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BAIBA attenuates insulin resistance and inflammation induced by palmitate or a high fat diet via an AMPK–PPARδ-dependent pathway in mice
Open accessAbstract
Aims/hypothesis We explored the effects of β-aminoisobutyric acid (BAIBA) on hyperlipidaemic-condition-induced insulin resistance and inflammation as mediated through a signalling pathway involving AMP-activated protein kinase (AMPK) and peroxisome proliferator-activated receptor δ (PPARδ). Methods Mouse skeletal muscle C2C12 cells and C57BL/6J mice were treated with palmitate or a high-fat diet (HFD) and BAIBA. Inflammation and the expression of genes associated with insulin signalling were determined by western blot and quantitative real-time PCR. Selected genes from candidate pathways were evaluated by small interfering (si)RNA knockdown and specific inhibitors. Results BAIBA treatment ameliorated impairment of insulin receptor substrate (IRS)-1/Akt-mediated insulin signalling in palmitate-treated C2C12 myocytes and in skeletal muscle of HFD-fed mice. In addition, BAIBA treatment reversed HFD-induced increases in body weight and improved impaired glucose tolerance in mice. In vitro and in vivo, inhibitory κBα (IκBα) phosphorylation, nuclear factor κB (NFκB) nuclear translocation and downstream inflammatory cytokines were significantly suppressed by BAIBA. Furthermore, BAIBA treatment significantly induced AMPK phosphorylation and expression of PPARδ in C2C12 myocytes and in skeletal muscle of mice. Both compound C, an AMPK inhibitor, and Pparδ (also known as Ppard) siRNA abrogated the inhibitory effects of BAIBA on palmitate-induced inflammation and insulin resistance. BAIBA significantly induced the expression of genes associated with fatty acid oxidation, such as carnitine palmitoyltransferase 1 (Cpt1), acyl-CoA oxidase (Aco; also known as Acox1) and fatty acid binding protein 3 (Fabp3); this effect of BAIBA was significantly reduced by compound C and Pparδ siRNA. Conclusions/interpretation These results are the first to demonstrate that BAIBA attenuates insulin resistance, suppresses inflammation and induces fatty acid oxidation via the AMPK-PPARδ pathway in skeletal muscle.
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“BAIBA promotes increased VAT lipolysis, increased FFA oxidation, and glucose uptake in SkM [110,111,112].”
From The Role of Exercise in the Interplay between Myokines, Hepatokines, Osteokines, Adipokines, and Modulation of Inflammation for Energy Substrate Redistribution and Fat Mass Loss: A Review (2020) · cites this paper as [111]
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“For example, β‐aminoisobutyric acid (BAIBA), a novel exercise‐induced muscle factor, attenuates insulin resistance, improves glucose tolerance, and promotes the browning of white adipose tissue (WAT) and hepatic β‐oxidation (Roberts et al, 2014; Jung et al, 2015).”
From Exercise‐induced α‐ketoglutaric acid stimulates muscle hypertrophy and fat loss through OXGR1‐dependent adrenal activation (2020) · cites this paper as Jung et al, 2015
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“In another study using C2C12 mouse myocytes and a wild-type mouse model (palmitate or high-fat diet exposure), BAIBA treatment attenuated insulin resistance, reduced inflammation and increased fatty acid oxidation through AMP-activated protein kinase (AMPK) and a AMPK-PPARδ-dependent pathway in skeletal muscle113.”
From Exerkines in health, resilience and disease (2022) · cites this paper as [113]
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Cites
2 retracted
Activation of Protein Phosphatase 2A by Palmitate Inhibits AMP-activated Protein Kinase
Wu, Y., Song, P., Xu, J., Zhang, M., & Zou, M. (2007) · Journal of Biological Chemistry · doi:10.1074/jbc.m608310200 · Cited by 283
RetractedDong, Y., Zhang, M., Wang, S., Liang, B., Zhao, Z., Liu, C., Wu, M., Choi, H. C., Lyons, T. J., & Zou, M. (2010) · Diabetes · doi:10.2337/db09-1637 · Cited by 187
RetractedInflammation and insulin resistance
Shoelson, S. E. (2006) · Journal of Clinical Investigation · doi:10.1172/jci29069 · Cited by 4,769
Thioredoxin-interacting protein links oxidative stress to inflammasome activation
Zhou, R., Tardivel, A., Thorens, B., Choi, I., & Tschopp, J. (2010) · Nature Immunology · doi:10.1038/ni.1831 · Cited by 2,708
Koves, T. R., Ussher, J. R., Noland, R. C., Slentz, D., Mosedale, M., Ilkayeva, O., Bain, J., Stevens, R., Dyck, J. R. B., Newgard, C. B., et al. (2008) · Cell Metabolism · doi:10.1016/j.cmet.2007.10.013 · Cited by 1,990
Kern, P. A., Ranganathan, S., Li, C., Wood, L., & Ranganathan, G. (2001) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.2001.280.5.e745 · Cited by 1,883
Role of Fatty Acids in the Pathogenesis of Insulin Resistance and NIDDM
Boden, G. (1997) · Diabetes · doi:10.2337/diab.46.1.3 · Cited by 1,728
Pickup, J. C., Mattock, M. B., Chusney, G. D., & Burt, D. J. (1997) · Diabetologia · doi:10.1007/s001250050822 · Cited by 1,246
AMPK and PPARδ Agonists Are Exercise Mimetics
Narkar, V. A., Downes, M., Yu, R. T., Embler, E., Wang, Y.-X., Banayo, E., Mihaylova, M. M., Nelson, M. C., Zou, Y., Juguilon, H., et al. (2008) · Cell · doi:10.1016/j.cell.2008.06.051 · Cited by 1,222
Brown adipose tissue regulates glucose homeostasis and insulin sensitivity
Stanford, K. I., Middelbeek, R. J. W., Townsend, K. L., An, D., Nygaard, E. B., Hitchcox, K. M., Markan, K. R., Nakano, K., Hirshman, M. F., Tseng, Y.-H., et al. (2013) · Journal of Clinical Investigation · doi:10.1172/jci62308 · Cited by 1,180
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Items 101–144 of 144
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Vallejo, J. A., Kitase, Y., Thiagarajan, G., Dallas, M., Xie, Y., Moore, D. S., Johnson, M. L., Bonewald, L. F., & Wacker, M. (2025) · Aging · doi:10.18632/aging.206325 · Cited by 5
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Zimmerman, J. M., Klein, A. J., Travis, K. B., & Vaughan, R. A. (2025) · Nutrients · doi:10.3390/nu17223619 · Cited by 6
Potential effects of Ag ion on the host by changing the structure of its gut microbiota
Wang, X., Yu, N., Ma, Y., Zhou, H., Wang, C., Wei, S., & Miao, A. (2023) · Journal of Hazardous Materials · doi:10.1016/j.jhazmat.2023.131879 · Cited by 5
Katano, S., Yano, T., Kouzu, H., Nagaoka, R., Numazawa, R., Yamano, K., Fujisawa, Y., Ohori, K., Nagano, N., Fujito, T., et al. (2023) · Heart and Vessels · doi:10.1007/s00380-023-02308-y · Cited by 5
Fukuyama, K., Motomura, E., & Okada, M. (2023) · Nutrients · doi:10.3390/nu15071621 · Cited by 5
Exercise-induced myokines in metabolic regulation: mechanisms, mimetics, and translational potential
Aslam, M. A., Lee, J., Bowen, T. S., & Huh, J. Y. (2026) · Archives of Pharmacal Research · doi:10.1007/s12272-026-01624-x · Cited by 7
Panghal, A., & Jena, G. (2024) · Mutation Research/Genetic Toxicology and Environmental Mutagenesis · doi:10.1016/j.mrgentox.2024.503820 · Cited by 4
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Oct-B: A derivative of L-BAIBA significantly alleviating high-fat diet-induced obesity in mice
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Awad, K. R., Kumar, A., Aziz, M. N., Brotto, L. S., Wang, Z., Bonewald, L. F., & Brotto, M. (2025) · Methods in molecular biology · doi:10.1007/978-1-0716-4534-5_16 · Cited by 2
Hu, X., Wang, C., Zou, P., Wu, T., Shi, H., Gao, B., Zhu, L., & Duan, R. (2025) · International Immunopharmacology · doi:10.1016/j.intimp.2025.115781 · Cited by 2
Cui, Q., Wang, H., Yu, H., Li, Y., Wang, Y., Shi, J., & Hou, Y. (2026) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2026.111159 · Cited by 2
Begriche, K., Massart, J., & Fromenty, B. (2026) · European Journal of Pharmacology · doi:10.1016/j.ejphar.2026.178879 · Cited by 2
Huang, J., Sun, M., Yu, J. H., Guo, Y., Li, B., Dai, L., Tang, Y., Wang, X., Han, S., & Lai, X. (2025) · Xenobiotica · doi:10.1080/00498254.2025.2520423 · Cited by 1
Berg, S. M., Havelund, J. F., Hasler‐Sheetal, H., Kruse, V., Pedersen, A. J. T., Hansen, A. B., Nybo, M., Beck‐Nielsen, H., Højlund, K., & Færgeman, N. J. (2017) · Journal of clinical lipidology · doi:10.1016/j.jacl.2017.02.009 · Cited by 1
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Mo, C., Wang, Z., Brotto, L. S., Pollack, D. A., Huang, J., & Brotto, M. A. P. (2019) · Springer eBooks · doi:10.1007/978-3-030-25890-0_4 · Cited by 1
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Haidar, S. A., de Vries, N. K., Karavetian, M., Laviano, A., & Rached, M. (2019) · Mediterranean Journal of Nutrition and Metabolism · doi:10.3233/mnm-190294
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Grano, M., & Colaianni, G. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-801238-3.11218-8
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Huang, J., Wang, Z., Brotto, L. S., Varanasi, V. G., Mo, C., & Brotto, M. A. P. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-801238-3.11214-0
Rodríguez, A. M., Bonet, M. L., & Ribot, J. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-813814-4.00026-2
Muskulatur: „peripheres mechanisch- und Signalstoff-gestütztes Zentrum der Gesundheit“
Laube, W. (2023) · Springer eBooks · doi:10.1007/978-3-662-67753-7_8
Zhang, Z., Li, X., Guo, J., He, B., Wu, L., Yang, R., Li, X., Fang, D., Yang, X., Yang, D., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26649402
Zhang, Z., Li, X., Guo, J., He, B., Wu, L., Yang, R., Li, X., Fang, D., Yang, X., Yang, D., et al. (2024) · Figshare · doi:10.6084/m9.figshare.24742978
Zhang, Z., Li, X., Guo, J., He, B., Wu, L., Yang, R., Li, X., Fang, D., Yang, X., Yang, D., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26649411
Zhang, Z., Li, X., Guo, J., He, B., Wu, L., Yang, R., Li, X., Fang, D., Yang, X., Yang, D., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26649414
Zhang, Z., Li, X., Guo, J., He, B., Wu, L., Yang, R., Li, X., Fang, D., Yang, X., Yang, D., et al. (2023) · Figshare · doi:10.6084/m9.figshare.24741800
Zhang, Z., Li, X., Guo, J., He, B., Wu, L., Yang, R., Li, X., Fang, D., Yang, X., Yang, D., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26649417
Zhang, Z., Li, X., Guo, J., He, B., Wu, L., Yang, R., Li, X., Fang, D., Yang, X., Yang, D., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26649420
Zhang, Z., Li, X., Guo, J., He, B., Wu, L., Yang, R., Li, X., Fang, D., Yang, X., Yang, D., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26649408
Zhang, Z., Li, X., Guo, J., He, B., Wu, L., Yang, R., Li, X., Fang, D., Yang, X., Yang, D., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26649405
Zhang, Z., Li, X., Guo, J., He, B., Wu, L., Yang, R., Li, X., Fang, D., Yang, X., Yang, D., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26649423
Chen, K., Xie, P.-Y., Liu, H., Gao, Z., & Wang, H. (2026) · Fish Physiology and Biochemistry · doi:10.1007/s10695-025-01630-8
Yamamoto, H., Ishii, A., & Kihara, S. (2026) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.66011
Lee, Y., Choi, Y., & Kim, Y. (2026) · The Korean Journal of Community Living Science · doi:10.7856/kjcls.2026.37.1.31
Effects of exercise-induced myokines on rehabilitation and metabolic regulation
ÖZTÜRK, E. Z., & Alataş, M. (2026) · Journal of Health Sciences and Medicine · doi:10.32322/jhsm.1883007
Allen, L. E., Sutton, P. J., Schrautemeier, A. C., Holley, K. F., Gaige, C. J., Krieger, J. M., Hagele, A. M., Gutierrez, K. A., Mumford, P. W., & Kerksick, C. M. (2026) · Nutrition Journal · doi:10.1186/s12937-026-01349-z
Lei, Y., Xu, Y.-B., Yan, Y.-T., Zhang, J.-R., Zhang, T.-Y., Huang, J.-J., Huang, Y.-L., Zhong, J.-Y., Wang, X.-L., Zhang, K., et al. (2026) · Microbiome · doi:10.1186/s40168-026-02464-z
BAIBA attenuates pulmonary fibrosis by modulating the iron/ROS–mitochondrion–apoptosis cascade
Du, C., Wang, J., Wang, X., Tan, K., Wang, B., Chen, J., Luo, B., Xiong, Z., Zhang, Z., Liu, S., et al. (2026) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2026.07.029
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Jin, L., Lin, Y., Zheng, Y., Wang, A., Liao, P., Luo, Y., Sui, Z., Ni, X., Zhang, J., Shen, Q., et al. (2026) · Chinese Medical Journal · doi:10.1097/cm9.0000000000004200
Fan, H., Zhai, C., He, C., Shen, L., Pan, H. Y., & Zheng, W. (2026) · Reviews in Cardiovascular Medicine · doi:10.31083/rcm50762
Bhutani, A., Patankar, N., Parti, A., Pakhale, K., Sanghavi, A., & Basu, D. (2026) · Cureus · doi:10.7759/cureus.117275
Exerkines During Pregnancy: Linking Maternal Exercise with Cardiometabolic Health—A Narrative Review
Kokić, I. Š., Znika, M., Brumnić, V., Jelica, S., & Kokić, T. (2026) · Medical Sciences · doi:10.3390/medsci14060630
Metadata
- Authors
- Jung, T. W., Hwang, H.-J., Hong, H. C., Yoo, H. J., Baik, S. H., & Choi, K. M.
- Affiliations
- Korea University Guro Hospital (KR)
- Corresponding author
- Choi, Kyung Mook
- Venue
- Diabetologia
- Published
- 2015-06-24
- Volume
- 58
- Issue
- 9
- Pages
- 2096-2105
- ISSN
- 0012-186X (ISSN-L)
- 1432-0428
- OpenAlex
- W2163244012
- Cited by
- 145
- References
- 35
- Citations by year
- 2026: 14 · 2025: 12 · 2024: 21 · 2023: 22 · 2022: 13 · 2021: 14 · 2020: 11 · 2019: 14 · 2018: 8 · 2017: 9 · 2016: 7
- FWCI
- 3.47
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Diabetologia (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Peroxisome Proliferator-Activated Receptors
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolism, Diabetes, and Cancer
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Adipokines, Inflammation, and Metabolic Diseases
- Keywords
- beta-aminoisobutyric acid, insulin resistance, inflammation, AMPK, PPARδ, palmitate, high-fat diet, skeletal muscle, fatty acid oxidation, NF-κB, compound C, carnitine palmitoyltransferase 1, acyl-CoA oxidase, fatty acid binding protein 3, glucose tolerance, hyperlipidemia
- MeSH terms
- Aminoisobutyric Acids, Animals, Carnitine O-Palmitoyltransferase, Diabetes Mellitus, Fatty Acids, Gene Expression Regulation, Glucose Tolerance Test, Inflammation, Insulin, Insulin Resistance, Male, Mice, Inbred C57BL, Oxygen, Palmitates, Signal Transduction, NF-kappa B, Receptors, Cytoplasmic and Nuclear, Muscle Fibers, Skeletal, Active Transport, Cell Nucleus, RNA, Small Interfering, Mice, AMP-Activated Protein Kinases, Diet, High-Fat
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