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The Journal of Clinical Endocrinology & Metabolism Vol. 88, No. 12 5914-5920
Copyright © 2003 by The Endocrine Society

The Trp64Arg Polymorphism of the ß3-Adrenergic Receptor Gene Is Not Associated with Body Weight or Body Mass Index in Japanese: A Longitudinal Analysis

Yumi Matsushita, Tetsuji Yokoyama, Nobuo Yoshiike, Yasuhiro Matsumura, Chigusa Date, Kazuo Kawahara and Heizo Tanaka

Graduate School, Tokyo Medical and Dental University (Y.M., K.K.), Tokyo 101-0062, Japan; National Institute of Public Health (T.Y.), Saitama 351-0197, Japan; National Institute of Health and Nutrition (N.Y., Y.M., H.T.), Tokyo 162-8636, Japan; and Mukogawa Women’s University (C.D.), Osaka 663-8558, Japan

Address all correspondence and requests for reprints to: Dr. Yumi Matsushita, Department of Health Policy Science, Graduate School, Tokyo Medical and Dental University, 2-3-21-4F Kanda-Surugadai, Chiyoda-ku, Tokyo 101-0062, Japan. E-mail: address ym.hcm{at}tmd.ac.jp.


   Abstract
Top
 Abstract
Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
The ß3-adrenergic receptor (ADRB3) is expressed mainly in visceral adipose tissue and is thought to contribute to lipolysis and the delivery of free fatty acids to the portal vein. Although many studies have examined the relationship between the Trp64Arg mutation of ADRB3 and obesity, the results have been inconsistent. We examined the cross-sectional relationship of ADRB3 variants with indexes of obesity, and their longitudinal changes over 10 yr, in men and women, aged 40–69 yr, who were randomly selected from the Japanese rural population. The study considered both dietary energy intake and physical activity levels. Among the 746 participants, the genotype frequencies of the Trp64Trp, Trp64Arg, and Arg64Arg variants were 483, 224, and 39, respectively. The cross-sectional analysis showed no significant differences in height, weight, body mass index, blood pressure, serum total and high density lipoprotein cholesterols, and hemoglobin A1c among the genotype groups even after adjustments for gender, age, smoking, alcohol drinking, physical activity, and energy intake. No significant differences in the weight changes between the genotype groups were evident in the longitudinal analysis. We conclude that the Trp64Arg mutation of ADRB3 has little or no influence on either body weight or body mass index in the general Japanese population.


   Introduction
Top
 Abstract
 Introduction
Subjects and Methods
 Results
 Discussion
 References
 
HUMAN OBESITY IS influenced by both genetic and environmental factors. Bouchard et al. (1) estimated that the inheritability of accumulating body fat reached approximately 25% of its interindividual variance. Notably, a cohort study involving genetically identical twins showed that genetic factors are strongly involved in the accumulation of visceral adipose tissue (2). In 1995, Walston et al. (3, 4, 5) identified a missense mutation in the ß3-adrenergic receptor (ADRB3) gene in Pima Indians. In humans, ADRB3 is mainly expressed in visceral adipose tissue, where it is thought to contribute to both lipolysis and the delivery of free fatty acids to the portal vein. At the protein level, the reported missense mutation caused the replacement of tryptophan, the 64th amino acid of ADRB3, with arginine (the Trp64Arg mutation). A study involving Japanese subjects reported that this mutation caused a 200 kcal/d decrease in the resting metabolic rate (6). Moreover, this mutation has been reported to be associated with obesity, abnormalities of calorigenic function, features of syndrome X (abdominal obesity, high blood sugar, insulin resistance, and blood pressure elevation), weight increase with aging, and the early onset of diabetes mellitus (3). This mutation is also considered to be a possible genetic marker for both obesity-related visceral adipose and insulin resistance syndrome (6, 7, 8). Among the reported ethnic groups, Alaskan Eskimos (9) and Pima Indians (3) displayed very high allelic frequencies of the Trp64Arg mutation (0.38 and 0.31, respectively). After these groups, the Japanese population also showed a high allelic frequency of this polymorphism (0.21) (10), which was 2- to 3-fold that found in Caucasian populations (6, 7, 8).

If the Trp64Arg gene mutation is associated with obesity and obesity-related diseases such as diabetes and hypertension, then the high frequency of this mutation in the Japanese population is of great significance to public health. Thus, it is important to measure the potential relationship between this mutation and disease. Such data may enable health professionals to recommend appropriate levels of energy intake for people with specific genotypes. However, previous studies of the relationship between the Trp64Arg mutation and obesity, or obesity-related diseases, have produced inconsistent findings. Several studies reported that people with the Trp64Arg mutation were at a high risk of developing obesity, glucose intolerance, and high blood pressure (4, 5, 11, 12, 13, 14), whereas other studies failed to find any correlation between this mutation and the standard obesity indexes, such as body mass index (BMI), body weight, and the amount of sc adipose (15, 16). These inconsistent findings may be due to differences in the target population (including gender, race, diabetes history, and obesity status) and environmental or lifestyle factors (e.g. dietary energy intake and physical activity levels). Of these factors, dietary energy intake and physical activity levels are important factors that relate directly to obesity and therefore should be included in the analysis. However, very few studies of the Trp64Arg mutation as a factor in obesity have simultaneously considered these two lifestyle factors. In addition, studies that examine a representative sample of the general population would be very informative from a public health viewpoint. However, very few studies have attempted such a large scale examination of the general Japanese population. Furthermore, to evaluate the relationship between the ADRB3 variation and obesity, it may be worthwhile to examine not only the cross-sectional relationships, but also the longitudinal weight changes in individuals with different ADRB3 genotypes. However, such longitudinal studies have rarely been undertaken (17).

In this study we used cross-sectional analysis to examine the relationship of the Trp64Arg ADRB3 variant with indexes of obesity. The dietary energy intake and physical activity levels, changes that had occurred during the past 10 yr of the subject’s life, and changes occurring after the age of 20 yr (a longitudinal analysis) were assessed within a representative sample of a Japanese rural population.


   Subjects and Methods
Top
 Abstract
 Introduction
 Subjects and Methods
Results
 Discussion
 References
 
The present study was undertaken as part of a larger study being carried out to monitor the changes in lifestyle and risk factors associated with cardiovascular diseases between 1990 and 2000 in Shiso, a rural area located in the northwest of Hyogo Prefecture in Japan. The study area encompassed five towns, designated Y, I, S, H, and C. All residents between 40 and 69 yr of age were within the eligible population, and the actual study subjects were selected from this group by stratified random sampling based on town and decade of age. The detailed sampling methods have been described previously (18).

The 347 male and 399 female participants selected were examined at local community halls. Body weight and height were measured using calibrated scales. The BMI was calculated as weight (kilograms) divided by squared height (meters squared). The blood pressure was measured twice on the right arm using a standard mercury sphygmomanometer and following a standardized procedure (19) by a staff physician who had received videotape training and had passed a certification test. The mean of the first and second blood pressure determinations was used for the analysis. The medical history was confirmed by a public health nurse’s interview.

The present study was approved by the ethics review committee of Tokyo Medical and Dental University School of Medicine, and written informed consent was obtained from all subjects.

Laboratory methods

Venous blood samples were drawn into both EDTA and serum tubes and were stored at 4 C for transport to the laboratory. The blood cells were frozen at -80 C until later DNA extraction. The serum concentrations of total cholesterol (T-Chol) and high density lipoprotein cholesterol (HDL-Chol) were determined by an enzymatic method with an autoanalyzer (model 7170, Hitachi, Ibaraki, Japan). The hemoglobin A1c (HbA1c) level was also determined.

Genomic DNA was prepared from leukocytes obtained from separated blood cells using Puregene (Gentra Systems, Inc., Minneapolis, MN). The determination of the ADRB3 variant was performed using the PCR method as described by Sivenius et al. (14). The genotypes were determined as Trp64Trp, Trp64Arg, and Arg64Arg without prior knowledge of the subjects’ status.

Assessment of lifestyle factors

Under the supervision of dietitians or nurses specially trained for this study, each of the participants filled out a standardized questionnaire that included questions regarding physical activity, smoking, alcohol consumption, body weight at 20 yr of age (self-reported), and other lifestyle-related factors.

The subjects were interviewed by a trained dietitian-interviewer for the collection of dietary data using the 24-h recall method. Each subject kept a record of his/her food intake over 1 d in advance of the examination, and the interviewer asked in detail about the foods he/she had eaten during the previous day. The portion size was also determined by this interview with the aid of both food scales and real-size food photograph booklets. Subsequently, energy intake was calculated based on the Standard Tables of Food Composition in Japan, 4th edition (20).

To evaluate the degree of physical activity, the intensity of physical activity as determined by a metabolic equivalents (METs) score was measured. One MET is defined as the resting metabolic rate, that is, approximately equivalent to 1 kcal/kg body weight·h (21). The subjects were queried to determine the frequency and average duration of various types of labor and job-related activities, including household activities, for every 2-month period over the previous 12 months (22). The active intensity index was defined as the average METs score over the 12-month study period, not including sleeping hours, and these METs scores were then divided into tertile groups (inactive, moderate, and active).

Longitudinal data

Residents in the study area had previously had annual health check-ups. At these annual check-ups, body height and weight were measured using a calibrated scale. These data were supplemented with archival data from the period of 1990–2000. The self-reported body weight at 20 yr of age was obtained at the examination in 1999 or 2000. The subjects included in the longitudinal analysis were those who had had check-ups at least twice in the past 10 yr, including the current examination (in 1999 or 2000), and the earliest check-up was performed at least 5 yr before the current examination. Of the participants aged 45 yr and older, 74.9% (64.8% of men and 83.7% of women) met these inclusion criteria.

Statistical analysis

The allele frequency was determined by direct counting. Deviation of the genotype distribution from the Hardy-Weinberg equilibrium was analyzed by the exact test. The prevalence of a medical history of diabetes was compared among the ADRB3 genotype groups by a logistic regression analysis adjusted for potential confounders. As diabetes and its treatment could influence body weight, we excluded those subjects with a medical history of diabetes from all of the following analyses unless otherwise indicated. The relationship between the ADRB3 genotype and other factors was examined by an analysis of covariance with a calculation for the least square mean (LSM) and SE adjusted for potential confounding factors; multiple comparisons were performed using Scheffé’s test. A multiple linear regression analysis was performed to examine whether the relationships of energy intake and physical activity level with the body weight and BMI differed according to the subject’s ADRB3 genotype. Furthermore, this analysis was tested statistically using the interaction term of genotype x energy intake or genotype x physical activity level. The longitudinal individual changes in body weight and BMI during the preceding 10 yr were examined using the random effects regression model with a random intercept and slope representing time, where the dependent variable was body weight or BMI; the independent variables were time (years), ADRB3 genotype, and the interaction of time x ADRB3 genotype; the unit was each individual. Changes in body weight and body mass index from the age of 20 yr until the time of the most recent examination were compared among the genotypes by analysis of covariance, followed by Scheffé’s test. All statistical analyses were performed using SAS software (version 8.2, SAS Institute, Inc., Cary, NC).


   Results
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
Discussion
 References
 
The mean ± SD age of the study subjects was 53.3 ± 8.8 yr in men and 54.0 ± 8.6 yr in women. The frequency of the ADRB3 genotype is shown in Table 1Go. The Trp64Trp genotype (wild-type) had an overall frequency of 64.7%, whereas the Trp64Arg heterozygote and the Arg64Arg homozygote frequencies were 30.0% and 5.2%, respectively. There was no notable difference in genotype distribution between men and women. The genotype frequency data did not differ from those expected from the Hardy-Weinberg equilibrium, and the mutant allele frequency data obtained were similar to those reported in other studies involving Japanese subjects (10).


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  		TABLE 1. Distribution of the Trp64Arg genotype in the study subjects

 
The frequency of those who had a medical history of diabetes was not significantly different among the three genotype groups (data not shown). The HbA1c levels were also similar among the genotype groups (gender- and age-adjusted LSM ± SE, 4.93 ± 0.04%, 4.92 ± 0.05%, and 5.08 ± 0.12% in the Trp64Trp, Trp64Arg, and Arg64Arg groups, respectively; P = 0.46; not shown in table). These results remained essentially unchanged even when they were separately analyzed for men and women and further adjusted for smoking, alcohol drinking, physical activity, and energy intake. As diabetes could influence body weight as a consequence of the disease, all of the following results were for those subjects without a medical history of diabetes.

In Table 2Go, the height, weight, BMI, systolic and diastolic blood pressures, T-Chol, and HDL-Chol among the different ADRB3 genotypes were compared. The age-adjusted LSM ± SE of BMI were very similar among the different ADRB3 genotype groups (23.11 ± 0.14, 23.02 ± 0.21, and 23.07 ± 0.48 kg/m2 in the Trp64Trp, Trp64Arg, and Arg64Arg groups, respectively; P = 0.94). Even after taking into consideration recessive, dominant, and additive effects, no significant differences in any of the variables were observed (P values not shown). There were also no significant differences in height, weight, systolic and diastolic blood pressures, T-Chol, and HDL-Chol among the different genotype groups for either men or women or in combined gender datasets. Additional adjustments for smoking, alcohol drinking, physical activity, and energy intake did not significantly affect the results.


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  		TABLE 2. Association of the Trp64Arg polymorphism of the ADRB3 gene with BMI and obesity-related factors with adjustment for potential confounders

 
The relationship of body weight and BMI with physical activity and energy intake was analyzed by a multiple linear regression model, and the strength of this relationship (expressed as partial regression coefficient) was compared among the ADRB3 genotype groups (Table 3Go). There were no significant differences in the partial regression coefficient among the three genotype groups.


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  		TABLE 3. Association of physical activity and energy intake with body weight and BMI according to the Trp64Arg polymorphism of the ADRB3 gene

 
The average annual changes in body weight and BMI in each of the ADRB3 genotype groups are compared in Table 4Go. In this table, the partial regression coefficient indicates the estimated average annual change in body weight and BMI during the period before the most recent examination in 1999 or 2000 (data from the most recent examination to 10 yr previous to this examination was included). In men, the average annual change in BMI was 0.052 ± 0.014 (regression coefficient ± SE) for the Trp64Trp subjects, 0.019 ± 0.019 for the Trp64Arg, and 0.018 ± 0.051 kg/m2 for the Arg64Arg genotype subjects. There were no significant differences in the amount of change between any of the genotype groups. In women, the average annual change in BMI was 0.036 ± 0.010 for the Trp64Trp, 0.023 ± 0.014 for the Trp64Arg, and 0.053 ± 0.036 kg/m2 for the Arg64Arg genotype groups. As reported above, there were no significant differences in the amount of change between any of these groups. Figure 1Go illustrates a detailed frequency distribution of the average annual change in BMI in each of the genotype groups (both genders combined). The distributions were very similar among the genotype groups.


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  		TABLE 4. Relationship between body weight and BMI changes and Trp64Arg polymorphism of the ADRB3 gene over a 10-year period

 


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  		FIG. 1. Distribution of the longitudinal change in BMI over a 10-yr period among individuals with different Trp64Arg genotypes. The change in BMI was estimated by a random effects regression model, with random intercept and slope representing time. Subjects who had a medical history of diabetes were excluded from the analysis. The distributions were not significantly different among the three genotype groups (see also Table 4Go).

 
In Table 5Go, the body weight and BMI of the subjects at 20 yr of age (from self-reported data) and at the time of this study (in 1999 or 2000) in addition to the changes in these variables during that period were compared among the genotypes. The BMIs at 20 yr of age were 22.55 ± 0.12, 22.41 ± 0.17, and 22.69 ± 0.39 kg/m2 (adjusted LSM ± SE) in men and 21.62 ± 0.10, 21.73 ± 0.15, and 22.46 ± 0.37 kg/m2 in women for the Trp64Trp, Trp64Arg, and Arg64Arg groups, respectively.


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  		TABLE 5. Changes in body weight and BMI occurring from the age of 20 yr according to the Trp64Arg polymorphism of the ADRB3 gene

 
There were no significant differences among the various genotypes in either men or women. The changes in BMI between the age of 20 yr and the age at the time of this study were 1.05 ± 0.21, 1.19 ± 0.29, and 0.16 ± 0.65 kg/m2 in men and 1.13 ± 0.17, 0.99 ± 0.26, and 0.88 ± 0.63 kg/m2 in women for the Trp64Trp, Trp64Arg, and Arg64Arg groups, respectively. As reported above, these data show that there were no significant differences in change in BMI among the genotypes. There were also no significant differences in the changes in height and weight among the genotype groups in either men or women.


   Discussion
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
References
 
In this study we analyzed the relationship between the Trp64Arg polymorphism of the ADRB3 gene and several obesity indexes. We did not find any significant differences in body weight, BMI, serum cholesterol levels, blood pressure, HbA1c levels, and the prevalence of diabetes among the genotype groups even after data were assessed with consideration for potential confounders (including physical activity and energy intake levels). We also compared the change in body weight and BMI during the 10 yr preceding the most recent examination and between the age of 20 yr to the time of the present examination among the three genotypes. This comparison did not show any significant differences in longitudinal changes in these variables between any of the genotype groups. Furthermore, the association of physical activity and energy intake with body weight and BMI was not significantly different between any of the genotype groups, indicating that there was no significant gene-environment interaction of the Trp64Arg polymorphism of the ADRB3 gene with physical activity and energy intake in determining body weight and BMI.

To measure the relationship between the Trp64Arg polymorphism of the human ADRB3 gene and BMI, three meta-analyses have been performed previously (23, 24, 25). According to these reports, the BMI was only slightly higher in individuals with the Arg mutation than in individuals without the mutation by 0.26 kg/m2 (23) (Trp64Trp variant vs. others, P < 0.01), 0.19 kg/m2 (24) (Trp64Trp vs. Trp64Arg, P = 0.07), and 0.30 kg/m2 (25) (Trp64Trp vs. others, P value not shown). However, some inherent limitations in these studies must be considered before any firm conclusions can be reached. First, environmental factors, in particular, energy intake and energy expenditure, have not been considered in most of these studies. Second, determination of the relationship of the ADRB3 variant to the BMI in cross-sectional studies should be viewed alongside evidence of long-term changes in BMI obtained through longitudinal studies. In addition, potential differences in the role of this ADRB3 gene mutation should be considered in relation to factors such as ethnicity, obesity levels, and the sampling methods used.

Energy intake and energy expenditure are thought to be the major determinants of obesity (26). Smoking and alcohol consumption can also influence body weight. If the effects of these environmental factors were much larger than those of the ADRB3 genetic mutation, then any effects from the latter would be concealed and difficult to detect. An adjusted analysis that considers these lifestyle factors is therefore important in accurate examination of the effects of a particular genetic mutation on body weight. As a significant effect of a genotype by smoking interaction on the serum leptin levels for the obesity-related quantitative trait locus in the immediate vicinity of ADRB3 gene has been reported previously (27, 28), the consideration of a genotype by smoking interaction may also be necessary for analysis of the ADRB3 gene and obesity. However, even the adjusted analysis indicated that the mutation did not have any significant effect on either body weight or BMI. The genotype by smoking interaction was not significant in our study sample, and therefore, the results were shown without any genotype by smoking interaction in the models.

Previously, a longitudinal study was carried out to determine the relationship between the Trp64Arg polymorphism of the ADRB3 gene and long-term changes in BMI in Japanese subjects (17). This study failed to detect any differences between the Trp64Trp and Trp64Arg genotype groups. However, the subjects of this study were male soldiers, a specialized group who engage in a high level of physical activity, and the study did not examine subjects with the Arg64Arg mutation genotype due to the small sample size. Another study examined longitudinal changes in BMI in a sample of Australian women (15) and also found no relationship between the Trp64Arg polymorphism and changes in BMI. However, the follow-up period in this study was only 2 yr. Our study, which considered and addressed all of the limitations mentioned above by using a random sample of the general population with a relatively long-term observation period, could not detect any association between the Trp64Arg mutation of the ADRB3 gene and longitudinal changes in the BMI.

Most of the previous studies examined subjects who were obese or suffering from diabetes mellitus (29). These studies did not determine whether the effects of the Trp64Arg mutation of the ADRB3 gene on body weight or BMI were significant among individuals in the general population who fall within a normal range of body weight. The present study was conducted using a random sample from a Japanese rural population in which the prevalence of obesity was relatively small compared with that found in Western countries. However, we did not observe any effects attributable to the Trp64Arg mutation of the ADRB3 gene in this population. Likewise, a previous study of the effects of the Trp64Arg mutation on BMI and visceral fat thickness in a general Japanese population (using a larger sample size) reported no significant effects (10). Therefore, in the general Japanese population (and possibly other racial populations), the Trp64Arg missense mutation of the ADRB3 gene is extremely unlikely to be the major determinant of body weight.

It is also possible that our observed results on gene-environment interactions could be somewhat diluted for the following reasons. First, we adopted a 24-h dietary recall method as a single measurement of food intake, which may not be an appropriate indicator of the average caloric intake of the individual subjects over a long period. On the other hand, the assessment method for physical activity levels was designed to estimate the average METs during the preceding 1 yr to avoid possible seasonal variations. The second consideration is that the lifestyle factors related to energy intake and expenditure were only measured at the time of the cross-sectional examinations in 1999 or 2000, although the main outcome of our observation was the change in body weight during the 10-yr period. This means that potential changes in lifestyle during the 10-yr period were not fully assessed by a single and rather crude measurement of diet and physical activity. The third issue is that the observed changes in body weight during the 10-yr period were rather small (mean ± SD, +1.0 ± 3.7 kg/10 yr in men and +0.6 ± 3.0 kg/10 yr in women), which might reduce the statistical power to detect the relationship between body weight change and gene-lifestyle factors. The small changes, however, seemed to be common in the general Japanese population, because birth cohort analyses from the National Nutrition Survey, Japan, also showed similar small changes in average body weight over a 10-yr period for each birth cohort (30) corresponding to the age groups of our subjects. Considering the above-mentioned limitations of our study, a longitudinal study that includes repeated measurements of diet and physical activity in a population with more significant body weight gain by age would be much more useful in testing the hypothesis that the ADRB3 gene mutation influences weight gain.

We conclude that among Japanese adults in a general population, the Trp64Arg mutation of the ADRB3 gene had very little influence on body weight or BMI, even after adjustments for potential confounding factors. However, it should be noted that although our findings provide no specific evidence to indicate that the Trp64Arg mutation has an effect on the development of obesity, we cannot exclude the effects of the ADRB3 gene itself. Additional studies should be carried out on the region of chromosome 8 containing the ADRB3 gene as well as other genes, such as the peroxisomal proliferator-activated receptor and uncoupling protein families, with consideration of the energy intake and energy expenditure in the experimental design. Such experiments will further advance knowledge regarding the development of obesity and will help to identify genetic targets for more effective prevention and treatment of obesity.


   Acknowledgments
 
We offer special thanks to Dr. Yoshihiro Kokubo for his useful advice regarding the DNA analysis. We are also indebted to the staffs and residents of Shiso County who participated in this study.


   Footnotes
 
This work was supported by Grant-in-Aid for General Scientific Research (12470094) from Ministry of Education, Culture, Sports, Science, and Technology of Japan; a National Cardiovascular Center grant-in-aid; and Japan Heart Foundation research grants.

Abbreviations: BMI, Body mass index; HBA1c, hemoglobin A1c; HDL-Chol, high density lipoprotein cholesterol; LSM, least square mean; MET, metabolic equivalent; T-Chol, total cholesterol.

Received April 16, 2003.

Accepted September 11, 2003.


   References
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 

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