The effect of third generation aromatase inhibitors on the several components of experimental metabolic syndrome

Authors

  • A. L. Zagayko National Pharmaceutical University
  • D. V. Lytkin National Pharmaceutical University
  • A. V. Maloshtan National Pharmaceutical University

DOI:

https://doi.org/10.11603/mcch.2410-681X.2017.v0.i4.8306

Keywords:

aromatase, inhibitors, metabolic syndrome, visceral fat, insulinresistance, letrozole, anastrozole, exemestane.

Abstract

Introduction. Nowadays, about 86 % among patients with metabolic syndrome have serious disorder of glucose tolerance and about 60 % of them suffer from visceral obesity. Moreover in many worldwide studies it was shown that these pathogenetic manifestations of the metabolic syndrome had a significant correlation with the imbalance of sex hormones.

The aim of the study – to learn the effect of third-generation aromatase inhibitors on the parameters of insulin resistance and visceral obesity in hamsters with the experimental metabolic syndrome.

Research Methods. The insulin level in the hamster`s blood serum was measured by the enzyme immunoassay method, and the glucose level by the electrochemical method. The mass coefficients of anatomical fragments of adipose tissue were calculated to estimate visceral obesity. The results were processed by using the Mann-Whitney U-test and the 4Pl method.

Results and Discussion. All studied drugs, in varying degrees, influenced on the pathogenetic components of the experimental metabolic syndrome. Exemestane was demonstrated the greatest effectiveness in reducing parameter of the insulin resistance by, butletrozole – in decreasing of visceral obesity ratio.

Сonclusion. Romatase inhibitors can become promising drugs for correcting

 the pathogenetic components of the metabolic syndrome, in particular insulin resistance and visceral obesity.

Author Biography

A. L. Zagayko, National Pharmaceutical University

 

References

Kaur, J. (2014). Comprehensive review on metabolic syndrome. Cardiology Research and Practice, Article ID 943162, retrieved from: https://www.hindawi. com/journals/crp/2014/943162/.

Desroches, S., & Lamarche, B. (2007). The evolving definitions and increasing prevalence of the metabolic syndrome. Applied Physiology, Nutrition and Metabolism, 32, 23-32.

Kolovou, G., Anagnostopoulou, K., Salpea K., & Mikhailidis, D. (2007). The prevalence of metabolic syndrome in various populations. The American Journal of the Medical Sciences, 333, 362-371.

Park, Y.W., Zhu, S.,&Palaniappan, L. (2003).Themetabolicsyndrome: prevalenceandassociatedriskfactorfindingsinthe US populationfromtheThirdNationalHealthandNutritionExaminationSurvey.ArchivesofInternalMedicine, 163, 427-436.

4. Park, Y.W., Zhu, S., & Palaniappan, L. (2003). The metabolic syndrome: prevalence and associated risk factor findings in the US population from the Third National Health and Nutrition Examination Survey. Archives of

Internal Medicine, 163, 427-436.

Charles, M.A., Landsman, P.B., & Grundy, S.M. (2006). Metabolic syndrome and hyperglycemia: congruence and divergence. American Journal of Cardiology, 98 (7), 982-985.

Yin, J., Li, M., & Xu, L. (2013). Insulin resistance determined by omeostasis Model Assessment (HOMA) and associations with metabolic syndrome among

Chinese children and teenagers. Diabetol. Metab. Syndr., 5, 71. retrieved from: https://www.ncbi.nlm.nih. gov/pmc/articles/PMC3833654/.

Cameron, A.J., Shaw, J.E., & Zimmet, P.Z. (2004). The metabolic syndrome: prevalence in worldwide populations. Endocrinology and Metabolism Clinics of North America, 33 (2), 351-375.

Xu, Q., Wells, C.C., & Garman, J.H. (2008). Imbalance in sex hormone levels exacerbates diabetic renal disease. Hypertension, 51 (4), 1218-1224.

Barros, R.P., Morani, A., Moriscot, A., & Machado, U.F. (2008). Insulin resistance of pregnancy involves estrogen-induced repression of muscle GLUT4. Mol. Cell. Endocrinol., 25, 295 (1-2), 24-31.

Bulun, S.E., Chen, D., & Moy, I. (2012). Aromatase, breast cancer and obesity: a complex interaction. Trends Endocrinol. Metab., 23, 83-89.

Morimoto, L.M., White, E., & Chen, Z. (2002). Obesity, body size, and risk of postmenopausal breast cancer: the Women’s Health Initiative (United States). Cancer Causes Control, 13, 741-751.

Zumoff, B. (1982). Relationship of obesity to blood estrogens. Cancer Res., 42 (8), 3289-3294.

Boonchaya-anant, P., Laichuthai, N., & Suwannasrisuk, P. (2016) Changes in testosterone levels and sex hormone-binding globulin levels in extremely obese men after bariatric surgery. International Journal of Endocrinology. Retrieved from: http://doi.org/10.1155/ 2016/1416503.

Cao, J., Chen, T.M., & Hao, W.J. (2012). Correlation between sex hormone levels and obesity in the elderly male. Aging Male, 15 (2), 85-89.

Kasim-Karakas, S.E., Vriend, H., & Almario, R. (1996). Effects of dietary carbohydrates on glucose andlipid metabolism in golden Syrian hamsters. J. Lab. Clin.Med., 128 (2), 208-213.

Wong, S.K., Chin, K.-Y., & Hj, F. (2016). Suhaimi Animal models of metabolic syndrome: a review. Nutr. Metab. (Lond), 13, 65.

Anroop, B.N., & Shery, J. (2016). A simple practice guide for dose conversion between animals and human. J. Basic Clin. Pharm., 7 (2), 27-31.

Stefanov, A.V. (Ed.). (2002). Preclinical research of drugs: method. Kyiv: Avicenna.

Popov, D., Simionescu, M., & Shepherd, P.R. (2003). Saturated-fat diet induces moderate diabetes and severe glomerulo sclerosis in hamsters. Diabetologia, 46, 1408-1418.

Lapach, S.N., Chubenko, A.V., & Babich, P.N. (2000). Statisticheskie metody v mediko-biologicheskikh issledovaniyakh s ispolzovaniyam Excel [Statistical methods in medical biological research using Excel]. Kyiv:

Morion [in Russian].

Rebrova, O.Yu. (2006). Statistichekiy analiz meditsinskikh dannykh. Primeneniya paketa prikladnykh program STATISTICA [Statistic alanalysis of medical data. Application of the application package STATISTICA. 3rd

ed]. Moscow: MediaSfera.

Garg, M.K., Dutta, M.K., & Mahalle, N. (2011). Study of beta-cell function (by HOMA model) in metabolic syndrome. Indian J. Endocrinol. Metab., 15 (1), 44-49.

Levy, J.C., Matthews, D.R., & Hermans, M.P. (1998). Correct homeostasis model assessment (HOMA) Evaluation Uses the Computer Program. Diabetes Care, 21 (12), 2191-2192.

Lynn, C. Anderson, Glen Otto, Kathleen R. Pritchett (2015). Laboratory animal medicine. Elsevier.Corning, & Mark, T. Whary

Published

2018-01-11

How to Cite

Zagayko, A. L., Lytkin, D. V., & Maloshtan, A. V. (2018). The effect of third generation aromatase inhibitors on the several components of experimental metabolic syndrome. Medical and Clinical Chemistry, (4), 41–50. https://doi.org/10.11603/mcch.2410-681X.2017.v0.i4.8306

Issue

Section

ORIGINAL INVESTIGATIONS