Associations between Surrogate Insulin Resistance Indices and the Risk of Metabolic Syndrome in Children
A well-defined insulin resistance (IR) is one of the requirements for the good understanding and evaluation of metabolic syndrome (MetS). However, underlying causes for the development of IR are not clear. Endothelial dysfunction also participates in the pathogenesis of this disease. IR indices are being determined in various obesity groups and also in diagnosing MetS. Components of MetS have been well established and used in adult studies. However, there are some ambiguities particularly in the field of pediatrics. The aims of this study were to compare the performance of fasting blood glucose (FBG), one of MetS components, with some other IR indices and check whether FBG may be replaced by some other parameter or ratio for a better evaluation of pediatric MetS. Five-hundred and forty-nine children were involved in the study. Five groups were constituted. Groups 109, 40, 100, 166, 110, 24 children were included in normal-body mass index (N-BMI), overweight (OW), obese (OB), morbid obese (MO), MetS with two components (MetS2) and MetS with three components (MetS3) groups, respectively. Age and sex-adjusted BMI percentiles tabulated by World Health Organization were used for the classification of obesity groups. MetS components were determined. Aside from one of the MetS components-FBG, eight measures of IR [homeostatic model assessment of IR (HOMA-IR), homeostatic model assessment of beta cell function (HOMA-%β), alanine transaminase-to-aspartate transaminase ratio (ALT/AST), alanine transaminase (ALT), insulin (INS), insulin-to-FBG ratio (INS/FBG), the product of fasting triglyceride and glucose (TyG) index, McAuley index] were evaluated. Statistical analyses were performed. A p value less than 0.05 was accepted as the statistically significance degree. Mean values for BMI of the groups were 15.7 kg/m2, 21.0 kg/m2, 24.7 kg/m2, 27.1 kg/m2, 28.7 kg/m2, 30.4 kg/m2 for N-BMI, OW, OB, MO, MetS2, MetS3, respectively. Differences between the groups were significant (p < 0.001). The only exception was MetS2-MetS3 couple, in spite of an increase detected in MetS3 group. Waist-to-hip circumference ratios significantly differed only for N-BMI vs, OB, MO, MetS2; OW vs MO; OB vs MO, MetS2 couples. ALT and ALT/AST did not differ significantly among MO-MetS2-MetS3. HOMA-%β differed only between MO and MetS2. INS/FBG, McAuley index and TyG were not significant between MetS2 and MetS3. HOMA-IR and FBG were not significant between MO and MetS2. INS was the only parameter, which showed statistically significant differences between MO-MetS2, MO-MetS3, and MetS2-MetS3. In conclusion, these findings have suggested that FBG presently considered as one of the five MetS components, may be replaced by INS during the evaluation of pediatric morbid obesity and MetS.
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 V. Higgins, and K. Adeli, “Pediatric metabolic syndrome: pathophysiology and laboratory assessment,” J. Int. Fed. Clin. Chem. Lab. Med., vol. 28, pp. 25-42, March 2017.
 T. T. K. Huang, S. S. Sun, and S. R. Daniels, “Understanding the nature of metabolic syndrome components in children and what they can and cannot do to predict adult disease,” J. Pediatr, vol.155, pp. e13-e14, Sept. 2009.
 T. T. K. Huang, “Finding thresholds of risk for components of the pediatric metabolic syndrome,” J. Pediatr., vol.152, pp.158-159, Feb. 2008.
 E. S. Ford, and C. Li, “Defining the metabolic syndrome in children and adolescents: Will the real definition please stand up?,” J. Pediatr., vol.152, pp. 160-164, Feb. 2008.
 R. Weiss, A. A. Bremer, R. H. Lustig, “What is metabolic syndrome, and why are children getting it?,” Ann. N. Y. Acad. Sci., vol.1281, pp.123-140, Apr. 2013.
 A. M. Freeman, K. Soman-Faulkner, and N. Pennings, Insulin resistance. NCBI Bookshelf, StatPearls Publishing LLC Jan. 2019.
 V. M. Tagi, “Insulin resistance in children,” Front. Endocrinol. (Lausanne), vol.10, pp.342, Jun.2019.
 D. R. Matthews, J. P. Hosker, A.S. Rudenski, B. A. Naylor, D. F. Treacher, R. C. Turner, “Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man.”, Diabetologia, vol. 28, no. 7, pp. 412–419, Jul. 1985.
 M. K. Kim, C. W. Ahn, S. Kang, J. S. Nam, K. R. Kim, and J. S. Park, Relationship between the triglyceride glucose index and coronary artery calcification in Korean adults. Cardiovasc. Diabetol., 16(1):108, Aug. 2017.
 J. H. Park, S. H. Kim, S. Park, and M. J. Park, “Alanine aminotransferase and metabolic syndrome in adolescents: The Korean National Health and Nutrition Examination Survey Study,” Ped. Obesity, vol. 9, pp. 411-418, 2013.
 L. Zhao, J. Cheng, Y. Chen, Q. Li, B. Han, Y. Chen, F. Xia, C. Chen, D. Lin, X. Yu, N. Wang, and Y. Lu, “Serum alanine aminotransferase/aspartate aminotransferase ratio is one of the best markers of insulin resistance in the Chinese population,” Nutr. Metab. (Lond.), vol. 14, pp. 64, Oct. 2017.
 S. Moon, J. H. Park, E. J. Jang, Y. K. Park, J. M. Yu, J. S. Park,Y. Ahn, S. H. Choi, and H. J. Yoo, “The cut-off values of surrogate measures for insulin sensitivity in a healthy population in Korea according to the Korean National Health and Nutrition Examination Survey (KNHANES) 2007-2010,” J. Korean Med. Sci., vol.33, no.29, pp.e197, Jul. 2018.
 Q. Tang, X. Li, P. Song, and L. Xu, “Optimal cut-off values for the homeostasis model assessment of insulin resistance (HOMA-IR) and pre-diabetes screening: Developments in research and prospects for the future,” Drug Discov. Ther., vol.9, pp.380-385, Dec. 2015.
 S. H. Khan, A. N. Khan, N. Chaudhry, R. Anwar, N. Fazal, M. Tariq, “Comparison of various steady state surrogate insulin resistance indices in diagnosing metabolic syndrome,” Diabetol. Metab. Syndr., vol. 11, pp.44, 2019.
 L. Zhang, X. Ma, Z. Jiang, K. Zhang, M. Zhang, Y. Li, X. Zhao, and H. Xiong, “Liver enzymes and metabolic syndrome: a large-scale case-control study,” Oncotarget, vol.6, no. 29, pp. 26782-26788, Sept. 2015.
 C. F. Liu, W. N. Zhou, Z. Lu, X. T. Wang, and Z. H. Qiu, “The associations between liver enzymes and the risk of metabolic syndrome,” Exp. Gerontol., vol. 106, pp.132-136, Feb. 2018.
 R. Kawamoto, K. Kohara, T. Kusunoki, Y. Tabara, M. Abe, and T. Miki, “Alanine aminotransferase/aspartate aminotransferase ratio is the best surrogate marker for insulin resistance in non-obese Japanese adults,” Cardiovasc. Diabetol., vol. 11, pp.117, Oct. 2012.
 World Health Organization (WHO). The WHO Child Growth Standards. Available at: http://www.who.int/childgrowth/en/ Accessed on June 10, 2016.
 P. Zimmet, K. G. Alberti, F. Kaufman, N. Tajima, M. Silink, S. Arslanian, G. Wong, P. Bennett, J. Shaw, S. Caprio, and IDF consensus group, “The metabolic syndrome in children and adolescents- an IDF consensus report”, Pediatr. Diabetes, vol. 8, no. 5, pp. 299 - 306, Oct. 2007.
 T. J. Kim, H. J. Kim, Y. B. Kim, J. Y. Lee, H. S. Lee, J. H. Hong, and J. W. Lee, “Comparison of surrogate markers as measures of uncomplicated insulin resistance in Korean adults,” Korean J. Fam. Med.,vol. 37, no. 3, pp. 188-196, May. 2016.
 G. Ramirez-Lopez, S. Moran-Villota, F. Mendoza-Carrera, E. Portilla-de Buen, V. Valles-Sanchez, X. H. Castro-Martinez, J. Sanchez-Corona, and J. Salmeron, “Metabolic and genetic markers’ associations with elevated levels of alanine aminotransferase in adolescents,” J. Pediatr. Endocrinol. Metab., vol. 31, no. 4, pp. 407-414, 2018.
 S. S. Kwon, S. G. Lee, “A high alanine aminotransferase/aspartate aminotransferase ratio determines insulin resistance and metabolically healthy/unhealthy obesity in a general adult population in Korea: The Korean National Health and Nutrition Examination Survey 2007-2010,”Exp. Clin. Endocrinol. Diabetes, Oct. 2018 (E-pub ahead of print).