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Copeptin and insulin resistance: effect modification by age and 11 β-HSD2 activity in a population-based study

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Abstract

Purpose

Arginine vasopressin (AVP) may be involved in metabolic syndrome (MetS) by altering liver glycogenolysis, insulin and glucagon secretion, and pituitary ACTH release. Moreover, AVP stimulates the expression of 11β-hydroxysteroid-dehydrogenase-type 2 (11β-HSD2) in mineralocorticosteroid cells. We explored whether apparent 11β-HSD2 activity, estimated using urinary cortisol-to-cortisone ratio, modulates the association between plasma copeptin, as AVP surrogate, and insulin resistance/MetS in the general adult population.

Methods

This was a multicentric, family-based, cross-sectional sample of 1089 subjects, aged 18–90 years, 47% men, 13.4% MetS, in Switzerland. Mixed multivariable linear and logistic regression models were built to investigate the association of insulin resistance (HOMA-IR)/fasting glucose and MetS/Type 2 Diabetes with copeptin, while considering potential confounders or effect modifiers into account. Stratified results by age and 11β-HSD2 activity were presented as appropriate.

Results

Plasma copeptin was higher in men [median 5.2, IQR (3.7–7.8) pmol/L] than in women [median 3.0, IQR (2.2–4.3) pmol/L], P < 0.0001. HOMA-IR was positively associated with copeptin after full adjustment if 11β-HSD2 activity was high [β (95% CI) = 0.32 (0.17–0.46), P < 0.001] or if age was high [β (95% CI) = 0.34 (0.20–0.48), P < 0.001], but not if either 11β-HSD2 activity or age was low. There was a positive association of type 2 diabetes with copeptin [OR (95% CI) = 2.07 (1.10–3.89), P = 0.024), but not for MetS (OR (95% CI) = 1.12 (0.74–1.69), P = 0.605), after full adjustment.

Conclusions

Our data suggest that age and apparent 11β-HSD2 activity modulate the association of copeptin with insulin resistance at the population level but not MeTS or diabetes. Further research is needed to corroborate these results and to understand the mechanisms underlying these findings.

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References

  1. Asferg CL, Andersen UB, Linneberg A, Goetze JP, Jeppesen JL (2014) Copeptin, a surrogate marker for arginine vasopressin secretion, is associated with higher glucose and insulin concentrations but not higher blood pressure in obese men. Diabet Med J Br Diabet Assoc 31(6):728–732. https://doi.org/10.1111/dme.12411

    Article  CAS  Google Scholar 

  2. Enhorning S, Bankir L, Bouby N, Struck J, Hedblad B, Persson M, Morgenthaler NG, Nilsson PM, Melander O (2013) Copeptin, a marker of vasopressin, in abdominal obesity, diabetes and microalbuminuria: the prospective Malmo Diet and Cancer Study cardiovascular cohort. Int J Obes 37(4):598–603. https://doi.org/10.1038/ijo.2012.88

    Article  CAS  Google Scholar 

  3. Enhorning S, Struck J, Wirfalt E, Hedblad B, Morgenthaler NG, Melander O (2011) Plasma copeptin, a unifying factor behind the metabolic syndrome. J Clin Endocrinol Metab 96(7):E1065–E1072. https://doi.org/10.1210/jc.2010-2981

    Article  PubMed  Google Scholar 

  4. Enhorning S, Wang TJ, Nilsson PM, Almgren P, Hedblad B, Berglund G, Struck J, Morgenthaler NG, Bergmann A, Lindholm E, Groop L, Lyssenko V, Orho-Melander M, Newton-Cheh C, Melander O (2010) Plasma copeptin and the risk of diabetes mellitus. Circulation 121(19):2102–2108. https://doi.org/10.1161/circulationaha.109.909663

    Article  PubMed  PubMed Central  Google Scholar 

  5. Saleem U, Khaleghi M, Morgenthaler NG, Bergmann A, Struck J, Mosley TH Jr, Kullo IJ (2009) Plasma carboxy-terminal provasopressin (copeptin): a novel marker of insulin resistance and metabolic syndrome. J Clin Endocrinol Metab 94(7):2558–2564. https://doi.org/10.1210/jc.2008-2278

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  6. Struck J, Morgenthaler NG, Bergmann A (2005) Copeptin, a stable peptide derived from the vasopressin precursor, is elevated in serum of sepsis patients. Peptides 26(12):2500–2504. https://doi.org/10.1016/j.peptides.2005.04.019

    Article  PubMed  CAS  Google Scholar 

  7. Morgenthaler NG, Struck J, Alonso C, Bergmann A (2006) Assay for the measurement of copeptin, a stable peptide derived from the precursor of vasopressin. Clin Chem 52(1):112–119. https://doi.org/10.1373/clinchem.2005.060038

    Article  PubMed  CAS  Google Scholar 

  8. Roussel R, Fezeu L, Marre M, Velho G, Fumeron F, Jungers P, Lantieri O, Balkau B, Bouby N, Bankir L, Bichet DG (2014) Comparison between copeptin and vasopressin in a population from the community and in people with chronic kidney disease. J Clin Endocrinol Metab 99(12):4656–4663. https://doi.org/10.1210/jc.2014-2295

    Article  PubMed  CAS  Google Scholar 

  9. Roussel R, El Boustany R, Bouby N, Potier L, Fumeron F, Mohammedi K, Balkau B, Tichet J, Bankir L, Marre M, Velho G (2016) Plasma copeptin, AVP gene variants, and incidence of Type 2 diabetes in a cohort from the community. J Clin Endocrinol Metab 101(6):2432–2439. https://doi.org/10.1210/jc.2016-1113

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Rothermel J, Kulle A, Holterhus PM, Toschke C, Lass N, Reinehr T (2016) Copeptin in obese children and adolescents: relationships to body mass index, cortisol and gender. Clin Endocrinol (Oxf). https://doi.org/10.1111/cen.13235

    Article  Google Scholar 

  11. Rubis B, Krozowski Z, Trzeciak WH (2006) Arginine vasopressin stimulates 11beta-hydroxysteroid dehydrogenase type 2 expression in the mineralocorticosteroid target cells. Mol Cell Endocrinol 256(1–2):17–22. https://doi.org/10.1016/j.mce.2006.04.032

    Article  PubMed  CAS  Google Scholar 

  12. Crowley RK, Hughes B, Gray J, McCarthy T, Hughes S, Shackleton CH, Crabtree N, Nightingale P, Stewart PM, Tomlinson JW (2014) Longitudinal changes in glucocorticoid metabolism are associated with later development of adverse metabolic phenotype. Eur j endocrinol Eur Fed Endoc Soc 171(4):433–442. https://doi.org/10.1530/eje-14-0256

    Article  CAS  Google Scholar 

  13. Di Dalmazi G, Pagotto U, Pasquali R, Vicennati V (2012) Glucocorticoids and type 2 diabetes: from physiology to pathology. J Nutr Metab 2012:525093. https://doi.org/10.1155/2012/525093

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  14. Pereira CD, Azevedo I, Monteiro R, Martins MJ (2012) 11beta-Hydroxysteroid dehydrogenase type 1: relevance of its modulation in the pathophysiology of obesity, the metabolic syndrome and type 2 diabetes mellitus. Diabetes Obes Metab 14(10):869–881. https://doi.org/10.1111/j.1463-1326.2012.01582.x

    Article  PubMed  CAS  Google Scholar 

  15. Funder JW, Pearce PT, Smith R, Smith AI (1988) Mineralocorticoid action: target tissue specificity is enzyme, not receptor, mediated. Science 242(4878):583–585

    Article  PubMed  CAS  Google Scholar 

  16. Pivonello R, De Leo M, Vitale P, Cozzolino A, Simeoli C, De Martino MC, Lombardi G, Colao A (2010) Pathophysiology of diabetes mellitus in Cushing’s syndrome. Neuroendocrinology 92(Suppl 1):77–81. https://doi.org/10.1159/000314319

    Article  PubMed  CAS  Google Scholar 

  17. Newell-Price J, Bertagna X, Grossman AB, Nieman LK (2006) Cushing’s syndrome. Lancet 367(9522):1605–1617. https://doi.org/10.1016/s0140-6736(06)68699-6

    Article  PubMed  CAS  Google Scholar 

  18. Hollis G, Huber R (2011) 11beta-Hydroxysteroid dehydrogenase type 1 inhibition in type 2 diabetes mellitus. Diabetes Obes Metab 13(1):1–6. https://doi.org/10.1111/j.1463-1326.2010.01305.x

    Article  PubMed  CAS  Google Scholar 

  19. Stewart PM, Tomlinson JW (2009) Selective inhibitors of 11beta-hydroxysteroid dehydrogenase type 1 for patients with metabolic syndrome: is the target liver, fat, or both? Diabetes 58(1):14–15

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. Stomby A, Andrew R, Walker BR, Olsson T (2014) Tissue-specific dysregulation of cortisol regeneration by 11betaHSD1 in obesity: has it promised too much? Diabetologia 57(6):1100–1110. https://doi.org/10.1007/s00125-014-3228-6

    Article  PubMed  CAS  Google Scholar 

  21. Mussig K, Remer T, Haupt A, Gallwitz B, Fritsche A, Haring HU, Maser-Gluth C (2008) 11beta-hydroxysteroid dehydrogenase 2 activity is elevated in severe obesity and negatively associated with insulin sensitivity. Obesity (Silver Spring) 16(6):1256–1260. https://doi.org/10.1038/oby.2008.218

    Article  CAS  Google Scholar 

  22. Milagro FI, Campion J, Martinez JA (2007) 11-Beta hydroxysteroid dehydrogenase type 2 expression in white adipose tissue is strongly correlated with adiposity. J Steroid Biochem Mol Biol 104(1–2):81–84. https://doi.org/10.1016/j.jsbmb.2006.10.006

    Article  PubMed  CAS  Google Scholar 

  23. Ponte B, Pruijm M, Ackermann D, Vuistiner P, Guessous I, Ehret G, Alwan H, Youhanna S, Paccaud F, Mohaupt M, Pechere-Bertschi A, Vogt B, Burnier M, Martin PY, Devuyst O, Bochud M (2014) Copeptin is associated with kidney length, renal function, and prevalence of simple cysts in a population-based study. J Am So Nephrol 26(6):1415–1425. https://doi.org/10.1681/asn.2014030260

    Article  Google Scholar 

  24. Ponte B, Pruijm M, Ackermann D, Vuistiner P, Eisenberger U, Guessous I, Rousson V, Mohaupt MG, Alwan H, Ehret G, Pechere-Bertschi A, Paccaud F, Staessen JA, Vogt B, Burnier M, Martin PY, Bochud M (2014) Reference values and factors associated with renal resistive index in a family-based population study. Hypertension 63(1):136–142. https://doi.org/10.1161/hypertensionaha.113.02321

    Article  PubMed  CAS  Google Scholar 

  25. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC (1985) Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28(7):412–419

    Article  PubMed  CAS  Google Scholar 

  26. Third Report of the National Cholesterol Education Program (NCEP) (2002) Expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel III) final report. Circulation 106(25):3143–3421

    Article  Google Scholar 

  27. Shackleton CH (1993) Mass spectrometry in the diagnosis of steroid-related disorders and in hypertension research. J Steroid Biochem Mol Biol 45(1–3):127–140

    Article  PubMed  CAS  Google Scholar 

  28. Stewart PM, Boulton A, Kumar S, Clark PM, Shackleton CH (1999) Cortisol metabolism in human obesity: impaired cortisone ≥ cortisol conversion in subjects with central adiposity. J Clin Endocrinol Metab 84(3):1022–1027. https://doi.org/10.1210/jcem.84.3.5538

    Article  PubMed  CAS  Google Scholar 

  29. Tamma G, Goswami N, Reichmuth J, De Santo NG, Valenti G (2014) Aquaporins, vasopressin and aging: current perspectives. Endocrinology 156:777–778. https://doi.org/10.1210/en.2014-1812

    Article  PubMed  CAS  Google Scholar 

  30. Melander O (2016) Vasopressin, from regulator to disease predictor for diabetes and cardiometabolic risk. Ann Nutr Metab 68(Suppl 2):24–28. https://doi.org/10.1159/000446201

    Article  PubMed  Google Scholar 

  31. Chapman K, Holmes M, Seckl J (2013) 11beta-hydroxysteroid dehydrogenases: intracellular gate-keepers of tissue glucocorticoid action. Physiol Rev 93(3):1139–1206. https://doi.org/10.1152/physrev.00020.2012

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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Acknowledgements

We thank the study nurses Marie-Odile Levy, Guler Gök-Sogüt, Ulla Schüpbach, and Dominique Siminski for their involvement and help with recruitment. We also thank Sandrine Estoppey and JulienWeber for their help in logistic and database management. We thank the study nurses involved in the study and the recruitment: Marie-Odile Levy, GulerGök Sogüt, Ulla Spüchbach, Dominique Siminski.

Author information

Authors and Affiliations

  1. Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, Switzerland

    S. Canivell & M. Bochud

  2. University Clinic for Nephrology, Hypertension and Clinical Pharmacology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland

    M. Mohaupt, D. Ackermann, G. Escher & B. Vogt

  3. Service of Nephrology and Hypertension, University Hospital of Lausanne (CHUV), Lausanne, Switzerland

    M. Pruijm

  4. Department of Community Medicine, Primary Care and Emergency Medicine, University Hospital of Geneva, Geneva, Switzerland

    I. Guessous

  5. Institute of Social and Preventive Medicine, University Hospital of Lausanne, Lausanne, Switzerland

    I. Guessous

  6. Cardiology Service, Department of Specialties of Internal Medicine, University Hospital of Geneva, Geneva, Switzerland

    G. Ehret

  7. Unit of Hypertension, Departments of Specialties of Medicine and Community Medicine and Primary Care and Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland

    A. Pechère-Bertschi

  8. Institute of Physiology, University of Zurich, Zurich, Switzerland

    O. Devuyst

  9. Nephrology Service, University Hospital of Lausanne, Lausanne, Switzerland

    M. Burnier

  10. Department of Clinical Research, University of Bern, Bern, Switzerland

    M. Burnier

  11. Nephrology Service, Department of Specialties of Internal Medicine, University Hospital of Geneva, Geneva, Switzerland

    P.-Y. Martin & B. Ponte

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  1. S. Canivell
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Correspondence to S. Canivell.

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Informed consent was obtained from all individual participants included in the study.

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Co-last authorship: B. Ponte and M. Bochud.

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Canivell, S., Mohaupt, M., Ackermann, D. et al. Copeptin and insulin resistance: effect modification by age and 11 β-HSD2 activity in a population-based study. J Endocrinol Invest 41, 799–808 (2018). https://doi.org/10.1007/s40618-017-0807-7

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  • DOI: https://doi.org/10.1007/s40618-017-0807-7

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