RETN Gene Single Nucleotide Polymorphism Profile on Triglyceride-Glucose Index as Insulin Resistance Proxy Among Cohort Population of Non-Communicable Diseases in Bogor
Keywords:Cohort, Diabetes Melitus, Resistin, Single Nucleotide Polymorphism, Triglyceride-Glucose index
AbstractGenetic factors such as single nucleotide polymorphisms (SNPs) are thought to contribute to the increasing incidence of diabetes mellitus (DM) through insulin resistance. SNPs in the RETN (resistin) gene encoding the resistin protein have been reported to play a role in causing abnormalities in blood glucose and lipid metabolism. Still, studies related to this have rarely been explored in cohort population models. This study aimed to evaluate the relationship of resistin gene SNPs to the trend of the triglyceride-glucose index (TyG) as a proxy for insulin resistance. The data were obtained from the results of the biomedical laboratory examination among participants of a cohort study in the Kebon Kalapa subdistrict, Bogor, every odd year period between 2015-2021 and from RETN genotyping (rs3745367). The generalized linear model (GLM) repeated measurement technique was used with the TyG index value as the dependent variable. The results of the GLM analysis showed that although there was a significant difference in the trend of the TyG index between the observation periods [F(2,87, 1671,1)=41,10, p-value <0.001], that’s not the case for RETN gene SNP [F(5,73, 1671,1) = 1.09, p-value = 0.367]. However, the multivariate test results suggested the association of these SNPs with age and DM status [F(4, 583)=2.48, p-value = 0.043]. In conclusion, RETN gene SNPs may require interaction with other factors or genes to induce insulin resistance or act by indirect glucose–fatty acid metabolic cycle mechanisms.
Misra A, Gopalan H, Jayawardena R, Hills AP, Soares M, Reza-Albarrán AA, et al. Diabetes in developing countries. J Diabetes. 2019;11(7):522–39.
Lin X, Xu Y, Pan X, Xu J, Ding Y, Sun X, et al. Global, regional, and national burden and trend of diabetes in 195 countries and territories: an analysis from 1990 to 2025. Sci Rep [Internet]. 2020;10(1):1–11. Available from: https://doi.org/10.1038/s41598-020-71908-9
Mambiya M, Shang M, Wang Y, Li Q, Liu S, Yang L, et al. The Play of Genes and Non-genetic Factors on Type 2 Diabetes. Front Public Heal. 2019;7(November):1–8.
Sun W, Yao S, Tang J, Liu S, Chen J, Deng D, et al. Integrative analysis of super enhancer SNPs for type 2 diabetes. PLoS One. 2018;13(1):1–16.
Liao WL, Tsai FJ. Personalized medicine in type 2 diabetes. Biomed. 2014;4(2):1–8.
Vardarlı AT, Harman E, Çetintaş VB, Kayıkçıoğlu M, Vardarlı E, Zengi A, et al. Polymorphisms of lipid metabolism enzyme-coding genes in patients with diabetic dyslipidemia. Anatol J Cardiol. 2017;17(4):313–21.
Samuel VT, Shulman GI. The pathogenesis of insulin resistance: Integrating signaling pathways and substrate flux. J Clin Invest. 2016;126(1):12–22.
Sharma VR, Matta ST, Haymond MW, Chung ST. Measuring Insulin Resistance in Humans. Horm Res Paediatr. 2021;93(11–12):577–88.
Buchanan TA, Watanabe RM, Xiang AH. Limitations in surrogate measures of insulin resistance. J Clin Endocrinol Metab. 2010;95(11):4874–6.
Lee DY, Lee ES, Kim JH, Park SE, Park C, Oh K, et al. Predictive Value of Triglyceride Glucose Index for the Risk of Incident Diabetes : A 4-Year Retrospective Longitudinal Study. 2016;1–14.
Adriana S, Mancillas-adame L, Gonz V, Alejandro D, Solis RC, Alvarez-villalobos NA, et al. Diagnostic Accuracy of the Triglyceride and Glucose Index for Insulin Resistance : A Systematic Review. 2020;2020.
Aman M, Resnawita D, Rasyid H, Kasim H, Bakri S, Umar H, et al. The concordance of triglyceride glucose index (TyG index) and homeostatic model assessment for insulin resistance (Homa-IR) in non-diabetic subjects of adult Indonesian males. Clin Epidemiol Glob Heal [Internet]. 2021;9(September 2020):227–30. Available from: https://doi.org/10.1016/j.cegh.2020.09.003
Costanza MC, Beer-Borst S, James RW, Gaspoz JM, Morabia A. Consistency between cross-sectional and longitudinal SNP: Blood lipid associations. Eur J Epidemiol. 2012;27(2):131–8.
Morris AP, Voight BF, Teslovich TM, Ferreira T, Segrè A V., Steinthorsdottir V, et al. Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat Genet. 2012;44(9):981–90.
Simental-Mendía LE, Guerrero-Romero F. The correct formula for the triglycerides and glucose index. Eur J Pediatr. 2020;179(7):1171.
Armstrong RA. TESTING AND CORRECTING FOR SPHERICITY AND USE OF MANOVA AND. :1–19.
Chung CM, Lin TH, Chen JW, Leu HB, Yin WH, Ho HY, Sheu SH, Tsai WC, Chen JH, Lin SJ PW. Common quantitative trait locus downstream of RETN gene identified by genome-wide association study is associated with risk of type 2 diabetes mellitus in Han Chinese: a Mendelian randomization effect. Diabetes Metab Res Rev [Internet]. 2014;30(3):232–40. Available from: http://www.heartcenter.org.tw/ch/wp-content/uploads/2015/03/Referred-paper-No.-75.pdf
rs3745367 RefSNP Report - dbSNP - NCBI [Internet]. [cited 2022 Feb 10]. Available from: https://www.ncbi.nlm.nih.gov/snp/rs3745367
Huang T, Shu Y, Cai YD. Genetic differences among ethnic groups. BMC Genomics [Internet]. 2015;16(1):1–10. Available from: http://dx.doi.org/10.1186/s12864-015-2328-0
Salazar J, Bermúdez V, Calvo M, Olivar LC, 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. F1000Research. 2017;6:1337.
Moon S, Park JS, Ahn Y. The Cut-off Values of Triglycerides and Glucose Index for Metabolic Syndrome in American and Korean Adolescents. J Korean Med Sci. 2017;32(3):427–33.
Endukuru CK, Gaur GS, Yerrabelli D, Sahoo J, Vairappan B. Cut-off values and clinical utility of surrogate markers for insulin resistance and beta-cell function to identify metabolic syndrome and its components among southern indian adults. J Obes Metab Syndr. 2021;29(4):281–91.
Perkumpulan Endokrinologi Indonesia (PERKENI). Pedoman Pengelolaan dan Pencegahan Diabetes Melitus Tipe 2 Dewasa di Indonesia 2020. (2020). PB PERKENI. PERKENI [Internet]. 2020;46. Available from: https://pbperkeni.or.id/wp-content/uploads/2021/11/22-10-21-Website-Pedoman-Pengelolaan-dan-Pencegahan-DMT2-Ebook.pdf
Salmon AB. Oxidative stress in the etiology of age-associated decline in glucose metabolism. Longev Heal. 2012;1(1):1–8.
Lakens D. Calculating and reporting effect sizes to facilitate cumulative science: A practical primer for t-tests and ANOVAs. Front Psychol. 2013;4(NOV):1–12.
Kale HE, Tekindal MA. Comparison of Test Statistics of Nonnormal and Unbalanced Samples for Multivariate Analysis of Variance in terms of Type-I Error Rates. 2019;2019.
Galaviz KI, Narayan KMV, Lobelo F, Weber MB. Lifestyle and the Prevention of Type 2 Diabetes: A Status Report. Am J Lifestyle Med. 2018;12(1):4–20.
Sacks M. F, Carey J. V, Anderson A. M. C, Miller III R. E, Copeland T, Charleston J, et al. Effects of High vs Low Glycemic Index of Dietary Carbohydrate on Cardiovascular Disease Risk Factors and Insulin Sensitivity. JAMA - J Am Med Assoc [Internet]. 2014;312(23):2531–41. Available from: https://pubmed.ncbi.nlm.nih.gov/25514303/
Kim KS, Kim SJ, Kim S, Choi D, Ju YJ, Park E. Association of self-reported sedentary time with insulin resistance among Korean adults without diabetes mellitus : a cross- sectional study. 2018;1–8.
Tiwari A, Kumar D, Ansari MS, Chaubey SK, Gupta NR, Agarwal V, et al. Impact of lockdown on self-care management among patients with type 2 Diabetes Mellitus residing in Lucknow city, India – A cross-sectional study. Clin Epidemiol Glob Heal [Internet]. 2021;10(February):100703. Available from: https://doi.org/10.1016/j.cegh.2021.100703
Lau CH, Muniandy S. Lack of evidence for intermolecular epistatic interactions between adiponectin and resistin gene polymorphisms in Malaysian male subjects. Genet Mol Biol. 2012;35(1):38–44.
Kumar D, Lee B, Puan KJ, Lee W, Luis BS, Yusof N, et al. Resistin expression in human monocytes is controlled by two linked promoter SNPs mediating NFKB p50/p50 binding and C-methylation. Sci Rep. 2019;9(1):1–16.
Tarkowski A, Bjersing J, Shestakov A, Bokarewa MI. Resistin competes with lipopolysaccharide for binding to toll-like receptor 4. J Cell Mol Med. 2010;14(6 B):1419–31.
Gerrits AJ, Gitz E, Koekman CA, Visseren FL, van Haeften TW, Akkerman JWN. Induction of insulin resistance by the adipokines resistin, leptin, plasminogen activator inhibitor-1 and retinol binding protein 4 in human megakaryocytes. Haematologica. 2012;97(8):1149–57.
Wang T, Huang T, Zheng Y, Rood J, Bray GA, Sacks FM QL. Genetic variation of fasting glucose and changes in glycemia in response to 2-year weight-loss diet intervention: the POUNDS Lost trial. Int J Obes [Internet]. 2016;40(7):1164–9. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4935586/pdf/nihms-759150.pdf
Samuel VT, Shulman GI. Mechanisms for insulin resistance: Common threads and missing links. Cell [Internet]. 2012;148(5):852–71. Available from: http://dx.doi.org/10.1016/j.cell.2012.02.017
Kumar V, Singh J, Bala K, Singh J. Association of resistin (rs3745367) and urotensin II (rs228648 and rs2890565) gene polymorphisms with risk of type 2 diabetes mellitus in Indian population. Mol Biol Rep [Internet]. 2020;47(12):9489–97. Available from: https://doi.org/10.1007/s11033-020-05991-6
Lee SB, Ahn CW, Lee BK, Kang S, Nam JS, You JH, et al. Association between triglyceride glucose index and arterial stiffness in Korean adults. Cardiovasc Diabetol [Internet]. 2018;17(1):11–6. Available from: https://doi.org/10.1186/s12933-018-0692-1
Zook JM, Chapman B, Wang J, Mittelman D, Hofmann O, Hide W, et al. Integrating human sequence data sets provides a resource of benchmark SNP and indel genotype calls. Nat Biotechnol. 2014;32(3):246–51.
Elkhattabi L, Morjane I, Charoute H, Amghar S, Bouafi H, Elkarhat Z, et al. In silico analysis of coding/noncoding SNPs of human RETN gene and characterization of their impact on resistin stability and structure. J Diabetes Res. 2019;2019.
How to Cite
All articles submitted by the author and published in the Jurnal Profesi Medika : Jurnal Kedokteran dan Kesehatan, are fully copyrighted by the publication of Jurnal Profesi Medika : Jurnal Kedokteran dan Kesehatan under the Creative Commons Attribution-NonCommercial 4.0 International License by technically filling out the copyright transfer agreement and sending it to the publisher
The author can include in separate contractual arrangements for the non-exclusive distribution of rich versions of journal publications (for example: posting them to an institutional repository or publishing them in a book), with the acknowledgment of their initial publication in this journal.
Authors are permitted and encouraged to post their work online (for example: in an institutional repository or on their website) before and during the submission process because it can lead to productive exchanges, as well as earlier and more powerful citations of published works. (See Open Access Effects).