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Keywords:

  • β3 adrenergic receptor;
  • polymorphism;
  • obesity phenotypes;
  • gender

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References

Objectives: Obesity is a complex trait that is affected by both environmental and genetic risk factors. The β3 adrenergic receptor (ADRB3) is expressed in adipose tissue and plays a role in energy metabolism. A missense mutation on codon 64 of this gene (W64R) is associated with receptor malfunction. Previous studies examining the relation between this polymorphism and obesity produced inconsistent findings. The current study assessed the association between the W64R genotype and obesity-related phenotypes, including body weight, BMI, and serum triglycerides, cholesterol, and glucose.

Research Methods and Procedures: We determined the ADRB3 W64R genotypes and fasting serum lipid and glucose concentrations for 695 hypertensive adults (336 men, 359 women) from a rural county in Anhui Province, China. Multivariate linear regression models were fit to detect associations between the genetic polymorphism and obesity-related phenotypes.

Results: The ADRB3 W64R polymorphism was significantly associated with body weight and BMI in men but not in women. After controlling for potential confounding variables, men who were homozygous for the R64 allele were 11.8 kg heavier (p < 0.001) and had a BMI that was 3.7 kg/m2 greater (p = 0.001) than men who were homozygous for the W64 allele. Serum concentrations of lipids and glucose were found not associated with the genetic polymorphism.

Discussion: The ADRB3 R64 allele was associated with increased body weight and BMI in men but not in women. The genetic association was not modified by triglyceride, cholesterol, blood glucose, or blood pressure levels of the subjects.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References

Obesity and overweight are significant public health problems worldwide, affecting an estimated 1 billion persons and contributing to hypertension, type II diabetes, cardiovascular disease, and death (1, 2, 3). The high concordance of body composition in monozygotic twins and the results of familial aggregation studies suggest that genetic factors may be important determinants of human obesity (1, 4). However, studies that have examined the association between specific genes and obesity have produced inconsistent results (2).

The β3 adrenergic receptor (ADRB3),1 the gene of which is located on human chromosome 8p12-p11.2, is mainly expressed in adipose tissue and contributes to population variations in energy expenditure and body fat distribution (5). A missense mutation of the gene, resulting in replacement of tryptophan by arginine at codon 64 (W64R), has been described recently (6, 7, 8). This single nucleotide polymorphism (SNP) has been associated with insulin resistance (7), obesity in both adults (8, 9, 10) and children (11), hyperinsulinemia (12), and hypertension (13). This SNP has also been associated with BMI and an increased capacity to gain weight (8) and fasting concentrations of high-density lipoprotein (14) and glucose (15). Interestingly, a subset of previous reports show gender-specific effects of the W64R genotype. For example, in a Spanish Mediterranean population, Corella et al. found that the R64 allele was significantly associated with BMI and total cholesterol concentration in men but not in women (15). Similarly, Kawamura et al. reported an association between the R64 allele and upper body obesity in Japanese-American men but not in women (16). Despite these findings, several studies have failed to show a relation between this SNP and obesity in other populations, including Aymara natives from Chile (17), Mexican-Americans (18), Chinese (19), and Finns (20). In the current study, we investigated the relation between this polymorphism and obesity-related phenotypes in a cohort of hypertensive Chinese men and women.

Research Methods and Procedures

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References

Study Population

This study was a part of the Anhui Hypertension Health Care Study, conducted from July 2000 to May 2001 in Anhui Province, China. The study protocol was approved by the Institutional Review Boards of the Anhui Medical University and the Harvard School of Public Health. Informed consent was obtained from all the study participants. This study recruited participants with elevated blood pressure levels [diastolic blood pressure (DBP) of 90 to 120 mm Hg, systolic blood pressure (SBP) of 140 to 200 mm Hg, or both] from Huoqiu County. Women were excluded if they were pregnant or nursing. Therefore, all these subjects included in this study were affected by hypertension. There were a total of 605 families included (13 families of 3 siblings, 64 families of 2 siblings, and 528 families of 1 singleton offspring).

Phenotypic Data Collection

The study participants came to the research center at ∼8 am after an overnight fast. After the participants rested for 1 hour in a supine position, their blood pressures were measured. Then, a standard questionnaire was administered to obtain information on demographic variables, disease history, smoking status, and alcohol consumption. The subjects were also asked to remove their outer clothes and their body weight and height were measured to the nearest 0.1 kg and 0.1 cm, respectively. Median cubital venous blood samples were collected using venipuncture using a BD Safety-Lok blood collection set (Becton Dickinson, Franklin Lakes, NJ) and was placed into a 10-mL vacutainer (Becton Dickinson). DNA was extracted by methods previously described (21). Serum total cholesterol, triglycerides, and glucose were measured using a clinical chemistry kit (Shanghai Kehua Bioengineering Co., LTD, Shanghai, China) with a Beckman CX5CE clinical analyzer system (Beckman Coulter, Inc., Brea, CA).

Genotyping

The ADRB3 W64R polymorphism was genotyped using a polymerase chain reaction (PCR) amplification of genomic DNA followed by restriction endonuclease digestion. The PCR primers were 5′-CAATACCGCCAACACCAGTGGG-3′ and 5′-GGTCATGGTCTGGAGTCTCG-3′. PCR was carried out in a volume of 10 μL containing 30 ng of genomic DNA, 2.0 mM MgCl2, 200 μM deoxynucleotide triphosphate, 300 nM of each primer, 0.025 U Taq DNA polymerase (Applied Biosystems, Foster City, CA), and 1× reaction buffer. PCR began with an initial denaturation at 94 °C for 10 min, followed by 35 amplification cycles (94 °C for 30 sec, 64 °C for 45 sec, and 72 °C for 45 sec) and an additional 7 min at 72 °C. The PCR amplicon was digested with 3 U of MspI (New England Biolabs, Beverly, MA) at 37 °C for 15 h. Digestion products underwent electrophoresis on 3.5% Seakem LE agarose gels (FMC Bioproducts, Rockland, ME) and visualized with ethidium bromide staining under ultraviolet illumination.

Statistical Analysis

We performed descriptive analyses first of the clinical and sociodemographic characteristics of the study population, including calculations of the means and SDs of the phenotypes of interest by specific genotypes. The central focus of the analysis was to determine the association between ADRB3 W64R genotype and the obesity-related phenotypes, including body weight, BMI, serum triglycerides, cholesterol, and glucose, with adjustment for important confounders. Then, we performed association analysis between the ADRB3 W64R genotype and obesity-related phenotypes using regression methods. We applied a pooled multivariate linear regression model to evaluate the main effects of the genotype and gender on the outcome variables, with inclusion of an interaction term defined as the cross product of genotype and gender. Because male and female subjects were found to differ significantly in regard to a number of demographic and clinical variables such as height, weight, BMI, and plasma triglycerides level, and the interaction term of genotype × gender in the multivariate regression analysis was statistically significant (p = 0.003), we performed all association analyses after stratification by gender. We treated the W64 (i.e., the wild-type allele) homozygotes as the reference group, and defined the W64R and R64R genotypes as two separate dummy variables. In the multivariate model, we also adjusted for the confounding effects of age, age2, height, height2, smoking status, SBP, DBP, and alcohol use. To account for the influences of intra-family correlation, a generalized estimation equation was applied to properly adjust the standard errors. All data were analyzed using SAS 6.12 (SAS Institute, Cary, NC) and Splus 2000 Professional (Mathsoft Inc., Cambridge, MA) software packages. We also calculated the heterozygosity and polymorphism information content of W64R using POLYMORPHISM v2.2 (22). Statistical deviations of the W64R genotype distribution from Hardy-Weinberg equilibrium were tested using χ2 analysis.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References

The characteristics of the 695 study subjects (336 men, 359 women) are summarized in Table 1. Overall, the mean BMIs of the study group were 24.7 and 25.5 kg/m2 for men and women, respectively, and the mean BMI for women was significantly greater than that of men (p = 0.002). Men had significantly higher rates of cigarette smoking and alcohol use compared with women. The allele frequency of R64 (the mutant allele) in the overall study group was 16.7%, with no significant difference observed between men and women (p = 0.51). The heterozygosity and polymorphism information content for the W64R polymorphism were 0.278 and 0.240, respectively, and the genotype frequency distributions were in Hardy-Weinberg equilibrium in both genders.

Table 1. . Clinical characteristics and ADRB3 genotype of study cohort*
 Men (n = 336)Women (n = 359)p value
  • *

    Continuous variables were summarized as mean ± SD, and the p value was derived from Student's t test; categorical variables were summarized as percentages, and the p value was obtained from Pearson's χ2 test.

Age (years)47.9 ± 8.548.4 ± 7.00.482
Height (cm)167.3 ± 6.0156.4 ± 5.7<0.001
Weight (kg)69.6 ± 11.962.8 ± 10.6<0.001
BMI (kg/m2)24.7 ± 3.425.5 ± 3.50.002
Blood pressure BMI (mm Hg)   
 Systolic at baseline145.5 ± 14.3152.9 ± 14.4<0.001
 Diastolic at baseline93.3 ± 8.692.9 ± 8.20.582
Plasma parameters (mM × 10)   
 Triglycerides13.3 ± 9.711.6 ± 7.20.012
 Cholesterol48.5 ± 9.149.5 ± 8.00.143
 Glucose47.1 ± 8.347.4 ± 10.00.667
Former smoker (%)13.1%1.7%<0.001
Current smoker (%)39.0%0.6%<0.001
Former drinker (%)8.3%3.6%0.013
Current drinker (%)49.4%1.4%<0.001
ADRB3 W64R genotype frequency, count (%)  0.510
 W64W226 (67.3%)256 (71.3%) 
 W64R100 (29.3%)94 (26.2%) 
 R64R10 (3.0%)9 (2.5%) 

To test whether the genotype and gender had a synergetic effect on BMI, we introduced the interaction term (genotype × gender) into the regression model and found a significant genotype × gender interaction (p = 0.003). The associations between the ADRB3 genotype and the clinical phenotypes of interest are shown in Table 2. In men, the average BMI of the R64R homozygotes was 3.7 kg/m2 greater (p = 0.001) and the average body weight was 11.8 kg heavier (p < 0.001) than those of the referent group (W64W homozygotes). However, the BMI and body weight of men with the W64R genotype were not significantly different from those of the reference group (p = 0.60 for BMI; p = 0.31 for body weight). In women, no association of the ADRB3 genotype with either BMI or body weight was observed. No relation was observed between ADRB3 genotype and fasting plasma concentrations of glucose, triglycerides, or total cholesterol, and no association was found between genotype and plasma levels of low-density lipoprotein and high-density lipoprotein cholesterol levels in both genders (data not shown). All subjects in our cohort were hypertensive, but their blood pressure values still exhibited a relatively wide distribution (Table 1). Therefore, we repeated the association tests with adjustment for blood pressure (i.e., both baseline levels of SBP and DBP), and the direction and magnitude of the relationship between genotype and obesity phenotypes remained essentially unchanged (in men, β = 3.0 kg/m2 and p = 0.006; in women, β = 0.3 kg/m2 and p = 0.79). In the entire sample, 14.0% of the subjects were found to be ever treated with antihypertensive medications. By conducting Student's t test, we found that the medication was not associated with BMI (in men, p = 0.19; in women, p = 0.93). To avoid bias introduced by the influence of previous therapies of hypertension, we excluded all those subjects who had ever used antihypertensive medication and repeated the association tests between ADBR3 genotype and BMI. The findings remain unchanged (in men, β = 3.5 kg/m2 and p < 0.001; in women, β = 0.5 kg/m2 and p = 0.68).

Table 2. . Association of ADRB3 genotype with body weight, BMI, and plasma biochemical parameters*
 Men (n = 336)Women (n = 359)
 β ± SEp valueβ ± SEp value
  • *

    BMI adjusted by age, age2, height, height2, smoking status, and alcohol drinking; blood lipid and glucose levels were presented in the unit of millimolar. ADRB3 W64W homozygotes were used as reference group. β, regression coefficient.

BMI (kg/m2)    
 W64WReferent Referent 
 W64R0.2 ± 0.40.600.0 ± 0.40.95
 R64R3.7 ± 1.10.001−0.4 ± 1.20.73
Weight (kg)    
 W64WReferent Referent 
 W64R1.2 ± 1.20.310.9 ± 1.10.40
 R64R11.8 ± 3.1<0.001−0.9 ± 3.20.77
Triglycerides (mM × 10)    
 W64WReferent Referent 
 W64R−1.3 ± 1.20.291.1 ± 0.90.21
 R64R−0.1 ± 3.40.97−1.0 ± 2.80.72
Cholesterol (mM × 10)    
 W64WReferent Referent 
 W64R−1.5 ± 1.10.200.9 ± 1.00.36
 R64R−0.4 ± 3.20.902.9 ± 3.00.34
Glucose (mM × 10)    
 W64WReferent Referent 
 W64R0.7 ± 1.00.520.7 ± 1.20.55
 R64R3.8 ± 3.00.201.3 ± 3.50.71

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References

The primary finding in this study was that men with ADRB3 R64R homozygous genotype were significantly heavier and had a significantly greater BMI than men with W64R and W64W genotypes. This association was not observed in women. It should be noted that the R64 frequency in this study population was relatively low (<20%), which yielded only 10 male subjects in the R64R group who had significantly elevated BMI (Table 1). Our results are similar to previous findings in a Japanese population, where a significant proportion (13.6%) of the ADRB3 R64R subjects (n = 38) were obese, whereas as low as 2.1% and 3.3% were found to be obese among W64R (n = 476) and W64R (n = 1155) subjects, respectively (23). Furthermore, a review of prior studies found that several reports showed that only those subjects with R64R genotype had an increased BMI (24). Previous literatures also demonstrated that, on average, R64R carriers are 3 kg/m2, and W64R carriers are only ∼1 kg/m2 greater than the W64W carriers in terms of BMI (24).

The inconsistency of the previous report on this gene effect could be due to multiple reasons. First, the frequency of the R64 allele varies greatly across distinct ethnic populations. It is 8% to 10% among whites (6, 24), 13% among Mexican Americans (6), 12% among blacks (6), 17.0% among Japanese (23), and 16.7% in Chinese (this study), but much higher in Alaskan Eskimos (40%) (24), Pima Indians (31%) (6), and Canadian Oji-Cree (40%) (25). Second, the average BMI differs across populations of different ethnicities [for example, the mean BMI of a Mediterranean population had an average BMI of 26.4 ± 3.8 in men and 23.6 ± 4.2 in women (17), whereas the average BMI was 24.7 ± 3.4 in men and 25.5 ± 3.5 in women in the current study]. The previous literature appears to show that in populations that are lean (with an average BMI < 25kg/m2), the observations are in agreement with a recessive effect of the ADRB3 R64 allele on BMI. Because of the rareness (<4%) of the R64R homozygotes in such populations (e.g., Asians such as Chinese and Japanese), large sample sizes would be a necessity to ensure a sufficiently high statistical power. Compared with our study, some previous negative studies have relatively small-to-moderate sample sizes [e.g., n = 137 in Chinese (19) and n = 152 in a Chile population (17)], and their negative findings may be due to a lack of statistical power. Given a sufficiently large sample size, the effect of the R64R homozygotes can be detected, such as in (23) and in the current study. In contrast, in populations with a higher mean BMI (i.e., ≥25 kg/m2), which are often from the western societies, the impact of the ADRB3 W64R heterozygotes on BMI seems to be detectable (8, 10, 26). One possible biological rationale is presented as follows. W64R, which leads to a substitution of tryptophan by arginine at codon 64 in the coding sequence of the ADRB3 protein, alters the receptor's sequence at the beginning of the first intracellular loop. This ADRB3 protein domain is thought to function in trafficking of the receptor to the cell surface and its coupling to G proteins (6). The presence of the mutant allele (R64) may reduce the receptor synthesis, binding, or signaling (6). In westernized populations with high prevalences of sedentary lifestyle and dietary intake of fat, W64R heterozygotes (i.e., malfunction of only one copy of the β3 receptor) could already lead to an observable increase of BMI; however, in populations with a low dietary intake of fat and a high prevalence of physical exertion (such as the Chinese population of the current study), only R64R homozygotes can manifest a noticeable effect on BMI.

The molecular mechanisms underlying the association of the ADRB3 W64R genotype and various physiological phenotypes are still unknown. Some recent reports suggest that the R64 allele may contribute to obesity by altering lipid and glucose metabolism (8, 27). For example, Corella et al. (15) found an association of the R64 allele with both BMI and total cholesterol in men in a Spanish Mediterranean population. However, we found that the ADRB3 genotype was not associated with fasting blood glucose or lipid levels in Chinese of this study. The absence of this association between genotype and serum biomarkers in our study could be due to differences of nutritional and lifestyle factors between this rural county in China and the westernized societies. Our observations suggest that the R64 allele can be associated with obesity independent of blood lipid or glucose levels.

Our observation suggests that the genetic effect of W64R polymorphism is gender-specific. Such findings in this Chinese population are concordant with the same gender-specific effects observed in other studies of ADRB3 genotype-BMI associations in a Spanish Mediterranean population (15) and a Japanese-American population (16). A spurious gender specificity to the development of the obese phenotype in persons with the ADRB3 SNP could occur if the genotype interacts with certain environmental exposures that were unevenly distributed across gender. For example, in our subjects, men and women are clearly distinct in certain aspects of lifestyle, such as tobacco and alcohol use (Table 1). However, we found that the male-specific association between ADRB3 genotype and a higher BMI persisted when these factors were controlled in the statistical analysis.

A feature of our study population to consider is that all the subjects were hypertensive. Because the ADRB3 polymorphism has been associated with hypertension and other obesity-related disorders, the selection of our subjects on the basis of hypertension may have enriched our study population with subjects with other ADRB3-related metabolic disorders. Several limitations need to be noted in considering our current findings in terms of the propensity to develop obesity. First, our study only examined a single SNP in one candidate obesity gene. Obesity is a complex trait, and other candidate genes have been identified in other studies, including genes for leptin, the leptin receptor, pro-opiomelanocortin, pro-hormone convertase-1, and the melanocortin-4 receptor (2, 24). Second, our findings may be influenced by confounding due to uncontrolled or inadequately controlled risk factors, such as nutritional status or physical activity. Third, this study was conducted in subjects with essential hypertension. Finally, our key findings were based on a relatively moderate number of R64 homozygous males; until more data are available, caution is needed to generalize the study findings to other populations.

Acknowledgment

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References

This study was supported in part by the Anhui Provincial Ministry of Education, Anhui Medical University Biomedical Institute and by the National Institute of Environmental Health Science (Grant ES00002). We gratefully acknowledge the assistance and cooperation of the faculty and staff of the Anhui Medical University. We thank all the study participants and their families.

Footnotes
  • 1

    Nonstandard abbreviations: ADRB3, β3 adrenergic receptor; SNP, single nucleotide polymorphism; DBP, diastolic blood pressure; SBP, systolic blood pressure; PCR, polymerase chain reaction.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References
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