Introduction

Accumulating evidence shows that angiotensin II (AII), a major effector peptide of the renin–angiotensin system (RAS), contributes to the pathogenesis of the metabolic syndrome and atherosclerosis.1, 2, 3 It is noted that human adipose tissue possesses all of the components necessary for production of AII and AII type 1 receptor (AT1R). The adipose tissue RAS has a role in the process of adipogenic differentiation and in the regulation of body weight.3 Most physiological responses triggered by AII occur through activation of the G-protein-coupled AT1R. A common polymorphism in the AT1R (A1166C) has been linked to enhanced physiological responses to AII.4 In addition, this polymorphism in the human AT1R has been associated with phenotypic effects including insulin sensitivity and metabolic syndrome traits as well as high blood pressure.5, 6 Although this polymorphism is located in the 3′-untranslated region of the human AT1R, recent evidence shows that the polymorphism can lead to increased AT1R densities through inhibition of the ability of miR-155 to attenuate translation of AT1R mRNA.7

Adipose tissue is a highly active metabolic and endocrine organ that secretes many biologically active substances, collectively known as adipocytokines.8 Adiponectin is an anti-atherogenic and insulin-sensitizing adipocytokine that is stably present in the plasma at very high concentrations. Human studies showed that adiponectin is downregulated in patients with obesity-related diseases, including type 2 diabetes, metabolic syndrome and hypertension.9 Importantly, AII infusion decreases plasma adiponectin levels,10 and RAS blockade decreases adipocyte size with improvement in insulin sensitivity in rats.11 In addition, blockade of the RAS increases plasma adiponectin concentrations in patients with essential hypertension.12 However, it remains to be determined whether AT1R A1166C affects plasma adiponectin concentrations in humans. Furthermore, plasma adiponectin concentrations were lower in mice fed a high-fat diet compared with control mice.13 Another study reported that a high-fat meal did not elicit changes in serum adiponectin compared with fasting baseline levels in healthy male subjects.14 Thus, the effects of dietary fat intake on plasma adiponectin concentrations are unclear at present.

It is well established that atherosclerosis is a progressive multifactorial process that begins in early life.15, 16, 17 However, few studies have examined the risk factors of atherosclerosis development in young women. In particular, the interaction between genes and environmental factors in the development of early atherosclerosis in young female populations is not clear. Thus, this study was designed to investigate the association between AT1R A1166C and plasma adiponectin concentrations in young female subjects. We also investigated the influence of AT1R A1166C on the correlation between dietary fat intake and plasma adiponectin concentrations in these subjects.

Methods

Participants

Between July 2004 and December 2007, 416 students from 18 to 23 years of age were recruited from Mukogawa Women's University. We received approval from the Institutional Review Board and written informed consent was obtained from all participants in this study.

Body composition and biochemical measurements

Blood samples were taken from each of the participants in the morning following overnight fasting. We measured the fasting plasma glucose, insulin, hemoglobin A1c (HbA1c), lipoprotein lipase (LPL), high-sensitivity C-reactive protein (hs-CRP), free fatty acid (FFA) and serum lipid concentrations including triglycerides (TG), high-density lipoprotein (HDL) cholesterol and low-density lipoprotein (LDL) cholesterol by standard laboratory techniques. Plasma levels of adiponectin and plasminogen-activator inhibitor 1 (PAI-1) were measured with commercial kits. Body composition was determined by dual-energy X-ray absorptiometry. Blood pressure was measured between 0900 and 1200 h (noon), with participants resting in the sitting position. Intima-media thickness (IMT) in the carotid artery was measured with the participants in a supine position after a few minutes of rest. Indices of obesity and insulin resistance were derived from body mass index (BMI) and a homeostasis model assessment of insulin resistance (HOMA-IR), respectively.

Estimation of habitual food intake

Percentages of protein, fat and carbohydrate in the diet were estimated by using the responses to a self-administered diet history questionnaire, developed for use in the evaluation of nutrient intake levels and health education among both healthy individuals and high-risk populations. The diet history questionnaire was designed to obtain information about dietary habits for the previous month with regard to total energy and 17 nutrients.18

Determination of AT1R A1166C polymorphism genotypes

Genomic DNA was extracted from 200 μl of whole blood, following the blood spin protocol recommended by the manufacturer for use of the QIAamp DNA Blood Kit (Qiagen Inc., Valencia, CA, USA). AT1R A1166C polymorphism genotypes were determined by the TaqMan polymerase chain reaction method. The primers and probes for genotype determinations were as follows: forward primer 5′-CATTCCTCTGCAGCACTTCACT-3′, reverse primer 5′-CGGTTCAGTCCACATAATGCAT-3′, probe for A (1166) 5′-FAM-CAAATGAGCATTAGCTACMGB-3′, probe for C (1166) 5′-VIC-CAAATGAGCCTTAGCTACT-MGB-3′. Each reaction included 1 μl of the DNA sample including 30 ng of genetic DNA, 0.3 μl of each primer, 0.1 μl of each probe, 5 μl of the TaqMan Universal Master Mix (Applied Biosystems, Foster City, CA, USA) and 3.2 μl of sterile distilled water. Polymerase chain reaction cycling conditions were 1 cycle at 95 °C for 10 min, 45 cycles at 92 °C for 15 s and 60 °C for 1 min. Polymerase chain reaction and allelic detection were carried out using an ABI Sequence Detection System 7500 and allelic discrimination software, both from Applied Biosystems.

Ultrasound studies

IMT was measured by ultrasonic diagnosis equipment (Shimazu SDU-2200, Shimazu, Tokyo, Japan) that was programmed with IMT software (Intimascope, Media Cross Co. Ltd., Tokyo, Japan) as described.19 This software makes it possible to automatically recognize the edges of the internal and the external membranes of the blood vessels and to automatically measure the distance at a sub-pixel level (estimated to be 0.01 mm), using a three-dimensional polynomial measurement formula.

Carotid artery ultrasonography was performed using a 10-MHz scanning frequency in B mode. One skilled observer, blinded to the subjective data, scanned the vessel in transverse planes. Subjects were examined in a supine position. Images were obtained in the 20 mm proximal to the origin of the bulb at the far wall of the right common carotid artery. In all subjects examined in this study, no plaque was observed in this segment. Average IMT was the average value of 250 computer-based points in the region.

Statistical analysis

Agreement with the Hardy–Weinberg equilibrium was tested by comparing the observed and expected genotype frequencies of the participants using the χ2-test for good fit with Fisher's exact tests. On account of the very low frequency of the 1166C allele, participants who were homozygous for CC were combined in the analysis with those who were heterozygous AC to increase the statistical power. Normality of variable distribution was tested by the Kolmogorov–Smirnov test.

Quantitative data with a normal distribution were presented as the mean±s.d., and data with a skewed distribution were presented as the median (interquartile range). Comparisons between carriers of the C allele and non-carriers were made using unpaired t-tests for continuous variables with normal distribution and with the nonparametric Mann–Whitney U-test for continuous variables with a skewed distribution. Pearson's and Spearman's coefficients of correlation were used as appropriate. A univariate generalized linear model was used to test for the heterogeneity of regression. To examine the independent contribution of the AT1R A1166C polymorphism to plasma adiponectin levels when adjusting for the effects of other clinical characteristics, logistic regression analysis with forward stepwise selection was used. For this analysis, participants were divided into two groups at the median of plasma adiponectin concentrations. We adjusted for confounders with the use of analysis of covariance (ANCOVA). To normalize variables with skewed distributions, logarithm, square root and inverse were used for data transformations as appropriate. Data were analyzed with SPSS (release 16.0J; SPSS Japan, Tokyo, Japan) and differences were considered significant with a P-value of ⩽0.05.

Results

Genotype and participant characteristics

We examined the influence of AT1R A1166C on anthropometric features. The distributions of AT1R A1166C genotypes were as follows: AT1R A1166C AA, 83.2% (n=346); AC, 15.9% (n=66); and CC, 0.9% (n=4). The observed genotype frequencies in this study were in the Hardy–Weinberg equilibrium (χ2=0.185, P=0.912) and were similar to results from previous studies of Japanese populations.20 There were no significant differences between carriers of the C allele and non-carriers in terms of age, height, weight, BMI, SBP, DBP, pulse rate, trunk fat mass, plasma concentrations of lipoproteins, plasma fasting glucose levels, HOMA-IR, HbA1c or IMT (Table 1). However, plasma adiponectin concentrations were significantly lower in carriers of the C allele compared with non-carriers. For comparison of plasma adiponectin concentrations between genotype groups, we used ANCOVA with BMI, HDL-Ch and HOMA-IR as covariates. The results of the evaluation of the assumptions of normality for sampling distributions and the homogeneity of variance were satisfactory. After adjustment by covariates, plasma adiponectin levels were significantly lower in carriers of the C allele compared with non-carriers (P=0.043) (Table 2). As shown in Table 3, multiple logistic regression analysis with forward stepwise selection, after controlling for age, BMI, HDL-Ch, triglycerides and HOMA-IR, showed that the genotype with the C allele of the AT1R A1166C polymorphism was the strongest and the most independent determinant of lower plasma adiponectin concentrations (odds ratio: 2.055, 95% CI: 1.184–3.565, P=0.010), followed by BMI (odds ratio: 1.110, 95% CI: 1.015–1.213, P=0.022) and HDL-Ch (odds ratio: 0.965, 95% CI: 0.950–0.980, P<0.001). There were no significant differences, however, in plasma PAI-1 concentrations between these two groups.

Table 1 Characteristics and plasma adipocytokine concentrations of carriers and non-carriers of the C allele of the AT1R A1166C polymorphism
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Table 2 Analysis of covariance of genotype groups of AT1R A1166C toward plasma adiponectin concentration, with BMI, HDL-Ch and HOMA-IR as the covariates
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Table 3 Stepwise logistic regression analysis with above and below the median of plasma adiponectin concentrations as the dependent variable and selected variables as the independent variable
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Next, we examined whether clinical parameters differed between the participants in the lowest quartile of plasma adiponectin concentrations and those in the highest quartile. The participants in the lowest quartile of plasma adiponectin concentration showed significantly lower HDL-Ch and LPL levels and higher BMI and trunk fat mass when compared with participants in the highest quartile. Importantly, carotid IMT levels were significantly higher in the lowest quartile of plasma adiponectin concentrations than those in the highest quartile. No significant differences in low-density lipoprotein cholesterol, triglycerides, HOMA-IR and blood pressure, however, were observed between these groups (Table 4).

Table 4 Characteristics of the participants in the lowest or highest quartiles of plasma adiponectin concentrations
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Correlations between percentage of fat in the diet and plasma adiponectin concentrations in the genotype groups

Next, we examined the effects of dietary fat intake on plasma adiponectin concentrations in both genotypes. There were no significant differences in the mean or median intake of protein, fat and carbohydrate in the diet between carriers of the C allele and non-carriers (Table 5). Unexpectedly, a weak but significant positive correlation was found between the estimated percentages of fat in the diet and plasma adiponectin concentrations in non-carriers of the C allele (r=0.161, P=0.004) but not in carriers (r=0.148, P=0.263). There was no significant difference between the slopes of regression for carriers and non-carriers of the C allele (P=0.731) (Figure 1).

Table 5 Estimated habitual food intakes in carriers and non-carriers of the C allele of the AT1R A1166C polymorphism
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Figure 1
figure 1

Correlations between dietary fat intake (percentage of energy) and plasma concentrations of adiponectin.

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Discussion

In this study, we found that plasma adiponectin concentrations were significantly lower in carriers of the C allele of the AT1R A1166C gene polymorphism compared with non-carriers among a population of young Japanese women. To our knowledge, this report is the first to show that the AT1R A1166C polymorphism may influence changes in plasma adiponectin concentrations in humans. Adiponectin is a unique and essential adipocytokine that is produced very abundantly from adipocytes and is stably present in the plasma at very high concentrations. Recent studies emphasize the part played by adiponectin in the homeostasis of adipose tissue and in the pathogenesis of the metabolic syndrome and atherosclerosis.21 Adiponectin levels are positively correlated with HDL-cholesterol but inversely with insulin; the levels are reduced in obesity and type II diabetes9 and lower in hypertensive patients compared with normotensive patients.22 Plasma concentrations of adiponectin are, however, stable throughout the menstrual cycle23 and also not affected by menopause in healthy women.24

Interestingly, participants in the lowest quartile of plasma adiponectin concentration had lower HDL-Ch and LPL levels and higher trunk fat mass compared with those in the highest quartile. In addition, the participants in the lowest quartile had thicker carotid IMT levels compared with those in the highest quartile. These results suggest that carriers of the C allele with lower adiponectin concentrations may be more susceptible to the development of atherosclerosis.

Although the mechanism underlying lower adiponectin concentrations in carriers of the C allele of the AT1R A1166C gene polymorphism is not clear at present, a silent polymorphism, A1166C, occurs in the 3′-untranslated region of the human AT1R gene that can lead to increased AT1R densities.7 This suggests that the effect of AII may be enhanced in carriers of the C allele of the AT1R A1166C polymorphism.4, 25, 26, 27 It is noted that AII infusion decreases plasma adiponectin levels through its type 1 receptor in rats,10 and treatment with an AII type 1 receptor antagonist increases plasma adiponectin levels in hypertensive patients.12 These results suggest that a difference in activation of the local RAS may be directly involved in the variation between genotypes with regard to plasma adiponectin concentrations. However, further investigation is required to confirm this hypothesis.

In this study, we also found a genotype-dependent correlation between the percentage of fat in the diet and plasma adiponectin concentrations. Unexpectedly, there was a weak but significant positive correlation between plasma adiponectin concentrations and percentage of fat in the diet in non-carriers of the C allele, but not in carriers. Although the mechanism of this result is not clear, it was reported earlier that no correlation was found between dietary fat intake and plasma adiponectin concentration in humans,14 suggesting that this relation may be specific for this genotype. Follow-up studies are necessary to clarify these points.

In conclusion, we showed that plasma adiponectin concentrations were associated with the C allele of the AT1R gene in young healthy women and that the AT1R genotype might affect plasma levels of adiponectin when these young women consume a high-fat diet. These results suggest that genotyping of the AT1R A1166C polymorphism may help to prevent the development of metabolic syndrome and atherosclerosis in young women.