Low-calorie sweeteners augment tissue-specific insulin sensitivity in a large animal model of obesity

Abstract

Purposes

Whether low-calorie sweeteners (LCS), such as sucralose and acesulfame K, can alter glucose metabolism is uncertain, particularly given the inconsistent observations relating to insulin resistance in recent human trials. We hypothesized that these discrepancies are accounted for by the surrogate tools used to evaluate insulin resistance and that PET 18FDG, given its capacity to quantify insulin sensitivity in individual organs, would be more sensitive in identifying changes in glucose metabolism. Accordingly, we performed a comprehensive evaluation of the effects of LCS on whole-body and organ-specific glucose uptake and insulin sensitivity in a large animal model of morbid obesity.

Methods

Twenty mini-pigs with morbid obesity were fed an obesogenic diet enriched with LCS (sucralose 1 mg/kg/day and acesulfame K 0.5 mg/kg/day, LCS diet group), or without LCS (control group), for 3 months. Glucose uptake and insulin sensitivity were determined for the duodenum, liver, skeletal muscle, adipose tissue and brain using dynamic PET 18FDG scanning together with direct measurement of arterial input function. Body composition was also measured using CT imaging and energy metabolism quantified with indirect calorimetry.

Results

The LCS diet increased subcutaneous abdominal fat by ≈ 20% without causing weight gain, and reduced insulin clearance by ≈ 40%, while whole-body glucose uptake and insulin sensitivity were unchanged. In contrast, glucose uptake in the duodenum, liver and brain increased by 57, 66 and 29% relative to the control diet group (P < 0.05 for all), while insulin sensitivity increased by 53, 55 and 28% (P < 0.05 for all), respectively. In the brain, glucose uptake increased significantly only in the frontal cortex, associated with improved metabolic connectivity towards the hippocampus and the amygdala.

Conclusions

In miniature pigs, the combination of sucralose and acesulfame K is biologically active. While not affecting whole-body insulin resistance, it increases insulin sensitivity and glucose uptake in specific tissues, mimicking the effects of obesity in the adipose tissue and in the brain.

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Abbreviations

LCS:

Low-calorie sweeteners

18FDG:

18Fluorodeoxyglucose

PET-CT:

Positron emission tomography coupled with computed tomography

MRglu:

Metabolic rate for glucose utilization

ROI:

Region of interest

VOI:

Volume of interest

References

  1. 1.

    Pepino MY, Tiemann CD, Patterson BW, Wice BM, Klein S. Sucralose affects glycemic and hormonal responses to an oral glucose load. Diabetes Care. 2013;36:2530–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. 2.

    Suez J, Korem T, Zeevi D, Zilberman-Schapira G, Thaiss CA, Maza O, et al. Artificial sweeteners induce glucose intolerance by altering the gut microbiota. Nature. 2014;514:181–6.

    Article  CAS  PubMed  Google Scholar 

  3. 3.

    Suez J, Korem T, Zilberman-Schapira G, Segal E, Elinav E. Non-caloric artificial sweeteners and the microbiome: findings and challenges. Gut Microbes. 2015;6:149–55.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Lertrit A, Srimachai S, Saetung S, Chanprasertyothin S, Chailurkit L-O, Areevut C, et al. Effects of sucralose on insulin and glucagon-like peptide-1 secretion in healthy subjects: A randomized, double-blind, placebo-controlled trial. Nutrition. 2018;55-56:140–5.

    Article  CAS  Google Scholar 

  5. 5.

    Romo-Romo A, Aguilar-Salinas CA, Brito-Córdova GX, Gómez-Díaz RA, Almeda-Valdes P. Sucralose decreases insulin sensitivity in healthy subjects: a randomized controlled trial. Am J Clin Nutr. 2018;108:485–91.

    Article  PubMed  Google Scholar 

  6. 6.

    Bonnet F, Tavenard A, Esvan M, Laviolle B, Viltard M, Lepicard EM, et al. Consumption of a Carbonated Beverage with High-Intensity Sweeteners Has No Effect on Insulin Sensitivity and Secretion in Nondiabetic Adults. J Nutr. 2018;148:1293–9.

    Article  PubMed  Google Scholar 

  7. 7.

    Hess EL, Myers EA, Swithers SE, Hedrick VE. Associations Between Nonnutritive Sweetener Intake and Metabolic Syndrome in Adults. J Am Coll Nutr. 2018:1–7.

  8. 8.

    Liang Y, Steinbach G, Maier V, Pfeiffer EF. The effect of artificial sweetener on insulin secretion. 1. The effect of acesulfame K on insulin secretion in the rat (studies in vivo). Horm Metab Res. 1987;19:233–8.

    Article  CAS  PubMed  Google Scholar 

  9. 9.

    Cong WN, Wang R, Cai H, Daimon CM, Scheibye-Knudsen M, Bohr VA, et al. Long-term artificial sweetener acesulfame potassium treatment alters neurometabolic functions in C57BL/6J mice. PLoS One. 2013;8:e70257.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Malaisse WJ, Vanonderbergen A, Louchami K, Jijakli H, Malaisse-Lagae F. Effects of artificial sweeteners on insulin release and cationic fluxes in rat pancreatic islets. Cell Signal. 1998;10:727–33.

    Article  CAS  PubMed  Google Scholar 

  11. 11.

    Simon BR, Parlee SD, Learman BS, Mori H, Scheller EL, Cawthorn WP, et al. Artificial sweeteners stimulate adipogenesis and suppress lipolysis independently of sweet taste receptors. J Biol Chem. 2013;288:32475–89.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Zheng Y, Sarr MG. Effect of the artificial sweetener, acesulfame potassium, a sweet taste receptor agonist, on glucose uptake in small intestinal cell lines. J Gastrointest Surg. 2013;17:153–8 discussion p. 158.

    Article  PubMed  Google Scholar 

  13. 13.

    Liang Y, Maier V, Steinbach G, Lalić L, Pfeiffer EF. The effect of artificial sweetener on insulin secretion. II. Stimulation of insulin release from isolated rat islets by Acesulfame K (in vitro experiments). Horm Metab Res. 1987;19:285–9.

    Article  CAS  PubMed  Google Scholar 

  14. 14.

    Nakagawa Y, Nagasawa M, Yamada S, Hara A, Mogami H, Nikolaev VO, et al. Sweet taste receptor expressed in pancreatic β-cells activates the calcium and cyclic AMP signaling systems and stimulates insulin secretion. PLoS One. 2009;4:e5106.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Mace OJ, Affleck J, Patel N, Kellett GL. Sweet taste receptors in rat small intestine stimulate glucose absorption through apical GLUT2. J Physiol. 2007;582:379–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Moran AW, Al-Rammahi MA, Arora DK, Batchelor DJ, Coulter EA, Daly K, et al. Expression of Na+/glucose co-transporter 1 (SGLT1) is enhanced by supplementation of the diet of weaning piglets with artificial sweeteners. Br J Nutr. 2010;104:637–46.

    Article  CAS  PubMed  Google Scholar 

  17. 17.

    Smith K, Karimian-Azari E, LaMoia TE, Hussain T, Vargova V, Karolyi K, et al. T1R2 receptor-mediated glucose sensing in the upper intestine potentiates glucose absorption through activation of local regulatory pathways. Mol Metab. 2018.

  18. 18.

    Burke MV, Small DM. Physiological mechanisms by which non-nutritive sweeteners may impact body weight and metabolism. Physiol Behav. 2015;152:381–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. 19.

    Honka M-J, Latva-Rasku A, Bucci M, Virtanen KA, Hannukainen JC, Kalliokoski KK, et al. Insulin-stimulated glucose uptake in skeletal muscle, adipose tissue and liver: a positron emission tomography study. Eur J Endocrinol. 2018;178:523–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. 20.

    Goodpaster BH, Bertoldo A, Ng JM, Azuma K, Pencek RR, Kelley C, et al. Interactions among glucose delivery, transport, and phosphorylation that underlie skeletal muscle insulin resistance in obesity and type 2 Diabetes: studies with dynamic PET imaging. Diabetes. 2014;63:1058–68.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. 21.

    Swithers SE. Artificial sweeteners produce the counterintuitive effect of inducing metabolic derangements. Trends Endocrinol Metab. 2013;24:431–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Swithers SE, Laboy AF, Clark K, Cooper S, Davidson TL. Experience with the high-intensity sweetener saccharin impairs glucose homeostasis and GLP-1 release in rats. Behav Brain Res. 2012;233:1–14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Collison KS, Makhoul NJ, Zaidi MZ, Saleh SM, Andres B, Inglis A, et al. Gender dimorphism in aspartame-induced impairment of spatial cognition and insulin sensitivity. PLoS One. 2012;7:e31570.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Lammertsma AA. Forward to the Past: The Case for Quantitative PET Imaging. J Nucl Med. 2017;58:1019–24.

    Article  CAS  Google Scholar 

  25. 25.

    Malbert C-H, Picq C, Divoux J-L, Henry C, Horowitz M. Obesity-associated alterations in glucose metabolism are reversed by chronic bilateral stimulation of the abdominal vagus nerve. Diabetes. 2017;66:848–57.

    Article  CAS  PubMed  Google Scholar 

  26. 26.

    Sylvetsky AC, Welsh JA, Brown RJ, Vos MB. Low-calorie sweetener consumption is increasing in the United States. Am J Clin Nutr. 2012;96:640–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Bahri S, Horowitz M, Malbert CH. Inward Glucose Transfer Accounts for Insulin-Dependent Increase in Brain Glucose Metabolism Associated with Diet-Induced Obesity. Obesity (Silver Spring). 2018.

  28. 28.

    Boellaard R. Standards for PET Image Acquisition and Quantitative Data Analysis. J Nucl Med. 2009;50:11S–20S.

    Article  CAS  PubMed  Google Scholar 

  29. 29.

    Ilback N-G, Alzin M, Jahrl S, Enghardt-Barbieri H, Busk L. Estimated intake of the artificial sweeteners acesulfame-K, aspartame, cyclamate and saccharin in a group of Swedish diabetics. Food Addit Contam. 2003;20:115–26.

    Google Scholar 

  30. 30.

    Val-Laillet D, Blat S, Louveau I, Malbert CH. A computed tomography scan application to evaluate adiposity in a minipig model of human obesity. Br J Nutr. 2010;104:1719–28.

    Article  CAS  PubMed  Google Scholar 

  31. 31.

    Malbert C-H. AniMate-An open source software for absolute PET quantification. Annual Congress of the European Association of Nuclear Medicine. 2016:43.

  32. 32.

    Iozzo P, Gastaldelli A, Järvisalo MJ, Kiss J, Borra R, Buzzigoli E, et al. 18F-FDG assessment of glucose disposal and production rates during fasting and insulin stimulation: a validation study. J Nucl Med. 2006;47:1016–22.

    CAS  PubMed  Google Scholar 

  33. 33.

    Rehal MS, Fiskaare E, Tjäder I, Norberg Å, Rooyackers O, Wernerman J. Measuring energy expenditure in the intensive care unit: a comparison of indirect calorimetry by E-sCOVX and Quark RMR with Deltatrac II in mechanically ventilated critically ill patients. Crit Care. 2016;20:54.

    Article  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Golay A, DeFronzo RA, Ferrannini E, Simonson DC, Thorin D, Acheson K, et al. Oxidative and non-oxidative glucose metabolism in non-obese type 2 (non-insulin-dependent) diabetic patients. Diabetologia. 1988;31:585–91.

    Article  CAS  PubMed  Google Scholar 

  35. 35.

    Munk OL, Keiding S, Bass L. A method to estimate dispersion in sampling catheters and to calculate dispersion-free blood time-activity curves. Med Phys. 2008;35:3471–81.

    Article  PubMed  PubMed Central  Google Scholar 

  36. 36.

    Yushkevich PA, Piven J, Hazlett HC, Smith RG, Ho S, Gee JC, et al. User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage. 2006;31:1116–28.

    Article  PubMed  PubMed Central  Google Scholar 

  37. 37.

    Saikali S, Meurice P, Sauleau P, Eliat PA, Bellaud P, Randuineau G, et al. A three-dimensional digital segmented and deformable brain atlas of the domestic pig. J Neurosci Methods. 2010;192:102–9.

    Article  PubMed  Google Scholar 

  38. 38.

    Poulsen PH, Smith DF, Ostergaard L, Danielsen EH, Gee A, Hansen SB, et al. In vivo estimation of cerebral blood flow, oxygen consumption and glucose metabolism in the pig by [15O]water injection, [15O]oxygen inhalation and dual injections of [18F]fluorodeoxyglucose. J Neurosci Methods. 1997;77:199–209.

    Article  CAS  PubMed  Google Scholar 

  39. 39.

    Iozzo P, Jarvisalo MJ, Kiss J, Borra R, Naum GA, Viljanen A, et al. Quantification of liver glucose metabolism by positron emission tomography: validation study in pigs. Gastroenterology. 2007;132:531–42.

    Article  CAS  PubMed  Google Scholar 

  40. 40.

    Honka H, Mäkinen J, Hannukainen JC, Tarkia M, Oikonen V, Teräs M, et al. Validation of [18F]fluorodeoxyglucose and positron emission tomography (PET) for the measurement of intestinal metabolism in pigs, and evidence of intestinal insulin resistance in patients with morbid obesity. Diabetologia. 2013;56:893–900.

    Article  CAS  PubMed  Google Scholar 

  41. 41.

    Virtanen KA, Peltoniemi P, Marjamäki P, Asola M, Strindberg L, Parkkola R, et al. Human adipose tissue glucose uptake determined using [(18)F]-fluoro-deoxy-glucose ([(18)F]FDG) and PET in combination with microdialysis. Diabetologia. 2001;44:2171–9.

    Article  CAS  PubMed  Google Scholar 

  42. 42.

    Peltoniemi P, Lönnroth P, Laine H, Oikonen V, Tolvanen T, Grönroos T, et al. Lumped constant for [(18)F]fluorodeoxyglucose in skeletal muscles of obese and nonobese humans. Am J Physiol Endocrinol Metab. 2000;279:E1122–30.

    Article  CAS  PubMed  Google Scholar 

  43. 43.

    Patlak CS, Blasberg RG, Fenstermacher JD. Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data. J Cereb Blood Flow Metab. 1983;3:1–7.

    Article  CAS  PubMed  Google Scholar 

  44. 44.

    Hong YT, Fryer TD. Kinetic modelling using basis functions derived from two-tissue compartmental models with a plasma input function: general principle and application to [18F]fluorodeoxyglucose positron emission tomography. Neuroimage. 2010;51:164–72.

    Article  PubMed  Google Scholar 

  45. 45.

    Yakushev I, Drzezga A, Habeck C. Metabolic connectivity. Curr Opin Neurol. 2017;30:677–85.

    Article  PubMed  Google Scholar 

  46. 46.

    Xia M, Wang J, He Y. BrainNet Viewer: a network visualization tool for human brain connectomics. PLoS One. 2013;8:e68910.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. 47.

    Hammers A, Allom R, Koepp MJ, Free SL, Myers R, Lemieux L, et al. Three-dimensional maximum probability atlas of the human brain, with particular reference to the temporal lobe. Hum Brain Mapp. 2003;19:224–47.

    Article  Google Scholar 

  48. 48.

    Pepino MY. Metabolic effects of non-nutritive sweeteners. Physiol Behav. 2015;152:450–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. 49.

    Maersk M, Belza A, Stødkilde-Jørgensen H, Ringgaard S, Chabanova E, Thomsen H, et al. Sucrose-sweetened beverages increase fat storage in the liver, muscle, and visceral fat depot: a 6-mo randomized intervention study. Am J Clin Nutr. 2012;95:283–9.

    Article  CAS  PubMed  Google Scholar 

  50. 50.

    Mäkinen J, Hannukainen JC, Karmi A, Immonen HM, Soinio M, Nelimarkka L, et al. Obesity-associated intestinal insulin resistance is ameliorated after bariatric surgery. Diabetologia. 2015;58:1055–62.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. 51.

    Hare TA, Camerer CF, Rangel A. Self-control in decision-making involves modulation of the vmPFC valuation system. Science. 2009;324:646–8.

    Article  CAS  Google Scholar 

  52. 52.

    Weygandt M, Mai K, Dommes E, Ritter K, Leupelt V, Spranger J, et al. Impulse control in the dorsolateral prefrontal cortex counteracts post-diet weight regain in obesity. Neuroimage. 2015;109:318–27.

    Article  PubMed  Google Scholar 

  53. 53.

    Lee SH, Zabolotny JM, Huang H, Lee H, Kim YB. Insulin in the nervous system and the mind: Functions in metabolism, memory, and mood. Mol Metab. 2016;5:589–601.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. 54.

    Cheke LG, Bonnici HM, Clayton NS, Simons JS. Obesity and insulin resistance are associated with reduced activity in core memory regions of the brain. Neuropsychologia. 2017;96:137–49.

    Article  PubMed  PubMed Central  Google Scholar 

  55. 55.

    Tuulari JJ, Karlsson HK, Hirvonen J, Hannukainen JC, Bucci M, Helmiö M, et al. Weight loss after bariatric surgery reverses insulin-induced increases in brain glucose metabolism of the morbidly obese. Diabetes. 2013;62:2747–51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. 56.

    Hirvonen J, Virtanen KA, Nummenmaa L, Hannukainen JC, Honka MJ, Bucci M, et al. Effects of insulin on brain glucose metabolism in impaired glucose tolerance. Diabetes. 2011;60:443–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. 57.

    Virtanen KA, Lönnroth P, Parkkola R, Peltoniemi P, Asola M, Viljanen T, et al. Glucose uptake and perfusion in subcutaneous and visceral adipose tissue during insulin stimulation in nonobese and obese humans. J Clin Endocrinol Metab. 2002;87:3902–10.

    Article  CAS  PubMed  Google Scholar 

  58. 58.

    Iozzo P. Metabolic imaging in obesity: underlying mechanisms and consequences in the whole body. Ann N Y Acad Sci. 2015;1353:21–40.

    Article  PubMed  Google Scholar 

  59. 59.

    Viner M, Mercier G, Hao F, Malladi A, Subramaniam RM. Liver SULmean at FDG PET/CT: interreader agreement and impact of placement of volume of interest. Radiology. 2013;267:596–601.

    Article  PubMed  Google Scholar 

  60. 60.

    Boellaard R, Delgado-Bolton R, Oyen WJ, Giammarile F, Tatsch K, Eschner W, et al. European Association of Nuclear Medicine EANM: FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0. Eur J Nucl Med Mol Imaging. 2015;42:328–54.

    Article  CAS  Google Scholar 

  61. 61.

    Vállez Garcia D, Casteels C, Schwarz AJ, Dierckx RA, Koole M, Doorduin J. A standardized method for the construction of tracer specific PET and SPECT rat brain templates: validation and implementation of a toolbox. PLoS One. 2015;10:e0122363.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The authors thank staff of the UEPR unit for animal care, Mickael Genissel, Julien Georges, Alain Chauvin, Francis Le Gouevec, and Vincent Piedvache. We also thank Paula Aneb and Emilie Lebrun for their involvement in running the Aniscan imaging, and Raphael Comte (Pegase unit) for insulin measurements. The authors also thank Eric Bobillier for the development of the in-line radiation detector and robotic feeders.

Funding

The study was conducted within the Aniscan Imaging Center (Aniscan, INRA), which is supported by BPIFrance within the Investments for the Future Program.

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Contributions

C-H.M. planned the experiments, conducted the studies, analyzed the data and wrote the manuscript. R.Y. and M.H. were involved in planning the experiments, writing the manuscript and interpretation of the data. C-H.M. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Corresponding author

Correspondence to Charles-Henri Malbert.

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C-H. Malbert declares that he has no conflict of interest. M. Horowitz declares that he has no conflict of interest. R. Young declares that he has no conflict of interest.

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All applicable international, national and/or institutional guidelines for the care and use of animals were followed.

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Malbert, CH., Horowitz, M. & Young, R.L. Low-calorie sweeteners augment tissue-specific insulin sensitivity in a large animal model of obesity. Eur J Nucl Med Mol Imaging 46, 2380–2391 (2019). https://doi.org/10.1007/s00259-019-04430-4

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Keywords

  • Brain connectivity
  • Compartmental analysis
  • Glucose uptake
  • Insulin sensitivity
  • Miniature pig
  • Statistical parameter mapping
  • Sweeteners