The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
Diminished anabolic signaling response to insulin induced by intramuscular lipid accumulation is associated with inflammation in aging but not obesity
Open accessAbstract
The loss of skeletal muscle mass is observed in many pathophysiological conditions, including aging and obesity. The loss of muscle mass and function with aging is defined as sarcopenia and is characterized by a mismatch between skeletal muscle protein synthesis and breakdown. Characteristic metabolic features of both aging and obesity are increases in intramyocellular lipid (IMCL) content in muscle. IMCL accumulation may play a mechanistic role in the development of anabolic resistance and the progression of muscle atrophy in aging and obesity. In the present study, aged and high-fat fed mice were used to determine mechanisms leading to muscle loss. We hypothesized the accumulation of bioactive lipids in skeletal muscle, such as ceramide or diacylglycerols, leads to insulin resistance with aging and obesity and the inability to activate protein synthesis, contributing to skeletal muscle loss. We report a positive association between bioactive lipid accumulation and the loss of lean mass and muscle strength. Obese and aged animals had significantly higher storage of ceramide and diacylglycerol compared with young. Furthermore, there was an attenuated insulin response in components of the mTOR anabolic signaling pathway. We also observed differential increases in the expression of inflammatory cytokines and the phosphorylation of IκBα with aging and obesity. These data challenge the accepted role of increased inflammation in obesity-induced insulin resistance in skeletal muscle. Furthermore, we have now established IκBα with a novel function in aging-associated muscle loss that may be independent of its previously understood role as an NF-κB inhibitor.
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“Intermyocellular adipose tissue (IMAT) and IMCL secrete myostatin, CCL2, TNF-α, IL-1β, and IL-6, thus inducing IR and lipotoxicity, which is discussed in the next section [30].”
From Sarcopenic obesity, insulin resistance, and their implications in cardiovascular and metabolic consequences (2020) · cites this paper as [30]
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Holland, W. L., Brozinick, J. T., Wang, L.-P., Hawkins, E. D., Sargent, K. M., Liu, Y., Narra, K., Hoehn, K. L., Knotts, T. A., Siesky, A., et al. (2007) · Cell Metabolism · doi:10.1016/j.cmet.2007.01.002 · Cited by 1,232
Attenuation of skeletal muscle and strength in the elderly: the Health ABC Study
Goodpaster, B. H., Carlson, C. L., Visser, M., Kelley, D. E., Scherzinger, A., Harris, T. B., Stamm, E., & Newman, A. B. (2001) · Journal of Applied Physiology · doi:10.1152/jappl.2001.90.6.2157 · Cited by 1,226
Hand-Grip Dynamometry Predicts Future Outcomes in Aging Adults
Bohannon, R. W. (2008) · Journal of Geriatric Physical Therapy · doi:10.1519/00139143-200831010-00002 · Cited by 951
A PCR primer bank for quantitative gene expression analysis
Wang, X. (2003) · Nucleic Acids Research · doi:10.1093/nar/gng154 · Cited by 856
Holland, W. L., Bikman, B. T., Wang, L.-P., Yuguang, G., Sargent, K. M., Bulchand, S., Knotts, T. A., Shui, G., Clegg, D. J., Wenk, M. R., et al. (2011) · Journal of Clinical Investigation · doi:10.1172/jci43378 · Cited by 705
Wind, A. E., Takken, T., Helders, P. J. M., & Engelbert, R. (2009) · European Journal of Pediatrics · doi:10.1007/s00431-009-1010-4 · Cited by 583
Turner, N., Kowalski, G. M., Leslie, S. J., Risis, S., Yang, C., Lee-Young, R. S., Babb, J. R., Meikle, P. J., Lancaster, G. I., Henstridge, D. C., et al. (2013) · Diabetologia · doi:10.1007/s00125-013-2913-1 · Cited by 430
STAT3 signaling controls satellite cell expansion and skeletal muscle repair
Tierney, M. T., Aydogdu, T., Sala, D., Malecova, B., Gatto, S., Puri, P. L., Latella, L., & Sacco, A. (2014) · Nature Medicine · doi:10.1038/nm.3656 · Cited by 401
Skeletal Muscle Triglycerides, Diacylglycerols, and Ceramides in Insulin Resistance
Amati, F., Dubé, J. J., Alvarez-Carnero, E., Edreira, M. M., Chomentowski, P., Coen, P. M., Switzer, G. E., Bickel, P. E., Stefanovic-Racic, M., Toledo, F. G. S., et al. (2011) · Diabetes · doi:10.2337/db10-1221 · Cited by 395
Martins, A. R., Nachbar, R. T., Gorjão, R., Vinolo, M. A. R., Festuccia, W. T., Lambertucci, R. H., Cury‐Boaventura, M. F., Silveira, L. R., Curi, R., & Hirabara, S. M. (2012) · Lipids in Health and Disease · doi:10.1186/1476-511x-11-30 · Cited by 306
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Sarcopenia: Aging-Related Loss of Muscle Mass and Function
Larsson, L., Degens, H., Li, M., Salviati, L., Lee, Y. I., Thompson, W., Kirkland, J. L., & Sandri, M. (2019) · Physiological Reviews · doi:10.1152/physrev.00061.2017 · Cited by 1,797
Kalinkovich, A., & Livshits, G. (2017) · Ageing Research Reviews · doi:10.1016/j.arr.2016.09.008 · Cited by 882
Wilkinson, D. J., Piasecki, M., & Atherton, P. J. (2018) · Ageing Research Reviews · doi:10.1016/j.arr.2018.07.005 · Cited by 950
Chronic inflammation and the hallmarks of aging
Baechle, J. J., Chen, N., Makhijani, P., Winer, S., Furman, D., & Winer, D. A. (2023) · Molecular Metabolism · doi:10.1016/j.molmet.2023.101755 · Cited by 471
Hong, S.-H., & Choi, K. M. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21020494 · Cited by 390
Metadata
- Authors
- Rivas, D. A., McDonald, D. J., Rice, N. P., Haran, P. H., Dolnikowski, G. G., & Fielding, R. A.
- Affiliations
- Tufts University (US)
- Corresponding author
- Rivas, Donato A.
- Venue
- American Journal of Physiology-Regulatory, Integrative and Comparative Physiology
- Publisher
- American Physiological Society
- Published
- 2016-04-01
- Volume
- 310
- Issue
- 7
- Pages
- R561-R569
- ISSN
- 0363-6119 (ISSN-L)
- 1522-1490
- PMC
- PMC4867383
- OpenAlex
- W2321444106
- Cited by
- 132
- References
- 53
- Citations by year
- 2026: 9 · 2025: 8 · 2024: 19 · 2023: 10 · 2022: 21 · 2021: 15 · 2020: 13 · 2019: 7 · 2018: 16 · 2017: 11 · 2016: 3
- FWCI
- 6.41
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- American Journal of Physiology-Regulatory, Integrative and Comparative Physiology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- U.S. Department of Agriculture (USDA) (58-1950-4-003)
- HHS | NIH | National Institute on Aging (U.S. National Institute on Aging) (1P30AG031679)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Muscle Physiology and Disorders
- Health Sciences › Nursing › Nutrition and Dietetics › Muscle metabolism and nutrition
- Health Sciences › Medicine › Physiology (medical) › Nutrition and Health in Aging
- Keywords
- sarcopenia, skeletal muscle atrophy, intramyocellular lipid, insulin resistance, anabolic signaling, mTOR signaling, ceramide, diacylglycerol, bioactive lipids, inflammation, IκBα phosphorylation, NF-κB, aging, obesity, muscle protein synthesis, muscle strength
- MeSH terms
- Aging, Animals, Insulin, Insulin Resistance, Lipids, Male, Metabolism, Mice, Inbred C57BL, Myositis, Obesity, Signal Transduction, Muscle, Skeletal, Lipid Metabolism, Mice, Sarcopenia
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