Introduction

The role of the dopamine receptor 2/ankyrin repeat domain and content kinase 1 (DRD2/ANKK1) gene polymorphisms in addictive behaviors such as gambling, substance and alcohol abuse has been well described [1,2,3,4,5]. The DRD2 gene codifies a Ser/Thr kinase involved in dopamine transduction, and DRD2 expression in the brain reward system (BRS) [6]. One of the most relevant genetic variants is the DRD2/ANKK1 TaqIA polymorphism (rs1800497), in which the A1 allele affects DRD2 receptor density and increases l-DOPA activity [7]. Indeed, A1 allele carriers have addictive behaviors, negative emotions and cognitive alterations [3,4,5]. Eating behavior is also regulated by dopamine along with other neurotransmitters (GABA, dopamine, serotonin, opioids, and cannabinoids) in the BRS [8,9,10]. Eating for rewarding purposes is a learned survival process, and humans make strategies for obtaining rewards [9]. Additionally, unhealthy food behaviors and obesity have been associated with the functionality of the DRD2 gene, and the Taq1A polymorphism [11, 12] as well as other cultural and environmental risk factors [13].

Dietary patterns characterized by high consumption of saturated fats and simple sugars play a crucial role in obesity progression [14]. It has been documented that the process of food choice requires both a cognitive assessment and personal desires to evoke decisions towards food consumption [15]. However, the tendency of selecting more often high-energy-dense palatable foods is due to the pleasure that they elicit [16]. This observation was demonstrated in animal models exposed to high-fat and high-sugar diets that contributed to alterations in dopamine release and the consumption of more calories [17, 18]. In humans, healthy individuals consumed palatable foods such as sugars and fats which correlated with meal pleasantness and dopamine release [19]. Moreover, the intake of these palatable foods is poorly controlled during binge episodes in people with obesity [20,21,22,23]. Therefore, uncontrolled eating behavior could be a risk factor that contributes to obesity.

In Mexico, 72.5% of the population is either overweight or obese [24]. Consequently, Mexicans have high rates of metabolic abnormalities associated with obesity including hypertriglyceridemia and hypercholesterolemia. This scenario ultimately can lead to non-communicable chronic diseases [25]. Furthermore, Mexico presents one of the highest frequencies of the A1 allele (67%) in the world, which was observed in a Native Mexican population [26]. This genetic factor could be exacerbating unhealthy food behaviors, although it has not yet been assessed among Mexican mestizos, a population with a genetic admixture of Native American, European and African ancestries that varies by geographic location [27,28,29]. Therefore, this study aimed to investigate the association of DRD2/ANKK1 TaqIA polymorphism with the consumption of dietary intake, the intake frequency of food groups and biochemical profile in Mexican mestizo subjects.

Materials and methods

Study design and participants

In a cross-sectional and analytical study, 276 unrelated Mexican mestizo adults were included. Patients diagnosed with chronic diseases (cardiovascular, liver, kidney or pancreas disease), subjects taking medication that alter satiety or appetite, pregnant or breastfeeding women, active smokers, and subjects who reported changes in their food intake in the last 6 months were excluded. Eligible volunteers completed a medical health record, body composition, biochemical and dietary assessment, and gave informed written consent. The study was conducted at the Nutrigenetic Clinic of the Department of Molecular Biology in Medicine, Civil Hospital of Guadalajara “Fray Antonio Alcalde”. The Institutional Review Board of the Civil Hospital of Guadalajara “Fray Antonio Alcalde” approved this study and was conducted under The Code of Ethics of the World Medical Association [30].

Dietary and body composition assessment

Trained nutritionists assessed participants’ dietary intake using two different food records. A food frequency questionnaire (FFQ) of 64 items was administered [31]. High-frequency consumption was based on more than three times per week, whereas the food consumption of fewer than three times per week was considered a low frequency. Habitual intake was assessed with a 24-h dietary recall and then analyzed with 2011 Nutrikcal VO® (Mexico City, Mexico), a software that contains Mexican food items. A daily average of energy and nutrients was obtained.

Height was measured according to the WHO guidelines without shoes to the nearest 0.1 cm using a stadiometer (Rochester Clinical Research, New York, USA); body circumferences were measured using a steel flexible tape (Ross Craft Anthrotape, Rosscraft Innovations Inc., Toronto, Canada). Waist circumference was measured at the midpoint between the iliac crest and the edge of the last rib in a horizontal plane to the nearest 0.1 cm; hip circumferences were measured at the maximum protuberance of the gluteus in a horizontal plane to the nearest 0.1 cm. Weight, fitness score and body composition were assessed by electrical bioimpedance (In Body 3.7, Seoul, Korea). BMI was calculated as the ratio of weight (kg), by height (m2). BMI cut-off points were as follows: normal weight (18.5–24.9 kg/m2), overweight (25–29.9 kg/m2), and obesity (> 30 kg/m2) [32].

Biochemical tests

Peripheral blood samples (10 mL) were drawn following a 12-h overnight fast. Biochemical tests included glucose (mg/dL), insulin (µU/mL), total cholesterol (mg/dL), c-LDL (mg/dL), c-HDL (mg/dL), c-VLDL (mg/dL) and triglycerides (mg/dL). All biochemical tests were determined with the AU5800 Clinical Chemistry System (Beckman Coulter’s Inc. USA) at the Central Core Laboratory at the Civil Hospital of Guadalajara “Fray Antonio Alcalde”. An insulin resistance score (HOMA-IR) was calculated with the formula: IR = fasting plasma glucose (mg/dL) × fasting serum insulin (µU/mL)/405. Insulin resistance was defined as a HOMA-IR of 2.5 or above [33]. The criteria for considering abnormal values were glucose > 100 mg/dL, insulin > 10 µU/mL, HOMA-IR > 2.5, total cholesterol > 200 mg/dL, c-LDL > 100 mg/dL, c-HDL < 40 mg/dL, c-VLDL > 30 mg/dL and triglycerides > 150 mg/dL [33, 34].

DNA extraction and genotyping

Genomic DNA extraction from leukocytes with a modified salting-out technique was performed [36]. A 20 ng/µL DNA aliquot was stored at − 70 °C until use. A real-time PCR system was used to determine the DRD2/ANKK1 TaqIA polymorphism (rs1800497) (Assay Number, C_7486676_10, Applied Biosystems, Foster City, CA, USA) by using a 96-well plate read on a StepOnePlus thermocycler (Applied Biosystems). The thermocycling conditions were as follows: first denaturalization stage at 95 °C for 10 min, 40 amplification cycles at 95 °C for 15 s and annealing/extension stages at 60 °C for 1 min. Three positive controls for each possible genotype and a blank control were included in each 96-well plate.

Statistical analysis

The sample size was calculated for a cross-sectional and analytical study [37] which resulted in 200 subjects using the allelic frequencies reported elsewhere [26]. Continuous variables were shown as the mean and standard deviation, while categorical variables were expressed as frequencies and percentages. Normal distribution of quantitative variables was assessed using Kolmogorov–Smirnov’s test. Normally distributed data were analyzed with parametric tests (one-way ANOVA), followed by post hoc analysis (Bonferroni’s and Dunnett’s T3). For non-normally distributed data, non-parametric tests (Kruskal–Wallis and Mann–Whitney) were used. The χ2 test was used to evaluate differences between qualitative variables. The association of DRD2/ANKK1 TaqIA genotypes with the variables of interest was estimated with odds ratio (OR) test and a 95% confidence interval (CI). A p value of < 0.05 was considered significant. Statistical analyses were performed using SPSS software (Ver 20.0; IBM™, Chicago, IL, USA). Hardy–Weinberg equilibrium (HWE) was calculated using the Arlequin software (Version 3.1; Bern, Switzerland).

Results

Demographic and anthropometric characteristics by DRD2/ANKK1 TaqIA genotypes

Demographic and anthropometric characteristics of the study population classified by DRD2/ANKK1 TaqIA genotypes are shown in Table 1. Allelic frequencies were A1 (41.1%) and A2 (58.9%). Genotype distribution was as follows: A1A1 (18.48%), A1A2 (45.29%) and A2A2 (36.23%). Genotype frequencies were in Hardy–Weinberg equilibrium (p = 0.721). In regard to BMI, 26.45% of participants had a normal weight, 27.14% were overweight, and 46.38% had obesity. There were no significant differences in body composition between genotype groups.

Table 1 Demographic and anthropometric characteristics by DRD2/ANKK1 genotype
Full size table

Comparison of dietary intake according to DRD2/ANKK1 TaqIA genotypes and gender

Dietary intake by genotype was compared between genetic models A1A1 + A1A2 vs. A2A2 (Table 2). Energy consumption did not differ among DRD2/ANKK1 TaqIA genotype groups. However, MUFA intake was slightly higher in the A2A2 group (p = 0.012) while carbohydrate intake was higher in A1A1 + A1A2 vs A2A2 (p = 0.038). Food consumption frequency was compared between genetic models (Table 3). A1A1 + A1A2 group had a higher consumption of meats (p = 0.005), fried dishes (p = 0.039), sugars (p = 0.009) and lower consumption frequency of legumes (0.038).

Table 2 Dietary intake of the study population by DRD2/ANKK1 genotype
Full size table
Table 3 Food frequency consumption by DRD2/ ANKK1 genotype (n = 276)
Full size table

Dietary intake was assessed by gender (Table 4). Male carriers of A1A1 + A1A2 genotypes had a higher consumption of carbohydrates (p = 0.009) than those with the A2A2 genotype. Males with the A2A2 genotype had a higher consumption of fat (0.012), MUFA (0.008) and PUFA (0.009) than A1A1 + A1A2 genotypes. The food frequency assessment by gender (Table 5) showed that females in the A1A1 + A1A2 had a lower consumption frequency of legumes (p = 0.005) than A2A2 carriers, and males in the A1A1 + A1A2 group had a higher consumption frequency of meat products (p = 0.018).

Table 4 Dietary intake by gender and DRD2/ANKK1 genotype (n = 276)
Full size table
Table 5 Food frequency consumption by gender and DRD2/ANKK1 genotype (n = 276)
Full size table

The A1A1 + A1A2 genotype was associated with lower consumption frequency of healthy foods such as legumes (OR 1.89, 95% CI 1.04–3.29, p = 0.038) and a higher consumption frequency of unhealthy foods such as fried dishes (OR 3.79, 95% CI 1.53–9.35, p = 0.002) and meats (OR 2.31, 95% CI 1.32–4.05, p = 0.003) (Fig. 1).

Fig. 1
figure 1

Association of DRD2/ANKK1 genotype with food frequency consumption

Full size image

Comparison of dietary intake according to DRD2/ANKK1 TaqIA genotypes and BMI

Dietary intake was also compared by BMI (Table 6). Obese people with the risk allele had a higher intake of energy (p = 0.009) and carbohydrates (p = 0.016) as well as a lower intake of MUFA (p = 0.024) than normal weight participants.

Table 6 Dietary intake of the study population by DRD2/ANKK1 genotype
Full size table

Metabolic abnormalities according to DRD2/ANKK1 TaqIA genotypes

The DRD2/ANKK1 TaqIA genotypes did not differ in biochemical parameters (Supplementary Table 1). However, comparison of normal vs abnormal parameters showed that the A1A1 + A1A2 carriers had significantly higher glucose >100 mg/dl (p = 0.037) and triglyceride levels >150 mg/dl (p = 0.011) than the A2A2 carriers (Table 7). The A1A1 + A1A2 genotype was associated with risk of abnormal glucose, triglycerides, and VLDL levels (OR 2.148, 95% CI 1.068–4.322, p = 0.036; OR 1.999, 95% CI 1.194–3.348, p = 0.011; OR 2.021, 95%CI 1.203–3.392, p = 0.007, respectively) (Fig. 2).

Table 7 Normal vs abnormal biochemical levels by DRD2/ANKK1 genotype
Full size table
Fig. 2
figure 2

Association of DRD2/ANKK1 genotype with an abnormal biochemical profile

Full size image

Discussion

The DRD2/ANKK1 TaqIA polymorphism is one of the numerous genetic variations involved in the reduced expression and binding of the DRD2 receptors in the dopaminergic system [7], which has a key role in addictive behaviors [3,4,5]. In the present study, we report an association of the DRD2/ANKK1 TaqIA polymorphism, with a higher food consumption frequency of unhealthy food groups showing biochemical abnormalities as well. Specific interactions between genes and environmental factors of the Mexican population may explain these results.

The DRD2/ANNK1 TaqI A1 allele is known to influence eating behaviors [38,39,40]. However, its influence may vary according to the genetic composition of each population due to differences in the prevalence of the TaqI A1 allele across countries. Caucasian people have a low prevalence (2.95%) [41], Chinese and Indian populations have reported a frequency of 37.9% and 29.0%, respectively [39], and higher frequencies have been reported in Asian American college students [40]. Our group previously reported the highest TaqI A1 allele prevalence in the world in which 67% of Native Mexicans and 47.3% of Mexican mestizos are carriers of this risk allele [26]. In agreement with this data, in the present study, the prevalence of the A1 allele was 41.1%. This underlying genetic factor was previously associated with the excessive consumption of alcohol [26]. However, the influence of the DRD2/ANKK1 TaqIA polymorphism in food consumption frequency had not been analyzed in the Mexican population.

Previous research has shown that the DRD2/ANKK1 TaqIA polymorphism associates with BMI and weight increments [41, 42]. However, later studies have not found associations of the TaqIA variant with BMI or anthropometric characteristics [43, 44]. In line with these studies, we also did not find any associations of the A1 allele with anthropometric measurements. This lack of association may be related to the fact that all patients in the study group consumed the same dietary pattern denoted as an obesogenic and hepatopathogenic diet [46]. In this regard, Mexico has experienced a nutritional transition along with the progression of the globalization era. Specifically, the Mexican food culture has evolved from a traditional Mesoamerican-based food pattern to an 87.1% increase in the consumption frequency of processed foods containing saturated and trans-unsaturated fatty acids, simple sugars, and sodium [47]. These shifts in dietary intake are due to more availability of industrialized foods containing sugars and fats [48]. The sources of added sugar in the modern-day Mexican diet are sodas, pastries, and commercial instant soups whereas fat sources come from processed red meats, typical Mexican fried dishes, and chips. Also, Mexicans have given such foods a significant sentimental value. Processed foods are perceived as having better social status [47].

The DRD2/ANKK1 TaqA1 polymorphism may indirectly influence obesity by impairing rewarding food behaviors [49], adherence [50] and exacerbating the consumption of the obesogenic and hepatopathogenic diet. TaqI A1 carriers exhibit compulsive behaviors towards the intake of energy-dense foods [16, 48,49,50]. In the present study, A1A1 + A1A2 carriers showed a higher intake of carbohydrates than A2A2 carriers. Similarly, it was reported that TaqI A1 carriers craved more often for carbohydrates and fast foods and presented higher rewarding feelings after the intake of sugary and fatty foods [40]. Eating based on rewards could be a risk factor for developing addictive behaviors, which are further characterized by being highly recurrent. In this study, food consumption frequency was assessed with an FFQ. TaqI A1 allele carriers present a higher consumption frequency of sugars, meats, and fried dishes as well as a lower consumption frequency of legumes. We speculate that the consumption of this dietary profile could also be favored by the genetics that drives food flavor preference in which the indulgent flavor of fats and sugars may detonate their higher use. In regard to this point, our group identified a genetic-based choice for sweet (TAS1R2) [51] and fat (CD36) [52] flavors among Mexicans, which may elicit addictive food behaviors which should be explored in further studies.

It has been reported that there are significant differences according to gender in addictive behaviors, including food behavior [53, 54]. Therefore, it was interesting to assess if the DRD2/ANKK1 TaqI A1 variant could interfere with the quality of food choice among females and males in this study. Herein, we found that TaqI A1 female carriers consume more food servings from fruits but have a lower frequency selection of legumes. In contrast, TaqI A1 male carriers consumed fewer sources of healthy fats and consumed higher amounts of carbohydrates, consumed more food servings from sugars and more frequently selected meats. These sex differences could be explained because women tend to care more about their food intake and choose healthier sweet options such as higher servings of fruit [13, 55]. It is also possible that females have a higher preference for sweet flavors from fruits than bitterness that comes from legumes [57].

In contrast, men do not often take care of their food habits and do not hesitate in consuming carbohydrates, sugars, and fats from meats and processed foods [13, 55]. Obregon and colleagues found that the DRD2/ANKK1 TaqIA polymorphism interacts with sex by influencing the preference of different food behaviors. They found that among obese girls, TaqI A1 allele interacts with emotional eating while among boys, A1 allele interacts with feelings of pleasure [54].

Recently, it was reported that the consumption of sugars and refined carbohydrates in the Mexican diet was associated with metabolic abnormalities such as low HDL levels [58]. In Mexico, the leading metabolic abnormalities are hypertriglyceridemia and hypoalphalipoproteinemia [25]. In the present study, we found that DRD2/ANKK1 TaqIA A1 was associated with higher risk of metabolic abnormalities related to glucose, triglycerides, and VLDL. These abnormalities may be related to its association with insulin resistance by HOMA-IR reported in obese Brazilian adolescents [59]. These associations of TaqIA with abnormal metabolic parameters may be due to the higher frequency consumption of meat products, fried foods and sugars and low intake of fiber food sources in this group. In Mexico, processed foods and fried traditional foods that were only consumed in celebrations have become more available on a daily basis [47]. Therefore, the high exposure to fats and sugars becomes a risk for uncontrolled food behaviors in TaqI A1 carriers. Nonetheless, other genetic polymorphisms such as Apo E e2 and e4 alleles may also be involved in the development of the common dyslipidemias in Mexico [60]. Finally, given the complexity of the interactions between genes and environmental factors, regional studies in other subpopulations of Mexico may provide further insight into the interactions of TaqI A1 allele with different foods and food culture.

In conclusion, DRD2/ANKK1 TaqIA (rs1800497) polymorphism could be a genetic risk factor for detrimental dietary quality by inducing unhealthy food behaviors that may predispose to metabolic disturbances. The knowledge of the influence of genes on eating behaviors in populations with high genetic risk could help to integrate personalized nutrigenetic strategies to avoid obesity and related co-morbidities.