Background
Obesity is a significant health challenge worldwide and has negative impacts on health, from reducing life expectancy to increasing the risks of several diseases. It is believed that the main reasons for the increase in obesity in the last 40 years are changes in lifestyle and food supply, behavioral factors such as physical inactivity, and unhealthy diets including more processed foods. However, obesity is also caused by interactions among genetic variants, and is highly heritable [
1].
Genome-wide association studies (GWAS) are powerful tools for discovering genetic variants associated with obesity and other diseases [
2,
3]. The first gene discovered to have variants associated with obesity was fat mass and obesity-associated protein (FTO) [
4]. Other genes associated with obesity have since been reported, including the melanocortin-4 receptor (MC4R) [
5], adiponectin, C1Q and collagen domain containing [
6], brain-derived neurotrophic factor [
7], leptin [
8], peroxisome proliferator-activated receptor gamma-2 [
9] and SH2B1 genes [
10]. Among these genes, some single-nucleotide polymorphisms (SNPs) near MC4R (rs17782313, rs571312, rs17700144, and rs2331841) are strongly associated with obesity in adults, adolescents, and children, indicating that subjects with minor alleles of these SNPs typically exhibit higher BMIs than those with the major allele [
3,
11‐
13]. An association between MC4R rs17782313 and obesity has been reported in a European population [
11,
14]. There was also a strong association between MC4R rs17782313 polymorphisms in subjects either heterozygous or homozygous for the C allele (CT or CC as opposed to TT) and higher body mass index (BMI) in Tatar women and Chinese people [
14,
15]. In Korea, the MC4R variant rs17782313 was associated with BMI in a replication gene association study and a GWAS [
16,
17] and BMI increased with C allele (minor allele) of MC4R rs17782313 by 0.22 kg/m
2 BMI [
17]. Subjects with the minor allele of MC4R rs17782313 exhibited a positive association with BMI and it tended to be related to a positive energy balance with possible impacts on dietary intake [
18].
MC4R is expressed in regions of the central nervous system, including the hypothalamus, cerebral cortex, brain stem, and spinal cord [
18]. MC4R is a component of the leptin system, which regulates energy intake with neuropeptide effectors such as pro-opiomelanocortin (POMC), α–melanocyte-stimulating hormone (α-MSH), and agouti-related peptide (AGRP) [
19]. When the body is in a negative energy state, the decrease in leptin levels leads to lower POMC expression, which reduces α-MSH levels, simultaneously stimulating the expression of AGRP in the orexigenic neurons of the arcuate nucleus, which is an antagonist at the MC4R [
19,
20]. The decrease in α-MSH and increase in AGRP, and subsequent sustained repression of MC4R, result in increased food intake, which may cause obesity [
18,
19].
MC4R polymorphisms may be associated with lifestyle, food intake, dietary habits, and specific nutrient preference [
18,
21,
22]; however, this is still controversial. A study in Europeans indicated that MC4R rs17782313 is associated with higher BMI and overeating behaviors [
18,
21]. In Iranian adults, the MC4R rs17782313 variant is related to high energy intake and low intakes of carbohydrates and protein [
22]. However, Hassellbalch et al. [
23] has reported that MC4R genotypes do not influence dietary intake. In addition, accumulating evidence suggests a functional interaction between MC4R and stress response [
24]. Acute emotional stress activates POMC and its derivative α-MSH, which then increases the level of MC4R. MC4R activates the hypothalamic-pituitary-adrenal (HPA) axis and adrenocorticotropic hormone (ACTH), which increase the production and release of cortisol in response to stress [
25,
26]. Mental stress also activates the HPA axis: it immediately induces a corticotropin-releasing-hormone-mediated suppression of food intake and chronically elevated glucocorticoids result in chronically stimulated eating behavior and weight gain [
27]. Mental stress is known to increase the appetite for highly palatable and high-energy foods [
28,
29]. Stress-induced activation of the HPA axis is attenuated in a rat model of MC4R loss-of-function [
26]. MC4R facilitates an increase in anxiety-like and depression-like behaviors pursuant to chronic stress [
30]. Thus, the MC4R polymorphism and stress may interactively change eating behavior leading to overweight and obesity. However, no study has been conducted to determine the interaction of MC4R polymorphisms and mental stress and nutrient intake.
Because MC4R is involved in eating behavior and stress and MC4R variants are associated with obesity, MC4R variants may modulate energy balance via gene-nutrient interactions. We hypothesized that MC4R variants affect body weight by modulating eating behavior and stress responses. To investigate this, we determined the interaction between the MC4R variant rs17782313 and both nutrient intake and mental stress in the development of overweight and obesity among 8842 Korea adults over 40 years of age from the Korean Genome Epidemiology Study (KoGES) study.
Discussion
Many studies have indicated that the expression of MC4R in the hypothalamus leads to excessive energy intake [
15,
16], and also that it is regulated by stress through the HPA axis [
22]. It has also been reported that MC4R variants are associated with the incidence of obesity [
5,
10,
12]. We hypothesized that there is an interaction between MC4R rs17782313 variants and diet and lifestyle that influence the risk of obesity. There was a positive interaction between MC4R variants and mental stress levels that was significantly associated with the risk of obesity after adjusting for age, gender, residence area, daily energy intake, smoking status and physical activity. In subjects with high stress, those with MC4R minor alleles had higher BMIs after adjusting for confounders without modulating energy and nutrient intake; they also had a preference for spicy taste. Furthermore, in the group with energy intake higher than EER, subjects with MC4R minor alleles had higher BMIs than those with the major alleles but with similar energy intakes. Therefore, MC4R variants interacted with energy intake and mental stress levels to promote obesity. To the best of our knowledge, no previous studies have investigated the interactions between MC4R variants and nutrient intake and mental stress in Korean adults.
In several populations, the MAF of MC4R rs17782313 varies from 24 % to 26 %; Therefore, the MAF of MC4R rs17782313 in Koreans (25 %) was comparable to studies in other ethnicities [
11,
14,
16]. Those previous studies found that the MC4R rs17782313 C allele was a risk allele for obesity. The MC4R rs17782313 CC genotype has a strong positive association with BMI which has been clearly demonstrated in European and Tatar populations in which subjects with the rs17782313 variant had higher BMIs [
11,
14]. These results suggest that the MC4R minor allele is a risk factor for obesity across ethnicities. In the Korean population, people with the MC4R minor allele exhibit a small but significant increase in BMI (0.5 ± 0.04 kg/m
2) in comparison to the MC4R major allele, but in European population the BMI difference between MC4R genotypes is 4.1 ± 9.1 kg/m
2 [
36]. The differences in BMI between MC4R genotypes were higher in the participants with high levels of stress (0.78 ± 0.05 kg/m
2). However, it was still a much lower difference in Koreans than in Europeans [
36] and Native Americans [
37]. The small difference in BMI in the Korean population was associated with participants within a normal range of BMI (24.1 ± 3.1 kg/m
2) in comparison to European population (31.8 ± 9.5 kg/m
2). In addition, the average caloric intake of Koreans was also mostly within the EER. The higher BMI in subjects with the MC4R minor alleles was related to a small increase in daily energy intake and high fat intake in the present study. Even though daily energy intake was slightly and insignificantly higher in participants with MC4R minor alleles, it influenced the increase in BMI. In the participants with higher than EER, the participants with MC4R minor alleles had much higher BMI than those with major alleles. The present study demonstrated that MC4R rs17782313 minor allele increased BMI in participants with energy intake higher than EER. Thus, the greater increase of BMI in MC4R minor allele in European population may be involved in higher energy intake, and the less pronounced effect of the minor alleles on the BMI of Koreans may be due to overall lower BMIs and lower energy intakes in the Korean population.
Gene-environment interactions play an important role in the etiology of obesity. MC4R variants have been implicated in the modulation of nutrient intake in previous studies [
21,
22]. Some studies have indicated a positive association between the MC4R rs17782313 variant and the consumption of higher-energy and fatty foods [
21]. An NHS cohort study indicated a positive association between the MC4R rs17782313 variant and the consumption of higher-energy and fatty foods in the United States using FFQ [
11] and multiple 1-week dietary records, and the same result was confirmed in Iran based on a 3-day food record [
21]. However, Qi et al. [
21] have shown that the MC4R C allele is significantly associated with high intakes of total energy (
P = 0.028), total fat (
P = 0.008) and protein (
P = 0.003) after adjustment for age, BMI, and diabetes status; although the associations between MC4R rs17782313 and BMI were significant (
P = 0.002) independent of dietary intakes. However, in the present study, the daily energy intake was not significantly different according to MC4R genotypes, but subjects with MC4R C alleles had higher intakes of processed foods than those with T alleles. This was consistent with the results that subjects with MC4R C alleles had higher fat percent based on energy intake than others. Consistent with the present study, daily energy, carbohydrates, protein and fat intakes were not significantly different among MC4R genotypes [
23]. However, unlike the present study, MC4R genotype has a positive association with intake of energy, fat and protein [
21]. Therefore, the association between MC4R genotypes and food intake remains unclear and further multi-center studies are needed.
No studies have reported interactions between MC4R genotypes and mental stress. We found new evidence that the MC4R rs17782313 C allele interacts with mental stress to promote obesity; but in this population, only in subjects with high stress. Some animal studies have demonstrated a relationship between MC4R gene, mental stress and food intake through the HPA axis [
24‐
26]. MC4R facilitates the regulation of the HPA axis in response to psychological stress [
26]. In MC4R knockout mice the plasma ACTH and corticosterone levels are significantly lower in response to restraint stress, suggesting that MC4R is a mediator of communication between brain and peripheral stress system to facilitate mental stress [
25,
38]. Infusion of a selective MC4R agonist into the medial amygdala elicits anxiety in the elevated plus-maze test and decreases food intake [
25]. In contrast, an MC4R antagonist infusion blocks restraint stress-induced anxiogenic and anorectic effects [
26]. These results suggest that acute stress decreases food intake via the HPA axis. Saegusa et al. [
38] reported that MC4R stimulation by stress results in decreased peripheral ghrelin concentrations, thereby suppressing food intake in animals. However, long-term stress increases serum glucocorticoid levels to induce food intake. Thus, MC4R genotypes may influence eating behaviors through stress response and may be involved in weight gain in humans.
Mental stress influences eating choices but people with mental stress have different choice of comfort food [
39]. People differ in their preferences for spicy, oily, or sweet foods as comfort foods when stressed [
40]. High stress situations change eating patterns and increase the consumption of highly palatable foods, which in turn augments incentive salience of highly palatable foods. Thus, the alteration of eating patterns enhances risk of weight gain and obesity [
41]. Emotional eaters with stress consume more sweet foods and oily foods than unstressed and non-emotional eaters [
40]. Participants with a high level of work stress consumed more saturated fat and high-energy foods [
42,
43]. Korean high school students consumed more sweet foods with mental stress [
43]. Thus, the choice of comfort foods is somewhat different according to age, gender, and personality, but may also be related to differences in genetic backgrounds. In the present study, subjects with MC4R minor alleles consumed a higher percentage of processed foods, which might be related to a busy lifestyle but not the preference of taste.
There were several limitations to our analysis. First, cause-and-effect cannot be established because this was a cross-sectional cohort study. Second, obese participants with the rs17782313 CC genotype were underrepresented (
n = 544). Third, preferences for particular foods were not strongly correlated with food intake as measured by the FFQ. There are 103 kinds of foods in the FFQ, but only 5 spicy foods (cabbage kimchi, radish kimchi, nabak kimchi, green pepper, and onion), and spiciness is not dependent on the kind of food but rather on the amount of red pepper used. Thus, the preference for spicy foods cannot be matched with the results of the FFQs. Only green peppers can be said to partly reflect the preference of spiciness but this pepper is not frequently consumed. However, the preference of sour taste and fruit intake was somewhat consistent: subjects with the MC4R minor allele consumed less fruits and subjects with MC4R minor allele did not prefer sour taste in low stress state. Nonetheless, the consumption of green peppers tended to increase with the MC4R C allele but the association was not significant. Thus, MC4R variants were positively associated with a preference for spicy foods. The FFQ included seven processed foods: cheese, ramen, frozen dumplings, sausage, chips, canned tuna, and ham. The preference for processed foods may be well reflected by the FFQ. However, Brazilian subjects who consumed more processed foods did not consider processed foods to be a preference, but they preferred to consume oily foods [
44].
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
SP and JWD participated in the experimental design, interpreted the data and wrote the manuscript. XZ and HSJ analyzed the genetic data and YHL and HJL participated to discuss the results and to write the manuscript. All authors listed in a manuscript have contributed substantially to the work and seen and approved the submitted version. No part of the work has been published before.