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The triglyceride-glucose index, an insulin resistance marker in newborns?

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Abstract

The study aims to assess the utility of the triglyceride-glucose index (TyG) as a marker of insulin resistance (IR) in neonates. TyG and the homeostatic model assessment (HOMA-IR) values were compared in 196 singleton, term normoweight and without distress newborns. A Decision Tree procedure (CHAID) was used to classify cases into groups or predict values of a dependent (Ln HOMA-IR) variable. Three nodes were drawn for TyG: ≤ 6.7, > 6.7–7.8 and > 7.8 (p < 0.0001; F = 20.52). The predictability of those TyG values vs HOMA-IR was statistically significant (p < 0.0001). It was neither affected by gender (p = 0.084), glucose challenge test (p = 0.138) classifications nor by the TyG node* glucose challenge test and TyG node*gender interactions (p = 0.456 and p = 0.209, respectively). Glucose, HOMA-IR, and the triglyceride/HDL cholesterol ratio increased progressively from node 1 to 3 for TyG while QUICKI decreased.

Conclusion: In conclusion, TyG appears to be a suitable tool for identifying IR at birth, justifying the further insulin determination in those neonates. TyG ≥ 7.8 is recommended as cut-off point in neonates. The need for a follow-up study to confirm the TyG as early IR marker is desirable.

What is Known

HOMA-IR and the triglyceride-glucose index (TyG) show a high correlation.

The TyG has been used as an insulin resistance marker in adults.

What is New

This is the first study where TyG has been assessed in neonates.

TyG appears to be a suitable and cheap tool for identifying insulin resistance at birth.

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Abbreviations

CHAID:

Chi-squared automatic interaction detection

GDM:

Gestational diabetes mellitus

GH:

Growth hormone

HDLc:

High density lipoprotein cholesterol

HOMA-IR:

Homeostatic model assessment-insulin resistance

IGF-1:

Insulin-like growth factor 1

IGT:

Impaired glucose tolerance

IR:

Insulin resistance

MS:

Metabolic syndrome

QUICKI:

Quantitative insulin sensitivity check index

T2DM:

Type 2 diabetes mellitus

TG:

Triglycerides

TyG:

Triglyceride-glucose index

References

  1. Abbasi F, Reaven GM (2011) Comparison of two methods using plasma triglyceride concentration as a surrogate estimate of insulin action in nondiabetic subjects: triglycerides × glucose versus triglyceride/high-density lipoprotein cholesterol. Metabolism 60(12):1673–1676. https://doi.org/10.1016/j.metabol.2011.04.006

    Article  CAS  PubMed  Google Scholar 

  2. Al-Hamad D, Raman V (2017) Metabolic syndrome in children and adolescents. Transl Pediatr 6(4):397–407. https://doi.org/10.21037/tp.2017.10.02

    Article  PubMed  PubMed Central  Google Scholar 

  3. Bastida S, Sánchez-Muniz FJ, Cuesta C, Perea S, Aragonés A (1997) Male and female cord blood lipoprotein profile differences throughout the term-period. J Perinat Med 25(2):184–191. https://doi.org/10.1515/jpme.1997.25.2.184

    Article  CAS  PubMed  Google Scholar 

  4. Gesteiro E, Bastida S, Sánchez-Muniz FJ (2009) Insulin resistance markers in term, normoweight neonates. The Mérida cohort. Eur J Pediatr 168:281–288

    Article  CAS  PubMed  Google Scholar 

  5. Gesteiro E, Bastida S, Sánchez-Muniz FJ (2011) Effects of maternal glucose tolerance, pregnancy diet quality and neonatal insulinemia upon insulin resistance/sensitivity biomarkers in normoweight neonates. Nutr Hosp 26:1447–1455

    CAS  PubMed  Google Scholar 

  6. Gesteiro E, Bastida S, Sánchez-Muniz FJ (2013) Cord-blood lipoproteins, homocysteine, insulin sensitivity/resistance marker profile, and concurrence of dysglycaemia and dyslipaemia in full-term neonates of the Merida study. Eur J Ped 172:883–894

    Article  CAS  Google Scholar 

  7. Gesteiro E, Rodríguez Bernal B, Bastida S, Sánchez-Muniz FJ (2012) Maternal diets with low healthy eating index or Mediterranean diet adherence scores are associated with high cord-blood insulin levels and insulin resistance markers at birth. Eur J Clin Nutr 66(9):1008–1015. https://doi.org/10.1038/ejcn.2012.92

    Article  CAS  PubMed  Google Scholar 

  8. Gesteiro E, Sánchez-Muniz FJ, Bastida S (2017) Hypercortisolaemia and hyperinsulinaemia interaction and their impact upon insulin resistance/sensitivity markers at birth. In: Mauricio AC (ed) Blood banking for clinical application and regenerative medicine. InTech. Rijeka, Croatia, pp 69–98

    Google Scholar 

  9. Gesteiro E, Sánchez-Muniz FJ, Ortega-Azorín C, Guillén M, Corella D, Bastida S (2016) Maternal and neonatal FTO rs9939609 polymorphism affect insulin sensitivity markers and lipoprotein profile at birth in appropriate-for-gestational-age term neonates. J Physiol Biochem 72(2):169–181. https://doi.org/10.1007/s13105-016-0467-7

    Article  CAS  PubMed  Google Scholar 

  10. Guerrero Romero F, Simental Mendia LE, Gonzalez Ortiz M, Martinez Abundis E, Ramos Zavala MG, Hernandez Gonzalez SO et al (2010) The product of triglycerides and glucose, a simple measure of insulin sensitivity. Comparison with the euglycemic-hyperinsulinemic clamp. J Clin Endocrinol Metab 95(7):3347–3351. https://doi.org/10.1210/jc.2010-0288

    Article  CAS  PubMed  Google Scholar 

  11. Higgins V, Adeli K (2017) Pediatric metabolic syndrome: pathophysiology and laboratory assessment. EJIFCC 28(1):25–42

    PubMed  PubMed Central  Google Scholar 

  12. Irace C, Carallo C, Scavelli FB, De Franceschi MS, Esposito T, Tripolino C, Gnasso A (2013) Markers of insulin resistance and carotid atherosclerosis. A comparison of the homeostasis model assessment and triglyceride glucose index. Int J Clin Pract 67(Suppl. 7):665–672. https://doi.org/10.1111/ijcp.12124

    Article  CAS  PubMed  Google Scholar 

  13. Janghorbani M, Almasi SZ, Amini M (2015) The product of triglycerides and glucose in comparison with fasting plasma glucose did not improve diabetes prediction. Acta Diabetol 52(4):781–788. https://doi.org/10.1007/s00592-014-0709-5

    Article  CAS  PubMed  Google Scholar 

  14. de Jong M, Cranendonk A, van Weissenbruch MM (2015) Components of the metabolic syndrome in early childhood in very-low-birth-weight infants and term small and appropriate for gestational age infants. Pediatr Res 78:457–461

    Article  PubMed  Google Scholar 

  15. Kim JW, Park SH, Kim Y, Im M, Han HS (2016) The cutoff values of indirect indices for measuring insulin resistance for metabolic syndrome in Korean children and adolescents. Ann Pediatr Endocrinol Metab 21(3):143–148. https://doi.org/10.6065/apem.2016.21.3.143

    Article  PubMed  PubMed Central  Google Scholar 

  16. Lissau I, Overpeck MD, Ruan WJ, Due P, Holstein BE, Hediger ML, Health behaviour in school-aged children obesity Working Group (2004) Body mass index and overweight in adolescents in 13 European countries, Israel, and the United States. Arch Pediatr Adolesc Med 158(1):27–33. https://doi.org/10.1001/archpedi.158.1.27

    Article  PubMed  Google Scholar 

  17. Mohd Nor NS, Lee S, Bacha F, Tfayli H, Arslanian S (2016) Triglyceride glucose index as a surrogate measure of insulin sensitivity in obese adolescents with normoglycemia, prediabetes, and type 2 diabetes mellitus: comparison with the hyperinsulinemic-euglycemic clamp. Pediatr Diabetes 17(6):458–465. https://doi.org/10.1111/pedi.12303

    Article  CAS  PubMed  Google Scholar 

  18. Muniyappa R, Lee S, Chen H, Quon MJ (2008) Current approaches for assessing insulin sensitivity and resistance in vivo: advantages, limitations, and appropriate usage. Am J Physiol Endocrinol Metab 294(1):E15–E26. https://doi.org/10.1152/ajpendo.00645.2007

    Article  CAS  PubMed  Google Scholar 

  19. Navarro-González D, Sánchez-Íñigo L, Pastrana-Delgado J, Fernández-Montero A, Martinez JA (2016) 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 86:99–105

    Article  PubMed  Google Scholar 

  20. Nielsen JH, Haase TN, Jaksch C, Nalla A, Søstrup B, Nalla AA, Larsen L, Rasmussen M, Dalgaard LT, Gaarn LW, Thams P, Kofod H, Billestrup N (2014) Impact of fetal and neonatal environment on beta cell function and development of diabetes. Acta Obstet Gynecol Scand 93(11):1109–1122. https://doi.org/10.1111/aogs.12504

    Article  PubMed  Google Scholar 

  21. O’Sullivan BA, Henderson ST, Davis JM (1998) Gestational diabetes. JAm Pharm Assoc (Wash) 38(3):364–371; quiz 372-373. https://doi.org/10.1016/S1086-5802(16)30332-1

    Article  Google Scholar 

  22. Plagemann A (2005) Perinatal programming and functional teratogenesis: impact on body weight regulation and obesity. Physiol Behav 86(5):661–668. https://doi.org/10.1016/j.physbeh.2005.08.065

    Article  CAS  PubMed  Google Scholar 

  23. Rodríguez-Morán M, Simental-Mendía LE, Guerrero-Romero F (2017) The triglyceride and glucose index is useful for recognising insulin resistance in children. Acta Paediatr 106(6):979–983. https://doi.org/10.1111/apa.13789

    Article  PubMed  Google Scholar 

  24. Sánchez-Íñigo L, Navarro-González D, Fernández-Montero A, Pastrana-Delgado J, Martínez JA (2016) The TyG index may predict the development of cardiovascular events. Eur J Clin Investig 46(2):189–197. https://doi.org/10.1111/eci.12583

    Article  Google Scholar 

  25. Sánchez-Muniz FJ, Gesteiro E, Espárrago Rodilla M, Rodríguez Bernal B, Bastida S (2013) Maternal nutrition during pregnancy conditions the fetal pancreas development, hormonal status and diabetes mellitus and metabolic syndrome biomarkers at birth. Nutr Hosp 28:250–274

    PubMed  Google Scholar 

  26. Singh B, Saxena A (2010) Surrogate markers of insulin resistance: a review. World J Diabetes 1(2):36–47. https://doi.org/10.4239/wjd.v1.i2.36

    Article  PubMed  PubMed Central  Google Scholar 

  27. Unger G, Benozzi SF, Perruzza F, Pennacchiotti GL (2014) Triglycerides and glucose index: a useful indicator of insulin resistance. Endocrinol Nutr 61(10):533–540. https://doi.org/10.1016/j.endonu.2014.06.009

    Article  PubMed  Google Scholar 

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Acknowledgements

We thank the Gynaecology and Obstetrics Department and Laboratory Services of Mérida Hospital (Extremadura, Spain) and participant mothers and neonates.

Funding

Partially supported by the Spanish Project AGL 2014-53207-C2-2-R.

Author information

Authors and Affiliations

Authors

Contributions

E Gesteiro contributed to the data acquisition, analysis, discussion and writing of the paper; FJ Sánchez-Muniz contributed to the study design, data discussion, writing of the paper and is the corresponding author and guarantor of the paper; S Bastida contributed to the study design and data discussion; L Barrios has contributed to the design and discussion of the statistical study.

Corresponding author

Correspondence to Francisco J Sánchez-Muniz.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Informed consent

The study performed in accordance with the Helsinki Declaration of 1975 as revised in year 2000, following approval by the Management and Ethical Committee of the Hospital. Data were obtained from an anonymous hospital screening record.

Nonetheless, informed consent is available from 35 mothers whose pregnancy diet was studied and wished to be engaged in a follow-up study.

Additional information

Communicated by Mario Bianchetti

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Cite this article

Gesteiro, E., Bastida, S., Barrios, L. et al. The triglyceride-glucose index, an insulin resistance marker in newborns?. Eur J Pediatr 177, 513–520 (2018). https://doi.org/10.1007/s00431-018-3088-z

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  • DOI: https://doi.org/10.1007/s00431-018-3088-z

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