Determination of the association of some polymorphisms with metabolic syndrome in residents of the city of Nur-Sultan

Kamshat Akhmetova 1 2 * , Tamara Vochshenkova 1, Erbolat Dalenov 2, Aigul Abduldayeva 2, Talapbek Azhenov 3
More Detail
1 Сenter of Gerontology, Medical Centre Hospital of President’s Affairs Administration of the Republic of Kazakhstan, Nur-Sultan, Kazakhstan
2 Department of Preventive Medicine and Nutrition, Astana Medical University, Nur-Sultan, Kazakhstan
3 Surgical department №1, Medical Centre Hospital of President’s Affairs Administration of the Republic of Kazakhstan, Nur-Sultan, Kazakhstan
* Corresponding Author
J CLIN MED KAZ, Volume 18, Issue 6, pp. 76-80. https://doi.org/10.23950/jcmk/11391
OPEN ACCESS
Download Full Text (PDF)

ABSTRACT

Aim: Metabolic syndrome develops as a result of a combined effect of environmental factors and genetics. Therefore, this study is an attempt to detect polymorphisms that influence the development of metabolic syndrome among people of reproductive age in the case of Nur-Sultan.
Material and methods:128 polymorphisms were selected from those involved in metabolic disorders in other studied populations; further, their effect on developing metabolic syndrome in the focused group was studied. The study involved 717 respondents aged 18 to 49 with an average age of 40.2 years. Out of them, 243 participants were diagnosed with metabolic syndrome with IDF criteria.
Results: Based on the study results, five polymorphisms that influence the development of metabolic syndrome were found: rs7903146, rs157582, rs 4506565, rs7578597, rs4072037. T allele in polymorphisms as rs 7903146 ​​- 1.56 (СI 1.14-2.14; p = 0.004), rs 157582 - 1.54 (СI 1.16-2.04; p = 0.001), rs 4506565 - 1.5 (СI 1.1-2.03; p = 0.007), rs 7578597 - 1.59 (СI 1.02-2.46; р = 0.016) increases the risk of metabolic syndrome development approximately by 1.5 times according to the additive model, whereas C allele by polymorphism rs 4072037 does the risk of MS development by 1.99 (СI 1,1-3,6; р = 0,016) times according to the recessive model.
Conclusion: The identified five polymorphisms make it possible to assess the risks of MS and associated diseases.
Keywords: metabolic syndrome, polymorphism, allele, genotype

CITATION

Akhmetova K, Vochshenkova T, Dalenov E, Abduldayeva A, Azhenov T. Determination of the association of some polymorphisms with metabolic syndrome in residents of the city of Nur-Sultan. J CLIN MED KAZ. 2021;18(6):76-80. https://doi.org/10.23950/jcmk/11391

REFERENCES

  • Kang, Y. and J. Kim, Gender difference on the association between dietary patterns and metabolic syndrome in Korean population. Eur J Nutr. 2016; 55(7):2321-30. https://doi.org/10.1007/s00394-015-1127-3
  • Biryukova, E.V., Molecular-genetic, hormonal-metabolic and clinical aspects of metabolic syndrome [in Russian]. Abstract. Doctor of Medical Sciences: 14.00.03. 2009; p. 48.
  • Stančáková, A. and M. Laakso, Genetics of metabolic syndrome. Rev Endocr Metab Disord. 2014; 15(4):243-52. https://doi.org/10.1007/s11154-014-9293-9
  • Kong, X., et al., The Association of Type 2 Diabetes Loci Identifed in Genome-Wide Association Studies with Metabolic Syndrome and Its Components in a Chinese Population with Type 2 Diabetes. PLoS One. 2015; 10(11):e0143607. https://doi.org/10.1371/journal.pone.0143607
  • Lin, H.F., et al., Heritabilities of the metabolic syndrome and its components in the Northern Manhattan Family Study. Diabetologia. 2005; 48(10):2006-12. https://doi.org/10.1007/s00125-005-1892-2
  • Cho, Y.S., et al., Meta-analysis of genome-wide association studies identifes eight new loci for type 2 diabetes in east Asians. Nat Genet. 2011; 44(1):67-72. https://doi.org/10.1038/ng.1019
  • González, J.R., et al. Maximizing association statistics over genetic models. Genet Epidemiol. 2008; 32(3):246-54.
  • Floud, S., et al., Marital status and ischemic heart disease incidence and mortality in women: a large prospective study. BMC Med. 2014;12:42. https://doi.org/10.1186/1741-7015-12-42
  • Abnet, C.C., et al., A shared susceptibility locus in PLCE1 at 10q23 for gastric adenocarcinoma and esophageal squamous cell carcinoma. Nat Genet. 2010; 42(9):764-7. https://doi.org/10.1038/ng.649
  • Yin, L., et al., Human MUC1 carcinoma antigen regulates intracellular oxidant levels and the apoptotic response to oxidative stress. J Biol Chem. 2003; 278(37): 35458-64. https://doi.org/10.1074/jbc.M301987200
  • Driscoll, I., et al., A candidate gene study of risk for dementia in older, postmenopausal women: Results from the Women's Health Initiative Memory Study. Int J Geriatr Psychiatry. 2019; 34(5):692-699. https://doi.org/10.1002/gps.5068
  • Willette, A.A., et al., Family history and TOMM40 '523 interactive associations with memory in middle-aged and Alzheimer's disease cohorts. Alzheimers Dement. 2017; 13(11):1217-1225. https://doi.org/10.1016/j.jalz.2017.03.009
  • Pugazhenthi, S., L. Qin, and P.H. Reddy, Common neurodegenerative pathways in obesity, diabetes, and Alzheimer's disease. Biochim Biophys Acta Mol Basis Dis. 2017; 1863(5):1037-1045. https://doi.org/10.1016/j.bbadis.2016.04.017
  • Phillips, C.M., et al., Dietary saturated fat, gender and genetic variation at the TCF7L2 locus predict the development of metabolic syndrome. J Nutr Biochem. 2012; 23(3):239-44. https://doi.org/10.1016/j.jnutbio.2010.11.020
  • Zafar, U., et al. TCF7-L2 rs7903146 polymorphism in metabolic syndrome with and without acute coronary syndrome. J Pak Med Assoc. 2020; 70(10):1774-1778. https://doi.org/10.5455/JPMA.45480
  • O'Beirne, S.L., et al., Type 2 Diabetes Risk Allele Loci in the Qatari Population. PLoS One. 2016; 11(7):e0156834. https://doi.org/10.1371/journal.pone.0156834
  • IDF., IDF Diabetes Atlas Eighth Edition. International Diabetes Federation, 2017.
  • Gamboa-Meléndez, M.A., et al., Contribution of common genetic variation to the risk of type 2 diabetes in the Mexican Mestizo population. Diabetes. 2012; 61(12):3314-21.https://doi.org/10.2337/db11-0550