CHDH-PNPLA3 Gene-Gene Interactions Predict Insulin Resistance in Children with Obesity.
Diabetes Metab Syndr Obes
; 13: 4483-4494, 2020.
Article
en En
| MEDLINE
| ID: mdl-33239899
INTRODUCTION: Insulin resistance plays a major role in metabolic syndrome and is recognized as the most common risk factor for non-alcoholic fatty liver disease (NAFLD). Identifying predictors for insulin resistance could optimize screening and prevention. PURPOSE: To evaluate the contribution of multiple single nucleotide polymorphisms across genes related to NAFLD and choline metabolism, in predicting insulin resistance in children with obesity. METHODS: One hundred fifty-three children with obesity (73 girls), aged 7-18 years, were evaluated within the NutriGen Study (ClinicalTrials.gov-NCT02837367). Insulin resistance was defined by Homeostatic Model Assessment for insulin-resistance cut-offs that accommodated pubertal and gender differences. Anthropometric, metabolic, intake-related variables, and 55 single nucleotide polymorphisms related to NAFLD and choline metabolism were evaluated. Gene-gene interaction effects were assessed using Multiple Data Reduction Software. RESULTS: Sixty percent (93/153) of participants showed insulin resistance (58.7% of boys, 63% of girls). Children with insulin resistance presented significantly higher values for standardized body mass index, triglycerides, transaminases and plasma choline when compared to those without insulin resistance. Out of 52 single nucleotide polymorphisms analysed, the interaction between genotypes CHDH(rs12676) and PNPLA3(rs738409) predicted insulin resistance. The model presented a 6/10 cross-validation consistency and 0.58 testing accuracy. Plasma choline levels and alanine aminotransferase modulated the gene interaction effect, significantly improving the model. CONCLUSION: The interaction between genotypes in CHDH and PNPLA3 genes, modulated by choline and alanine aminotransferase levels, predicted insulin-resistance status in children with obesity. If replicated in larger cohorts, these findings could help identify metabolic risk in children with obesity.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Diabetes Metab Syndr Obes
Año:
2020
Tipo del documento:
Article
País de afiliación:
Rumanía