Evaluation of polygenic score in dopamine receptors (D2, D4) and dopamine transporter (DAT) and food behavior in children with sucking habit: a cohort study

Abstract

Although sucking habits have been extensively studied over the years, questions regarding genetic variation as a possible risk factor have not yet been addressed in the literature. Thus, the purpose of this retrospective cohort study will be investigate whether a specific polygenic score reflecting the gene network of the dopamine receptors (D2, D4) and dopamine transporter (DAT) predicts the presence of sucking habits (pacifiers and thumb sucking) in young children.As a secondary objective, we will verify if there is interaction between genetic scores and presence of sucking habits in food behavior and metabolism outcomes. The sample will comprise of 260 children from Montreal (Quebec) and Hamilton (Ontario), Canada, to be recruited from an established birth cohort called MAVAN (Maternal Adversity, Vulnerability and Neurodevelopment). The inclusion criteria for MAVAN were mothers aged e 18 years old, singleton pregnancy, and fluency in French or English. Women with severe chronic illness, placenta previa, history of incompetent cervix, impending delivery, or had a fetus/infant born at gestational age <37 weeks or born with a major anomaly were excluded. Genotype of 42,211 autosomal SNPs was performed using genome-wide platforms (PsychArray/PsychChip, Illumina) with 200ng of genomic DNA derived from buccal epithelial cells and submitted to quality control procedures. A biologically informed polygenic score comprising the gene network of D2, D4 and DAT genes will be created based on levels of co-expression with the dopamine receptors and dopamine transporter in striatum and prefrontal cortex, and calculated based on the genotype data. MAVAN has a comprehensive assessment of feeding behavior including lab-based consumption tasks and questionnaires addressing the eating styles (e.g. CEBQ, DEBQ). Data will be statistically analyzed using the SPSS 24.0 software (IBM Corp., NY, EUA), considering an alpha level of 5%. Normality will be checked by using the Kolmogorov-Smirnov test and Quantile-quantile-plot graphs (QQ-plot). A K-means cluster analysis approach will be performed to identify subgroups of children who are very similar considering the variables under study and perform a complete description of those clusters. For descriptive purposes, differences will be assessed using the One-way ANOVA test, with Tukey post-test, considering the final clusters as factors. (AU)