Objectives: It is suggested that interaction of dyslipidemia related polymorphisms with obesity is one of the possible mechanisms of expression of cardiometabolic risk factors in obese children. In this study, in order to classify high risk obese children and consequently prioritize health care resources for better management of childhood obesity,we investigated the outcome of GCKR(rs780094), GCKR(rs1260333), MLXIPL(rs3812316) and FADS(rs174547) polymorphisms interaction with obesity in the occurrence of cardiometabolic risk factors in Iranian children.
Methods: In this case- control study, 600 frozen blood samples from overweight /obese (n=300) and normal weight (n=300) samples were selected randomly. Demographic and anthropometric characteristics of the selected cases were recorded.
Biochemical measurements of the selected samples were recorded also. Based on recorded data, cases with cardiometabolic risk factors was determined. Allelic and genotypic frequencies of GCKR (rs780094), GCKR (rs1260333), MLXIPL(rs3812316) and FADS(rs174547) polymorphisms were determined in the studied groups .Interaction of studies SNPs with obesity in the occurrence of cardiometabolic risk factors was evaluated.
Results: In this study, from 528 children 249(47.2%) had more than one cardio metabolic risk factors. Rate of familial history of non communicable diseases was significantly higher in children with cardiometabolic risk factors(P=0.03,X2=3.86).Frequency of tt allele of GCKR(rs1260333) was significantly higher in children with cardiometabolic risk factors than those without it (P=0.03,X2=6.50). Frequency of minor alleles of FADS(rs174547)[tc and cc] was significantly higher in children with cardiometabolic risk factors than those without it (52.6% vs. 44.8%,P=0.04,X2=3.21).
Logic regression analysis regarding the interaction of obesity with studied SNPs in the occurrence of cardiometabolic risk factors provide us 3 Boolean combinations of 7 binary predictor variables. The overall results demonstrated that the interaction of obesity with minor alleles of GCKR (rs1260333) and FADS (rs174547) have an significant role in development of cardiometabolic risk factors.
Conclusion: The current findings support the concept that genetic determinant of diseases could not substantially affect the expression of cardiometabolic risk factors in children, but they could increase the risk by interacting with phenotypes such as obesity or environmental exposure. On the other hand it is also suggested that the differences between obese patients with and without cardiometabolic risk factors may be due to the interaction of several related SNPs with overweight and obesity.
19 - 21 Sep 2019
European Society for Paediatric Endocrinology