Interactions with the MC4R rs17782313 variant, mental stress and energy intake and the risk of obesity in Genome Epidemiology Study

Abstract

BackgroundThe melanocortin-4 receptor (MC4R) regulates metabolism by modulating eating behavior and MC4R variants (rs17782313 and rs571312) are associated with obesity in Asians and Caucasians. However, the impact of their interactions with nutritional and lifestyle factors on obesity are poorly described. Therefore, we investigated the interaction of MC4R variants and dietary patterns on the risk of obesity in Korean middle-aged adults.MethodsData collected included, genetic variations, anthropometric and biochemical measurements, dietary and lifestyle habits, and food intake. Data were obtained from the 8830 adults aged 40–69 years in the Ansung and Ansan cohort of the Korean Genome Epidemiology Study.ResultsThe MC4R rs18882313 minor allele had a higher frequency in the obese group (P < 0.01). MC4R genotypes were not associated with differences in daily energy and macronutrient intakes. However, the intakes of processed foods and fat (as percentages of energy) were significantly higher and intake of fruits were significantly lower in subjects with MC4R minor alleles (P < 0.05). Interestingly, there was a positive interaction between MC4R variants and mental stress levels that were associated with the risk of obesity after adjusting for age, gender, residence area, daily energy intake, smoking status and physical activity (interaction P = 0.0384). Only in subjects with high stress were MC4R minor alleles associated with higher BMIs after adjusting for confounders. The association was present without modulating energy and nutrient intake. In the group with energy intakes higher than estimated energy requirement (EER), subjects with MC4R minor alleles had higher BMIs than those with the major alleles (P < 0.001).ConclusionsThe interactions of mental stress and energy intakes with the MC4R minor allele genotype might be associated with increased risk of obesity in Korean adults. This research might identify subjects with a specific MC4R minor alleles as a human subset of people with a low metabolic tolerance for excessive energy intake, especially when under stress.

Searching for the relationship between the parameters of metabolic syndrome and the rs17782313 (T&gt;C) polymorphism of the <em>MC4R </em>gene in postmenopausal women

“…Interactions between genetic and environmental factors play an important part in the etiology of MS and obesity 21. MS diagnosed on the basis of the IDF criteria of 2005 was observed in 39.3% of women with the T/T genotype.…”

Depression increases the genetic susceptibility to high body mass index: Evidence from UK Biobank

“…This is supported further by our finding that rs6567160 near the MC4R gene was the main variant driving the interaction with depression on BMI. Interestingly rs17782313, which is in perfect LD with rs6567160, has previously been reported to interact with stress, and influence obesity risk (Park et al, ). The importance of the MCR4 gene in the depression‐high BMI relationship is also evident in animal‐based pharmacological studies, in which the antagonist of MCR4 receptor has shown anxiolytic and antidepressant effects, particularly under conditions of high stress (Okubo & Chaki, ).…”

High Genetic Risk Scores of <b><i>ASIC2, MACROD2, CHRM3</i></b>, and <b><i>C2orf83</i></b> Genetic Variants Associated with Polycystic Ovary Syndrome Impair Insulin Sensitivity and Interact with Energy Intake in Korean Women

“…Information on age, education, income, smoking history, alcohol consumption, and physical activity was collected during a health interview, and physical characteristics such as height, weight, and body composition were measured as described in the previous studies [20,21]. The stress level was evaluated by asking subjects to answer 10 questions concerning their state of agitation and anxiety in the workplace and family situations in their daily life.…”

“…DNA samples from the participants were isolated from their peripheral blood, and genotyping was conducted using the Affymetrix Genome-Wide Human SNP array 5.0 (Affymetrix, Santa Clara, CA, USA). The accuracy of the genotyping was checked using the Bayesian Robust Linear Modeling with the Mahalanobis Distance genotyping algorithm [21]. The exclusion criteria of genotyping were as follows: low genotyping accuracies (< 98%), high missing genotype call rates (≥4%), high heterozygosity (> 30%), and gender bias.…”

“…The genotyping and quality-control processes were described in detail previously [21,22]. DNA samples from the participants were isolated from their peripheral blood, and genotyping was conducted using the Affymetrix Genome-Wide Human SNP array 5.0 (Affymetrix, Santa Clara, CA, USA).…”