F1000Research · doi:10.12688/f1000research.17196.1 · Cited by 447
The adverse metabolic effects of branched-chain amino acids are mediated by isoleucine and valine
Yu, D., Richardson, N. E., Green, C. L., Spicer, A. B., Trautman, M. E., Flores, V., Jang, C., Kasza, I., Nikodémová, M., Wakai, M. H., et al. (2021) · Cell Metabolism · doi:10.1016/j.cmet.2021.03.025 · Cited by 398
Targeting the biology of aging with mTOR inhibitors
Mannick, J. B., & Lamming, D. W. (2023) · Nature Aging · doi:10.1038/s43587-023-00416-y · Cited by 372
Naghshi, S., Sadeghi, O., Willett, W. C., & Esmaillzadeh, A. (2020) · BMJ · doi:10.1136/bmj.m2412 · Cited by 371
FOXO3: A Major Gene for Human Longevity - A Mini-Review
Morris, B. J., Willcox, D. C., Donlon, T. A., & Willcox, B. J. (2015) · Gerontology · doi:10.1159/000375235 · Cited by 353
Dietary restriction and lifespan: lessons from invertebrate models
Kapahi, P., Kaeberlein, M., & Hansen, M. (2017) · Ageing Research Reviews · doi:10.1016/j.arr.2016.12.005 · Cited by 340
Restoration of metabolic health by decreased consumption of branched‐chain amino acids
Richardson, N. E., Williams, E. M., Kasza, I., Konon, E. N., Schaid, M. D., Schmidt, B., Poudel, C., Sherman, D. S., Yu, D., Apelo, S. I. A., et al. (2017) · The Journal of Physiology · doi:10.1113/jp275075 · Cited by 348
Nutrition, longevity and disease: From molecular mechanisms to interventions
Longo, V. D., & Anderson, R. M. (2022) · Cell · doi:10.1016/j.cell.2022.04.002 · Cited by 345
Animal models of aging research: implications for human aging and age-related diseases
Mitchell, S. J., Scheibye-Knudsen, M., Longo, D. L., & de Cabo, R. (2015) · Annual Review of Animal Biosciences · doi:10.1146/annurev-animal-022114-110829 · Cited by 328
Solon‐Biet, S. M., Cogger, V. C., Pulpitel, T., Wahl, D., Clark, X., Bagley, E. E., Gregoriou, G. C., Senior, A. M., Wang, Q., Brandon, A. E., et al. (2019) · Nature Metabolism · doi:10.1038/s42255-019-0059-2 · Cited by 338
Self-citationCommensal bacteria and essential amino acids control food choice behavior and reproduction
Leitão-Gonçalves, R., Carvalho-Santos, Z., Francisco, A. P., Fioreze, G. T., Anjos, M., Baltazar, C., Elias, A. P., Itskov, P. M., Piper, M. D. W., & Ribeiro, C. (2017) · PLOS Biology · doi:10.1371/journal.pbio.2000862 · Cited by 315
Daily Fasting Improves Health and Survival in Male Mice Independent of Diet Composition and Calories
Mitchell, S. J., Bernier, M., Mattison, J. A., Aon, M. A., Kaiser, T. A., Anson, R. M., Ikeno, Y., Anderson, R. M., Ingram, D. K., & de Cabo, R. (2018) · Cell Metabolism · doi:10.1016/j.cmet.2018.08.011 · Cited by 305
Calorie restriction as an intervention in ageing
López‐Lluch, G., & Navas, P. (2015) · The Journal of Physiology · doi:10.1113/jp270543 · Cited by 301
Intermittent and periodic fasting, longevity and disease
Longo, V. D., Tano, M. D., Mattson, M. P., & Guidi, N. (2021) · Nature Aging · doi:10.1038/s43587-020-00013-3 · Cited by 301
Drosophila as a model for ageing
Piper, M. D. W., & Partridge, L. (2018) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2017.09.016 · Cited by 273
Richardson, N. E., Konon, E. N., Schuster, H. S., Mitchell, A. T., Boyle, C., Rodgers, A. C., Finke, M., Haider, L. R., Yu, D., Flores, V., et al. (2021) · Nature Aging · doi:10.1038/s43587-020-00006-2 · Cited by 267
Horizons in the evolution of aging
Flatt, T., & Partridge, L. (2018) · BMC Biology · doi:10.1186/s12915-018-0562-z · Cited by 273
Protein and amino acid restriction, aging and disease: from yeast to humans
Mirzaei, H., Suarez, J. A., & Longo, V. D. (2014) · Trends in Endocrinology and Metabolism · doi:10.1016/j.tem.2014.07.002 · Cited by 249
Macronutrient balance, reproductive function, and lifespan in aging mice
Solon-Biet, S. M., Walters, K. A., Simanainen, U. K., McMahon, A. C., Ruohonen, K., Ballard, J. W. O., Raubenheimer, D., Handelsman, D. J., Le Couteur, D. G., & Simpson, S. J. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1422041112 · Cited by 243
Self-citationCardio-Metabolic Effects of High-Fat Diets and Their Underlying Mechanisms—A Narrative Review
Wali, J. A., Jarzebska, N., Raubenheimer, D., Simpson, S. J., Rodionov, R. N., & O’Sullivan, J. (2020) · Nutrients · doi:10.3390/nu12051505 · Cited by 256
Self-citationFGF21 Signals Protein Status to the Brain and Adaptively Regulates Food Choice and Metabolism
Hill, C. M., Laeger, T., Dehner, M., Albarado, D. C., Clarke, B., Wanders, D., Burke, S. J., Collier, J. J., Qualls-Creekmore, E., Solon-Biet, S. M., et al. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.05.022 · Cited by 229
Self-citationBranched chain amino acids, aging and age-related health
Couteur, D. G. L., Solon‐Biet, S. M., Cogger, V. C., Ribeiro, R. V., de Cabo, R., Raubenheimer, D., Cooney, G. J., & Simpson, S. J. (2020) · Ageing Research Reviews · doi:10.1016/j.arr.2020.101198 · Cited by 237
Self-citationFibroblast Growth Factor 21: A Versatile Regulator of Metabolic Homeostasis
BonDurant, L. D., & Potthoff, M. J. (2018) · Annual Review of Nutrition · doi:10.1146/annurev-nutr-071816-064800 · Cited by 222
Caldwell, A. S. L., Edwards, M. C., Desai, R., Jimenez, M., Gilchrist, R. B., Handelsman, D. J., & Walters, K. A. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1616467114 · Cited by 228
Diet strategies for promoting healthy aging and longevity: An epidemiological perspective
Hu, F. B. (2023) · Journal of Internal Medicine · doi:10.1111/joim.13728 · Cited by 241
FGF21 Is a Sugar-Induced Hormone Associated with Sweet Intake and Preference in Humans
Søberg, S., Sandholt, C. H., Jespersen, N. Z., Toft, U., Madsen, A. L., von Holstein-Rathlou, S., Grevengoed, T. J., Christensen, K. B., Bredie, W. L. P., Potthoff, M. J., et al. (2017) · Cell Metabolism · doi:10.1016/j.cmet.2017.04.009 · Cited by 216
Piper, M. D. W., Soultoukis, G. A., Blanc, E., Mesaros, A., Herbert, S. L., Juricic, P., He, X., Atanassov, I., Salmonowicz, H., Yang, M., et al. (2017) · Cell Metabolism · doi:10.1016/j.cmet.2017.02.005 · Cited by 214
Self-citationDefining the Nutritional and Metabolic Context of FGF21 Using the Geometric Framework
Solon-Biet, S. M., Cogger, V. C., Pulpitel, T., Heblinski, M., Wahl, D., McMahon, A. C., Warren, A., Durrant-Whyte, J., Walters, K. A., Krycer, J. R., et al. (2016) · Cell Metabolism · doi:10.1016/j.cmet.2016.09.001 · Cited by 212
Self-citationThe impact of low-protein high-carbohydrate diets on aging and lifespan
Le Couteur, D. G., Solon-Biet, S., Cogger, V. C., Mitchell, S. J., Senior, A., de Cabo, R., Raubenheimer, D., & Simpson, S. J. (2016) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-015-2120-y · Cited by 209
Self-citationDietary Protein to Carbohydrate Ratio and Caloric Restriction: Comparing Metabolic Outcomes in Mice
Solon-Biet, S. M., Mitchell, S. J., Coogan, S. C. P., Cogger, V. C., Gokarn, R., McMahon, A. C., Raubenheimer, D., de Cabo, R., Simpson, S. J., & Le Couteur, D. G. (2015) · Cell Reports · doi:10.1016/j.celrep.2015.05.007 · Cited by 207
Self-citationSharples, A. P., Hughes, D. C., Deane, C. S., Saini, A. S., Selman, C., & Stewart, C. E. (2015) · Aging Cell · doi:10.1111/acel.12342 · Cited by 204
The Effects of Intermittent Fasting on Brain and Cognitive Function
Gudden, J., Vásquez, A. A., & Bloemendaal, M. (2021) · Nutrients · doi:10.3390/nu13093166 · Cited by 212
Antioxidants and HNE in redox homeostasis
Łuczaj, W., Gęgotek, A., & Skrzydlewska, E. (2016) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2016.11.033 · Cited by 201
Inhibition of the Mechanistic Target of Rapamycin (mTOR)–Rapamycin and BeyondPreprint
Lamming, D. W. (2016) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a025924 · Cited by 205
Jensen, K., McClure, C. D., Priest, N. K., & Hunt, J. (2015) · Aging Cell · doi:10.1111/acel.12333 · Cited by 196
High-protein diets increase cardiovascular risk by activating macrophage mTOR to suppress mitophagy
Zhang, X., Sergin, I., Evans, T. D., Jeong, S.-J., Rodriguez-Velez, A., Kapoor, D., Chen, S., Song, E., Holloway, K. B., Crowley, J. R., et al. (2020) · Nature Metabolism · doi:10.1038/s42255-019-0162-4 · Cited by 191
Nutritional Ecology and Human Health
Raubenheimer, D., & Simpson, S. J. (2016) · Annual Review of Nutrition · doi:10.1146/annurev-nutr-071715-051118 · Cited by 194
Self-citationPutting the Balance Back in Diet
Simpson, S. J., Couteur, D. G. L., & Raubenheimer, D. (2015) · Cell · doi:10.1016/j.cell.2015.02.033 · Cited by 188
Self-citationAmino acid catabolism in Alzheimer’s disease brain: Friend or foe?
Griffin, J. W. D., & Bradshaw, P. C. (2017) · Oxidative Medicine and Cellular Longevity · doi:10.1155/2017/5472792 · Cited by 185
Diet-Microbiome Interactions in Health Are Controlled by Intestinal Nitrogen Source Constraints
Holmes, A. J., Chew, Y. V., Colakoglu, F., Cliff, J. B., Klaassens, E., Read, M. N., Solon-Biet, S. M., McMahon, A. C., Cogger, V. C., Ruohonen, K., et al. (2017) · Cell Metabolism · doi:10.1016/j.cmet.2016.10.021 · Cited by 183
Self-citationKatewa, S. D., Akagi, K., Bose, N., Rakshit, K., Camarella, T., Zheng, X., Hall, D., Davis, S., Nelson, C. S., Brem, R. B., et al. (2016) · Cell Metabolism · doi:10.1016/j.cmet.2015.10.014 · Cited by 173
Dietary protein, aging and nutritional geometry
Simpson, S. J., Le Couteur, D. G., Raubenheimer, D., Solon-Biet, S. M., Cooney, G. J., Cogger, V. C., & Fontana, L. (2017) · Ageing Research Reviews · doi:10.1016/j.arr.2017.03.001 · Cited by 169
Self-citationCaloric restriction and the aging process: a critique
Sohal, R. S., & Forster, M. J. (2014) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2014.05.015 · Cited by 187
Dietary regulation in health and disease
Wu, Q., Gao, Z., Yu, X., & Wang, P. (2022) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-01104-w · Cited by 190
The impact of dietary protein intake on longevity and metabolic health
Kitada, M., Ogura, Y., Monno, I., & Koya, D. (2019) · EBioMedicine · doi:10.1016/j.ebiom.2019.04.005 · Cited by 175
“demonstrated that LPHC diets, but not high-protein and/or diluted diets that reduce calorie intake, are associated with longevity and metabolic health, including lower blood pressure, improved glucose tolerance, higher levels of high-density lipoprotein, and reduced levels of low-density lipoprotein and triglycerides…”
BackgroundSex‐ and tissue‐specific changes in mTOR signaling with age in C57 BL /6J mice
Baar, E. L., Carbajal, K. A., Ong, I. M., & Lamming, D. W. (2016) · Aging Cell · doi:10.1111/acel.12425 · Cited by 177
Dietary restriction with and without caloric restriction for healthy aging
Lee, C. D., & Longo, V. D. (2016) · F1000Research · doi:10.12688/f1000research.7136.1 · Cited by 178
Pak, H. H., Haws, S. A., Green, C. L., Koller, M., Lavarias, M. T., Richardson, N. E., Yang, S. E., Dumas, S. N., Sonsalla, M., Bray, L., et al. (2021) · Nature Metabolism · doi:10.1038/s42255-021-00466-9 · Cited by 171
A liver stress-endocrine nexus promotes metabolic integrity during dietary protein dilution
Maida, A., Zota, A., Sjøberg, K. A., Schumacher, J., Sijmonsma, T. P., Pfenninger, A., Christensen, M. M., Gantert, T., Fuhrmeister, J., Rothermel, U., et al. (2016) · Journal of Clinical Investigation · doi:10.1172/jci85946 · Cited by 170
Regulation of reproduction and longevity by nutrient-sensing pathways
Templeman, N. M., & Murphy, C. T. (2017) · The Journal of Cell Biology · doi:10.1083/jcb.201707168 · Cited by 175
Jensen-Cody, S. O., Flippo, K. H., Claflin, K. E., Yavuz, Y., Sapouckey, S. A., Walters, G. C., Usachev, Y. M., Atasoy, D., Gillum, M. P., & Potthoff, M. J. (2020) · Cell Metabolism · doi:10.1016/j.cmet.2020.06.008 · Cited by 166
Hormetic Effects of Phytochemicals on Health and Longevity
Martel, J., Ojcius, D. M., Ko, Y., Ke, P., Wu, C.-Y., Peng, H., & Young, J. D. (2019) · Trends in Endocrinology and Metabolism · doi:10.1016/j.tem.2019.04.001 · Cited by 168
The central moTOR of metabolism
Simcox, J., & Lamming, D. W. (2022) · Developmental Cell · doi:10.1016/j.devcel.2022.02.024 · Cited by 174
Mechanisms of Lifespan Regulation by Calorie Restriction and Intermittent Fasting in Model Organisms
Hwangbo, D., Lee, H., Abozaid, L. S., & Min, K. (2020) · Nutrients · doi:10.3390/nu12041194 · Cited by 173
Protein Leverage: Theoretical Foundations and Ten Points of Clarification
Raubenheimer, D., & Simpson, S. J. (2019) · Obesity · doi:10.1002/oby.22531 · Cited by 157
Self-citationWilder, S. M., Raubenheimer, D., & Simpson, S. J. (2015) · Functional Ecology · doi:10.1111/1365-2435.12460 · Cited by 159
Self-citationGenomic analysis of diet composition finds novel loci and associations with health and lifestyle
Meddens, S. F. W., de Vlaming, R., Bowers, P., Burik, C. A. P., Linnér, R. K., Lee, C. W., Okbay, A., Turley, P., Rietveld, C. A., Fontana, M. A., et al. (2020) · Molecular Psychiatry · doi:10.1038/s41380-020-0697-5 · Cited by 165
The gut microbiome influences host diet selection behavior
Trevelline, B. K., & Kohl, K. D. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2117537119 · Cited by 162
Recent Advances in the Integrative Nutrition of Arthropods
Simpson, S. J., Clissold, F. J., Lihoreau, M., Ponton, F., Wilder, S. M., & Raubenheimer, D. (2014) · Annual Review of Entomology · doi:10.1146/annurev-ento-010814-020917 · Cited by 154
Self-citationCatterson, J. H., Khericha, M., Dyson, M. C., Vincent, A. J., Callard, R., Haveron, S. M., Rajasingam, A., Ahmad, M., & Partridge, L. (2018) · Current Biology · doi:10.1016/j.cub.2018.04.015 · Cited by 152
Low-Protein Diet Induces IRE1α-Dependent Anticancer Immunosurveillance.
Rubio-Patiño, C., Bossowski, J. P., de Donatis, G. D., Mondragón, L., Villa, E., Aira, L., Chiche, J., Mhaidly, R., Lebeaupin, C., Marchetti, S., et al. (2018) · Cell Metabolism · doi:10.1016/j.cmet.2018.02.009 · Cited by 123
Nutrition, dietary interventions and prostate cancer: the latest evidence
Lin, P., Aronson, W. J., & Freedland, S. J. (2015) · BMC Medicine · doi:10.1186/s12916-014-0234-y · Cited by 159
Diet, Microbiota, and Metabolic Health: Trade-Off Between Saccharolytic and Proteolytic Fermentation
Korpela, K. (2018) · Annual Review of Food Science and Technology · doi:10.1146/annurev-food-030117-012830 · Cited by 161
Reduced Circulating Insulin Enhances Insulin Sensitivity in Old Mice and Extends Lifespan
Templeman, N. M., Flibotte, S., Chik, J. H. L., Sinha, S., Lim, G. E., Foster, L. J., Nislow, C., & Johnson, J. D. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.06.048 · Cited by 151
Wahl, D., Solon‐Biet, S. M., Cogger, V. C., Fontana, L., Simpson, S. J., Couteur, D. G. L., & Ribeiro, R. V. (2019) · Neurobiology of Disease · doi:10.1016/j.nbd.2019.104481 · Cited by 155
Self-citationDietary Protein, Metabolism, and Aging
Soultoukis, G. A., & Partridge, L. (2016) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-060815-014422 · Cited by 148
Dietary Restrictions and Nutrition in the Prevention and Treatment of Cardiovascular Disease
Brandhorst, S., & Longo, V. D. (2019) · Circulation Research · doi:10.1161/circresaha.118.313352 · Cited by 148
Henriques, S. F., Dhakan, D. B., Serra, L., Francisco, A. P., Carvalho-Santos, Z., Baltazar, C., Elias, A. P., Anjos, M., Zhang, T., Maddocks, O. D. K., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18049-9 · Cited by 152
Impact of Longevity Interventions on a Validated Mouse Clinical Frailty Index
Kane, A. E., Hilmer, S. N., Boyer, D., Gavin, K., Nines, D., Howlett, S. E., de Cabo, R., & Mitchell, S. J. (2015) · The Journals of Gerontology Series A · doi:10.1093/gerona/glu315 · Cited by 147
Anti-aging pharmacology: Promises and pitfalls
Vaiserman, A. M., Lushchak, O. V., & Koliada, A. K. (2016) · Ageing Research Reviews · doi:10.1016/j.arr.2016.08.004 · Cited by 148
Leulier, F., MacNeil, L. T., Lee, W., Rawls, J. F., Cani, P. D., Schwarzer, M., Zhao, L., & Simpson, S. J. (2017) · Cell Metabolism · doi:10.1016/j.cmet.2017.02.001 · Cited by 152
Self-citationReproductive Endocrinology of Nonalcoholic Fatty Liver Disease
Grossmann, M., Wierman, M. E., Angus, P., & Handelsman, D. J. (2018) · Endocrine Reviews · doi:10.1210/er.2018-00158 · Cited by 146
Antiaging diets: Separating fact from fiction
Lee, M. B., Hill, C. M., Bitto, A., & Kaeberlein, M. R. (2021) · Science · doi:10.1126/science.abe7365 · Cited by 147
Dietary restriction.; mitochondrial function and aging: From yeast to humans
Ruetenik, A., & Barrientos, A. (2015) · Biochimica et Biophysica Acta (BBA) - Bioenergetics · doi:10.1016/j.bbabio.2015.05.005 · Cited by 139
Life history evolution, reproduction, and the origins of sex‐dependent aging and longevity
Brooks, R. C., & Garratt, M. (2016) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.13302 · Cited by 144
Internal states drive nutrient homeostasis by modulating exploration-exploitation trade-off
Corrales-Carvajal, V. M., Faisal, A. A., & Ribeiro, C. (2016) · eLife · doi:10.7554/elife.19920 · Cited by 143
Macronutrients and caloric intake in health and longevity
Solon‐Biet, S. M., Mitchell, S. J., de Cabo, R., Raubenheimer, D., Couteur, D. G. L., & Simpson, S. J. (2015) · Journal of Endocrinology · doi:10.1530/joe-15-0173 · Cited by 140
Self-citationEpigenetic drift of H3K27me3 in aging links glycolysis to healthy longevity in Drosophila
Ma, Z., Wang, H., Cai, Y. A., Wang, H., Niu, K., Wu, X., Ma, H., Yang, Y., Tong, W., Liu, F., et al. (2018) · eLife · doi:10.7554/elife.35368 · Cited by 135
Wahl, D., Solon‐Biet, S. M., Wang, Q., Wali, J. A., Pulpitel, T., Clark, X., Raubenheimer, D., Senior, A. M., Sinclair, D. A., Cooney, G. J., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.10.070 · Cited by 135
Self-citationAmino acids in the regulation of aging and aging-related diseases
Canfield, C.-A. E., & Bradshaw, P. C. (2019) · Translational Medicine of Aging · doi:10.1016/j.tma.2019.09.001 · Cited by 138
The potential role of necroptosis in inflammaging and aging
Royce, G. H., Brown‐Borg, H. M., & Deepa, S. S. (2019) · GeroScience · doi:10.1007/s11357-019-00131-w · Cited by 137
Speakman, J. R., Mitchell, S. E., & Mazidi, M. (2016) · Experimental Gerontology · doi:10.1016/j.exger.2016.03.011 · Cited by 131
Hill, C. M., Albarado, D. C., Coco, L. G., Spann, R. A., Khan, M. S., Qualls-Creekmore, E., Burk, D. H., Burke, S. J., Collier, J. J., Yu, S., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-29499-8 · Cited by 117
Wells, J. C. K., & Stock, J. T. (2020) · Frontiers in Endocrinology · doi:10.3389/fendo.2020.00325 · Cited by 139
Diurnal transcriptome landscape of a multi-tissue response to time-restricted feeding in mammals
Deota, S., Lin, T. C., Chaix, A., Williams, A. E., Le, H. D., Calligaro, H., Ramasamy, R., Huang, L., & Panda, S. (2023) · Cell Metabolism · doi:10.1016/j.cmet.2022.12.006 · Cited by 142
Kohl, K. D., Coogan, S. C. P., & Raubenheimer, D. (2015) · BioEssays · doi:10.1002/bies.201400171 · Cited by 125
Self-citationIntermittent fasting: from calories to time restriction
Duregon, E., Pomatto, L. C. D., Bernier, M., Price, N. L., & de Cabo, R. (2021) · GeroScience · doi:10.1007/s11357-021-00335-z · Cited by 134
The Multifaceted Role of Nutrient Sensing and mTORC1 Signaling in Physiology and Aging
Fernandes, S., & Demetriades, C. (2021) · Frontiers in Aging · doi:10.3389/fragi.2021.707372 · Cited by 131
Green, C. L., Trautman, M. E., Chaiyakul, K., Jain, R., Alam, Y. H., Babygirija, R., Pak, H. H., Sonsalla, M. M., Calubag, M. F., Yeh, C., et al. (2023) · Cell Metabolism · doi:10.1016/j.cmet.2023.10.005 · Cited by 121
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review