Polymorphism PLIN1 11482 G>A interacts with dietary intake to modulate anthropometric measures and lipid profile in adults with normal-weight obesity syndrome

• Published in: British journal of nutrition Vol. 128; no. 6; pp. 1004 - 1012
• Main Authors: Holzbach, Luciana Carla, Silveira, Amanda Gonçalves Zardini, Franco, Lana Pacheco, Horst, Maria Aderuza, Cominetti, Cristiane
• Format: Journal Article
• Language: English
• Published: Cambridge, UK Cambridge University Press 28.09.2022
• Subjects: Adipocytes; Adult; Adults; Anthropometry; Biochemical markers; Biomarkers; Body composition; Body fat; Body Mass Index; Body measurements; Carbohydrates; Cardiovascular Diseases; Cholesterol; Cross-Sectional Studies; Diabetes; Diet; Dietary intake; Eating; Energy; Food intake; Gene polymorphism; Glucose; High density lipoprotein; Humans; Insulin; Insulin resistance; Lifestyles; Lipids; Low density lipoprotein; Metabolic disorders; Metabolism; Molecular Nutrition; Nutrients; Nutrition research; Obesity; Obesity - genetics; Perilipin-1; Polymorphism; Polymorphism, Single Nucleotide; Regression analysis; Regression models; Sample size; Single-nucleotide polymorphism; Women; Dyslipidaemias; Insulin resistance; Nutrigenetics; Food habits; Genetic polymorphism
• ISSN: 0007-1145; 1475-2662
• DOI: 10.1017/S0007114521004396

Evidence shows that genetic polymorphisms in perilipin 1 gene (PLIN1) are associated with excessive accumulation of body fat and disturbances in cardiometabolic markers. Therefore, the aim of this study was to verify whether the SNP PLIN1 11482 G>A (rs894160) interacts with nutrient intake, anthropometric, body composition and cardiometabolic markers in adults with normal-weight obesity (NWO) syndrome. A cross-sectional study was carried out with 116 individuals aged 20–59 years, with normal BMI and high percentage of body fat. Anthropometric and body composition measures, glycaemic control and serum lipid markers, SNP PLIN1 11482 G>A and nutrient intake were evaluated. Interactions between nutrient intake and the SNP were determined by regression models and adjusted for potential confounders. The SNP frequency was 56·0 % GG, 38·8 % GA and 5·2 % AA. Anthropometric measures and biochemical markers were not different according to genotype, except for total cholesterol (TC), LDL-cholesterol and non-HDL-cholesterol concentrations. However, important interactions between the SNP and dietary intake were observed. Carbohydrate intake interacted with the SNP PLIN1 11482 G>A to modulate waist circumference (WC) and the homeostatic model assessment of insulin resistance index. Interaction of lipid intake and the SNP modulated TC and LDL-cholesterol concentrations, and the interaction between protein intake and the SNP tended to modulate weight, WC and BMI. The SNP PLIN1 11482 G>A seems to modulate responses in anthropometric and lipid profile biomarkers of subjects with NWO depending on the dietary macronutrient composition, which may have long-term impact on cardiometabolic markers.