Specific metabolic rates of major organs and tissues across adulthood: Evaluation by mechanistic model of resting energy expenditure
Open accessAbstract
Background The specific resting metabolic rates (K(i); in kcal · kg(-1 )· d(-1)) of major organs and tissues in adults were suggested by Elia (in Energy metabolism: tissue determinants and cellular corollaries. New York, NY: Raven Press, 1992) to be as follows: 200 for liver, 240 for brain, 440 for heart and kidneys, 13 for skeletal muscle, 4.5 for adipose tissue, and 12 for residual organs and tissues. However, Elia's K(i) values have never been fully evaluated.Objectives The objectives of the present study were to evaluate the applicability of Elia's K(i) values across adulthood and to explore the potential influence of age on the K(i) values.Design A new approach was developed to evaluate the K(i) values of major organs and tissues on the basis of a mechanistic model: REE = Σ(K(i) × T(i)), where REE is whole-body resting energy expenditure measured by indirect calorimetry, and T(i) is the mass of individual organs and tissues measured by magnetic resonance imaging. With measured REE and T(i), marginal 95% CIs for K(i) values were calculated by stepwise univariate regression analysis. An existing database of nonobese, healthy adults [n = 131; body mass index (in kg/m²) <30] was divided into 3 age groups: 21-30 y (young, n = 43), 31-50 y (middle-age, n = 51), and > 50 y (n = 37).Results Elia's K(i) values were within the range of 95% CIs in the young and middle-age groups. However, Elia's K(i) values were outside the right boundaries of 95% CIs in the >50-y group, which indicated that Elia's study overestimated K(i) values by 3% in this group. Age-adjusted K(i) values for adults aged >50 y were 194 for liver, 233 for brain, 426 for heart and kidneys, 12.6 for skeletal muscle, 4.4 for adipose tissue, and 11.6 for residuals.Conclusion The general applicability of Elia's K(i) values was validated across adulthood, although age adjustment is appropriate for specific applications.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
Muscle tissue during activity or occlusion situations represents the highest metabolic activity in comparison to other peripheral tissue being measured.
“The first position was that muscle tissue during activity or occlusion situations would represent the highest metabolic activity in comparison to other peripheral tissue being measured.43”
From Near-infrared spectroscopy-derived muscle oxygen saturation on a 0% to 100% scale: reliability and validity of the Moxy Monitor (2019) · cites this paper as [43]
This pattern agrees with prior work reporting elevated tissue-specific metabolic rates in children and adolescents and reduced rates in older adults.
“consistent with previous work indicating that tissue-specific metabolic rates are elevated in children and adolescents (22, 24) and reduced in older adults (21, 23, 25).”
From Daily energy expenditure through the human life course (2021) · cites this paper as [23]
At rest, the heart, liver, brain, and kidneys have much higher tissue-specific metabolic rates than muscles, other lean tissue, or fat.
“At rest, the tissue-specific metabolic rates (Watts/gram) of the heart, liver, brain, and kidneys are much greater than those of the muscles and other lean tissue or fat (21–25).”
From Daily energy expenditure through the human life course (2021) · cites this paper as [23]
After considering average adult weight, brain and muscle emerge as the most metabolically active structures, even at rest.
“However, after considering the average adult weight of these organs, brain (1.33 kg) and muscle (26.3 kg) emerge as the most metabolically active structures, even at rest [25].”
From Vitamins and Minerals for Energy, Fatigue and Cognition: A Narrative Review of the Biochemical and Clinical Evidence (2020) · cites this paper as [25]
Under resting conditions, fractional daily energy expenditure is highest for heart and kidney (each approximately 440 kcal/kg), then brain (approximately 240 kcal/kg), then liver (200 kcal/kg), while resting skeletal muscle needs only approximately 13 kcal/kg.
“Under resting conditions, the fractional daily energy expenditure is the highest for heart and kidney (each approximately 440 kcal/kg), then for the brain (approximately 240 kcal/kg), then the liver (200 kcal/kg), while the resting skeletal muscle would need only approximately 13 kcal/kg.”
From Vitamins and Minerals for Energy, Fatigue and Cognition: A Narrative Review of the Biochemical and Clinical Evidence (2020) · cites this paper as [25]
Cites
STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT
Martin Bland, J., & Altman, D. (1986) · The Lancet · doi:10.1016/s0140-6736(86)90837-8 · Cited by 47,965 · see citing works
Beckett, A. H., Rowland, M., & TURNER, P. (1965) · The Lancet · doi:10.1016/s0140-6736(65)91037-8 · Cited by 16,917 · see citing works
Beckman, R. J., & Weisberg, S. (1987) · Technometrics · doi:10.2307/1269895 · Cited by 2,835 · see citing works
Anthropometric Standardization Reference Manual
Lohman, T. J., Roache, A. F., & Martorell, R. (1992) · Medicine & Science in Sports & Exercise · doi:10.1249/00005768-199208000-00020 · Cited by 2,764 · see citing works
Scaling: Why is Animal Size so Important?
Schmidt-Nielsen, K. (1984) · doi:10.1017/cbo9781139167826 · Cited by 2,677 · see citing works
Scaling Why is animal size so important?
Schmidt‐Nielsen, K. (1984) · Cited by 2,654 · see citing works
Mitochondrial dysfunction in the elderly: possible role in insulin resistance
Petersen, K. F., Befroy, D., Dufour, S., Dziura, J., Ariyan, C., Rothman, D. L., DiPietro, L., Cline, G. W., & Shulman, G. I. (2003) · Science · doi:10.1126/science.1082889 · Cited by 2,107 · see citing works
Report of the task group on reference man
(1979) · Annals of the ICRP · doi:10.1016/0146-6453(79)90123-4 · Cited by 1,715 · see citing works
Positron emission tomography study of human brain functional development
Chugani, H. T., Phelps, M. E., & Mazziotta, J. C. (1987) · Annals of Neurology · doi:10.1002/ana.410220408 · Cited by 1,548 · see citing works
Weisberg, S. (2005) · Wiley series in probability and statistics · doi:10.1002/0471704091 · Cited by 1,469 · see citing works
Fao, J. (2004) · Medical Entomology and Zoology · Cited by 947 · see citing works
Roche, A. F., Heymsfield, S. B., & Lohman, T. G. (2005) · Medical Entomology and Zoology · Cited by 743 · see citing works
Self-citationTotal-body skeletal muscle mass: Estimation by a new dual-energy X-ray absorptiometry method
Kim, J., Wang, Z., Heymsfield, S. B., Baumgartner, R. N., & Gallagher, D. (2002) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/76.2.378 · Cited by 737 · see citing works
Self-citationEnergy Metabolism: Tissue Determinants and Cellular Corollaries
Kinney, J. M. (1992) · Medical Entomology and Zoology · Cited by 595 · see citing works
Organ-tissue mass measurement allows modeling of REE and metabolically active tissue mass
Gallagher, D., Belmonte, D., Deurenberg, P., Wang, Z., Krasnow, N., Pi-Sunyer, F. X., & Heymsfield, S. B. (1998) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.1998.275.2.e249 · Cited by 470 · see citing works
Self-citationMüller, M. J., Bosy‐Westphal, A., Kutzner, D., & Heller, M. (2002) · Obesity Reviews · doi:10.1046/j.1467-789x.2002.00057.x · Cited by 241 · see citing works
Self-citationDual-Energy X-Ray Absorptiometry
Lohman, T. G., & Chen, Z. (2005) · Human Body Composition · doi:10.5040/9781492596950.ch-005 · Cited by 219 · see citing works
Metabolically active components of fat free mass and resting energy expenditure in nonobese adults
Illner, K., Brinkmann, G., Heller, M., Bosy‐Westphal, A., & Müller, M. J. (2000) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.2000.278.2.e308 · Cited by 168 · see citing works
Self-citationBosy‐Westphal, A., Eichhorn, C., Kutzner, D., Illner, K., Heller, M., & Müller, M. J. (2003) · Journal of Nutrition · doi:10.1093/jn/133.7.2356 · Cited by 146 · see citing works
Self-citationBosy‐Westphal, A., Reinecke, U., Schlörke, T., Illner, K., Kutzner, D., Heller, M., & Müller, M. J. (2003) · International Journal of Obesity · doi:10.1038/sj.ijo.0802526 · Cited by 137 · see citing works
Self-citationCouture, P., & Hulbert, A. J. (1995) · American Journal of Physiology-Regulatory, Integrative and Comparative Physiology · doi:10.1152/ajpregu.1995.268.3.r641 · Cited by 118 · see citing works
Wakabayashi, H., Nishiyama, Y., Ushiyama, T., Maeba, T., & Maeta, H. (2002) · Journal of Surgical Research · doi:10.1006/jsre.2002.6462 · Cited by 104 · see citing works
Resting Energy Expenditure: Systematic Organization and Critique of Prediction Methods
Wang, Z., Heshka, S., Zhang, K., Boozer, C. N., & Heymsfield, S. B. (2001) · Obesity Research · doi:10.1038/oby.2001.42 · Cited by 88 · see citing works
Self-citationSmaller Organ Tissue Mass in the Elderly Fails to Explain Lower Resting Metabolic Rate
GALLAGHER, D., ALLEN, A., WANG, Z., HEYMSFIELD, S. B., & KRASNOW, N. (2000) · Annals of the New York Academy of Sciences · doi:10.1111/j.1749-6632.2000.tb06499.x · Cited by 84 · see citing works
Self-citationComputed Tomography and Magnetic Resonance Imaging
Ertürk, Ş. M., Cay, E., & Ros, P. R. (2009) · Springer eBooks · doi:10.1007/978-3-540-93842-2_38 · Cited by 81 · see citing works
Hsu, A., Heshka, S., Janumala, I., Song, M.-Y., Horlick, M., Krasnow, N., & Gallagher, D. (2003) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/77.6.1506 · Cited by 67 · see citing works
Adipose tissue and skeletal muscle blood flow during mental stress
Linde, B., Hjemdahl, P., FREYSCHUSS, U., & JUHLIN‐DANNFELT, A. (1989) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.1989.256.1.e12 · Cited by 65 · see citing works
A cellular-level approach to predicting resting energy expenditure across the adult years
Wang, Z., Heshka, S., Heymsfield, S. B., Shen, W., & Gallagher, D. (2005) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/81.4.799 · Cited by 61 · see citing works
Self-citationMetabolically active portion of fat-free mass: a cellular body composition level modeling analysis
Wang, Z., Heshka, S., Wang, J., Gallagher, D., Deurenberg, P., Chen, Z., & Heymsfield, S. B. (2006) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.00485.2005 · Cited by 53 · see citing works
Self-citationThe Application of Blood Flow Measurements to the Study of Aging Muscle
Holloszy, J. O., McCully, K. K., & Posner, J. D. (1995) · The Journals of Gerontology Series A · doi:10.1093/gerona/50a.special_issue.130 · Cited by 52 · see citing works
Computed Tomography and Magnetic Resonance Imaging
Ross, R., & Janssen, I. (2005) · doi:10.5040/9781492596950.ch-007 · Cited by 31 · see citing works
Wang, Z., Heymsfield, S. B., Ying, Z., Pierson, R. N., Gallagher, D., & Gidwani, S. (2010) · American Journal of Human Biology · doi:10.1002/ajhb.21020 · Cited by 23 · see citing works
Self-citation
Flagged first, then by citations
1 of the 33 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Multi-dimensional Roles of Ketone Bodies in Fuel Metabolism, Signaling, and Therapeutics
Puchalska, P., & Crawford, P. A. (2017) · Cell Metabolism · doi:10.1016/j.cmet.2016.12.022 · Cited by 1,617 · see citing works
Mitochondrial energetics in the kidney
Bhargava, P., & Schnellmann, R. G. (2017) · Nature Reviews Nephrology · doi:10.1038/nrneph.2017.107 · Cited by 1,363 · see citing works
Mitochondrial dysfunction in diabetic kidney disease
Forbes, J. M., & Thorburn, D. R. (2018) · Nature Reviews Nephrology · doi:10.1038/nrneph.2018.9 · Cited by 641 · see citing works
Daily energy expenditure through the human life course
Pontzer, H., Yamada, Y., Sagayama, H., Ainslie, P. N., Andersen, L. F., Anderson, L. J., Arab, L., Baddou, I., Bedu-Addo, K., Blaak, E. E., et al. (2021) · Science · doi:10.1126/science.abe5017 · Cited by 583 · see citing works
Liu, L., MacKenzie, K. R., Putluri, N., Maletić-Savatić, M., & Bellen, H. J. (2017) · Cell Metabolism · doi:10.1016/j.cmet.2017.08.024 · Cited by 556 · see citing works
Tardy, A.-L., Pouteau, E., Marquez, D., Yilmaz, C., & Scholey, A. (2020) · Nutrients · doi:10.3390/nu12010228 · Cited by 541 · see citing works
A Quantitative Proteome Map of the Human Body
Jiang, L., Wang, M., Lin, S., Jian, R., Li, X., Chan, J., Dong, G., Fang, H., Robinson, A. E., Aguet, F., et al. (2020) · Cell · doi:10.1016/j.cell.2020.08.036 · Cited by 458 · see citing works
Sirtuins in Renal Health and Disease
Morigi, M., Perico, L., & Benigni, A. (2018) · Journal of the American Society of Nephrology · doi:10.1681/asn.2017111218 · Cited by 359 · see citing works
Kidney physiology and susceptibility to acute kidney injury: implications for renoprotection
Scholz, H., Boivin, F. J., Schmidt-Ott, K. M., Bachmann, S., Eckardt, K., Scholl, U. I., & Persson, P. B. (2021) · Nature Reviews Nephrology · doi:10.1038/s41581-021-00394-7 · Cited by 328 · see citing works
Regulation of Mitochondrial ATP Production: Ca2+ Signaling and Quality Control
Boyman, L., Karbowski, M., & Lederer, W. J. (2019) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2019.10.007 · Cited by 309 · see citing works
Stokes, T., Hector, A., Morton, R., McGlory, C., & Phillips, S. (2018) · Nutrients · doi:10.3390/nu10020180 · Cited by 263 · see citing works
NAD + Metabolism in Cardiac Health, Aging, and Disease
Abdellatif, M., Sedej, S., & Kroemer, G. (2021) · Circulation · doi:10.1161/circulationaha.121.056589 · Cited by 262 · see citing works
Scientific Opinion on Dietary Reference Values for energy
EFSA Panel on Dietetic Products, N. A. A. (. (2013) · EFSA Journal · doi:10.2903/j.efsa.2013.3005 · Cited by 258 · see citing works
Oxidative Stress and Mitochondrial Dysfunction in Chronic Kidney Disease
Ho, H.-J., & Shirakawa, H. (2022) · Cells · doi:10.3390/cells12010088 · Cited by 255 · see citing works
Inhibiting aerobic glycolysis suppresses renal interstitial fibroblast activation and renal fibrosis
Ding, H., Jiang, L., Xu, J., Bai, F., Zhou, Y., Yuan, Q., Luo, J., Zen, K., & Yang, J. (2017) · American Journal of Physiology-Renal Physiology · doi:10.1152/ajprenal.00036.2017 · Cited by 250 · see citing works
Liu, X., Ma, Y., Ouyang, R., Zeng, Z., Zhan, Z., Lu, H., Cui, Y., Dai, Z., Luo, L., He, C., et al. (2020) · Journal of Neuroinflammation · doi:10.1186/s12974-020-01905-2 · Cited by 241 · see citing works
Even, P. C., & Nadkarni, N. A. (2012) · American Journal of Physiology-Regulatory, Integrative and Comparative Physiology · doi:10.1152/ajpregu.00137.2012 · Cited by 237 · see citing works
Antioxidant supplements and endurance exercise: Current evidence and mechanistic insights
Mason, S. A., Trewin, A. J., Parker, L., & Wadley, G. D. (2020) · Redox Biology · doi:10.1016/j.redox.2020.101471 · Cited by 226 · see citing works
Mitochondrial disease and endocrine dysfunction
Chow, J. C. K., Rahman, J., Achermann, J. C., Dattani, M., & Rahman, S. (2016) · Nature Reviews Endocrinology · doi:10.1038/nrendo.2016.151 · Cited by 212 · see citing works
Miller, V. J., Villamena, F. A., & Volek, J. S. (2018) · Journal of Nutrition and Metabolism · doi:10.1155/2018/5157645 · Cited by 200 · see citing works
Spatially resolved isotope tracing reveals tissue metabolic activity
Wang, L., Xing, X., Zeng, X., Jackson, S. R., TeSlaa, T. A., Al‐Dalahmah, O., Samarah, L. Z., Goodwin, K., Yang, L., McReynolds, M. R., et al. (2022) · Nature Methods · doi:10.1038/s41592-021-01378-y · Cited by 187 · see citing works
Salidroside stimulates the Sirt1/PGC-1α axis and ameliorates diabetic nephropathy in mice
Xue, H., Li, P., Luo, Y., Wu, C., Liu, Y., Qin, X., Huang, X., & Sun, C. (2018) · Phytomedicine · doi:10.1016/j.phymed.2018.10.031 · Cited by 190 · see citing works
Metabolism at the crossroads of inflammation and fibrosis in chronic kidney disease
Miguel, V., Shaw, I., & Kramann, R. (2024) · Nature Reviews Nephrology · doi:10.1038/s41581-024-00889-z · Cited by 206 · see citing works
O’Keefe, S. J. (2019) · The Lancet. Gastroenterology & hepatology · doi:10.1016/s2468-1253(19)30257-2 · Cited by 190 · see citing works
Inflammation and Oxidative Stress in Chronic Kidney Disease and Dialysis Patients
Ebert, T., Neytchev, O., Witasp, A., Kublickiene, K. R., Stenvinkel, P., & Shiels, P. G. (2021) · Antioxidants and Redox Signaling · doi:10.1089/ars.2020.8184 · Cited by 190 · see citing works
Ma, H., Guo, X., Cui, S., Wu, Y., Zhang, Y., Shen, X., Xie, C., & Li, J. (2021) · Kidney International · doi:10.1016/j.kint.2021.10.028 · Cited by 183 · see citing works
Cai, T., Ke, Q., Fang, Y., Wen, P., Chen, H., Yuan, Q., Luo, J., Zhang, Y., Sun, Q., Lv, Y., et al. (2020) · Cell Death and Disease · doi:10.1038/s41419-020-2544-7 · Cited by 183 · see citing works
Adaptive thermogenesis with weight loss in humans
Müller, M. J., & Bosy‐Westphal, A. (2013) · Obesity · doi:10.1002/oby.20027 · Cited by 181 · see citing works
Self-citationMOF Acetyl Transferase Regulates Transcription and Respiration in Mitochondria
Chatterjee, A., Seyfferth, J., Lucci, J., Gilsbach, R., Preißl, S., Böttinger, L., Mårtensson, C. U., Panhale, A., Stehlé, T., Kretz, O., et al. (2016) · Cell · doi:10.1016/j.cell.2016.09.052 · Cited by 179 · see citing works
Sclerostin influences body composition by regulating catabolic and anabolic metabolism in adipocytes
Kim, S. P., Frey, J. L., Li, Z., Kushwaha, P., Zoch, M. L., Tomlinson, R. E., Da, H., Aja, S. M., Noh, H. L., Kim, J. K., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1707876115 · Cited by 179 · see citing works
Feldmann, A., Schmitz, R. W., & Erlacher, D. (2019) · Journal of Biomedical Optics · doi:10.1117/1.jbo.24.11.115001 · Cited by 159 · see citing works
“The first position was that muscle tissue during activity or occlusion situations would represent the highest metabolic activity in comparison to other peripheral tissue being measured.(43) Therefore, when comparing NIRS-derived values for SmO2 against invasive measures of SvO2, the SmO2 values cannot be higher than t…”
BackgroundKowalski, G. M., & Bruce, C. R. (2014) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.00165.2014 · Cited by 154 · see citing works
Energetic dysfunction in sepsis: a narrative review
Préau, S., Vodovar, D., Jung, B., Lancel, S., Zafrani, L., Flatres, A., Oualha, M., Voiriot, G., Jouan, Y., Joffre, J., et al. (2021) · Annals of Intensive Care · doi:10.1186/s13613-021-00893-7 · Cited by 156 · see citing works
Shortage of Cellular ATP as a Cause of Diseases and Strategies to Enhance ATP
Johnson, T. A., Jinnah, H. A., & Kamatani, N. (2019) · Frontiers in Pharmacology · doi:10.3389/fphar.2019.00098 · Cited by 148 · see citing works
The energetic cost of allostasis and allostatic load
Bobba‐Alves, N., Juster, R., & Picard, M. A. (2022) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2022.105951 · Cited by 155 · see citing works
Mitochondrial metabolic reprogramming in diabetic kidney disease
Fan, X., Yang, M., Lang, Y., Lu, S., Kong, Z., Gao, Y., Shen, N., Zhang, D., & Lv, Z. (2024) · Cell Death and Disease · doi:10.1038/s41419-024-06833-0 · Cited by 158 · see citing works
The Role of miR-378a in Metabolism, Angiogenesis, and Muscle Biology
Krist, B., Florczyk, U., Pietraszek‐Gremplewicz, K., Józkowicz, A., & Dulak, J. (2015) · International Journal of Endocrinology · doi:10.1155/2015/281756 · Cited by 146 · see citing works
Kraja, A. T., Liu, C., Fetterman, J. L., Graff, M., Have, C. T., Gu, C. C., Yanek, L. R., Feitosa, M. F., Arking, D. E., Chasman, D. I., et al. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2018.12.001 · Cited by 145 · see citing works
Voltage-energized calcium-sensitive ATP production by mitochondria
Wescott, A. P., Kao, J. P. Y., Lederer, W. J., & Boyman, L. (2019) · Nature Metabolism · doi:10.1038/s42255-019-0126-8 · Cited by 144 · see citing works
Zhang, Y., Wen, P., Luo, J., Ding, H., Cao, H., He, W., Zen, K., Zhou, Y., Yang, J., & Jiang, L. (2021) · Cell Death and Disease · doi:10.1038/s41419-021-04134-4 · Cited by 131 · see citing works
The Link Between the Mitochondrial Fatty Acid Oxidation Derangement and Kidney Injury
Console, L., Scalise, M., Giangregorio, N., Tonazzi, A., Barile, M., & Indiveri, C. (2020) · Frontiers in Physiology · doi:10.3389/fphys.2020.00794 · Cited by 125 · see citing works
Amino acid is a major carbon source for hepatic lipogenesis
Liao, Y., Chen, Q., Liu, L., Huang, H., Sun, J., Bai, X., Jin, C., Li, H., Sun, F., Xiao, X., et al. (2024) · Cell Metabolism · doi:10.1016/j.cmet.2024.10.001 · Cited by 122 · see citing works
The Role of GDF15 as a Myomitokine
Johann, K., Kleinert, M., & Klaus, S. (2021) · Cells · doi:10.3390/cells10112990 · Cited by 121 · see citing works
O 2 Economizer for Inhibiting Cell Respiration To Combat the Hypoxia Obstacle in Tumor Treatments
Yu, W., Liu, T., Zhang, M., Wang, Z., Ye, J., Li, C., Liu, W., Li, R., Feng, J. X., & Zhang, X. (2019) · ACS Nano · doi:10.1021/acsnano.8b07852 · Cited by 115 · see citing works
Self-citationPaying the brain's energy bill
Padamsey, Z., & Rochefort, N. L. (2023) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2022.102668 · Cited by 114 · see citing works
Understanding the Role of Exercise in Cancer Cachexia Therapy
Hardee, J. P., Counts, B. R., & Carson, J. A. (2017) · American Journal of Lifestyle Medicine · doi:10.1177/1559827617725283 · Cited by 108 · see citing works
Mitochondrial Dysfunction and Kidney Stone Disease
Chaiyarit, S., & Thongboonkerd, V. (2020) · Frontiers in Physiology · doi:10.3389/fphys.2020.566506 · Cited by 109 · see citing works
Cardiac ketone body metabolism
Kadir, A. A., Clarke, K., & Evans, R. D. (2020) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2020.165739 · Cited by 108 · see citing works
Vascular complications in diabetes: Old messages, new thoughts
Forbes, J. M., & Fotheringham, A. K. (2017) · Diabetologia · doi:10.1007/s00125-017-4360-x · Cited by 106 · see citing works
Management of cardiovascular risk in patients with multiple myeloma
Plummer, C., Driessen, C., Szabó, Z. R., & Mateos, M. (2019) · Blood Cancer Journal · doi:10.1038/s41408-019-0183-y · Cited by 106 · see citing works
The Molecular Aspect of Nephrolithiasis Development
Wigner, P., Grębowski, R., Bijak, M., Szemraj, J., & Saluk, J. (2021) · Cells · doi:10.3390/cells10081926 · Cited by 105 · see citing works
Immunometabolic rewiring of tubular epithelial cells in kidney disease
van der Rijt, S., Leemans, J. C., Florquin, S., Houtkooper, R. H., & Tammaro, A. (2022) · Nature Reviews Nephrology · doi:10.1038/s41581-022-00592-x · Cited by 102 · see citing works
A major mechanism for immunomodulation: Dietary fibres and acid metabolites
Xie, L., Alam, J., Marques, F. Z., & Mackay, C. R. (2023) · Seminars in Immunology · doi:10.1016/j.smim.2023.101737 · Cited by 97 · see citing works
Evolving concepts on adjusting human resting energy expenditure measurements for body size
Heymsfield, S. B., Thomas, D. M., Bosy‐Westphal, A., Shen, W., Peterson, C. M., & Müller, M. J. (2012) · Obesity Reviews · doi:10.1111/j.1467-789x.2012.01019.x · Cited by 98 · see citing works
Self-citationCritical role of mitochondrial dysfunction and impaired mitophagy in diabetic nephropathy
Saxena, S., Mathur, A., & Kakkar, P. (2019) · Journal of Cellular Physiology · doi:10.1002/jcp.28712 · Cited by 96 · see citing works
Pandora's growing box: Inferring the evolution and development of hominin brains from endocasts
Zollikofer, C. P. E., & León, M. S. P. D. (2013) · Evolutionary Anthropology Issues News and Reviews · doi:10.1002/evan.21333 · Cited by 94 · see citing works
Advances in the understanding of specific metabolic rates of major organs and tissues in humans
Müller, M. J., Wang, Z., Heymsfield, S. B., Schautz, B., & Bosy‐Westphal, A. (2013) · Current Opinion in Clinical Nutrition & Metabolic Care · doi:10.1097/mco.0b013e328363bdf9 · Cited by 96 · see citing works
Self-citationThe role of lipotoxicity in kidney disease: From molecular mechanisms to therapeutic prospects
Ren, L., Cui, H., Wang, Y., Ju, F., Cai, Y., Gang, X., & Wang, G. (2023) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2023.114465 · Cited by 99 · see citing works
Barth Syndrome: Connecting Cardiolipin to Cardiomyopathy
Ikon, N., & Ryan, R. O. (2017) · Lipids · doi:10.1007/s11745-016-4229-7 · Cited by 93 · see citing works
Hepatic ketogenic insufficiency reprograms hepatic glycogen metabolism and the lipidome
d’Avignon, D. A., Puchalska, P., Erçal, B., Chang, Y., Martin, S. E., Graham, M. J., Patti, G. J., Han, X., & Crawford, P. A. (2018) · JCI Insight · doi:10.1172/jci.insight.99762 · Cited by 90 · see citing works
Body size-dependent energy storage causes Kleiber’s law scaling of the metabolic rate in planarians
Rink, J. C., Thommen, A., Werner, S., Frank, O., Philipp, J., Knittelfelder, O., Quek, Y., Fahmy, K., Shevchenko, A., Friedrich, B. M., et al. (2019) · eLife · doi:10.7554/elife.38187 · Cited by 90 · see citing works
Characterization of Glycolytic Enzymes and Pyruvate Kinase M2 in Type 1 and 2 Diabetic Nephropathy
Gordin, D., Shah, H., Shinjo, T., St-Louis, R., Qi, W., Park, K., Paniagua, S. M., POBER, D. M., Wu, I., Bahnam, V., et al. (2019) · Diabetes Care · doi:10.2337/dc18-2585 · Cited by 89 · see citing works
Ketones can become the major fuel source for the heart but do not increase cardiac efficiency
Ho, K. L., Karwi, Q. G., Wagg, C. S., Zhang, L., Vo, K., Altamimi, T., Uddin, G. M., Ussher, J. R., & Lopaschuk, G. D. (2020) · Cardiovascular Research · doi:10.1093/cvr/cvaa143 · Cited by 89 · see citing works
Müller, M. J., Langemann, D., Gehrke, I., Later, W., Heller, M., Glüer, C., Heymsfield, S. B., & Bosy‐Westphal, A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0022732 · Cited by 88 · see citing works
Self-citationMediterranean diet and cognitive function: From methodology to mechanisms of action
Siervo, M., Shannon, O. M., Llewellyn, D. J., Stephan, B. C. M., & Fontana, L. (2021) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2021.09.018 · Cited by 86 · see citing works
Contribution of brown adipose tissue to human energy metabolism
Fernández‐Verdejo, R., Marlatt, K. L., Ravussin, É., & Galgani, J. E. (2019) · Molecular Aspects of Medicine · doi:10.1016/j.mam.2019.07.003 · Cited by 86 · see citing works
Metabolic Communication and Healthy Aging: Where Should We Focus Our Energy?
Smith, H. J., Sharma, A., & Mair, W. B. (2020) · Developmental Cell · doi:10.1016/j.devcel.2020.06.011 · Cited by 82 · see citing works
Fazzini, F., Lamina, C., Fendt, L., Schultheiß, U. T., Kotsis, F., Hicks, A. A., Meiselbach, H., Weißensteiner, H., Forer, L., Krane, V., et al. (2019) · Kidney International · doi:10.1016/j.kint.2019.04.021 · Cited by 80 · see citing works
Salt-Losing Tubulopathies in Children: What’s New, What’s Controversial?
Kleta, R., & Böckenhauer, D. (2017) · Journal of the American Society of Nephrology · doi:10.1681/asn.2017060600 · Cited by 81 · see citing works
Schöttl, T., Kappler, L., Fromme, T., & Klingenspor, M. (2015) · Molecular Metabolism · doi:10.1016/j.molmet.2015.07.001 · Cited by 77 · see citing works
Augmenter of liver regeneration protects the kidney from ischaemia‐reperfusion injury in ferroptosis
Huang, L., Liao, X., Sun, H., Jiang, X., Liu, Q., & Zhang, L. (2019) · Journal of Cellular and Molecular Medicine · doi:10.1111/jcmm.14302 · Cited by 77 · see citing works
Metabolomic and immune alterations in long COVID patients with chronic fatigue syndrome
Saito, S., Shahbaz, S., Luo, X., Osman, M. S., Redmond, D., Tervaert, J. W. C., Li, L., & Elahi, S. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1341843 · Cited by 77 · see citing works
Radley‐Crabb, H. G., Marini, J. C., Sosa, H. A., Castillo, L. I., Grounds, M. D., & Fiorotto, M. L. (2014) · PLoS ONE · doi:10.1371/journal.pone.0089277 · Cited by 77 · see citing works
Sure, V. N. L. R., Sakamuri, S. S. V. P., Sperling, J. A., Evans, W. R., Merdžo, I., Mostany, R., Murfee, W. L., Busija, D. W., & Katakam, P. V. G. (2018) · GeroScience · doi:10.1007/s11357-018-0037-8 · Cited by 76 · see citing works
The Clinical Assessment of Intraventricular Flows
Bermejo, J., Martínez‐Legazpi, P., & del Álamo, J. C. (2014) · Annual Review of Fluid Mechanics · doi:10.1146/annurev-fluid-010814-014728 · Cited by 76 · see citing works
Dimitrova‐Shumkovska, J., Krstanoski, L., & Veenman, L. (2020) · Marine Drugs · doi:10.3390/md18050242 · Cited by 73 · see citing works
Bartter Syndrome and Gitelman Syndrome
Fulchiero, R., & Seo-Mayer, P. W. (2018) · Pediatric Clinics of North America · doi:10.1016/j.pcl.2018.08.010 · Cited by 75 · see citing works
Targeting immune cell metabolism in kidney diseases
Basso, P. J., Andrade‐Oliveira, V., & Câmara, N. O. S. (2021) · Nature Reviews Nephrology · doi:10.1038/s41581-021-00413-7 · Cited by 75 · see citing works
Casanova, N., Beaulieu, K., Finlayson, G., & Hopkins, M. (2019) · Proceedings of The Nutrition Society · doi:10.1017/s0029665118002811 · Cited by 73 · see citing works
The Vicious Cycle of Renal Lipotoxicity and Mitochondrial Dysfunction
Ge, M., Fontanesi, F., Merscher, S., & Fornoni, A. (2020) · Frontiers in Physiology · doi:10.3389/fphys.2020.00732 · Cited by 71 · see citing works
Metabolomics – a novel window into inflammatory disease
Fitzpatrick, M. A., & Young, S. P. (2013) · Swiss Medical Weekly · doi:10.4414/smw.2013.13743 · Cited by 71 · see citing works
Advances in the Science and Application of Body Composition Measurement
Baracos, V. E., Caserotti, P., Earthman, C. P., Fields, D. A., Gallagher, D., Hall, K. D., Heymsfield, S. B., Müller, M. J., Rosen, A. N., Pichard, C., et al. (2012) · Journal of Parenteral and Enteral Nutrition · doi:10.1177/0148607111417448 · Cited by 71 · see citing works
Self-citationMitochondrial Pathophysiology on Chronic Kidney Disease
Braga, P. C., Alves, M. G., Rodrigues, A. S., & Oliveira, P. F. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23031776 · Cited by 69 · see citing works
Harnessing reactive oxygen/nitrogen species and inflammation: Nanodrugs for liver injury
Liu, M., Huang, Q., Zhu, Y., Chen, L., Li, Y., Gong, Z., & Ai, K. (2022) · Materials Today Bio · doi:10.1016/j.mtbio.2022.100215 · Cited by 69 · see citing works
Cancer cachexia: Pathophysiology and association with cancer-related pain
Law, M. L. (2022) · Frontiers in Pain Research · doi:10.3389/fpain.2022.971295 · Cited by 69 · see citing works
Metabolic switches during development and regeneration
Mahmoud, A. I. (2023) · Development · doi:10.1242/dev.202008 · Cited by 64 · see citing works
Kosmiski, L. A., Schmiege, S. J., Mascolo, M., Gaudiani, J. L., & Mehler, P. S. (2013) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2013-1694 · Cited by 69 · see citing works
Geisler, C., Braun, W., Pourhassan, M., Schweitzer, L., Glüer, C., Bosy‐Westphal, A., & Müller, M. J. (2016) · Nutrients · doi:10.3390/nu8060322 · Cited by 66 · see citing works
Self-citationNormalizing resting energy expenditure across the life course in humans: challenges and hopes
Müller, M. J., Geisler, C., Hübers, M., Pourhassan, M., Braun, W., & Bosy‐Westphal, A. (2018) · European Journal of Clinical Nutrition · doi:10.1038/s41430-018-0151-9 · Cited by 66 · see citing works
Self-citationResting Energy Expenditure: From Cellular to Whole‐Body Level, a Mechanistic Historical Perspective
Heymsfield, S. B., Smith, B., Dahle, J. H., Kennedy, S., Fearnbach, N., Thomas, D. M., Bosy‐Westphal, A., & Müller, M. J. (2021) · Obesity · doi:10.1002/oby.23090 · Cited by 65 · see citing works
Self-citationTonazzi, A., Giangregorio, N., Console, L., Palmieri, F., & Indiveri, C. (2021) · Biomolecules · doi:10.3390/biom11040521 · Cited by 64 · see citing works
Tubular Cell Glucose Metabolism Shift During Acute and Chronic Injuries
Faivre, A., Verissimo, T., Auwerx, H., Legouis, D., & de Seigneux, S. (2021) · Frontiers in Medicine · doi:10.3389/fmed.2021.742072 · Cited by 64 · see citing works
Decoding the Liver-Heart Axis in Cardiometabolic Diseases
Capone, F., Vacca, A., Bidault, G., Sarver, D. C., Kamińska, D., Strocchi, S., Vidal‐Puig, A., Greco, C. M., Lusis, A. J., & Schiattarella, G. G. (2025) · Circulation Research · doi:10.1161/circresaha.125.325492 · Cited by 72 · see citing works
Bioengineering adult human heart tissue: How close are we?
Mills, R. J., & Hudson, J. E. (2019) · APL Bioengineering · doi:10.1063/1.5070106 · Cited by 63 · see citing works
Issues in characterizing resting energy expenditure in obesity and after weight loss
Bosy‐Westphal, A., Braun, W., Schautz, B., & Müller, M. J. (2013) · Frontiers in Physiology · doi:10.3389/fphys.2013.00047 · Cited by 62 · see citing works
Self-citationIchihara, G., Katsumata, Y., Sugiura, Y., Matsuoka, Y., Maeda, R., Endo, J., Anzai, A., Shirakawa, K., Moriyama, H., Kitakata, H., et al. (2023) · Circulation Research · doi:10.1161/circresaha.123.323517 · Cited by 62 · see citing works
Geisler, C., Braun, W., Pourhassan, M., Schweitzer, L., Glüer, C., Bosy‐Westphal, A., & Müller, M. J. (2015) · The Journals of Gerontology Series A · doi:10.1093/gerona/glv211 · Cited by 60 · see citing works
Self-citationMarchianò, S., Bertero, A., & Murry, C. E. (2019) · Pediatric Cardiology · doi:10.1007/s00246-019-02165-5 · Cited by 56 · see citing works
Beale, P. K., Marsh, K. J., Foley, W. J., & Moore, B. D. (2017) · Biological reviews/Biological reviews of the Cambridge Philosophical Society · doi:10.1111/brv.12364 · Cited by 59 · see citing works
Tessier, A., Wing, S. S., Rahme, E., Morais, J. A., & Chevalier, S. (2019) · Journal of Cachexia Sarcopenia and Muscle · doi:10.1002/jcsm.12462 · Cited by 58 · see citing works
- Authors
- Wang, Z., Ying, Z., Bosy-Westphal, A., Zhang, J., Schautz, B., Later, W., Heymsfield, S. B., & Müller, M. J.
- Affiliations
- St. Luke's-Roosevelt Hospital Center (US)
- Pennington Biomedical Research Center (US)
- Venue
- The American Journal of Clinical Nutrition
- Publisher
- Elsevier BV
- Published
- 2010-12
- Volume
- 92
- Issue
- 6
- Pages
- 1369-1377
- ISSN
- 0002-9165 (ISSN-L)
- PMC
- PMC2980962
- OpenAlex
- W2123746079
- Cited by
- 546
- References
- 33
- Citations by year
- 2026: 55 · 2025: 61 · 2024: 52 · 2023: 60 · 2022: 48 · 2021: 56 · 2020: 56 · 2019: 41 · 2018: 38 · 2017: 25 · 2016: 10 · 2015: 14 · 2014: 7 · 2013: 11 · 2012: 6
- FWCI
- 4.76
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- American Journal of Clinical Nutrition (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Deutsche Forschungsgemeinschaft
- National Institutes of Health
- National Institute of Diabetes and Digestive and Kidney Diseases (R21DK081633, DK081633)
- Topics
- Health Sciences › Medicine › Physiology › Body Composition Measurement Techniques
- Health Sciences › Nursing › Nutrition and Dietetics › Clinical Nutrition and Gastroenterology
- Health Sciences › Medicine › Physiology › Adipose Tissue and Metabolism
- Keywords
- resting energy expenditure, specific metabolic rate, hepatic metabolism, brain metabolism, skeletal muscle, adipose tissue, healthy adults, indirect calorimetry
- MeSH terms
- Adipose Tissue, Adult, Age Factors, Basal Metabolism, Brain, Energy Metabolism, Female, Heart, Humans, Kidney, Liver, Male, Middle Aged, Models, Biological, Reference Values, Regression Analysis, Muscle, Skeletal, Young Adult
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