Animal studies suggested that , , and genes could be involved in the association between overnutrition and obesity. This study aims to investigate interactions involving these genes and macronutrient intakes affecting obesity-related phenotypes. We used a traditional statistical method, logistic regression, and compared it to alternative statistical method, multifactor dimensionality reduction (MDR) and penalized logistic regression (PLR), to better detect genes/environment interactions in the Toronto Nutrigenomics and Health Study ( = 1639) using dichotomized body mass index (BMI) and waist circumference as obesity-related phenotypes. Exposure variables included genotype on 54 single nucleotide polymorphisms (: 18, : 9, : 27), macronutrient (carbohydrates, protein, fat) and alcohol intakes and ethno-cultural background. After correction for multiple testing, no interaction was found using logistic regression. MDR identified interactions between SOCS3 rs6501199 and rs4969172, and rs3747811 affecting BMI in the Caucasian population; SOCS3 rs6501199 and rs1609798 affecting WC in the Caucasian population; and SOCS3 rs4436839 and IKBKB rs3747811 affecting WC in the South Asian population. PLR found a main effect of SOCS3 rs12944581 on BMI among the South Asian population. While MDR and PLR had discordant results, some models support results from previous studies. These results emphasize the need to use alternative statistical methods to investigate high-order interactions and suggest that variants in the nutrient-responsive hypothalamic IKKB/NF-kB signaling pathway may be involved in obesity pathogenesis.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6409307PMC
http://dx.doi.org/10.3389/fgene.2019.00151DOI Listing

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