ORIGINAL ARTICLE
Genetic variation rs1121980 in the fat mass and obesity-associated gene (FTO) is associated with dietary intake in Koreans
Young Goh and Jeong-Hwa Choi*
Department of Food Science and Nutrition, Keimyung University, Daegu, Korea
Popular scientific summary
- This study examined the association between the genetic variation rs1121980 in FTO and dietary and nutritional intakes in a large-scale epidemiological study cohort of Koreans.
- The FTO rs1121980 T obesity risk allele was associated with fat-tasting food intake, including coffee creamer, in Koreans.
- FTO genetic variation had no significant effect on macronutrient intake in Koreans.
Abstract
Background: Fat mass and obesity-associated gene (FTO) is a well-known gene associated with body weight and obesity risk. Recent studies have suggested that genetic variations in FTO may play a role in the regulation of food preference and consumption. However, little is known with respect to Asian populations.
Objective: This study examined whether rs1121980 C > T in FTO is associated with food intake in Koreans.
Design: This study was performed using data from the Korean Genome and Epidemiology Study (Ansan/Ansung cohort). Dietary intake was determined using the semi-food frequency questionnaire, and the FTO rs1121980 genotypes of 6,262 individuals (3,049 males and 3,213 females) were analyzed along with sex and body mass index (BMI).
Result: Genetic variation did not show a significant association with the population’s energy-nutrient intake. However, female T allele carriers with BMI ≥ 25 consumed more blue fish and coffee, and their coffee creamer consumption was decisively higher than that of T allele non-carriers (Padjusted = 0.004). In males, the presence of the T allele showed a putative association with the consumption of sweets, snacks, and coffee creamer by the BMI level.
Conclusion: The FTO rs1121980 variation was associated with a preference for foods particularly high in fat (e.g. coffee creamer, blue fish, sweets, and snacks) in Koreans; these preferences varied by sex and BMI.
Keywords: food intake; food preference; FTO; genetic variation; Korean; obesity
Citation: Food & Nutrition Research 2022, 66: 8059 - http://dx.doi.org/10.29219/fnr.v66.8059
Copyright: © 2022 Young Goh and Jeong-Hwa Choi. This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material for any purpose, even commercially, provided the original work is properly cited and states its license.
Received: 1 July 2022; Revised: 11 August 2022; Accepted: 16 August 2022; Published: 16 November 2022
*Jeong-Hwa Choi, Department of Food Science and Nutrition, Keimyung University, 1095 Dalgubeol-daero, Dalseogu, Daegu 42601, Korea, Tel: +82-53-580-5913, Fax: +82-53-580-6286. Email: jhchoi@kmu.ac.kr
Competing interests and funding: The authors declare no potential conflicts of interest.
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Obesity is a disease in which fat accumulates in fat tissues in the body (1), and such excess body fat can negatively affect health. In 2018, the prevalence of obesity among Korean adults was 45.4% among males and 26.5% among females (2). Moreover, the prevalence of abdominal obesity in Korea has increased over the past decade, especially among males (28.1%) (2). Obesity increases the risk of developing type 2 diabetes, cardiovascular diseases, metabolic syndrome, and cancers (3). Obesity is also known to be related to psychological conditions, such as depression, anorexia, and bulimia (4).
Genetic variants have an important role in adiposity including in the number of adipocytes, the distribution of body fat, obesity development, and energy consumption (1). Earlier genome-wide association studies reported that single nucleotide polymorphisms (SNPs) present in the first intron of the fat mass and obesity-associated gene (FTO) increase the risk of obesity by 1.2-fold and are associated with an average increase in body mass index (BMI) of 0.39 kg/m2 (body weight 1,130 g) (5). For instance, SNPs in the FTO gene (rs178117449, rs8050136, rs1421085, rs9930506, rs9939609, and rs1121980) are associated with weight, BMI, body composition, and obesity risk. Such an association has been commonly evident in multiple age and ethnic groups (5).
The precise role of FTO in obesity etiology has not yet been revealed. However, among the potential mechanisms of action, FTO may be associated with controlling dietary intake, and this may possibly contribute to FTO-related disease risk: FTO is highly expressed in the hypothalamus, a region involved in appetite regulation. People with a higher risk of obesity had higher levels of ghrelin, an appetite-promoting hormone, than those with a lower risk of obesity and showed a strong appetite or preference (6). Earlier studies have provided evidence that FTO genetic variation may play a role in the regulation of food intake and preference (7, 8). In a study of 4,839 subjects from the Swedish Malmö Diet and Cancer study (MDCS) cohort, rs9939609 of the FTO gene showed a significant association with obesity risk related to fat and carbohydrate intake (7). Another study in the same cohort also reported that FTO genetic variation was associated with certain food intake, especially energy-dense foods (8). In the case of FTO rs1121980, homozygous subjects for the obesity risk allele had a higher saturated fat intake in Americans, but no significant association with carbohydrate intake was evident (9). However, little is known with respect to Asian populations. Since each race/ethnicity has its own physiological metabolism, eating habits, and cultures, the effects of genetic variants may vary. Therefore, we evaluated whether FTO rs1121980 is associated with dietary intake in Koreans. This study was performed to ascertain the association of the FTO rs1121980 genetic variation with the intake of macronutrients and selected food groups in Koreans stratified by the BMI level. Additionally, the study employed a sex-stratified approach since sex differences exist in health and dietary behaviors (10).
Materials and methods
Study subjects and data collection
This study was conducted with data from a population-based cohort, the Ansan and Ansung study, a part of the Korean Genome and Epidemiology Study (KoGES) conducted from 2001 to 2002. The KoGES is a cohort project initiated by the Korea Centers for Disease Control and Prevention to identify the relationship between risk factors and chronic diseases that commonly affect Koreans. Subjects were 40- to 69-year-old adults living in Ansan (urban) and Ansung (rural) in Gyeonggi Province (11). Of the 8,840 subjects with genetic and epidemiological characteristic data, subjects with a history of diabetes (n = 554), hyperlipidemia (n = 128), myocardial infarction (n = 35), or cancer (n = 85) and no information or history of hypertension (n = 1,062) were excluded. Additionally, subjects without anthropometric (n = 4), alcohol consumption (n = 77), or smoking (n = 67), physical activity (n = 270), and education level (n = 47) information were also excluded from the dataset. Finally, this study was conducted with 3,049 males and 3,213 females, for a total of 6,262 subjects, excluding those with unknown daily energy intake (n = 182) or implausible total caloric intake (<500 or >5,000 kcal/day, n = 67, Fig. 1). The KoGES was conducted following a protocol approved by the Institutional Review Board (IRB). All subjects provided written consent before study initiation. This study was approved by the IRB (40525-201802-HR-121-07).
Fig. 1. Simplified process of study subjects selection.
n, number of subjects.
Collection of general characteristics and anthropometric measures
General characteristics such as sex, region, age, and educational level of KoGES study subjects were collected through a baseline survey (11). According to smoking and alcohol consumption, subjects were classified into three groups: never, past, and current. The level of education was classified into three groups: low (elementary school or less), middle (middle or high school), and high (college or higher). The intensity of each type of physical activity was evaluated by calculating the metabolic equivalent of task (MET) using the type and duration of physical activity (12). The BMI of the subjects was computed as weight (kg) divided by the squared height (m2).
Collection and analyses of dietary data
Using semi-quantitative food frequency questionnaire (SQFFQ) data collected by the KoGES, the subjects’ diet and nutrition conditions were investigated (13). Subjects were interviewed on the amount and frequency of 103 food items they ate over the past year. To investigate the influence of FTO rs1121980 on Koreans’ food intake, among the 103 foods, selected items were grouped as follows by taking into account Koreans’ dietary culture and earlier studies (8): all vegetables, all fruits, meats, white meats, red meats, organ meats, fishes, blue fishes, white fishes, sweets and snacks, coffee, and coffee creamer. Additionally, there were nine options for the frequency of intake: never or barely, 1 time a month, 2~3 times a month, 1~2 times a week, 3~4 times a week, 5~6 times a week, 1 time a day, 2 times a day, or ≥3 times a day. The serving size of each food item consists of three options: small, medium, or large. Food intake was converted to daily average nutritional intake using the database of The Korean Nutrition Society (14).
Genotyping and SNP selection
DNA samples for genotype analysis were obtained from the subject’s peripheral blood. Detailed information is described elsewhere (15). Briefly, the genotype was analyzed using Affymetrix Genome-Wide Human SNP array 5.0 (Affymetrix Inc., Santa Clara, CA, USA), and quality control of data was performed under Bayesian robust linear modelling using the Mahalanobis distance algorithm. Samples were excluded if they presented low quality, including sex and ethnic inconsistencies, genotyping call rate <96%, excessive heterozygosity, or cryptic relatedness. Genetic loci were excluded if they possessed a call rate <95%, had a low minor allele frequency (MAF) of <0.01, or deviated from Hardy–Weinberg equilibrium (P < 1 × 10-6). From the KoGES dataset, three genetic variants (rs9939973, rs9939609, and rs1121980) in FTO region were available. According to the LDlink analyses, rs1121980 was strongly associated with the other two variants in the Asian population (D’ = 1.0 for both, r 2 = 0.78 and 1.0 for rs9939973 and rs9939609, respectively) (16). From the preliminary analyses, rs1121980 showed a similar but rational association with dietary intake than the two other variants. For this reason, further analyses were performed with the rs1121980 variation (Supplementary Tables 1–4).
Statistical methods
General characteristics of the subjects were analyzed by applying Student’s t-test and Chi-squared test according to the types of variables. Continuous variables such as age, height, weight, BMI, METs, and food and nutrition intake were logarithmically transformed before analyses. Food and macronutrient intake data were analyzed after adjustment for total energy intake using Willett’s residual method (17). In the case of any food intake being zero, a small value (0.001) was added before logarithmic transformation (8).
Analyses were also performed in two BMI subgroups defined following the Korean Society for the Study of Obesity guidelines: normal weight and obese (BMI < 25 or ≥25 kg/m2) (18). General linear models were used to test the difference in dietary and nutrient intake according to FTO genotype. Model I is a crude statistical model. Model II is an adjusted model considering covariates such as residential area, age, BMI, educational level, alcohol consumption, smoking status, and physical activity.
Statistical analyses were performed using SAS version 9.4 (Statistical Analysis System, SAS Institute Inc., Cary, NC, USA) and SPSS version 26 (Statistical Package for Social Science, SPSS Inc., Chicago, IL, USA). Two-tailed P-values < 0.0042 were recognized as statistically significant to correct for multiple testing issues following Bonferroni’s rule (0.0042 = 0.05/12, number of dietary-related variables examined).
Results
General characteristics of study subjects by FTO rs1121980 genotype and BMI level
The descriptive data of the subjects according to FTO rs1121980 genotype and sex are shown in Table 1. A total of 6,262 individuals (male = 3,049; female = 3,213) with known FTO rs1121980 genotypes were analyzed using a sex-stratified approach. Among them, 2,166 males (71.0%) and 2,286 females (71.1%) had the CC genotype, while 83 males (2.7%) and 85 females (2.6%) had the TT genotype. Because of the limited number of subjects with the TT genotype, the subjects were grouped according to the presence of the T allele. Thus, 883 males (29.0%) and 927 females (28.9%) were defined as minor T allele carriers, and the following analyses were performed according to the presence of the T allele (CT + TT versus CC genotype).
Age, residential area, height, weight, physical activity, alcohol consumption, smoking status, and the level of education in subjects were not significantly different by the FTO rs1121980 genotype. In the case of BMI, there was a difference between normal male genotypes. T allele carriers (CT and TT genotypes) tended to have a higher BMI than CC carriers (22.5 ± 1.9 and 22.3 ± 1.9 kg/m2, P = 0.038). In females, neither the normal nor obese groups were associated with BMI.
FTO rs1121980 genotype, total energy, and macronutrient intake
The results of the analysis of whether the FTO rs1121980 genotype, total energy, and macronutrient intake were associated are shown in Table 2. In males, both crude model I and adjusted model II suggested that the presence of the T allele was not associated with differences in the consumption of total energy, carbohydrate, fat, and protein. In the case of females, again, both models I and II suggested that the T allele showed no association with total energy and macronutrient intake.
FTO rs1121980 genotype and dietary intake
In further analyses, we evaluated the association between the FTO rs1121980 genetic variant and dietary consumption, taking into account obesity status and sex. Our findings suggested that obese males with FTO rs1121980 T alleles tended to consume more sweets and snacks; moreover, in the group of males with normal BMI, minor T allele carriers tended to consume more coffee creamer (Table 3). However, such diet and genotype associations were not significant in model II adjusted for covariates, including residential area, age, BMI, education level, alcohol consumption, smoking status, and physical activity METs.
In obese females, T allele carriers tended to consume more organ meats, blue fishes, and coffee than T allele non-carriers (Table 4). In particular, the association between T alleles and food intake differed significantly for coffee creamer intake. T alleles of FTO rs1121980 in obese females were significantly associated with the higher intake of coffee creamer, and this significant gene-dietary intake association was retained in statistical model II considering subjects’ lifestyle factors (2.4 ± 3.4 and 1.9 ± 3.1 g/day, Padjusted = 0.004). These results suggested that although the type of foods was different by sex and BMI, the presence of the FTO-obesity risk allele was associated with some fat-tasting foods.
Discussion
FTO is a well-known genetic risk factor for obesity. This study examined the association between the genetic variation rs1121980 in FTO and dietary and nutritional intake in Koreans with an epidemiological approach. The findings of the current study suggested that rs1121980 T alleles in obese subjects were associated with some fat-tasting food intake including coffee creamer.
Earlier studies have suggested that variations in FTO may be associated with adipose metabolism and the regulation of food preference/intake. A common genetic variation rs9939609 in FTO was evident to be associated with BMI in multi-cohort studies (19). Genetic variation was also associated with both nutritional and food group-based intake (7, 8). Individuals with a homozygous genotype for another obesity risk allele in FTO rs1121980 were also associated with increased energy intake, especially fat intake (9). One meta-analyze suggested that risk alleles in FTO showed a significant association with lower total energy intake, but higher fat intake (20). However, inconsistencies in findings regarding FTO genetic variations and obesity and its related factors have also been reported. In another meta-analysis with multiple ethnicities, including African/Hispanic and Caucasian populations, no significant associations were observed between genetic variations and obesity risk (21). In a study in Europeans, rs1121980 was not associated with total energy, carbohydrate, fat, or protein intake (22). One Korean study reported that FTO variations were associated with fat intake, but this was only significant in adolescent and children, but not in adults (23). The cause for such differential findings regarding nutritional intake and FTO genetic variation in the studies remained unclear (24). However, FTO genetic variation studies have been conducted in various ethnicities, ages, sexes, and SNPs. The differences in ethnicity-specific genetics, physiological metabolism, and dietary culture might be associated with such varied findings. In line with this, in the present study, FTO genetic variation had no significant effect on macronutrient intake in Koreans. The reasons for the lack of association between the rs1121980 genetic variation and macronutrient intake in this Korean population may be hypothesized as follows: Koreans over 40 years old generally retain traditional eating habits centered on carbohydrates and vegetables. This type of traditional Korean diet contains less fat and sugar (25). The average calorie, fat, and sugar intakes of these Koreans were lower than those of subjects in previous studies, showing a significant association between genetic variation and dietary intake (26, 27). For this reason, the consumption of macronutrients was not decisively evident between genotype groups in Koreans.
In the present study, the FTO genotype tended to be associated with certain types of food, taking into account the BMI level and sex, although the effect of genetic variation was minimal in macronutrient intake. This gene-dietary intake association was mainly evident in both males and females with obesity. In females, the food that showed a decisive association with the FTO genotype was coffee creamer, which may be linked to fat taste. Coffee creamer, which Koreans usually add to instant coffee, is mainly made from vegetable oils with some food additives, such as emulsifiers, spices, and milk protein (28). In Korea, the fat content of coffee creamer is 7.7–14.0%, of which more than 99% are saturated fatty acids (29). In the case of coffee consumption, Koreans over the age of 40 prefer coffee with sugar or coffee creamer rather than black coffee. According to one Korean study, 50.3% of Koreans over the age of 40 had an instant coffee mix with sugar and cream (creamer) (30). The putative association between coffee preferences and the T allele in obese females may also possibly be attributed to the addition of coffee creamer to instant coffee. In addition, female T allele carriers tended to consume more organ meat and blue fish than poultry and white fish. Those organ meats and blue fish are also higher in fat than lean meat and white fish. Obese males with the T allele tended to consume more snacks and sweets, such as chocolate, cakes, biscuits, and ice cream, than fatty food. However, these types of foods also tend to have both high fat and sugar contents (31). Earlier studies of Swedish MDCS cohorts have reported that the obesity-susceptible minor A allele in FTO rs9939609 had no significant association with fat intake depending on genotype. The genetic variants seemed to be associated with the consumption of soft drinks and sucrose (8). However, FTO A allele carriers also showed a higher consumption of biscuits, pastries, and high-fat meat than A allele non-carriers (8). Other studies have observed an association between the FTO genotype and BMI among subjects consuming a high-fat diet, especially saturated fat and trans-fat (7, 9, 32, 33). Considering these and current findings comprehensively, it could not be dismissed that the genetic variation in FTO regulates food preference and intake in relation to fat taste.
FTO is known to be the critical locus in obesity etiology, but its detailed pathological role has not yet been fully identified. However, earlier studies have shown that the FTO gene increases the risk of obesity in association with BMI and the hormone ghrelin, which promotes appetite (5, 6). In addition to BMI and ghrelin, the results of this study may reveal that FTO is associated with appetite control and dietary intake, particularly the consumption of foods with fat taste-energy dense food. Human taste can perceive sweet, sour, salty, bitter, and umami (34). Additionally, fat taste was recently recognized as the sixth taste. Multiple proteins seemed to be involved in fat-sensing mechanisms. Cluster of differentiation 36 is a protein that recognizes the taste of fat (35) and is known to be associated with a mechanism for recognizing long-chain fatty acids in cell membranes and recognizing the taste of fat (36). In addition, some types of G protein-coupled receptors (GPCRs), including GPR40 and GPR120, have been reported to be associated with fatty acid recognition and intake (35). Experimental studies have suggested a role of FTO in protein metabolism and amino acid sensing (37–39). However, these studies were performed in cell lines and animal models and were not confirmed with human sensory tests (37–39). A meta-analysis of the FTO obesity risk allele among multiple ethnicities indicated that the risk allele was associated with increased dietary protein intake (40). One Chinese study reported that FTO variants were associated with a preference for meat-based meals in children and adolescents (41), although little is known about their relationship with food intake in Asian populations. In the present study, foods rich in protein (e.g. organ meat and blue fish) seemed to be preferred by T-allele carriers. This finding suggests a role for FTO in protein sensing and preference. However, the association between coffee creamer preference and genetic variant was clear; moreover, a number of studies have suggested that FTO variants are associated with fat and fat-containing energy-dense food preference and intake (23, 42–45). Given these findings, we cannot rule out the idea that FTO is associated with a preference for rich and/or high-fat foods. More studies are required to verify the association of FTO with nutrient sensing, food preference, and intake in the etiology of obesity.
This study examined the association between FTO rs1121980 and dietary intake in Koreans. This study is the first to explore FTO-associated food intake in Koreans but could harbor a few limitations. First, this study utilized a cross-sectional design. Since this study collected data only at a certain point in time, it may be difficult to determine the causal relationship between food intake and genetic variants. Second, this study analyzed data for general and dietary intakes for middle- to old-aged adults using data from the KoGES Ansan/Ansung cohort from 2001 to 2002. The KoGES is a representative epidemiological survey in Korea. However, this study may not fully present all dietary and genetic features of Koreans and the recent change in dietary consumption over time. Third, dietary data were collected using the SQFFQ. Korean dishes commonly contain many mixed types of foods and spices. Furthermore, there are limited types of dishes cooked with oils and seasonings. Thus, food-based FFQs may not accurately capture small amounts of food and nutritional intake (46, 47). Finally, alcohol consumption was not included in this study. Alcohol is the most commonly used addictive substance as well as a type of food (48). This study mainly focused on the influence of FTO variation on food intake. The degree of alcohol use varies, and there may be more complex linkages between the factors contributing to alcohol consumption. To verify the precise association between FTO variation and alcohol consumption, more intensive studies targeting such addictive substances are needed. Therefore, the findings of this study should be interpreted with caution.
Conclusion
In conclusion, the T allele of rs1121980 in FTO is associated with food intake preferences, particularly with preferential intake of rich foods (high in fat; e.g. coffee creamer, blue fish, sweets, and snacks) in Koreans, although these preferences vary according to sex and BMI. Our findings may contribute understanding of the role of FTO in dietary intake as well as the etiology of obesity among the Korean population.
Acknowledgments
This study was conducted with bioresources from the National Biobank of Korea, the Centers for Disease Control and Prevention, Republic of Korea (KBN 2018-18). This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean Government (MSIT) (Nos. NRF-2018R1A1A1A05019155 and 2021R1A2C1008635).
Conflict of intertest and funding
The authors declare no potential conflicts of interest.
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