The artificial sweetener erythritol and cardiovascular event risk (original) (raw)

Data availability

There are restrictions to the availability of some of the clinical data generated in the present study (Figs. 1 and 2), because we do not have permission in our informed consent from research subjects to share data outside our institution without their authorization. Where permissible, the datasets generated and/or analyzed during the present studies are available from the corresponding author Stanley L. Hazen (hazens@ccf.org) on request. An answer can be expected within 14 d.

Code availability

Custom R codes used in this manuscript are available at ‘https://doi.org/10.5281/zenodo.6780497’. The BinBase database is accessible using the following link ‘https://bitbucket.org/fiehnlab/binbase/src/master/?’.

References

  1. Abarca-Gómez, L. et al. Worldwide trends in body-mass index, underweight, overweight and obesity from 1975 to 2016: a pooled analysis of 2,416 population-based measurement studies in 128.9 million children, adolescents and adults. Lancet 390, 2627–2642 (2017).
    Article Google Scholar
  2. Sylvetsky, A. C. & Rother, K. I. Trends in the consumption of low-calorie sweeteners. Physiol. Behav. 164, 446–450 (2016).
    Article CAS PubMed PubMed Central Google Scholar
  3. Buerge, I. J., Buser, H. R., Kahle, M., Müller, M. D. & Poiger, T. Ubiquitous occurrence of the artificial sweetener acesulfame in the aquatic environment: an ideal chemical marker of domestic wastewater in groundwater. Environ. Sci. Technol. 43, 4381–4385 (2009).
    Article CAS PubMed Google Scholar
  4. Roberts, A. The safety and regulatory process for low calorie sweeteners in the United States. Physiol. Behav. 164, 439–444 (2016).
    Article CAS PubMed Google Scholar
  5. Mortensen, A. Sweeteners permitted in the European Union: safety aspects. Scand. J. Food Nutr. 50, 104–116 (2006).
    Article Google Scholar
  6. Gardner, C. et al. Nonnutritive sweeteners: current use and health perspectives: a scientific statement from the American Heart Association and the American Diabetes Association. Circulation 126, 509–519 (2012).
    Article PubMed Google Scholar
  7. British Dietetic Association. Policy statement—the use of artificial sweeteners. https://www.bda.uk.com/uploads/assets/11ea5867-96eb-43df-b61f2cbe9673530d/policystatementsweetners.pdf (2016).
  8. Markovic, T. P. et al. The Australian obesity management algorithm: a simple tool to guide the management of obesity in primary care. Obes. Res. Clin. Pract. 16, 353–363 (2022).
    Article PubMed Google Scholar
  9. Ruanpeng, D., Thongprayoon, C., Cheungpasitporn, W. & Harindhanavudhi, T. Sugar and artificially sweetened beverages linked to obesity: a systematic review and meta-analysis. QJM 110, 513–520 (2017).
    Article CAS PubMed Google Scholar
  10. Romo-Romo, A., Aguilar-Salinas, C. A., Brito-Córdova, G. X., Gómez-Díaz, R. A. & Almeda-Valdes, P. Sucralose decreases insulin sensitivity in healthy subjects: a randomized controlled trial. Am. J. Clin. Nutr. 108, 485–491 (2018).
    Article PubMed Google Scholar
  11. Imamura, F. et al. Consumption of sugar sweetened beverages, artificially sweetened beverages and fruit juice and incidence of type 2 diabetes: systematic review, meta-analysis and estimation of population attributable fraction. Br. Med. J. 351, h3576 (2015).
    Article Google Scholar
  12. Mossavar-Rahmani, Y. et al. Artificially sweetened beverages and stroke, coronary heart disease and all-cause mortality in the Women’s Health Initiative. Stroke 50, 555–562 (2019).
    Article PubMed PubMed Central Google Scholar
  13. Malik, V. S. et al. Long-term consumption of sugar-sweetened and artificially sweetened beverages and risk of mortality in US adults. Circulation 139, 2113–2125 (2019).
    Article CAS PubMed PubMed Central Google Scholar
  14. Mullee, A. et al. Association between soft drink consumption and mortality in ten European countries. JAMA Intern. Med. 179, 1479–1490 (2019).
    Article PubMed Google Scholar
  15. Lohner, S., Toews, I. & Meerpohl, J. J. Health outcomes of non-nutritive sweeteners: analysis of the research landscape. Nutr. J. 16, 55 (2017).
    Article PubMed PubMed Central Google Scholar
  16. Mitchell, H. (ed.) Sweeteners and Sugar Alternatives in Food Technology (Blackwell Publishing, 2006).
  17. European Food Safety Authority. Statement in relation to the safety of erythritol (E 968) in light of new data, including a new paediatric study on the gastrointestinal tolerability of erythritol. EFSA J. 8, 1650 (2010).
    Article Google Scholar
  18. Food and Drug Administration. GRAS notice (GRN) No. 789. https://www.fda.gov/media/132946/download (2018).
  19. Bornet, F. R., Blayo, A., Dauchy, F. & Slama, G. Plasma and urine kinetics of erythritol after oral ingestion by healthy humans. Regul. Toxicol. Pharm. 24, S280–S285 (1996).
    Article CAS Google Scholar
  20. Hootman, K. C. et al. Erythritol is a pentose-phosphate pathway metabolite and associated with adiposity gain in young adults. Proc. Natl Acad. Sci. USA 114, 4233–4240 (2017).
    Article Google Scholar
  21. Global erythritol market research report 2020. https://www.360researchreports.com/global-erythritol-market-15041957 (2020).
  22. Yokozawa, T., Kim, H. Y. & Cho, E. J. Erythritol attenuates the diabetic oxidative stress through modulating glucose metabolism and lipid peroxidation in streptozotocin-induced diabetic rats. J. Agric. Food Chem. 50, 5485–5489 (2002).
    Article CAS PubMed Google Scholar
  23. Flint, N. et al. Effects of erythritol on endothelial function in patients with type 2 diabetes mellitus: a pilot study. Acta Diabetol. 51, 513–516 (2014).
    CAS PubMed Google Scholar
  24. Rebholz, C. M. et al. Serum metabolomic profile of incident diabetes. Diabetologia 61, 1046–1054 (2018).
    Article CAS PubMed PubMed Central Google Scholar
  25. Selvin, E. et al. Association of 1,5-anhydroglucitol with cardiovascular disease and mortality. Diabetes 65, 201–208 (2016).
    Article CAS PubMed Google Scholar
  26. Zhu, W. et al. Gut microbial metabolite TMAO enhances platelet hyperreactivity and thrombosis risk. Cell 165, 111–124 (2016).
    Article CAS PubMed PubMed Central Google Scholar
  27. Schlicker, L. et al. Unexpected roles for ADH1 and SORD in catalyzing the final step of erythritol biosynthesis. J. Biol. Chem. 294, 16095–16108 (2019).
    Article CAS PubMed PubMed Central Google Scholar
  28. Regnat, K., Mach, R. L. & Mach-Aigner, A. R. Erythritol as sweetener-wherefrom and whereto? Appl. Microbiol. Biotechnol. 102, 587–595 (2018).
    Article CAS PubMed Google Scholar
  29. Tetzloff, W., Dauchy, F., Medimagh, S., Carr, D. & Bär, A. Tolerance to subchronic, high-dose ingestion of erythritol in human volunteers. Regul. Toxicol. Pharm. 24, S286–S295 (1996).
    Article CAS Google Scholar
  30. Bornet, F. R., Blayo, A., Dauchy, F. & Slama, G. Gastrointestinal response and plasma and urine determinations in human subjects given erythritol. Regul. Toxicol. Pharm. 24, S296–S302 (1996).
    Article CAS Google Scholar
  31. Munro, I. C. et al. Erythritol: an interpretive summary of biochemical, metabolic, toxicological and clinical data. Food Chem. Toxicol. 36, 1139–1174 (1998).
    Article CAS PubMed Google Scholar
  32. Gardener, H. et al. Diet soft drink consumption is associated with an increased risk of vascular events in the Northern Manhattan Study. J. Gen. Intern. Med. 27, 1120–1126 (2012).
    Article PubMed PubMed Central Google Scholar
  33. Narain, A., Kwok, C. S. & Mamas, M. A. Soft drinks and sweetened beverages and the risk of cardiovascular disease and mortality: a systematic review and meta-analysis. Int. J. Clin. Pract. 70, 791–805 (2016).
    Article CAS PubMed Google Scholar
  34. Vyas, A. et al. Diet drink consumption and the risk of cardiovascular events: a report from the Women’s Health Initiative. J. Gen. Intern. Med. 30, 462–468 (2015).
    Article PubMed Google Scholar
  35. Lin, J. & Curhan, G. C. Associations of sugar and artificially sweetened soda with albuminuria and kidney function decline in women. Clin. J. Am. Soc. Nephrol. 6, 160–166 (2011).
    Article CAS PubMed PubMed Central Google Scholar
  36. de Koning, L. et al. Sweetened beverage consumption, incident coronary heart disease and biomarkers of risk in men. Circulation 125, 1735–1741 (2012).
    Article PubMed PubMed Central Google Scholar
  37. de Koning, L., Malik, V. S., Rimm, E. B., Willett, W. C. & Hu, F. B. Sugar-sweetened and artificially sweetened beverage consumption and risk of type 2 diabetes in men. Am. J. Clin. Nutr. 93, 1321–1327 (2011).
    Article PubMed PubMed Central Google Scholar
  38. Suez, J. et al. Personalized microbiome-driven effects of non-nutritive sweeteners on human glucose tolerance. Cell 185, 3307–3328 (2022).
    Article CAS PubMed Google Scholar
  39. Debras, C. et al. Artificial sweeteners and risk of cardiovascular diseases: results from the prospective NutriNet-Santé cohort. Br. Med. J. 378, e071204 (2022).
    Article Google Scholar
  40. Toews, I., Lohner, S., Küllenberg de Gaudry, D., Sommer, H. & Meerpohl, J. J. Association between intake of non-sugar sweeteners and health outcomes: systematic review and meta-analyses of randomised and nonrandomized controlled trials and observational studies. Br. Med. J. 364, k4718 (2019).
    Article Google Scholar
  41. Azad, M. B. et al. Nonnutritive sweeteners and cardiometabolic health: a systematic review and meta-analysis of randomized controlled trials and prospective cohort studies. Can. Med. Assoc. J. 189, 929–939 (2017).
    Article Google Scholar
  42. Miller, P. E. & Perez, V. Low-calorie sweeteners and body weight and composition: a meta-analysis of randomized controlled trials and prospective cohort studies. Am. J. Clin. Nutr. 100, 765–777 (2014).
    Article CAS PubMed PubMed Central Google Scholar
  43. McGlynn, N. D. et al. Association of low- and no-calorie sweetened beverages as a replacement for sugar-sweetened beverages with body weight and cardiometabolic risk: a systematic review and meta-analysis. JAMA Netw. Open 5, e222092 (2022).
    Article PubMed PubMed Central Google Scholar
  44. Sylvetsky, A. C., Blau, J. E. & Rother, K. I. Understanding the metabolic and health effects of low-calorie sweeteners: methodological considerations and implications for future research. Rev. Endocr. Metab. Disord. 17, 187–194 (2016).
    Article CAS PubMed PubMed Central Google Scholar
  45. Wang, Z. et al. Metabolomic pattern predicts incident coronary heart disease. Arterioscler. Thromb. Vasc. Biol. 39, 1475–1482 (2019).
    Article CAS PubMed PubMed Central Google Scholar
  46. Tang, W. H. et al. Intestinal microbial metabolism of phosphatidylcholine and cardiovascular risk. N. Engl. J. Med. 368, 1575–1584 (2013).
    Article CAS PubMed PubMed Central Google Scholar
  47. Wang, Z. et al. Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease. Nature 472, 57–63 (2011).
    Article CAS PubMed PubMed Central Google Scholar
  48. Stevens, L. A. et al. Comparative performance of the CKD Epidemiology Collaboration (CKD-EPI) and the Modification of Diet in Renal Disease (MDRD) study equations for estimating GFR levels above 60 ml min−1/1.73 m2. Am. J. Kidney Dis. 56, 486–495 (2010).
    Article PubMed PubMed Central Google Scholar
  49. König, M. et al. Cohort profile: role of lipoproteins in cardiovascular disease-the LipidCardio study. Br. Med. J. Open 9, e030097 (2019).
    Google Scholar
  50. STROBE Statement—checklist of items that should be included in reports of observational studies1 (STROBE Initiative). https://www.equator-network.org/wp-content/uploads/2015/10/STROBE_checklist_v4_combined.pdf (2008).
  51. Nemet, I. et al. A cardiovascular disease-linked gut microbial metabolite acts via adrenergic receptors. Cell 180, 862–877 (2020).
    Article CAS PubMed PubMed Central Google Scholar
  52. Gupta, N., Li, W. & McIntyre, T. M. Deubiquitinases modulate platelet proteome ubiquitination, aggregation and thrombosis. Arterioscler. Thromb. Vasc. Biol. 35, 2657–2666 (2015).
    Article CAS PubMed PubMed Central Google Scholar
  53. Scavone, M. et al. Platelet adhesion and thrombus formation in microchannels: the effect of assay-dependent variables. Int. J. Mol. Sci. 21, 750 (2020).
    Article CAS PubMed PubMed Central Google Scholar
  54. Witkowski, M. et al. Vascular endothelial tissue factor contributes to trimethylamine N-oxide-enhanced arterial thrombosis. Cardiovasc. Res. 118, 2367–2384 (2021).
    Article PubMed Central Google Scholar
  55. Ludäscher, B. & Raschid, L. (eds.) Data Integration in the Life Sciences (Springer, 2005).
  56. Wilson, P. W. et al. Prediction of coronary heart disease using risk factor categories. Circulation 97, 1837–1847 (1998).
    Article CAS PubMed Google Scholar
  57. SCORE2 Working Group and ESC Cardiovascular Risk Collaboration. SCORE2 risk prediction algorithms: new models to estimate 10-year risk of cardiovascular disease in Europe. Eur. Heart J. 42, 2439–2454 (2021).
    Article Google Scholar

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Acknowledgements

This work is supported by grants from the NIH and Office of Dietary Supplements P01 HL147823, R01 HL103866 (S.L.H.), the Leducq Foundation 17CVD01 (S.L.H. and U.L.) and the Deutsche Forschungsgemeinschaft WI 5229/1-1 (M.W.). A.H. is a participant in the BIH-Charité Advanced Clinician Scientist Program funded by the Charité—Universitätsmedizin Berlin and the Berlin Institute of Health. The LipidCardio Study was partially funded by the Sanofi-Aventis Deutschland GmbH (I.D. and U.L.). P.P.S. was supported in part by an AHA postdoctoral grant 20POST35210937. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We thank G. Deshpande (Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic) for technical support during whole blood in vitro thrombosis studies. We also thank M. Ferrell for assistance in data analysis and T. Weeks (both at the Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic) for editing the manuscript.

Author information

Author notes

  1. Hassan Alamri
    Present address: Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia
  2. Tomas Cajka
    Present address: Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic
  3. These authors contributed equally: Marco Witkowski, Ina Nemet.

Authors and Affiliations

  1. Department of Cardiovascular and Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
    Marco Witkowski, Ina Nemet, Hassan Alamri, Jennifer Wilcox, Nilaksh Gupta, Nisreen Nimer, Xinmin S. Li, Yuping Wu, Prasenjit Prasad Saha, W. H. Wilson Tang & Stanley L. Hazen
  2. Department of Cardiology, Angiology and Intensive Care, German Heart Center of Charité, Campus Benjamin Franklin, Berlin, Germany
    Arash Haghikia & Ulf Landmesser
  3. German Center for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
    Arash Haghikia & Ulf Landmesser
  4. Berlin Institute of Health (BIH), Berlin, Germany
    Arash Haghikia & Ulf Landmesser
  5. Friede Springer Cardiovascular Prevention Center at Charité, Berlin, Germany
    Arash Haghikia & Ulf Landmesser
  6. Department of Mathematics and Statistics, Cleveland State University, Cleveland, OH, USA
    Yuping Wu
  7. Department of Endocrinology and Metabolism, Charité-Universitätsmedizin Berlin, Berlin, Germany
    Ilja Demuth, Maximilian König & Elisabeth Steinhagen-Thiessen
  8. Berlin Institute of Health Center for Regenerative Therapies, Berlin, Germany
    Ilja Demuth
  9. West Coast Metabolomics Center, University of California, Davis, CA, USA
    Tomas Cajka & Oliver Fiehn
  10. Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, OH, USA
    W. H. Wilson Tang & Stanley L. Hazen

Authors

  1. Marco Witkowski
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  2. Ina Nemet
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  3. Hassan Alamri
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  4. Jennifer Wilcox
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  6. Nisreen Nimer
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  7. Arash Haghikia
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  8. Xinmin S. Li
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  9. Yuping Wu
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  10. Prasenjit Prasad Saha
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  11. Ilja Demuth
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  12. Maximilian König
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  14. Tomas Cajka
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  15. Oliver Fiehn
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  16. Ulf Landmesser
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  18. Stanley L. Hazen
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Contributions

M.W. participated in the design of all in vitro and in vivo studies, performed experiments and statistical analysis and drafted the manuscript. M.W. and I.N. wrote the manuscript with input from all authors. I.N. and H.A. developed and performed the mass spectrometry analysis in human and mouse samples. N.N. helped with mass spectrometry analysis. J.W. and M.W. coordinated the Cosette study. N.G. performed whole blood in vitro thrombosis assays. P.P.S. helped with calcium studies. T.C. and O.F. performed untargeted metabolic analysis. Y.W. and X.S.L. analyzed data. A.H., I.D., M.K., E.S.-T. and U.L. contributed clinical study samples and assisted with data analysis from the European validation cohort. W.H.W.T. coordinated the Cosette study and provided critical scientific input and discussions. S.L.H. conceived, designed and supervised all experiments and participated in the drafting and editing of the article. All authors contributed to the critical review of the manuscript.

Corresponding author

Correspondence toStanley L. Hazen.

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Competing interests

Hazen reports being named as co-inventor on pending and issued patents held by the Cleveland Clinic relating to cardiovascular diagnostics and therapeutics, being a paid consultant formerly for Procter and Gamble and currently with Zehna Therapeutics. He also reports having received research funds from Procter and Gamble, Zehna Therapeutics and Roche Diagnostics, and being eligible to receive royalty payments for inventions or discoveries related to cardiovascular diagnostics or therapeutics from Cleveland HeartLab, a wholly owned subsidiary of Quest Diagnostics, Procter and Gamble and Zehna therapeutics. Tang reports being a consultant for Sequana Medical A.G., Owkin Inc., Relypsa Inc. and PreCardiac Inc., having received an honorarium from Springer Nature for authorship/editorship and American Board of Internal Medicine for exam writing committee participation—all unrelated to the subject and contents of this paper. The other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

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Nature Medicine thanks Andrew Gray, Steffen Massberg and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Ming Yang, in collaboration with the Nature Medicine team.

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Extended data

Extended Data Fig. 1 Polyol metabolites and major adverse cardiovascular events (MACE) in untargeted metabolomics analyses of the discovery cohort.

Shown are boxplots with relative levels for the indicated polyol (defined as compounds with two or more hydroxyl groups**)** area in both patients with (red) and without (blue) incident (3 yr) MACE ranked by Mann Whitney P values. Compound relative areas are shown as log of fold change (no MACE vs. MACE) to facilitate comparison. Boxes represent interquartile ranges (IQR) with the notch indicating the median. Lower whiskers represent smallest observation (≥25% quantile -1.5×IQR) and upper whiskers largest observation (≤75% quantile +1.5×IQR). Two-sided P values were calculated by Mann–Whitney U-test. N for no MACE = 1041, n for MACE = 116. False discovery rate corrected two-sided P values (Benjamini-Hochberg method) are indicated as follows: ****P<0.0001, ***P < 0.001, **P < 0.01, *P < 0.05.

Extended Data Fig. 2 Chromatographic separation of erythritol from its structural isomer threitol.

After exhaustive acetylation with acetic acid anhydride, the polyols erythritol and its structural isomer, threitol, were baseline resolved by the HPLC method developed. Shown are the chromatograms generated by multiple reaction monitoring transitions (MRM) for the derivatized plasma analytes (m/z 308; [M+NH4]+) and synthetic isotopically labeled erythritol internal standard (D6-Erythritol; m/z 314; [M+NH4]+). With the column matrix and mobile phase /gradient employed, coupled with the characteristic parent [M+NH4+] —> daughter ion transition used (for both erythritol and threitol), baseline chromatographic resolution of the two structural isomers was achieved.

Extended Data Fig. 3 Plasma levels of erythritol are elevated in patients with major adverse cardiovascular events (MACE) and coronary artery disease (CAD) in both US and European validation cohorts.

Erythritol levels in patients stratified by presence of (3 year) MACE or CAD. Data are shown as log of plasma Erythritol. Plotted are individual values as dots. Boxes represent interquartile ranges (IQR) with the notch indicating the median. Lower whiskers represent smallest observation (≥25% quantile - 1.5×IQR) and upper whiskers largest observation (≤75% quantile + 1.5×IQR). Two-sided P values were calculated by Mann–Whitney U-test. Numbers of subjects within each group are indicated.

Extended Data Fig. 4 Erythritol increases platelet aggregation responses to submaximal concentrations of agonists.

ADP-stimulated and Thrombin receptor-activating peptide(TRAP)6-stimulated platelet aggregometry responses of human platelet-rich plasma with fixed concentration of erythritol (45 or 90 μM, red) versus normal saline (vehicle, blue). Data in bar graphs are represented as means (±s.d.), and two-sided P values were calculated by Mann Whitney Test (bar graphs) and by 2-way analysis of variance (overall P value is shown for erythritol effect) with Sidák’s post hoc test. Sidák’s adjusted P values for Erythritol 45 μM vs. vehicle: for ADP 2 μM P = 0.01, ADP 3 μM P = 0.005, for erythritol 90 μM vs. vehicle: TRAP6 5 μM: P = 0.0002. Numbers of independent biological replicates (n) are indicated. *P < 0.05, ** P < 0.01, ***P < 0.001.

Extended Data Fig. 5 Impact of glucose on platelet aggregation.

ADP-stimulated (left panel) and Thrombin receptor-activating peptide (TRAP) 6-stimulated (right panel) platelet aggregometry responses in human platelet-rich plasma incubated with glucose (270 μM, green) versus vehicle (saline, blue). Data in bar graphs are represented as means (±s.d.). Two-sided P values were calculated using Mann–Whitney U-test. Numbers of independent biological replicates (n) are indicated.

Extended Data Fig. 6 Impact of 1,5-Anhydroglucitol (AHG) on platelet aggregation and calcium release.

Panel A ADP-stimulated and Thrombin receptor-activating peptide (TRAP)6-stimulated platelet aggregometry responses in human platelet-rich plasma incubated with 1,5-AHG (green) versus vehicle (saline, blue). Two-sided P values were calculated by Mann Whitney Test. For ADP and TRAP6 stimulated platelet-rich plasma n = 7. Panel B shows thrombin-induced (0.02 U ml−1) changes in intracellular calcium concentration in Fura 2-filled washed human platelets incubated with 1,5-AHG (green) or vehicle (saline, blue). Data represent mean (±s.d.). Two-sided P values were calculated by Wilcoxon matched-pairs signed rank test. Numbers of independent biological replicates (n) are indicated.

Extended Data Fig. 7 Impact of 1,5-Anhydroglucitol (AHG) and glucose on platelet activation.

ADP-induced changes in GP IIb/IIIa (PAC-1 antibody staining) and P-selectin surface expression in washed human platelets pre-incubated with vehicle (saline, blue) or the indicated concentrations of either 1,5-AHG (green, panel A) or glucose (green, panel B). Bars represent means (±s.d.), Two-sided P values were calculated by Kruskal–Wallis test with Dunn’s post hoc test for multiple-group comparisons. Numbers of independent biological replicates (n) are indicated.

Extended Data Fig. 8 Impact of erythritol at different physiological concentrations on platelet aggregation responses.

Human platelet-rich plasma was incubated with erythritol (red) at low levels observed in fasting patients (18 μM) and higher concentrations observed after erythritol ingestions (6 mM) versus vehicle (saline, blue). Shown are thrombin receptor-activating peptide(TRAP)6-stimulated (panel A) and ADP-stimulated (panel B) platelet aggregometry responses. Data in bar graphs are represented as means (±s.d.). Two-sided P values were calculated by Mann Whitney Test. Numbers of independent biological replicates (n) are indicated.

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Witkowski, M., Nemet, I., Alamri, H. et al. The artificial sweetener erythritol and cardiovascular event risk.Nat Med 29, 710–718 (2023). https://doi.org/10.1038/s41591-023-02223-9

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