Opportunities and options for surrogate assessment of insulin resistance
https://doi.org/10.14341/omet10082
Abstract
The high prevalence of type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular diseases (CVD) determines the need for early detection and correction of key markers of cardio-metabolic risk (CMR). This prophylactic direction is closely related to metabolic syndrome (MS) based on the concept of insulin resistance (IR). At the same time, IR is the first link in the pathogenesis of T2DM and is a recognized risk factor for atherothrombosis. Therefore, early diagnosis of IR is of practical importance both for the detection of early disorders of carbohydrate metabolism (DCM) and prognosis of T2DM, and cardiological risk. Alternative indicators have been proposed for evaluating IR with the inclusion of lipid and anthropometric parameters, the diagnostic and prognostic significance of which in terms of CMR (DCM and CVD) has been evaluated in randomized clinical trials in comparison with the HOMA-IR index and clamp. The TyG index (calculated on the basis of plasma glucose and triglycerides) is consistent with the phenomenon of glucolipotoxicity with subsequent metabolic disorders in target organs. Its derivatives are proposed: TyG-WC (TyG / waist circumference) and TYG-BMI (TyG / BMI). Apply LAP indices (lipid accumulation index) and VAI (visceral obesity index), as well as TG / HDL (TG / HDL). Their ethnic and gender differences were revealed, attempts were made to calculate the cut-off points for these indices.
About the Authors
Lyudmila A. RuyatkinaNovosibirsk State Medical University; Novosibirsk Clinical Hospital №1
Russian Federation
MD, ScD, professor; endocrinologist - consultant
Dmitry S. Ruyatkin
Novosibirsk State Medical University
Russian Federation
MD, PhD, associate professor
Irina S. Iskhakova
Novosibirsk Clinical Hospital №1
Russian Federation
MD, PhD
References
1. Cabré J-J, Martín F, Costa B, et al. Metabolic Syndrome as a Cardiovascular Disease Risk Factor: Patients Evaluated in Primary Care. BMC Public Health. 2008;8(1):251. doi: 10.1186/1471-2458-8-251
2. Wilson PWF, D’Agostino RB, Levy D, et al. Prediction of Coronary Heart Disease Using Risk Factor Categories. Circulation. 1998;97(18):1837-1847. doi: 10.1161/01.CIR.97.18.1837
3. Piepoli MF, Hoes AW, Agewall S, et al. 2016 European Guidelines on cardiovascular disease prevention in clinical practice. Eur Heart J. 2016;37(29):2315-2381. doi: 10.1093/eurheartj/ehw106
4. Reaven GM. Role of Insulin Resistance in Human Disease. Diabetes. 1988;37(12):1595-1607. doi: 10.2337/diab.37.12.1595
5. DeFronzo RA, Ferrannini E. Insulin Resistance: A Multifaceted Syndrome Responsible for NIDDM, Obesity, Hypertension, Dyslipidemia, and Atherosclerotic Cardiovascular Disease. Diabetes Care. 1991;14(3):173-194. doi: 10.2337/diacare.14.3.173
6. Reaven GM. Insulin resistance, the insulin resistance syndrome, and cardiovascular disease. Panminerva Med. 2005;47(4):201-210. PMID: 16489319
7. Cordero A, Alegria-Ezquerra E. TG/HDL ratio as surrogate marker for insulin resistance. E-Journal of Cardiology Practice [Internet]. 2009;8(16) [cited 2019 Mar 16] Available from: https://www.escardio.org/Journals/E-Journal-of-Cardiology-Practice/Volume-8/TG-HDL-ratio-as-surrogate-marker-for-insulin-resistance
8. Майоров А.Ю., Урбанова К.А., Галстян Г.Р. Методы количественной оценки инсулинорезистентности // Ожирение и метаболизм. – 2009. – Т.6. – №2. – C.19-23. [Mayorov AY, Urbanova KA, Galstyan GR, et al. Methods for guantificative assessment of insulin resistance. Ožirenie i metabolizm. 2009;6(2):19-23 (In Russ.)] doi: 10.14341/2071-8713-5313
9. Reaven GM. Insulin Resistance: the Link Between Obesity and Cardiovascular Disease. Med Clin North Am. 2011;95(5):875-892. doi: 10.1016/j.mcna.2011.06.002
10. Conde SV, Ribeiro MJ, Melo BF, et al. Insulin resistance: a new consequence of altered carotid body chemoreflex? J Physiol. 2017;595(1):31-41. doi: 10.1113/JP271684
11. Malmström H, Walldius G, Carlsson 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
12. Дедов И.И., Ткачук В.А., Гусев Н.Б., и др. Сахарный диабет 2 типа и метаболический синдром: молекулярные механизмы, ключевые сигнальные пути и определение биомишеней для новых лекарственных средств // Сахарный диабет. – 2018. – Т.21. – №5. – С.364-375. [Dedov II, Tkachuk VA, Gusev NB, et al. Type 2 diabetes and metabolic syndrome: identifi cation of the molecular mechanisms, key signaling pathways and transcription factors aimed to reveal new therapeutical targets. Diabetes Mellitus. 2018;21(5):364-375. (In Russ.)] doi: 10.14341/DM9730
13. Festa A, Williams K, Hanley AJG, Haffner SM. β-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):1638-1644. doi: 10.2337/db07-0954
14. Irace C, Carallo C, Scavelli FB, et al. Markers of insulin resistance and carotid atherosclerosis. A comparison of the homeostasis model assessment and triglyceride glucose index. Int J Clin Pract. 2013;67(7):665-672. doi: 10.1111/ijcp.12124
15. Wallace TM, Levy JC, Matthews DR. Use and Abuse of HOMA Modeling. Diabetes Care. 2004;27(6):1487-1495. doi: 10.2337/diacare.27.6.1487
16. McLaughlin T, Abbasi F, Cheal K, et al. Use of Metabolic Markers To Identify Overweight Individuals Who Are Insulin Resistant. Ann Intern Med. 2003;139(10):802-809. doi: 10.7326/0003-4819-139-10-200311180-00007
17. Ren X, Chen Z a., Zheng S, et al. Association between Triglyceride to HDL-C Ratio (TG/HDL-C) and Insulin Resistance in Chinese Patients with Newly Diagnosed Type 2 Diabetes Mellitus. PLoS One. 2016;11(4):e0154345. doi: 10.1371/journal.pone.0154345
18. Liang J, Fu J, Jiang Y, et al. TriGlycerides and high-density lipoprotein cholesterol ratio compared with homeostasis model assessment insulin resistance indexes in screening for metabolic syndrome in the chinese obese children: a cross section study. BMC Pediatr. 2015;15(1):138. doi: 10.1186/s12887-015-0456-y
19. Giannini C, Santoro N, Caprio S, et al. The Triglyceride-to-HDL Cholesterol Ratio. Diabetes Care. 2011;34(8):1869-1874. doi: 10.2337/dc10-2234
20. Iwani NAKZ, Jalaludin MY, Zin RMWM, et al. Triglyceride to HDL-C Ratio is Associated with Insulin Resistance in Overweight and Obese Children. Sci Rep. 2017;7(1):40055. doi: 10.1038/srep40055
21. Zhou M, Zhu L, Cui X, et al. The triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio as a predictor of insulin resistance but not of β cell function in a Chinese population with different glucose tolerance status. Lipids Health Dis. 2016;15(1):104. doi: 10.1186/s12944-016-0270-z
22. Maturu A, DeWitt P, Kern PA, Rasouli N. The triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio as a predictor of β-cell function in African American women. Metabolism. 2015;64(5):561-565. doi: 10.1016/j.metabol.2015.01.004
23. Yoo D-Y, Kang YS, Kwon EB, Yoo E-G. The triglyceride-to-high density lipoprotein cholesterol ratio in overweight Korean children and adolescents. Ye J, ed. Ann Pediatr Endocrinol Metab. 2017;22(3):158-163. doi: 10.6065/apem.2017.22.3.158
24. Toth P. Triglyceride-rich lipoproteins as a causal factor for cardiovascular disease. Vasc Health Risk Manag. 2016;2016(12):171-183. doi: 10.2147/VHRM.S104369
25. Budoff M. Triglycerides and Triglyceride-Rich Lipoproteins in the Causal Pathway of Cardiovascular Disease. Am J Cardiol. 2016;118(1):138-145. doi: 10.1016/j.amjcard.2016.04.004
26. Ivert T, Malmström H, Hammar N, et al. Cardiovascular events in patients under age fifty with early findings of elevated lipid and glucose levels – The AMORIS study. Vinciguerra M, ed. PLoS One. 2018;13(8):e0201972. doi: 10.1371/journal.pone.0201972
27. Руяткина Л.А., Руяткин Д.С., Землянухина С.А. «Болевые» точки диабетических ангиопатий: фокус на гипертриглицеридемию и возможности фенофибрата // Фарматека. – 2016. – №5(318). – C.14-21. [Rujatkina LA, Rujatkin DS, Zemljanuhina SA. Diabetic angiopathy "painful" points: focus on hypertriglyceridemia and fenofibrate potential. Farmateka. 2016;(5):14-21 (In Russ.)]
28. Аметов А.С., Камынина Л.А., Ахмедова З.А. Глюкозо- и липотоксичность – взаимоотягощающие факторы при сочетании сахарного диабета типа 2 и ожирения // Эндокринология: новости, мнения, обучение. – 2014. – Т.4. – №4. – C.20-23. [Ametov A.S., Kamynina L.A., Akhmedova Z.A. Glyukozo- i lipotoksichnost' – vzaimootyagoshchayushchie faktory pri sochetanii sakharnogo diabeta tipa 2 i ozhireniya. Èndokrinologiâ. Novosti, mneniâ, obučenie. 2014;(4):20-23 (In Russ.)]
29. Guerrero-Romero F, Simental-Mendía LE, González-Ortiz M, et al. The Product of Triglycerides and Glucose, a Simple Measure of Insulin Sensitivity. Comparison with the Euglycemic-Hyperinsulinemic Clamp. J Clin Endocrinol Metab. 2010;95(7):3347-3351. doi: 10.1210/jc.2010-0288
30. Du T, Yuan G, Zhang M, et al. Clinical usefulness of lipid ratios, visceral adiposity indicators, and the triglycerides and glucose index as risk markers of insulin resistance. Cardiovasc Diabetol. 2014;13(1):146. doi: 10.1186/s12933-014-0146-3
31. Simental-Mendía LE, Rodríguez-Morán 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
32. Navarro-González D, Sánchez-Íñigo L, Pastrana-Delgado J, Fernández-Montero A, Martinez JA. Triglyceride–glucose index (TyG index) in comparison with fasting plasma glucose improved diabetes prediction in patients with normal fasting glucose: The Vascular-Metabolic CUN cohort. Prev Med (Baltim). 2016;86:99-105. doi: 10.1016/j.ypmed.2016.01.022
33. 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
34. Salazar J, Bermúdez V, Calvo M, et al. Optimal cutoff for the evaluation of insulin resistance through triglyceride-glucose index: A cross-sectional study in a Venezuelan population. F1000Research. 2018;6:1337. doi: 10.12688/f1000research.12170.3
35. Shin K-A. Triglyceride and Glucose (TyG) Index is a Clinical Surrogate Marker for the Diagnosis of Metabolic Syndrome. Ye J, ed. Biomed Sci Lett. 2017;23(4):348-354. doi: 10.15616/BSL.2017.23.4.348
36. Hameed EK. TyG index a promising biomarker for glycemic control in type 2 Diabetes Mellitus. Diabetes Metab Syndr Clin Res Rev. 2019;13(1):560-563. doi: 10.1016/j.dsx.2018.11.030
37. Kim B, Choi HY, Kim W, 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):e0206994. doi: 10.1371/journal.pone.0206994
38. Zheng S, Shi S, Ren X, et al. Triglyceride glucose-waist circumference, a novel and effective predictor of diabetes in first-degree relatives of type 2 diabetes patients: cross-sectional and prospective cohort study. J Transl Med. 2016;14(1):260. doi: 10.1186/s12967-016-1020-8
39. Er L-K, Wu S, Chou H-H, et al. Triglyceride Glucose-Body Mass Index Is a Simple and Clinically Useful Surrogate Marker for Insulin Resistance in Nondiabetic Individuals. PLoS One. 2016;11(3):e0149731. doi: 10.1371/journal.pone.0149731
40. Wang B, Zhang M, Liu Y, et al. Utility of three novel insulin resistance-related lipid indices for predicting type 2 diabetes mellitus among people with normal fasting glucose in rural China. J Diabetes. 2018;10(8):641-652. doi: 10.1111/1753-0407.12642
41. Tohidi M, Baghbani-Oskouei A, Ahanchi NS, et al. Fasting plasma glucose is a stronger predictor of diabetes than triglyceride–glucose index, triglycerides/high-density lipoprotein cholesterol, and homeostasis model assessment of insulin resistance: Tehran Lipid and Glucose Study. Acta Diabetol. 2018;55(10):1067-1074. doi: 10.1007/s00592-018-1195-y
42. Salazar J, Bermúdez V, Olivar LC, et al. Insulin resistance indices and coronary risk in adults from Maracaibo city, Venezuela: A cross sectional study. F1000Research. 2018;7:44. doi: 10.12688/f1000research.13610.1
43. Kim SH, Reaven G. Sex Differences in Insulin Resistance and Cardiovascular Disease Risk. J Clin Endocrinol Metab. 2013;98(11):E1716-E1721. doi: 10.1210/jc.2013-1166
44. Mazidi M, Gao H, Kengne AP. Lipid accumulation product and visceral adiposity index are associated with dietary patterns in adult Americans. Medicine (Baltimore). 2018;97(19):e0322. doi: 10.1097/MD.0000000000010322
45. Yang R-F, Zhang H, Wang Z, Liu X-Y, Lin Z. A study on the relationship between waist phenotype, hypertriglyceridemia, coronary artery lesions and serum free fatty acids in adult and elderly patients with coronary diseases. Immun Ageing. 2018;15(1):14. doi: 10.1186/s12979-018-0119-6
46. Chen C, Dai J-L. Triglyceride to high-density lipoprotein cholesterol (HDL-C) ratio and arterial stiffness in Japanese population: a secondary analysis based on a cross-sectional study. Lipids Health Dis. 2018;17(1):130. doi: 10.1186/s12944-018-0776-7
47. Ohkuma T, Ninomiya T, Tomiyama H, et al. Brachial-Ankle Pulse Wave Velocity and the Risk Prediction of Cardiovascular Disease. Hypertension. 2017;69(6):1045-1052. doi: 10.1161/HYPERTENSIONAHA.117.09097
48. Chi C, Teliewubai J, Lu Y-Y, et al. Comparison of various lipid parameters in association of target organ damage: a cohort study. Lipids Health Dis. 2018;17(1):199. doi: 10.1186/s12944-018-0800-y
49. Cao X, Wang D, Zhou J, Chen Z. Comparison of lipoprotein derived indices for evaluating cardio-metabolic risk factors and subclinical organ damage in middle-aged Chinese adults. Clin Chim Acta. 2017;475:22-27. doi: 10.1016/j.cca.2017.09.014
50. Osei K, Gaillard T. Disparities in Cardiovascular Disease and Type 2 Diabetes Risk Factors in Blacks and Whites: Dissecting Racial Paradox of Metabolic Syndrome. Front Endocrinol (Lausanne). 2017;8:204. doi: 10.3389/fendo.2017.00204
51. Dal Canto E, Farukh B, Faconti L. Why are there ethnic differences in cardio-metabolic risk factors and cardiovascular diseases? JRSM Cardiovasc Dis. 2018;7:204800401881892. doi: 10.1177/2048004018818923
Supplementary files
Review
For citations:
Ruyatkina L.A., Ruyatkin D.S., Iskhakova I.S. Opportunities and options for surrogate assessment of insulin resistance. Obesity and metabolism. 2019;16(1):27-33. (In Russ.) https://doi.org/10.14341/omet10082
Views:
3040
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).
Email this article 
