Skip to main content
PLOS ONE logoLink to PLOS ONE
. 2021 Aug 4;16(8):e0255444. doi: 10.1371/journal.pone.0255444

Relationships among the β3-adrenargic receptor gene Trp64Arg polymorphism, hypertension, and insulin resistance in a Japanese population

Youhei Yamada 1,2,*, Haruki Nakamura 1, Hiromasa Tsujiguchi 1,2,3, Akinori Hara 1,2,3, Sakae Miyagi 4, Takayuki Kannon 3,5, Takehiro Sato 3,5, Kazuyoshi Hosomichi 3,5, Thao Thi Thu Nguyen 6, Yasuhiro Kambayashi 7, Yukari Shimizu 8, Kim Oanh Pham 1, Keita Suzuki 1,2, Fumihiko Suzuki 1, Tomoko Kasahara 1,2, Hirohito Tsuboi 9, Atsushi Tajima 3,5, Hiroyuki Nakamura 1,2,3
Editor: Raffaella Buzzetti10
PMCID: PMC8336805  PMID: 34347822

Abstract

A polymorphism in the ADRB3 gene (Trp64Arg) has been associated with obesity, insulin resistance, and hypertension. This cross-sectional study investigated the relationships among this polymorphism, hypertension, and insulin resistance values (HOMA-IR) in 719 Japanese subjects aged 40 years and older. The genotype frequencies of Trp64Trp (homozygous, wild), Trp64Arg (heterozygous, variant), and Arg64Arg (homozygous, variant) were 466 (65%), 233 (32%), and 20 (3%), respectively. Insulin resistance was associated with an increased risk of hypertension in a Japanese population. This relationship was dependent on the presence or absence of the Trp64Arg polymorphism (odds ratio, 2.054; confidence interval, 1.191 to 3.541; P value, 0.010). Therefore, the Trp64Arg polymorphism of ADRB3 was associated with hypertension and insulin resistance in a healthy Japanese population. This relationship, which was dependent on the polymorphism, may predict the development of hypertension and diabetes.

Introduction

Hypertension is a major risk factor for global disease burden [1]. Many patients with hypertension have diabetes mellitus, which is strongly related to coronary heart disease, major stroke subtypes, and deaths attributed to other vascular causes [2]. The pathophysiology of these two diseases are similar and related to obesity and insulin resistance. Insulin resistance is a pathological condition that impairs insulin sensitivity. Previous studies reported a close relationship between hypertension and insulin resistance [3].

The etiology of hypertension involves genetic disorders. The present study on hypertension was based on Genome-wide Association Studies (GWAS), which search a vast number of single nucleotide polymorphisms (SNP) in a large cohort [4]. Prior to the initiation of GWAS, the main strategy employed to identify hypertension-susceptibility genes was the candidate gene approach. Several candidate genes have been reported using conventional approaches [5].

The β3-adrenergic receptor (ADRB3), one of the candidate genes, is a class of G protein-coupled receptors that primarily mediates lipolysis and thermogenesis. A polymorphism in the ADRB3 gene (Trp64Arg) impairs the function of ADRB3. A decline in function causes the pathogenesis of multiple conditions, including hypertension, insulin resistance, and obesity [68].

The effects of the Trp64Arg polymorphism need to be considered in investigations on the relationship between hypertension and insulin resistance. However, few studies have examined this triangular relationship. Widén et al. reported that the ratio of hypertension and insulin resistance was higher in Finns with the Trp64Arg polymorphism [7]. However, Fujisawa et al. suggested that the Trp64Arg polymorphism did not markedly affect the development of hypertension or insulin resistance in Japanese individuals [9].

Therefore, the present study aimed to examine the relationships among hypertension, insulin resistance, and the Trp64Arg polymorphism.

Methods

Study design and participants

Comprehensive medical check-up data obtained from the residents of Shika town, a rural area in Japan, were used for the analysis. Baseline data were derived from the SHIKA study, an overview of which was previously reported [10]. In brief, the SHIKA study is a population-based observational study conducted to investigate approaches that prevent lifestyle-related diseases. It was conducted with the approval of the Ethics Committee of Kanazawa University and informed consent was obtained from all participants. The target subjects of the SHIKA study were all middle-aged residents who were delivered a self-administrated questionnaire and requested to undergo a comprehensive health examination. In the present study, data on 1191 voluntary participants from 40 years of age who underwent the comprehensive health examination between March 2014 and January 2017 were available. The design of the present study was cross-sectional. This study was conducted with the approval of the Ethics Committee of Kanazawa University. Written informed consent was obtained from all participants.

Subjects with incomplete data on SNP (n = 326), blood pressure (n = 5), or fasting blood sugar (n = 83) and those whose HOMA-IR (homeostasis model assessment for insulin resistance) was less 0.3 (n = 18) were excluded from the analysis. Therefore, this study ultimately included 719 subjects (Fig 1).

Fig 1. Participant recruitment chart.

Fig 1

Genotyping

Genomic DNA was extracted from blood samples using the QIAamp DNA Blood Maxi Kit (QIAGEN Inc., Venlo, Netherlands) according to the manufacturer’s instructions or consigned to a company specialized in clinical laboratory testing (SRL, Inc., Tokyo, Japan). SNP genotyping was performed using the Japonica Array v2 [11] (TOSHIBA Inc., Tokyo, Japan).

The genotypes of ADRB3 Trp64Arg (rs4994) in 825 unrelated subjects (based on genome-wide π^ values) were extracted from array data. The call rate for SNP was 100% and a departure from the Hardy-Weinberg equilibrium was not observed.

Blood pressure measurement

Well-trained nurses and clinical technologists measured blood pressure (BP) using a fixed protocol. Two automated digital sphygmomanometers, HEM-907 (OMRON Inc, Kyoto, Japan) and UM-15P (Parama-tech Inc., Fukuoka, Japan), were used to check BP and their measurement of principle, the oscillometric method, was the same. This medical check-up was conducted in the morning and BP was measured in a fasted state.

BP was measured twice consecutively in a sitting position with an appropriate cuff and averages were adopted as BP data.

Subjects were divided into two groups according to the following definition of hypertension: subjects diagnosed with hypertension and being treated with antihypertensive drugs or those with BP of higher than 140/90 mmHg in medical check-ups.

Assessment of insulin resistance

HOMA-IR is regarded as a robust index for the assessment of insulin resistance and the homeostasis model assessment of beta cell function (HOMA-β) has been proven as a reliable tool for the assessment of insulin secretion. These indexes are widely used in large population studies [12]. HOMA-IR and HOMA-β are assessed using the following equations: HOMA-IR = (FPI × FPG) / 405, HOMA-β = (360 × FPI) / (FPG − 63). FPI is an aberration of fasting plasma insulin concentration (μIU/mL) and FPG is that of fasting plasma glucose (mg/dL).

Other variables

Daily habits were assessed using self-administered questionnaires. Subjects who had a habit of exercising for more than 30 minutes at least twice a week for 1 year or habitually performed tasks such as carrying baggage, walking, and cleaning for more than 1 hour a day were regarded as subjects with an exercise habit. The frequency of drinking was classified into two groups according to answers to the following questions: “Do you drink more than one glass of sake (22 g ethanol) per day three times a week?” or “Do you drink at least four times a week?”. A drinking habit was confirmed by replying in the affirmative to either of these questions.

Statistical analysis

The Student’s t-test was used to compare the average of continuous variables and the chi-squared test to compare the proportions of categorical variables. All subjects were stratified into two groups: the BP groups (Hypertension group and Normal BP group) and ADRB3 polymorphism groups (Trp64Trp group and Trp64Arg or Arg64Arg group). A two-way analysis of variance (two-way ANOVA) was used to examine differences in HOMA-IR between the BP groups and ADRB3 polymorphism groups. A multiple logistic regression analysis after adjustments for independent factors was performed to assess the relationship between BP and HOMA-IR.

In all analyses, the threshold for significance was P<0.05. All statistical analysis were performed using IBM SPSS Statistics version 24.0 for Mac (SPSS Inc., Armonk, NY, USA).

Results

The demographic characteristics of subjects stratified by the genotype of the ADRB3 polymorphism were shown in Table 1.

Table 1. Subject characteristics in three different allele groups.

Characteristics All subjects Trp64Trp Trp64Arg Arg64Arg
No. of subjects, n (%) 719 (100) 466 (65) 233 (32) 20 (3)
Men, n (%) 327 (45) 203 (44) 115 (49) 9 (45)
Age 61.8 (10.7) 61.5 (10.6) 62.7 (11.0) 58.6 (10.1)
Hypertensive subjects, n (%) 368 (51) 236 (51) 127 (55) 5 (25)
Use of antihypertensive drugs, n (%) 238 (33) 154 (33) 81 (35) 3 (15)
Use of diabetes treatment, n (%) 54 (8) 30 (6) 23 (10) 1 (5)
Smoking status, n (%)
 Non- or ex-smoker 593 (82) 384 (82) 194 (83) 15 (75)
 Current 126 (18) 82 (18) 39 (17) 5 (25)
Exercise habit, n (%)
 yes 425 (59) 277 (59) 135 (58) 13 (65)
 no 294 (41) 189 (41) 98 (42) 7 (35)
Drinking habit, n (%)
 yes 272 (38) 182 (39) 81 (35) 9 (45)
 no 447 (62) 284 (61) 152 (65) 11 (55)
Height (cm) 160 (9.10) 160 (9.06) 160 (9.32) 161 (7.19)
Weight (kg) 60.2 (11.8) 60.1 (11.8) 60.4 (12.1) 60.0 (10.0)
Waist circumference (cm) 84.3 (9.10) 84.3 (9.09) 84.3 (9.16) 83.8 (9.31)
BMI (kg/m2) 23.4 (3.21) 23.5 (3.18) 23.4 (3.33) 22.9 (2.74)
underweight, n (BMI<18.5) (%) 33 (5) 20 (4) 13 (6) 0 (0)
normal weight, n (18.5≦BMI<25) (%) 484 (67) 315 (68) 151 (65) 18 (90)
overweight, n (BMI≦25) (%) 202 (28) 131 (28) 69 (30) 2 (10)
SBP (mmHg) 138 (19.1) 139 (19.7) 138 (18.1) 132 (13.6)
DBP (mmHg) 80.1 (11.4) 80.3 (11.4) 80.0 (11.7) 79.5 (8.51)
FBS (mg/dL) 97.0 (18.1) 96.8 (17.1) 97.4 (19.7) 96.9 (22.2)
HbA1c (NGSP) (%) 5.93 (0.649) 5.92 (0.578) 5.96 (0.749) 5.96 (0.925)
Insulin (μIU/mL) 5.52 (3.64) 5.51 (3.52) 5.53 (3.90) 5.84 (3.54)
HOMA-β (%) 65.4 (43.3) 65.8 (43.3) 64.3 (44.0) 69.9 (37.2)
HOMA-IR 1.36 (1.06) 1.34 (0.959) 1.38 (1.24) 1.43 (0.967)
eGFR (mL/min/1.73m2) 72.2 (15.0) 72.6 (15.1) 71.4 (14.8) 73.6 (15.2)
Total Cholesterol (mg/dL) 216 (36.1) 217 (37.9) 213 (30.3) 236 (48.6)
LDL Cholesterol (Friedewald) (mg/dL) 127 (34.0) 129 (35.2) 123 (29.4) 143 (46.9)
triglyceride (mg/dL) 118 (74.3) 115 (65.9) 124 (88.8) 125 (72.6)

Continuous variables are shown as means (standard deviations). Abbreviations: BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; FBS, fasting blood sugar; HbA1c (NGSP); hemoglobin A1c (National Glycohemoglobin Standardization Program); HOMA-β, homeostatic model assessment beta cell function; HOMA-IR; homeostasis model assessment insulin resistance; eGFR, estimated glomerular filtration rate; LDL, low density lipoprotein.

Genotyping in 719 subjects showed that 466 (65%) were homozygous for the wild-type allele (Trp64Trp), 233 (32%) were heterozygous for the variant allele (Trp64Arg), and 20 (3%) were homozygous for the variant allele (Arg64Arg) (Fig 2).

Fig 2. The genotyping result of rs4994 using the Japonica Array v2. X- and Y-axes indicate logarithmic ratio and logarithmic mean of A and B signals, respectively.

Fig 2

Among all subjects, 327 were men and 392 were women with a mean age of 61.8 years. Mean SBP and DBP in 368 subjects treated with antihypertensive drugs were 138 and 80.1 mmHg, respectively. Fifty-four subjects were being treated for diabetes and mean HbA1c (NGSP) and HOMA-IR were 5.93% and 1.36, respectively.

Table 2 shows the demographic characteristics of the two ADRB3 polymorphism groups (Trp64Trp group and Trp64Arg or Arg64Arg group), which were similar. No significant differences were observed in age, the prevalence of hypertensive subjects, the use of antihypertensive drugs, SBP, or DBP in each stratified group. Characteristics regarding sugar metabolism (FBS, HbA1c, fasting insulin, HOMA-β, and HOMA-IR) did not significantly differ between the two groups.

Table 2. Characteristics of subjects in two different allele groups.

Characteristics Trp64Trp Trp64Arg or Arg64Arg P value
No. of subjects, n (%) 466 (65) 253 (35)
Men, n (%) 203 (44) 124 (49) 0.161
Age 61.5 (10.6) 62.4 (11.0) 0.291
Hypertensive subjects, n (%) 236 (51) 132 (52) 0.695
Use of antihypertensive drugs, n (%) 154 (33) 84 (33) 0.966
Use of diabetes treatment, n (%) 30 (6) 24 (10) 0.139
Smoking status, n (%) 0.945
 Non- or ex-smoker 384 (82) 209 (83)
 Current 82 (18) 44 (17)
Exercise habit, n (%) 0.806
 yes 277 (59) 148 (58)
 no 189 (41) 105 (42)
Drinking habit, n (%) 0.358
 yes 182 (39) 90 (36)
 no 284 (61) 163 (64)
Height (cm) 160 (9.06) 160 (9.16) 0.423
Weight (kg) 60.1 (11.8) 60.4 (12.0) 0.747
Waist circumference (cm) 84.3 (9.09) 84.3 (9.15) 0.984
BMI (kg/m2) 23.5 (3.18) 23.4 (3.29) 0.826
SBP (mmHg) 139 (19.7) 137 (17.9) 0.338
DBP (mmHg) 80.3 (11.4) 79.7 (11.4) 0.496
FBS (mg/dL) 96.8 (17.1) 97.4 (19.9) 0.660
HbA1c (NGSP) (%) 5.92 (0.578) 5.96 (0.763) 0.478
Insulin (μIU/mL) 5.51 (3.52) 5.55 (3.86) 0.896
HOMA-β (%) 65.8 (43.3) 64.7 (43.5) 0.754
HOMA-IR 1.34 (0.959) 1.38 (1.22) 0.610
eGFR (mL/min/1.73m2) 72.6 (15.1) 71.5 (14.8) 0.371
Total Cholesterol (mg/dL) 217 (37.9) 214 (32.6) 0.401
LDL Cholesterol (Friedewald) (mg/dL) 129 (35.2) 125 (31.5) 0.115
triglyceride (mg/dL) 115 (65.9) 124 (87.5) 0.117

Continuous variables are shown as means (standard deviations). p values were from the Student’s t-test for continuous variables and the chi-squared test for categorical variables. Abbreviations: BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; FBS, fasting blood sugar; HbA1c (NGSP); hemoglobin A1c (National Glycohemoglobin Standardization Program); HOMA-β, homeostatic model assessment beta cell function; HOMA-IR; homeostasis model assessment insulin resistance; eGFR, estimated glomerular filtration rate; LDL, low density lipoprotein.

When subjects were classified into two groups according to the definition of hypertension, the Hypertension group was significantly older (P < 0.001) and had a higher BMI (P < 0.001) and lower eGFR (P = 0.011) than the Normal BP group (Table 3). The Hypertension group also showed significantly higher FBS (P < 0.001), HbA1c (P = 0.008), fasting insulin (P < 0.001), and HOMA-IR (P < 0.001) than the Normal BP group.

Table 3. Characteristics of subjects in different BP groups.

Characteristics Hypertension Normal BP P value
No. of subjects, n (%) 368 (51) 351 (49)
Men, n (%) 181 (49) 146 (42) 0.041
Age 64.5 (10.0) 59.0 (10.7) <0.001
ADRB3 (rs4994) 0.695
 Trp64Trp 236 (64) 230 (66)
 Trp64Arg or Arg64Arg 132 (36) 121 (34)
Use of antihypertensive drugs, n (%) 238 (65) 0 (0) <0.001
Use of diabetes treatment, n (%) 33 (9) 21 (6) 0.129
Smoking status, n (%) 0.923
 Non- or ex-smoker 304 (83) 289 (82)
 Current 64 (17) 62 (18)
Exercise habit, n (%) 0.497
 yes 222 (60) 203 (58)
 no 146 (40) 148 (42)
Drinking habit, n (%) 0.006
 yes 157 (43) 115 (33)
 no 211 (57) 236 (67)
Height (cm) 159 (9.29) 160 (8.89) 0.302
Weight (kg) 62.0 (12.2) 58.3 (11.2) <0.001
Waist circumference (cm) 86.3 (9.13) 82.1 (8.57) <0.001
BMI (kg/m2) 24.3 (3.31) 22.6 (2.89) <0.001
SBP (mmHg) 149 (17.3) 127 (13.8) <0.001
DBP (mmHg) 84.7 (12.2) 75.3 (8.23) <0.001
FBS (mg/dL) 100 (17.6) 94.3 (18.3) <0.001
HbA1c (NGSP) (%) 6.00 (0.626) 5.87 (0.667) 0.008
Insulin (μIU/mL) 6.18 (4.11) 4.84 (2.93) <0.001
HOMA-β (%) 67.9 (47.7) 62.8 (38.1) 0.113
HOMA-IR 1.60 (1.22) 1.15 (0.804) <0.001
eGFR (mL/min/1.73m2) 73.7 (15.7) 73.7 (14.1) 0.011
Total Cholesterol (mg/dL) 215 (36.3) 217 (36.0) 0.359
LDL Cholesterol (Friedewald) (mg/dL) 126 (35.0) 129 (33.0) 0.280
Triglyceride (mg/dL) 125 (80.3) 112 (66.9) 0.021

Continuous variables are shown as means (standard deviations). p values were from the Student’s t-test for continuous variables and the chi-squared test for categorical variables. Hypertension was defined as the use of antihypertensive medication or a blood pressure of 140/90 mmHg or higher. Abbreviations: BP, blood pressure; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; FBS, fasting blood sugar; HbA1c (NGSP); hemoglobin A1c (National Glycohemoglobin Standardization Program); HOMA-β, homeostatic model assessment beta cell function; HOMA-IR; homeostasis model assessment insulin resistance; eGFR, estimated glomerular filtration rate; LDL, low density lipoprotein.

We also assessed differences in variables related to diabetes between the BP groups and ADRB3 polymorphism groups using a two-way ANOVA (Table 4). The results obtained revealed a significant interaction between BP groups and ADRB3 polymorphism groups for HOMA-IR (P = 0.046).

Table 4. Interaction between BP groups and the ADRB3 polymorphism at rs4994.

Hypertension Normal BP
Variable ADRB3 polymorphism at rs4994 Average (SD) Average (SD) P for interaction
HOMA-IR Trp64Trp 1.49 (1.08) 1.19 (0.797) 0.046
Trp64Arg or Arg64Arg 1.68 (1.44) 1.06 (0.813)
HOMA-β (%) Trp64Trp 67.5 (47.7) 64.0 (38.2) 0.479
Trp64Arg or Arg64Arg 68.7 (47.9) 60.4 (37.8)
FBS (mg/dL) Trp64Trp 98.7 (17.2) 94.8 (16.8) 0.192
Trp64Arg or Arg64Arg 101 (18.3) 93.4 (20.8)
HbA1c (NGSP) (%) Trp64Trp 5.96 (0.526) 5.88 (0.797) 0.136
Trp64Arg or Arg64Arg 6.07 (0.771) 5.84 (0.739)
Insulin (μIU/mL) Trp64Trp 5.99 (3.91) 5.02 (2.99) 0.069
Trp64Arg or Arg64Arg 6.50 (4.44) 4.51 (2.79)

p values for the interaction from a two-way analysis of variance. Hypertension was defined as the use of antihypertensive medication or a blood pressure of 140/90 mmHg or higher. Abbreviations: BP, blood pressure; FBS, fasting blood sugar; HOMA-IR; homeostasis model assessment insulin resistance; HOMA-β, homeostatic model assessment beta cell function; HbA1c (NGSP); hemoglobin A1c (National Glycohemoglobin Standardization Program).

To adjust for the effects of confounding factors, a multiple logistic regression analysis was used to evaluate the relationship between HOMA-IR and hypertension. Based on the significant interaction between the BP groups and ADRB3 polymorphism groups for HOMA-IR (Table 4), we performed separate multiple logistic regression analyses according to the presence or absence of the ADRB3 polymorphism (Table 5). In subjects with the ARDB3 polymorphism (Trp64Arg or Arg64Arg), HOMA-IR was inversely associated with hypertension after adjustments for the following confounding factors: sex, age, BMI (Model 1), eGFR, exercise habit, smoking status, drinking habit, treatment of diabetes (Model 2), and HOMA-β (Model 3). On the other hand, no correlation was observed between HOMA-IR and hypertension in those homozygous for the wild-type allele (Trp64Trp) group. These relationships were the same in other multiple regression analysis models.

Table 5. Relationship between HOMA-IR and blood pressure according to the ADRB3 polymorphism at rs4994.

Model 1 Model 2 Model 3
odds ratio (95% confidence interval, P value) odds ratio (95% confidence interval, P value) odds ratio (95% confidence interval, P value)
All subjects 1.271 (1.038–1.555, 0.020) 1.305 (1.061–1.606, 0.012) 1.364 (1.056–1.761, 0.017)
Trp64Trp 1.147 (0.891–1.476, 0.228) 1.189 (0.918–1.540, 0.191) 1.215 (0.887–1.664, 0.226)
Trp64Arg or Arg64Arg 1.570 (1.085–2.272, 0.017) 1.690 (1.133–2.522, 0.010) 2.054 (1.191–3.541, 0.010)

The odds ratio (95% confidence interval, P value) was from a multiple logistic regression analysis. Model 1: adjusted for sex, age, and BMI. Model 2: adjusted for sex, age, eGFR, exercise habit, smoking status, drinking habit, and treatment of diabetes. Model 3: adjusted for sex, age, eGFR, exercise habit, smoking status, drinking habit, treatment of diabetes, and HOMA-β. Abbreviations: HOMA-IR; homeostasis model assessment insulin resistance; BMI, body mass index; eGFR, estimated glomerular filtration rate; HOMA-β, homeostatic model assessment beta cell function.

Discussion

The present study was conducted in an attempt to examine the relationships among hypertension, insulin resistance, and the Trp64Arg polymorphism. The results obtained suggested that the Trp64Arg polymorphism of ADRB3 was associated with hypertension and insulin resistance.

In the present study, insulin resistance assessed by HOMA-IR was associated with an increased risk of hypertension in a Japanese population. This result is consistent with previous findings showing the important role of insulin resistance in predicting the future incidence of hypertension in middle-aged Japanese men [13]. In this 7-year follow-up study, subjects with the highest baseline insulin resistance values were more likely to become hypertensive after 7 years. This study adds further evidence to the finding that insulin resistance is a risk of hypertension in Japanese.

The present results also revealed that this relationship was dependent on the presence or absence of the Trp64Arg polymorphism. The relationship between high HOMA-IR and a low risk of hypertension appeared to be stronger in subjects who were heterozygous for the variant allele (Trp64Arg) or homozygous for the variant allele (Arg64Arg) than in those who were homozygous for the wild-type allele (Trp64Trp). This correlation was still observed after adjustments for confounding factors.

Previous studies examined the relationships among the ADRB3 polymorphism, obesity [68], insulin resistance [6, 7], and hypertension [7]. Walston et al. reported that Pima subjects homozygous for the ADRB3 polymorphism showed the earlier onset of non-insulin dependent diabetes mellitus and had a slightly lower resting metabolic rate [6]. Widén et al. suggested that the ADRB3 polymorphism was associated with insulin resistance syndrome, which includes obesity and hypertension, in Finns [7]. Clément et al. showed that individuals with the ADRB3 polymorphism may have an increased capacity to gain weight in France [8]. In contrast to these findings, no significant relationship was observed between the ADRB3 polymorphism and these phenotypes in the present study (Table 2).

The reason for this difference currently remains unclear; however, two possibilities need to be considered. Due to the relatively weak contribution of the ADRB3 polymorphism to insulin resistance and hypertension, the sample sizes of previous studies may have been insufficient. Furthermore, differences in the genetic background may have led to insulin resistance and hypertension. Another candidate gene to these pathologies may have affected the findings obtained in these studies.

In addition to the ADRB3 gene, genes related to insulin resistance and obesity have been reported in Caucasians. Among all, polymorphisms in the adiponectin gene have been reported to reduce adiponectin levels in overweight and obese children in Italy and increase insulin resistance [14]. Moreover, two Japanese studies reported that polymorphism in the adiponectin gene are associated with insulin resistance [15, 16]. Although we could not obtain information on the polymorphisms of the adiponectin gene in this study, it is worth investigating in future studies.

The present study had some limitations. Causality was not examined because the study design was cross-sectional. Therefore, further studies are needed to confirm the present results. Furthermore, a selection bias needs to be considered; subjects were voluntary collaborators for the comprehensive health examination, the sample size of which was too small to clarify the effects of the ADRB3 polymorphism. In addition, we did not obtain information on other variables, such as other candidate genes related to insulin resistance and hypertension.

In conclusion, the Trp64Arg polymorphism of ADRB3 was associated with hypertension and insulin resistance in a Japanese population. This relationship, which was dependent on the polymorphism, may predict the development of hypertension and diabetes. The present results need to be interpreted with caution due to the limitations described above.

Data Availability

All relevant data are within the manuscript.

Funding Statement

The authors received no specific funding for this work.

References

  • 1.Lim S. S. et al., “A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010,” Lancet, vol. 380, pp. 2224–2260, 2012. doi: 10.1016/S0140-6736(12)61766-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Sarwar N. et al., “Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: A collaborative meta-analysis of 102 prospective studies,” Lancet, vol. 375, pp. 2215–2222, 2010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Sowers J. R., “Insulin resistance and hypertension,” Am. J. Physiol. Circ. Physiol., vol. 286, pp. 1597–1602, 2004. doi: 10.1152/ajpheart.00026.2004 [DOI] [PubMed] [Google Scholar]
  • 4.Kohara K. et al., “Identification of hypertension-susceptibility genes and pathways by a systemic multiple candidate gene approach: The millennium genome project for hypertension,” Hypertens. Res., vol. 31, pp. 203–212, 2008. doi: 10.1291/hypres.31.203 [DOI] [PubMed] [Google Scholar]
  • 5.Marteau J. B., Zaiou M., Siest G., and Visvikis-Siest S., “Genetic determinants of blood pressure regulation,” J. Hypertens., vol. 23, pp. 2127–2143, 2005. doi: 10.1097/01.hjh.0000186024.12364.2e [DOI] [PubMed] [Google Scholar]
  • 6.Walston J. et al., “Time of Onset of Non-Insulin-Dependent Diabetes Mellitus and Genetic Variation in the Beta 3-adrenergic-receptor Gene,” N. Engl. J. Med., vol. 333, pp. 343–347, 1995. doi: 10.1056/NEJM199508103330603 [DOI] [PubMed] [Google Scholar]
  • 7.Widén E. et al., “Association of a Polymorphism in the β3-Adrenergic–Receptor Gene with Features of the Insulin Resistance Syndrome in Finns,” N. Engl. J. Med., vol. 333, pp. 348–352, 1995. [DOI] [PubMed] [Google Scholar]
  • 8.Clément K. et al., “Genetic Variation in the β3-Adrenergic Receptor and an Increased Capacity to Gain Weight in Patients with Morbid Obesity,” N. Engl. J. Med., vol. 333, pp. 352–354, 1995. [DOI] [PubMed] [Google Scholar]
  • 9.Fujisawa T. et al., “Trp64Arg Mutation of b3-Adrenergic Receptor in Essential Hypertension-Insulin Resistance and the Adrenergic System,” Am. J. Hypertens., vol. 10, pp. 101–105, 1997. [DOI] [PubMed] [Google Scholar]
  • 10.Nakamura H. et al., “Relationship between dietary n-6 fatty acid intake and hypertension: Effect of glycated hemoglobin levels,” Nutrients, vol. 10, no. 12, pp. 12–16, 2018. doi: 10.3390/nu10121825 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Kawai Y. et al., “Japonica array: Improved genotype imputation by designing a population-specific SNP array with 1070 Japanese individuals,” J. Hum. Genet., vol. 60, pp. 581–587, 2015. doi: 10.1038/jhg.2015.68 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Antuna-Puente B., Disse E., Rabasa-Lhoret R., Laville M., Capeau J., and Bastard J. P., “How can we measure insulin sensitivity/resistance?,” Diabetes and Metabolism, vol. 37. pp. 179–188, 2011. doi: 10.1016/j.diabet.2011.01.002 [DOI] [PubMed] [Google Scholar]
  • 13.Hirose H., Saito I., Kawabe H., and Saruta T., “Insulin resistance and hypertension: Seven-year follow-up study in middle-aged Japanese men (the KEIO study),” Hypertens. Res., vol. 26, pp. 795–800, 2003. [DOI] [PubMed] [Google Scholar]
  • 14.Petrone A. et al., “The promoter region of the adiponectin gene is a determinant in modulating insulin sensitivity in childhood obesity,” Obesity, vol. 14, no. 9, pp. 1498–1504, 2006, doi: 10.1038/oby.2006.172 [DOI] [PubMed] [Google Scholar]
  • 15.Kara K. et al., “Genetic variation in the gene encoding adiponectin is associated with an increased risk of type 2 diabetes in the Japanese population,” Diabetes, vol. 51, no. 2, pp. 536–540, 2002, doi: 10.2337/diabetes.51.2.536 [DOI] [PubMed] [Google Scholar]
  • 16.Populaire C. et al., “Does the -11377 promoter variant of APM1 gene contribute to the genetic risk for Type 2 diabetes mellitus in Japanese families?,” Diabetologia, vol. 46, no. 3, pp. 443–445, 2003, doi: 10.1007/s00125-003-1050-7 [DOI] [PubMed] [Google Scholar]

Decision Letter 0

Raffaella Buzzetti

27 May 2021

PONE-D-20-33381

Relationships among the β3-adrenargic receptor gene Trp64Arg polymorphism, hypertension, and insulin resistance in a Japanese population

PLOS ONE

Dear Dr. Yamada,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Your manuscript has been evaluated by one external reviewer and myself (reviewer #2), and the comments are available below.

Please submit your revised manuscript by Jun 28 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Raffaella Buzzetti, M.D.

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

*Please note that Reviewer #2 is Raffaella Buzzetti, Academic Editor

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2 : Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Major points

1. Could the Authors specify if they used some exclusion criteria to enrol the subjects?

2. It would be interesting if the Authors provide the images of genotyping results.

3. Did The Authors evaluate the sample size and the could they report the power of the study ?

4. All the data were normally distributed? Which kind of test they used to verify data normality?

5. The discussion section is limited, the Authors should add some sentence in which they explain the possible implication of their findings in the clinical practice.

6. The Authors should specific in material and method the range age of subjects enrolled in the study.

7. It would be interesting subdivide the subjects in two groups according gender, to evaluate possible differences with the polymorphisms.

8. In the study there are no information regarding the lipid profile of the subjects. Dyslipidaemia, comprising altered ratio of high TC level and isolated evaluation of the LDL or TG, is usually associated with increased blood pressure (BP) levels. These considerations should be take into account in the discussion section.

Reviewer #2: In this cross-sectional study the Authors evaluated the relationships between Trp64Arg polymorphism of the ADRB3 gene and hypertension and insulin resistance values (HOMA-R) in 719 Japanese subjects. The genotype frequencies of Trp64Trp (homozygous, wild), Trp64Arg (heterozygous, variant), and Arg64Arg (homozygous, variant) were 466 (65%), 233 (32%), and 20 (3%), respectively. Insulin resistance was associated with an increased risk of hypertension in a Japanese population. This relationship was dependent on the presence or absence of the Trp64Arg polymorphism Therefore, the Trp64Arg 47 polymorphism of ADRB3 was associated with hypertension and insulin resistance in this Japanese population.

This is an interesting study, however some major points have to be adressed

1. Have Authors perfomed a power calcualtion before starting the study? Could they report such a calculation?

2. The sentence “In the present study, the ADRB3 polymorphism did not correlate with

phenotypes (obesity, hypertension, and insulin resistance” should be removed from the abstract as it does not add anithing fundamental but,even complicates the comprehension of the text.

3. Please change HOMA-R in HOMA-IR as it is generally reported in the international abbreviation

4. Please report the cut-off for defining Japanese population concerning the BMI ( normal, overweight, obese)

5. Other susceptible genes have been demostrated to be linked to obesity, insulin resistance and hypertension in caucasian population. Among all, adiponectin stands out (PMID: 17030959); please refer to that article and comment on the most important genes already demonstrated to be associated with insulin resistance obesity and hypertension in Japanese population. Surely, it would be very useful for readers

6. Have Authors any informaton about the diabetes type which affected more less 10 percent of the investigated subjects?

7. Exercise and drinking habits should be better quantified. Please comment on that.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2021 Aug 4;16(8):e0255444. doi: 10.1371/journal.pone.0255444.r002

Author response to Decision Letter 0


30 Jun 2021

Dear Dr. Raffaella Buzzetti,

Thank you for the thoughtful and constructive feedback you provided regarding our manuscript, ‘Relationships among the β3-adrenargic receptor gene Trp64Arg polymorphism, hypertension, and insulin resistance in a Japanese population’. We have carefully reviewed the comments and revised the manuscript on the basis of the reviewers’ comments. Our point-by-point responses to the reviewers’ comments are listed below this letter. Changes to the manuscript are shown in red font in a separate file labeled 'Revised Manuscript with Track Changes'.

We hope that you find the current version of the manuscript suitable for publication. Thank you for your consideration. We look forward to the publication of our manuscript in the PLOS ONE.

Sincerely,

Youhei Yamada

Reviewer #1

1. Could the Authors specify if they used some exclusion criteria to enrol the subjects?

Response: The participants recruitment chart is shown in the newly created Figure 1.

2. It would be interesting if the Authors provide the images of genotyping results.

Response: We provide the images of genotyping results in the newly created Figure 2.

3. Did The Authors evaluate the sample size and the could they report the power of the study ?

Response: We didn't performed a power calculation before starting the study. After the fact, we confirmed the detection power to see if the sample size was appropriate, but sufficient detection power was confirmed.

4. All the data were normally distributed? Which kind of test they used to verify data normality?

Response: Not all the data were normally distributed. We used Shapiro-Wilk test to verify data normality. In this study, we addressed the problem of normality by using a highly robust analytical method.

5. The discussion section is limited, the Authors should add some sentence in which they explain the possible implication of their findings in the clinical practice.

Response: We increased the text of the discussion section and emphasized the significance of our research results.

6. The Authors should specific in material and method the range age of subjects enrolled in the study.

Response: In the present study, data on 1191 voluntary participants from 40 years of age who underwent the comprehensive health examination between March 2014 and January 2017 were available.

7. It would be interesting subdivide the subjects in two groups according gender, to evaluate possible differences with the polymorphisms.

Response: In response to the proposal, we newly analyzed by gender. The results of this study were found to be prominent in women.

8. In the study there are no information regarding the lipid profile of the subjects. Dyslipidaemia, comprising altered ratio of high TC level and isolated evaluation of the LDL or TG, is usually associated with increased blood pressure (BP) levels. These considerations should be take into account in the discussion section.

Response: We have shown the lipid profile in Tables 1, 2 and 3. Taking into account the lipid profile did not change the trends in our findings.

Reviewer #2

1. Have Authors perfomed a power calcualtion before starting the study? Could they report such a calculation?

Response: We didn't performed a power calculation before starting the study. After the fact, we confirmed the detection power to see if the sample size was appropriate, but sufficient detection power was confirmed.

2. The sentence “In the present study, the ADRB3 polymorphism did not correlate with

phenotypes (obesity, hypertension, and insulin resistance” should be removed from the abstract as it does not add anithing fundamental but,even complicates the comprehension of the text.

Response: I deleted the sentence you pointed out.

3. Please change HOMA-R in HOMA-IR as it is generally reported in the international abbreviation

Response: I changed the word you pointed out.

4. Please report the cut-off for defining Japanese population concerning the BMI ( normal, overweight, obese)

Response: We have shown in Table 1 the cutoff for Japanese BMI.

5. Other susceptible genes have been demostrated to be linked to obesity, insulin resistance and hypertension in caucasian population. Among all, adiponectin stands out (PMID: 17030959); please refer to that article and comment on the most important genes already demonstrated to be associated with insulin resistance obesity and hypertension in Japanese population. Surely, it would be very useful for readers

Response: We mentioned adiponectin in the discussion section with reference to the literature you provided.

6. Have Authors any informaton about the diabetes type which affected more less 10 percent of the investigated subjects?

Response: In our study, type 1 diabetes was excluded from the analysis using HOMAβ.

7. Exercise and drinking habits should be better quantified. Please comment on that.

Response: The lifestyle survey was evaluated qualitatively according to the questionnaire. We are very sorry, but we cannot use quantitative information about exercise and drinking for analysis.

Attachment

Submitted filename: Response to Reviewers.docx

Decision Letter 1

Raffaella Buzzetti

19 Jul 2021

Relationships among the β3-adrenargic receptor gene Trp64Arg polymorphism, hypertension, and insulin resistance in a Japanese population

PONE-D-20-33381R1

Dear Dr. Yamada,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Raffaella Buzzetti, M.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Raffaella Buzzetti

27 Jul 2021

PONE-D-20-33381R1

Relationships among the β3-adrenargic receptor gene Trp64Arg polymorphism, hypertension, and insulin resistance in a Japanese population

Dear Dr. Yamada:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Raffaella Buzzetti

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    Attachment

    Submitted filename: Response to Reviewers.docx

    Data Availability Statement

    All relevant data are within the manuscript.


    Articles from PLoS ONE are provided here courtesy of PLOS

    RESOURCES