Possibilities to assess insulin resistance as the metabolic syndrome is clustered in women in postmenopause
https://doi.org/10.21518/2079-701X-2019-4-88-93
Abstract
The formation of the MS cluster starting from insulin resistance (IR), visceral obesity, dyslipidemia, arterial hypertension and carbohydrate metabolism disorders (CMD) against the background of estrogenic deficiency defines postmenopause as a risk factor for type 2 diabetes mellitus (DM2) and increased cardiovascular risk. The TyG index (logarithmic ratio of triglyceride and fasting plasma glucose levels) is proposed for surrogate evaluation of IR, reflecting an integrated approach to metabolic disorders.
Aim: To assess the relationship between the TyG Index and HOMA2-IR and its informativeness in predicting the risk of DM2 in women in postmenopause.
Materials and methods: TyG and HOMA2-IR indices (C-peptide) were determined in 94 postmenopausal women 58.02 ± 5.88 years of age, evaluated according to NCEP ATP III criteria and divided into groups: 1st - DM2, 2nd - prediabetes, 3rd - without CMD (HbAlc 7.3 ± 1.0; 6.2 ± 0.2 and 5.5 ± 0.4%, respectively). By means of SPSS (version 17) we evaluated ME (25-75%); intergroup differences by Mann-Whitney criteria; we performed correlation and ROC-analysis.
Results: TyG correlates with HOMA2IR in group 2 (R = 0.61; p = 0.013) and 3 (R = 0.60; p = 0.001). In the process of ROC-analysis cut-off for TyG was revealed, reflecting the chance of presence of DM2 in groups 2 and 3: 7.5 (sensitivity 0.938 and specificity 0.813) and 8.0 (sensitivity 0.894 and specificity 0.810), respectively.
Conclusion: TyG index allows predicting the development of dysglycemia in women in postmenopause with the signs of MS through the phenomenon of lipoglucotoxicity.
About the Authors
L. A. RuyatkinaRussian Federation
Ruyatkina Lyudmila Aleksandrovna - Dr. of Sci. (Med), Professor.
630091, Novosibirsk, Krasny Prospekt, d. 52; tel: +7(913) 908-23-57
D. S. Ruyatkin
Russian Federation
Ruyatkin Dmitry Sergeevich - Cand. of Sci. (Med), Associate Professor.
630091, Novosibirsk, Krasny Prospekt, d. 52
I. S. Iskhakova
Russian Federation
Iskhakova Irina Sergeevna - Cand. of Sci. (Med), Endocrinologist.
630047, Novosibirsk, Zalessky St., 6, bldg. 4
L. V. Scherbakova
Russian Federation
Shcherbakova Liliya Valeryevna - Senior Researcher of the Research Institute of Therapy and Preventive Medicine, a branch.
630089, Novosibirsk, Boris Bogatkov Street, 175/1
References
1. Huang Y.Association betweenpre diabetes and risk of cardiovascular diseaseandallcausemor-taLity: systematicreview and meta-analysis. BMJ. 2016;355(i5953):1—11. doi: 10.1136/bmj.i5953.
2. Tancredi M., Rosengren A., Svensson A.-M., Kosiborod M., Pivodic A., Gudbjornsdottir S. et al. Excess Mortality among Persons with Type 2 Diabetes. N Engl J Med. 2015;373:1720-1732. doi: 10.1056/NEJMoa1504347.
3. Fernandez M.L., Murillo A.G. Postmenopausal Women Have Higher HDL and Decreased Incidence of Low HDL than Premenopausal Women with Metabolic Syndrome. Healthcare (Basel). 2016;16,4(1):20-30. doi: 10.3390/healthcare4010020.
4. Grigoryan O.R., Antsiferov M.B., Dedov I.I. Climax and Diabetes. Manual for doctors. The Endocrinology Research Center of The Russian Academy of Medical Sciences, 2012. (In Russ.)
5. Muka T., Asllanaj E., Avazverdi N., Jaspers L., Stringa N., Milic J. et al. Age at natural menopause and risk of type 2 diabetes: a prospective cohort study. Diabetologia. 2017;60(10):1951-1960. doi 10.1007/s00125-017-4346-8.
6. Stachowiak G., Pertynski T., Pertynska-Marczewska M. Metabolic disorders in menopause. Prz Menopauzalny. 2015;14(1):59-64. doi: 10.5114/pm.2015.50000.
7. Zhu B., zhang L., Cheng X.P., Wang L., Tian Y., Li X.X. et al. The association between metabolic syndrome and asymptomatic carotid artery stenosis in menopausal women: a cross-sectional study in a Chinese population. Ther Clin Risk Manag. 2018;2(14):2183-2188. https//doi.org/10.2147/TCRM.S177265.
8. Dos Santos Mota M.P, Gomes Moura I.C., Marinho R.M., Sternick E.B., Almeida A.M. Evaluation of Cardiovascular Risk in Climacteric Women: A Cross-Sectional Study. J Midlife Health. 2018;9(3):123-129. doi: 10.4103/jmhJMH_67_18.
9. Ebrahimpour P., Fakhrzadeh H., Heshmat R., Ghodsi M., Bandarian F., Larijani B. Metabolic syndrome and menopause: A population-based study. Diabetes & Metabolic Syndrome: Clinical Research & Reviews. 2010.;4(1):5-9. doi: 10.1016/j.dsx.2008.04.014.
10. Patni R., Mahajan A. The Metabolic Syndrome and Menopause. J Midlife Health. 2018;9(3):111-112. doi: 10.4103/0976-7800.241951.
11. Eshtiaghi R., Esteghamati A., Nakhjavani M. Menopause is an independent predictor of metabolic syndrome in Iranian women. Maturitas. 2010;65(3):262-266. doi: 10.1016/j.maturitas.2009.11.004.
12. Malmstrom H., Walldius G., Carlsson S., Grill V., Jungner I., Gudbjornsdottir S. et al. Elevations of metabolic risk factors 20 years or more before diagnosis of type 2 diabetes: Experience from the AMORIS study. Diabetes Obes Metab. 2018;20(6):1419-1426. doi: 10.1111/dom.13241.
13. Dedov I.I., Tkachuk V.A., Gusev N.B., Shirinskiy V.P., Vorotnikov A.V., Kocheguras T.N. et al. Type 2 diabetes mellitus and metabolic syndrome: molecular mechanisms, key signaling pathways and identification of biomedical targets for new drugs. Saharnyj diabet. 2018;21(5):364-375. doi:10.14341/DM9730. (In Russ.)
14. Wallace T.M., Levy J.C., Matthews D.R. Use and abuse of HOMA modeling. Diabetes Care. 2004;27(6):1487-95. https://doi.org/10.2337/diacare.27.6.1487.
15. Майоров А.Ю., Урбанова К.А., Галстян ГР. Методы количественной оценки инсулинорезистентности. Ожирение и метаболизм. 2009;6(2):19-23. [Mayorov A.Yu., Urbanova K.A., Galstyan G.R. Methods of quantitative assessment of insulin resistance. Ozhirenie i metabo-lizm. 2009;6(2):19-23.] (In Russ.)
16. Festa A., Williams K., Hanley AJ., Haffner S.M. Beta-cell dysfunction in subjects with impaired glucose tolerance and early type 2 diabetes: comparison of surrogate markers with first-phase insulin secretion from an intravenous glucose tolerance test. Diabetes. 2008;57(6):1638-44. doi: 10.2337/db07-0954.
17. McLaughlin T., Abbasi F., Cheal K., Chu J., Lamendola C., Reaven G. Use of metabolic markers to identify overweight individuals who are insulin resistant. Ann Intern Med. 2003;139(10):802-9. doi: 10.7326/0003-4819-139-10-200311180-00007.
18. Executive summary of the Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III). JAMA. 2001;285:2486-2497.
19. Ren Y., Zhang M., Liu Y., Sun X., Wang B., Zhao Y et al. Association of menopause and type 2 diabetes mellitus. Menopause. 2019;26(3):325-330. doi: 10.1097/GME.0000000000001200.
20. Navarro-Gonzalez D., Sanchez-lnigo L., Pastrana-Delgado J., Fernandez-Montero A., Martinez J.A. Triglyceride-glucose index (TyG index) in comparison with fasting plasma glucose improved diabetes prediction in patients with normal fasting glucose: The Vascular-Metabolic CUN co-hort. Prev Med. 2016;86:99-105. doi: 10.1016/j.ypmed.2016.01.022.
21. Kim B., Choi H.Y., Kim W., Ahn C., Lee J., Kim J.G. et al. The cut-off values of surrogate measures for insulin resistance in the Korean population according to the Korean Genome and Epidemiology Study (KOGES). PLoS One. 2018;13(11):1-10. https://doi.org/10.1371/jour-nal.pone.0206994.
22. Lee J.W., Lim N.K., Park H.Y. The product of fasting plasma glucose and triglycerides improves risk prediction of type 2 diabetes in middle-aged Koreans. BMC Endocr Disord. 2018;18(1):33. doi: 10.1186/s12902-018-0259-x.
23. Salazar J., Bermudez V., Calvo M., Olivar L.C., Luzardo E., Navarro C. et al. Optimal cutoff for the evaluation of insulin resistance through triglyceride-glucose index: A cross-sectional study in a Venezuelan population. Version 3. F1000Res. 2018;6:1337. doi: 10.12688/f1000re-search.12170.3.
24. Shin K.A. Triglyceride and Glucose (TyG) Index is a Clini-cal Surrogate Marker for the Diagnosis of Metabolic Syndrome. Biomedical Science Letters. 2017;23(4):348-354. doi: 10.15616/BSL.2017.23.4.348.
25. Ruyatkina L.A., Ruyatkin D.S., Zemlyanukhina S.A. «Painful» points of diabetic angiopathies: focus on hypertriglyceridemia and phenofibrate possibilities. Farmateka. 2016;(5):14-21. (In Russ.)
26. Reaven G.M. Banting lecture 1988. Role of insulin resistance in human disease. Diabetes. 1988;37(12):1595-607.
27. Ametov A.S., Kamynina L.A., Akhmedova Z.A. Glucoso- and lipotoxicity are mutually aggravating factors in combination of type 2 diabetes mellitus and obesity. Endokrinologiya: novo-sti, mneniya, obuchenie. 2014;4:20-23. (In Russ.)
28. Maturu A., DeWitt P., Kern P.A., Rasouli N. The triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio as a pre-dictor of |3-cell function in African American women. Metabolism. 2015;64(5):561-5. doi: 10.1016/j.metabol.2015.01.004.
29. Du T., Yuan G., Zhang M., Zhou X., Sun X., Yuet X. Clinical usefulness of lipid ratios, visceral adiposity indicators, and the triglycerides and glucose index as risk markers of insulin resistance. Cardiovasc Diabetol. 2014;13:146. doi: 10.1186/s12933-014-0146-3.
30. Simental-Mendia L.E., Rodriguez-Moran M., Guerrero-Romero F. The product of fasting glucose and triglycerides as surrogate for identifying insulin resistance in apparently healthy subjects. Metab Syndr Relat Disord. 2008;6(4):299-304. doi: 10.1089/met.2008.0034.
31. Tan H.W., Zhao N.Q., Yu Y.R., Han L.N., Zhang X.X. Pancreatic в -cell Dysfunction and Apoptosis Induced by Elevated Free Fatty Acids Synergize with Hyperglycemia. Medical Science Edition. 2017;48(1):71-75.
32. Tenenbaum A., Klempfner R., Fisman Z. Hypertriglyceridemia: a too long unfairly neglected major cardiovascular risk factor. Cardiovasc Diabetol. 2014;13:159. doi: 10.1186/s12933-014-0159-y.
33. Oh Y.S., Bae G.D., Baek DJ.. Park E.Y., Jun H.S. Fatty Acid-Induced Lipotoxicity in Pancreatic Beta-Cells During Development of Type 2 Diabetes. Front Endocrinol (Lausanne). 2018;9(384):1-10. doi: 10.3389/fendo.2018.00384.
34. Hameed E.K. TyG index a promising biomarker for glycemic control in type 2 Diabetes Mellitus. Diabetes Metab Syndr. 2019;13(1):560-563. doi: 10.1016/j.dsx.2018.11.030.
35. Hojlund K. Metabolism and insulin signaling in common metabolic disorders and inherited insulin resistance. Dan Med J. 2014;61(7):B4890.
36. Gurka MJ., Vishnu A., Santen RJ., DeBoer M.D. Progression of Metabolic Syndrome Severity During the Menopausal Transition. J Am Heart Assoc. 2016;5:e003609. doi: 10.1161/JAHA.116.003609.
Review
For citations:
Ruyatkina LA, Ruyatkin DS, Iskhakova IS, Scherbakova LV. Possibilities to assess insulin resistance as the metabolic syndrome is clustered in women in postmenopause. Meditsinskiy sovet = Medical Council. 2019;(4):88-93. (In Russ.) https://doi.org/10.21518/2079-701X-2019-4-88-93