Metabolomic Profiling of Adipose Tissue in Type 2 Diabetes: Associations with Obesity and Insulin Resistance
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Participants
2.2. Study Procedures
2.3. Glucose Uptake in Isolated Adipocytes, Ex Vivo
2.4. Adipose Tissue Metabolomics
2.5. Statistical and Enrichment Analyses
3. Results
3.1. Overview of the Analysed Metabolite Panel
3.2. Metabolic Alterations in Adipose Tissue in Subjects with and without T2D and Obesity
3.3. Comparison of Adipose Tissue Metabolites between Subjects with and without T2D
3.4. Correlation Analyses between Metabolites in Adipose Tissue and Clinical Characteristics
3.5. Associations between Adipose Tissue Metabolites and Adipocyte Size
3.6. Associations between Adipose Tissue Metabolites and Adipocyte Glucose Uptake
4. Discussion
4.1. Metabolomic Distinctions in Adipose Tissue between Subjects with and without T2D
4.2. Associations with Clinical Parameters
4.3. Adipocyte Size and Glucose Uptake in Relation to Metabolomics
4.4. Future Studies
4.5. Limitations
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Diabetes. Available online: https://www.who.int/news-room/fact-sheets/detail/diabetes (accessed on 20 June 2024).
- Boersma, G.J.; Johansson, E.; Pereira, M.J.; Heurling, K.; Skrtic, S.; Lau, J.; Katsogiannos, P.; Panagiotou, G.; Lubberink, M.; Kullberg, J.; et al. Altered Glucose Uptake in Muscle, Visceral Adipose Tissue, and Brain Predict Whole-Body Insulin Resistance and May Contribute to the Development of Type 2 Diabetes: A Combined PET/MR Study. Horm. Metab. Res. 2018, 50, e10. [Google Scholar]
- Kahn, S.E.; Hull, R.L.; Utzschneider, K.M. Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature 2006, 444, 840–846. [Google Scholar] [CrossRef] [PubMed]
- Pereira, M.J.; Skrtic, S.; Katsogiannos, P.; Abrahamsson, N.; Sidibeh, C.O.; Dahgam, S.; Mansson, M.; Riserus, U.; Kullberg, J.; Eriksson, J.W. Impaired adipose tissue lipid storage, but not altered lipolysis, contributes to elevated levels of NEFA in type 2 diabetes. Degree of hyperglycemia and adiposity are important factors. Metabolism 2016, 65, 1768–1780. [Google Scholar] [CrossRef] [PubMed]
- Patti, G.J.; Yanes, O.; Siuzdak, G. Innovation: Metabolomics: The apogee of the omics trilogy. Nat. Rev. Mol. Cell Biol. 2012, 13, 263–269. [Google Scholar] [CrossRef] [PubMed]
- Ahola-Olli, A.V.; Mustelin, L.; Kalimeri, M.; Kettunen, J.; Jokelainen, J.; Auvinen, J.; Puukka, K.; Havulinna, A.S.; Lehtimäki, T.; Kähönen, M.; et al. Circulating metabolites and the risk of type 2 diabetes: A prospective study of 11,896 young adults from four Finnish cohorts. Diabetologia 2019, 62, 2298–2309. [Google Scholar] [CrossRef] [PubMed]
- Wildberg, C.; Masuch, A.; Budde, K.; Kastenmüller, G.; Artati, A.; Rathmann, W.; Adamski, J.; Kocher, T.; Völzke, H.; Nauck, M.; et al. Plasma Metabolomics to Identify and Stratify Patients with Impaired Glucose Tolerance. J. Clin. Endocrinol. Metab. 2019, 104, 6357–6370. [Google Scholar] [CrossRef] [PubMed]
- Fanni, G.; Eriksson, J.W.; Pereira, M.J. Several Metabolite Families Display Inflexibility during Glucose Challenge in Patients with Type 2 Diabetes: An Untargeted Metabolomics Study. Metabolites 2023, 13, 131. [Google Scholar] [CrossRef] [PubMed]
- Diamanti, K.; Cavalli, M.; Pan, G.; Pereira, M.J.; Kumar, C.; Skrtic, S.; Grabherr, M.; Riserus, U.; Eriksson, J.W.; Komorowski, J.; et al. Intra- and inter-individual metabolic profiling highlights carnitine and lysophosphatidylcholine pathways as key molecular defects in type 2 diabetes. Sci. Rep. 2019, 9, 9653. [Google Scholar] [CrossRef]
- Diamanti, K.; Visvanathar, R.; Pereira, M.J.; Cavalli, M.; Pan, G.; Kumar, C.; Skrtic, S.; Riserus, U.; Eriksson, J.W.; Kullberg, J.; et al. Integration of whole-body [(18)F]FDG PET/MRI with non-targeted metabolomics can provide new insights on tissue-specific insulin resistance in type 2 diabetes. Sci. Rep. 2020, 10, 8343. [Google Scholar] [CrossRef]
- Vizioli, C.; Jaime-Lara, R.B.; Franks, A.T.; Ortiz, R.; Joseph, P.V. Untargeted Metabolomic Approach Shows No Differences in Subcutaneous Adipose Tissue of Diabetic and Non-Diabetic Subjects Undergoing Bariatric Surgery: An Exploratory Study. Biol. Res. Nurs. 2021, 23, 109–118. [Google Scholar] [CrossRef]
- Morais, T.; Seabra, A.L.; Patrício, B.G.; Guimarães, M.; Nora, M.; Oliveira, P.F.; Alves, M.G.; Monteiro, M.P. Visceral Adipose Tissue Displays Unique Metabolomic Fingerprints in Obesity, Pre-Diabetes and Type 2 Diabetes. Int. J. Mol. Sci. 2021, 22, 5695. [Google Scholar] [CrossRef] [PubMed]
- Wei, R.; Wang, J.; Su, M.; Jia, E.; Chen, S.; Chen, T.; Ni, Y. Missing Value Imputation Approach for Mass Spectrometry-Based Metabolomics Data. Sci. Rep. 2018, 8, 663. [Google Scholar] [CrossRef] [PubMed]
- A Grammar of Data Manipulation. Available online: https://dplyr.tidyverse.org/ (accessed on 25 June 2024).
- R: The R Project for Statistical Computing. Available online: https://www.r-project.org/ (accessed on 16 April 2024).
- Pang, Z.; Chong, J.; Li, S.; Xia, J. MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics. Metabolites 2020, 10, 186. [Google Scholar] [CrossRef] [PubMed]
- Goeman, J.J.; van de Geer, S.A.; de Kort, F.; van Houwelingen, H.C. A global test for groups of genes: Testing association with a clinical outcome. Bioinformatics 2004, 20, 93–99. [Google Scholar] [CrossRef] [PubMed]
- Braisted, J.; Patt, A.; Tindall, C.; Sheils, T.; Neyra, J.; Spencer, K.; Eicher, T.; Mathé, E.A. RaMP-DB 2.0: A renovated knowledgebase for deriving biological and chemical insight from metabolites, proteins, and genes. Bioinformatics 2023, 39, btac726. [Google Scholar] [CrossRef] [PubMed]
- Fiehn, O.; Garvey, W.T.; Newman, J.W.; Lok, K.H.; Hoppel, C.L.; Adams, S.H. Plasma metabolomic profiles reflective of glucose homeostasis in non-diabetic and type 2 diabetic obese African-American women. PLoS ONE 2010, 5, e15234. [Google Scholar] [CrossRef] [PubMed]
- Wopereis, S.; Rubingh, C.M.; van Erk, M.J.; Verheij, E.R.; van Vliet, T.; Cnubben, N.H.; Smilde, A.K.; van der Greef, J.; van Ommen, B.; Hendriks, H.F. Metabolic profiling of the response to an oral glucose tolerance test detects subtle metabolic changes. PLoS ONE 2009, 4, e4525. [Google Scholar] [CrossRef] [PubMed]
- Vanweert, F.; Schrauwen, P.; Phielix, E. Role of branched-chain amino acid metabolism in the pathogenesis of obesity and type 2 diabetes-related metabolic disturbances BCAA metabolism in type 2 diabetes. Nutr. Diabetes 2022, 12, 35. [Google Scholar] [CrossRef] [PubMed]
- Gonzalez-Franquesa, A.; Burkart, A.M.; Isganaitis, E.; Patti, M.E. What Have Metabolomics Approaches Taught Us about Type 2 Diabetes? Curr. Diab. Rep. 2016, 16, 74. [Google Scholar] [CrossRef]
- Kučera, J.; Spáčil, Z.; Friedecký, D.; Novák, J.; Pekař, M.; Bienertová-Vašků, J. Human White Adipose Tissue Metabolome: Current Perspective. Obesity 2018, 26, 1870–1878. [Google Scholar] [CrossRef]
- Newgard, C.B. Interplay between lipids and branched-chain amino acids in development of insulin resistance. Cell Metab. 2012, 15, 606–614. [Google Scholar] [CrossRef] [PubMed]
- Shahisavandi, M.; Wang, K.; Ghanbari, M.; Ahmadizar, F. Exploring Metabolomic Patterns in Type 2 Diabetes Mellitus and Response to Glucose-Lowering Medications—Review. Genes 2023, 14, 1464. [Google Scholar] [CrossRef] [PubMed]
- Cuomo, P.; Capparelli, R.; Iannelli, A.; Iannelli, D. Role of Branched-Chain Amino Acid Metabolism in Type 2 Diabetes, Obesity, Cardiovascular Disease and Non-Alcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2022, 23, 4325. [Google Scholar] [CrossRef] [PubMed]
- Piro, M.C.; Tesauro, M.; Lena, A.M.; Gentileschi, P.; Sica, G.; Rodia, G.; Annicchiarico-Petruzzelli, M.; Rovella, V.; Cardillo, C.; Melino, G.; et al. Free-amino acid metabolic profiling of visceral adipose tissue from obese subjects. Amino Acids 2020, 52, 1125–1137. [Google Scholar] [CrossRef] [PubMed]
- Sharma, N.K.; Das, S.K.; Mondal, A.K.; Hackney, O.G.; Chu, W.S.; Kern, P.A.; Rasouli, N.; Spencer, H.J.; Yao-Borengasser, A.; Elbein, S.C. Endoplasmic reticulum stress markers are associated with obesity in nondiabetic subjects. J. Clin. Endocrinol. Metab. 2008, 93, 4532–4541. [Google Scholar] [CrossRef] [PubMed]
- Liu, K.; Jin, X.; Zhang, X.; Lian, H.; Ye, J. The mechanisms of nucleotide actions in insulin resistance. J. Genet. Genom. 2022, 49, 299–307. [Google Scholar] [CrossRef] [PubMed]
- t Hart, L.M.; Vogelzangs, N.; Mook-Kanamori, D.O.; Brahimaj, A.; Nano, J.; van der Heijden, A.; Willems van Dijk, K.; Slieker, R.C.; Steyerberg, E.W.; Ikram, M.A.; et al. Blood Metabolomic Measures Associate with Present and Future Glycemic Control in Type 2 Diabetes. J. Clin. Endocrinol. Metab. 2018, 103, 4569–4579. [Google Scholar] [CrossRef] [PubMed]
- Lackey, D.E.; Lynch, C.J.; Olson, K.C.; Mostaedi, R.; Ali, M.; Smith, W.H.; Karpe, F.; Humphreys, S.; Bedinger, D.H.; Dunn, T.N.; et al. Regulation of adipose branched-chain amino acid catabolism enzyme expression and cross-adipose amino acid flux in human obesity. Am. J. Physiol. Endocrinol. Metab. 2013, 304, E1175–E1187. [Google Scholar] [CrossRef] [PubMed]
- Kim, J.I.; Huh, J.Y.; Sohn, J.H.; Choe, S.S.; Lee, Y.S.; Lim, C.Y.; Jo, A.; Park, S.B.; Han, W.; Kim, J.B. Lipid-overloaded enlarged adipocytes provoke insulin resistance independent of inflammation. Mol. Cell. Biol. 2015, 35, 1686–1699. [Google Scholar] [CrossRef]
- Sarabhai, T.; Koliaki, C.; Mastrototaro, L.; Kahl, S.; Pesta, D.; Apostolopoulou, M.; Wolkersdorfer, M.; Bönner, A.C.; Bobrov, P.; Markgraf, D.F.; et al. Dietary palmitate and oleate differently modulate insulin sensitivity in human skeletal muscle. Diabetologia 2022, 65, 301–314. [Google Scholar] [CrossRef]
- Pauls, S.D.; Rodway, L.A.; Winter, T.; Taylor, C.G.; Zahradka, P.; Aukema, H.M. Anti-inflammatory effects of α-linolenic acid in M1-like macrophages are associated with enhanced production of oxylipins from α-linolenic and linoleic acid. J. Nutr. Biochem. 2018, 57, 121–129. [Google Scholar] [CrossRef] [PubMed]
- Crupi, R.; Cuzzocrea, S. Role of EPA in Inflammation: Mechanisms, Effects, and Clinical Relevance. Biomolecules 2022, 12, 242. [Google Scholar] [CrossRef]
- El-Sohemy, A.; Baylin, A.; Ascherio, A.; Kabagambe, E.; Spiegelman, D.; Campos, H. Population-based study of alpha- and gamma-tocopherol in plasma and adipose tissue as biomarkers of intake in Costa Rican adults. Am. J. Clin. Nutr. 2001, 74, 356–363. [Google Scholar] [CrossRef]
- Green, C.R.; Wallace, M.; Divakaruni, A.S.; Phillips, S.A.; Murphy, A.N.; Ciaraldi, T.P.; Metallo, C.M. Branched-chain amino acid catabolism fuels adipocyte differentiation and lipogenesis. Nat. Chem. Biol. 2016, 12, 15–21. [Google Scholar] [CrossRef]
- Ma, Q.-X.; Zhu, W.-Y.; Lu, X.-C.; Jiang, D.; Xu, F.; Li, J.-T.; Zhang, L.; Wu, Y.-L.; Chen, Z.-J.; Yin, M.; et al. BCAA–BCKA axis regulates WAT browning through acetylation of PRDM16. Nat. Metab. 2022, 4, 106–122. [Google Scholar] [CrossRef]
- Magdalon, J.; Festuccia, W.T. Regulation of adiposity by mTORC1. Einstein 2017, 15, 507–511. [Google Scholar] [CrossRef] [PubMed]
- Chang, W.; Hatch, G.M.; Wang, Y.; Yu, F.; Wang, M. The relationship between phospholipids and insulin resistance: From clinical to experimental studies. J. Cell. Mol. Med. 2019, 23, 702–710. [Google Scholar] [CrossRef]
- Palau-Rodriguez, M.; Marco-Ramell, A.; Casas-Agustench, P.; Tulipani, S.; Miñarro, A.; Sanchez-Pla, A.; Murri, M.; Tinahones, F.J.; Andres-Lacueva, C. Visceral Adipose Tissue Phospholipid Signature of Insulin Sensitivity and Obesity. J. Proteome Res. 2021, 20, 2410–2419. [Google Scholar] [CrossRef] [PubMed]
- Solis, M.Y.; Artioli, G.G.; Gualano, B. Potential of Creatine in Glucose Management and Diabetes. Nutrients 2021, 13, 570. [Google Scholar] [CrossRef]
- Stockler-Pinto, M.B.; Saldanha, J.F.; Yi, D.; Mafra, D.; Fouque, D.; Soulage, C.O. The uremic toxin indoxyl sulfate exacerbates reactive oxygen species production and inflammation in 3T3-L1 adipose cells. Free Radic. Res. 2016, 50, 337–344. [Google Scholar] [CrossRef]
Without T2D (n = 20) | T2D (n = 20) | |
---|---|---|
N (women/men) | 10/10 | 10/10 |
Age (years) | 58 ± 11 | 58 ± 9 |
BMI (kg/m2) | 30.8 ± 4.6 | 30.7 ± 4.9 |
WHR | 0.96 ± 0.07 | 0.99 ± 0.05 |
Fasting plasma glucose (mmol/L) | 6.0 ± 0.7 | 8.2 ± 1.5 *** |
HbA1c (mmol/mol) | 37.3 ± 3.7 | 48.8 ± 8.6 *** |
Serum insulin (mIU/L) | 11.5 ± 5.2 | 15.5 ± 7.0 * |
HOMA-IR | 3.08 ± 1.58 | 5.26 ± 2.86 ** |
Matsuda index | 4.04 ± 2.11 | 2.65 ± 1.38 * |
Adipocyte glucose uptake, basal (fL/cell/s) | 37.1 ± 20.7 | 24.1 ± 9.3 * |
Adipocyte glucose uptake, 1000 µU/mL insulin (fL/cell/s) | 72.8 ± 44.8 | 41.2 ± 21.1 * |
Maximal Glucose Uptake (fold change) a | 1.94 ± 0.55 | 1.72 ± 0.51 |
Adipocyte size (µm) | 109 ± 10 | 106 ± 11 |
AUC OGTT glucose (mmol/L × min) | 1416 ± 340 | 2493 ± 522 *** |
AUC OGTT insulin (mIU/L × min) | 10,654 ± 6276 | 8072 ± 3981 |
AUC OGTT FFA (µmol/L × min) | 23,947 ± 5644 | 31,236 ± 8558 ** |
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Mathioudaki, A.; Fanni, G.; Eriksson, J.W.; Pereira, M.J. Metabolomic Profiling of Adipose Tissue in Type 2 Diabetes: Associations with Obesity and Insulin Resistance. Metabolites 2024, 14, 411. https://doi.org/10.3390/metabo14080411
Mathioudaki A, Fanni G, Eriksson JW, Pereira MJ. Metabolomic Profiling of Adipose Tissue in Type 2 Diabetes: Associations with Obesity and Insulin Resistance. Metabolites. 2024; 14(8):411. https://doi.org/10.3390/metabo14080411
Chicago/Turabian StyleMathioudaki, Argyri, Giovanni Fanni, Jan W. Eriksson, and Maria J. Pereira. 2024. "Metabolomic Profiling of Adipose Tissue in Type 2 Diabetes: Associations with Obesity and Insulin Resistance" Metabolites 14, no. 8: 411. https://doi.org/10.3390/metabo14080411