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Association between the AGTR1 polymorphism +1166A>C and serum levels of high-sensitivity C-reactive protein
Regulatory Peptides 152 (2009) 28–32
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Regulatory Peptides j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / r e g p e p
Association between the AGTR1 polymorphism +1166ANC and serum levels of high-sensitivity C-reactive protein☆ Petra Suchankova a,⁎, Susanne Henningsson a, Marie Olsson a, Fariba Baghaei b, Roland Rosmond b, Göran Holm b, Elias Eriksson a, Agneta Ekman a a b
Institute of Neuroscience and Physiology, Department of Pharmacology, University of Gothenburg, P.O. Box 431, SE-405 30 Gothenburg, Sweden Institute of Medicine, Department of Metabolism and Cardiovascular Research, University of Gothenburg, Gothenburg, Sweden
a r t i c l e
i n f o
Article history: Received 11 April 2008 Received in revised form 2 November 2008 Accepted 2 November 2008 Available online 6 November 2008 Keywords: Angiotensin II (AngII) Angiotensin II type 1 receptor (AGTR1) High-sensitivity C-reactive protein (hsCRP) Inflammation Renin–angiotensin system (RAS) +1444CNT polymorphism +1166ANC polymorphism
a b s t r a c t Genetic factors have been shown to influence high-sensitivity C-reactive protein (hsCRP) levels, however, which genes that are involved in this process remains to be clarified. The renin–angiotensin system (RAS) is of importance for the regulation of inflammation, and blockade of angiotensin II type 1 receptors (AGTR1) influences hsCRP levels. These findings prompted us to investigate whether a polymorphism in the AGTR1 gene may influence hsCRP levels. Additionally, a polymorphism in the CRP gene that has previously been shown to influence hsCRP levels was genotyped. Serum levels of hsCRP were measured in 270 42-year-old women recruited from the population registry. Two single nucleotide polymorphisms were analysed: +1166ANC and +1444CNT of the AGTR1 and CRP gene, respectively. The A allele of the AGTR1 polymorphism +1166ANC was dose-dependently associated with higher hsCRP levels (p = 0.014, adjusted for confounding factors and multiple comparisons). hsCRP levels were not significantly influenced by the CRP +1444CNT genotype; however, an interaction between the two studied polymorphisms with respect to hsCRP levels was observed (p = 0.018). The significant association between the AGTR1 polymorphism and hsCRP levels, which appears to be independent of anthropometric and metabolic traits, is yet another indication of a direct influence of RAS on inflammation. © 2008 Elsevier B.V. All rights reserved.
1. Introduction C-reactive protein (CRP) is a sensitive indicator of inflammation, the levels of which rise dramatically in response to inflammatory stimuli. The emergence of high-sensitivity methods for measuring low levels of CRP (i.e. hsCRP) in serum has led to accumulating evidence that modestly elevated levels of hsCRP, tentatively reflecting lowgrade inflammation, are an independent risk factor for cardiovascular disease (CVD) in both women and men [1–6]. Even though levels of hsCRP are known to be associated with lifestyle factors (e.g. exercise, smoking, estrogen use), sociodemographic factors (e.g. ethnicity, age, education, economic status), body mass index (BMI), and blood pressure (for refs, see [7–9]), family and twin studies suggest that genetic factors also contribute to interindividual differences in hsCRP levels [10–12]. In this vein, different single nucleotide polymorphisms (SNPs) [13–19], as well as one dinucleotide repeat polymorphism [20], in the CRP gene, have been shown to be associated with baseline hsCRP levels. ☆ Sponsorship: This study was supported by the Medical Research Council (8668), Torsten and Ragnar Söderberg's Foundation and Swedish Brain Power. ⁎ Corresponding author. Tel.: +46 31 786 34 48; fax: +46 31 786 30 65. E-mail address: [email protected] (P. Suchankova). 0167-0115/$ – see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.regpep.2008.11.001
The renin–angiotensin system (RAS) consists of an enzymatic cascade that results in the formation of angiotensin II (AngII). This peptide hormone acts as a potent vasoconstrictor and exerts its effects mainly through the activation of angiotensin II type 1 receptors (AGTR1). AngII is consistently linked to the pathogenesis of atherosclerosis (for refs, see [21]) and is believed to be involved in the development of both hypertension and insulin resistance [22]. Recent studies have demonstrated that AngII is important also for inflammation [23–25], and variations in the gene of both angiotensin converting enzyme [26] and angiotensinogen [27] have been associated with proneness for inflammation. Additionally, it has been demonstrated that treatment with AGTR1 blockers [28,29], as well as angiotensin converting enzyme inhibitors [30,31], decrease serum levels of hsCRP. One SNP in the 3′-untranslated region (3′UTR) of the AGTR1 gene (+1166ANC, ID: rs5186) has previously been associated with CVD [32,33] and essential hypertension [34–36]. Given the apparent influence of AGTR1 on hsCRP, and the fact that hsCRP levels are also associated with CVD, we aimed to explore to what extent this polymorphism is associated with elevated serum hsCRP levels in healthy subjects. To this end, hsCRP levels as well as this SNP were assessed in a population consisting of 270 women that were all at the age of 42 and recruited from the population registry. We also analysed
P. Suchankova et al. / Regulatory Peptides 152 (2009) 28–32
an SNP in the 3′UTR of the CRP gene itself (+1444CNT, ID: rs1130864) that has previously been reported to exert an effect on serum hsCRP [17–19]. 2. Methods 2.1. Subjects All women born on uneven days in the year of 1956 and living in Gothenburg, Sweden, constituted the primary cohort (n =1137); this population-based group had originally been recruited for a study of obesity, anthropometrics, and cardiovascular risk factors [37]. Reported self-measurements of body weight, height, and circumference ratio over the waist and hips (WHR) were completed and returned by 80% of the original cohort. WHR was then used for a selection of 450 women in total with low, median or high WHR. Of these women, 270 (60%) volunteered to provide blood samples for analyses and genotyping. At the time of blood sampling, an anthropometric examination recording weight, length and WHR were performed. The women also self-reported smoking habits. At the time of the investigation the participants were 42 years old. All participating women gave their informed consent and the study protocol was approved by the ethical committee of Göteborg University. 2.2. Determination of anthropometric and metabolic traits Venous blood samples were obtained between 0800 h and 1000 h after an overnight fast in the follicular phase of the menstrual cycle. Serum samples were stored at −80 °C until analysis. Measurement of anthropometric and metabolic traits has previously been described by Henningsson et al. [38]. hsCRP levels were determined by means of a high-sensitivity double-antibody ELISA purchased from Immundiagnostik A, Bensheim, Germany. The inter-assay and intra-assay coefficients of variance were 6.0% and 0.1–4.6%, respectively. 2.3. Genotyping Human genomic DNA was extracted from blood samples using the QIAamp DNA Blood Mini Kit (Qiagen, Hilden, Germany). The analysis of the A/C polymorphism at position 1166 in the 3′UTR region of the AGTR1 gene in the studied population has been described by Olsson et al. [39]. The CRP polymorphism chosen for genotyping was previously identified by Brull et al. [17] and is located in the 3′UTR of the CRP gene. This SNP was analysed by polymerase chain reaction (PCR) amplification using 5′-CTG GTC TGG GAG CTC GTT AAC TA-3′ and 5′-GCG CTT CCT TCT CAG CTC TT-3′ as the forward and reverse primer, respectively. The PCR was performed using HotstarTaq polymerase from Qiagen and GeneAmp PCR System 9700 (Applied Biosystems, Foster City, CA). A total volume of 20 µL containing 0.3 µM primers, 1.5 mM MgCl2, approximately 50 ng DNA and 200 μM of each dNTP was used. An initial 15 min denaturation step at 95 °C was followed by 41 cycles of 15 s at 95 °C, 30 s at 63 °C and 15 s at 72 °C. Once the cycles were completed the reaction was incubated at 72 °C for 7 min and then left at 4 °C. The PCR-product was genotyped using a Pyrosequencer PSQ 96 and the PSQ 96 SNP Reagent Kit (Pyrosequencing, Uppsala, Sweden). To identify the polymorphism +1444CNT, 15 pmol of the sequencing primer 5'-AAT TCT GAT TCT TTT GGA C-3′ was used. A total of 20 µL of PCR product was used for pyrosequencing in accordance with the manufacturer's instructions. 2.4. Statistical analysis Associations between serum levels of hsCRP (log normalised values of hsCRP were used) and genotypes were assessed using linear regression with BMI, WHR, systolic and diastolic blood pressure, levels of high-density lipoprotein (HDL), levels of low-density lipoprotein
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(LDL), hypertensive drug treatment, smoking status and the use of hormonal contraceptives as covariates. Additionally, an interaction term was added to the regression analysis in order to investigate whether the two studied polymorphisms interact with each other with regards to hsCRP levels. The relationship between anthropometric and metabolic traits on the one hand and serum levels of hsCRP on the other was investigated using Pearson product–moment correlation coefficient. All measured values are expressed as mean ± SD. Corrections for multiple comparisons were made using the Bonferroni technique (pvalues were multiplied with the number of analyses performed). The significance level was set to α = 0.05. The statistical analysis was carried out using the statistical software package SPSS for Windows (Version 13.0, SPSS, Chicago, IL, USA). 3. Results Neither the AGTR1 +1166ANC nor the CRP +1444CNT polymorphism distribution differed significantly from Hardy–Weinberg equilibrium (p = 0.47 and p = 0.12), and both genotype frequencies (Table 1) were in line with previously published data [17,18,34,40]. The mean serum level of hsCRP in the studied women was 1.84 ± 2.82 mg/L (median: 0.82 mg/L). Seven women had hsCRP levels above 10 mg/L, which may be indicative of an ongoing infection or inflammation; however, all women were included in the analyses since exclusion of these women did not change the results substantially. 34% of the studied women were smokers, 8% were being treated with hypertensive medication and 10% used hormonal contraceptives. There was a positive correlation between serum levels of hsCRP on the one hand and BMI and WHR on the other, and a negative correlation between hsCRP and HDL. In addition, a weak positive correlation was seen between serum levels of hsCRP and systolic blood pressure (Table 2). Table 1 Anthropometric and metabolic traits according to the AGTR1 +1166ANC and CRP +1444CNT genotype Pa +1166ANC n = 270 % BMI, kg/m2 WHR Systolic BP⁎, mm Hg Diastolic BP⁎, mm Hg HDL, mM LDL, mM hsCRP, mg/L +1444CNT n = 270 % BMI, kg/m2 WHR Systolic BP⁎, mm Hg Diastolic BP⁎, mm Hg HDL, mM LDL, mM hsCRP, mg/L
AA 130 48 24.9 ± 4.3 0.82 ± 0.07 110 ± 14
AC 111 41 24.7 ± 4.0 0.80 ± 0.07 111 ± 15
CC 29 11 24.4 ± 5.3 0.78 ± 0.07 108 ± 14
ns 0.01 ns
64 ± 9
65 ± 10
64 ± 12
ns
1.57 ± 0.38 2.99 ± 0.68 2.01 ± 2.92 CC 131 49 24.9 ± 4.7 0.80 ± 0.07 111 ± 15
1.61 ± 0.44 3.2 ± 0.80 1.72 ± 2.88 TC 106 39 24.4 ± 3.7 0.81 ± 0.07 109 ± 13
1.70 ± 0.41 2.92 ± 0.58 1.48 ± 2.07 TT 33 12 25.3 ± 4.5 0.82 ± 0.08 110 ± 15
ns ns 0.006
ns ns ns
65 ± 10
64 ± 9
66 ± 9
ns
1.57 ± 0.38 3.07 ± 0.71 1.85 ± 2.53
1.61 ± 0.37 3.08 ± 0.72 1.82 ± 3.36
1.67 ± 0.58 3.08 ± 0.82 1.84 ± 1.95
ns ns ns
Pb
R2 (%)
Pc
ns
0.002
31.5
ns
29.3
0.014
BMI, body mass index; WHR, waist to hip ratio; BP, blood pressure; HDL, high-density lipoprotein; LDL, low-density lipoprotein; hsCRP, high-sensitivity C-reactive protein; ns, non significant. All data are reported as mean ± SD. Pa = Significant levels obtained by linear regression without any adjustments. df = 1 for all tests. Pb = Significant levels obtained by linear regression with adjustments made for BMI, WHR, systolic and diastolic blood pressure, HDL, LDL, hypertensive drug treatment, smoking status and contraceptive treatment. df = 10. Pc = Bonferroni corrected P-value. ⁎mean obtained from two independent measurements, n = 267.
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Table 2 Correlations between hsCRP levels and anthropometric and metabolic traits, respectively
2
BMI, kg/m WHR Systolic BP⁎, mm Hg Diastolic BP⁎, mm Hg HDL, mM LDL, mM
n
Correlation
Pa
Pb
270 270 267 267 270 270
0.405 0.241 0.126 0.107 −0.216 0.116
b0.001 b0.001 0.039 ns b0.001 ns
b0.001 b0.001 ns ns 0.002 ns
Pa = Significant levels obtained by Pearson product–moment correlation without any adjustments. Pb = Bonferroni corrected P-value. ⁎mean obtained from two independent measurements.
When hsCRP levels were analysed with regard to the two studied polymorphisms, a significant association was found between the AGTR1 polymorphism and hsCRP, carriers of the A allele displaying higher hsCRP serum levels (Table 1). This association remained significant also when controlling for the confounding factors BMI, WHR, systolic and diastolic blood pressure, HDL and LDL levels, hypertensive drug treatment, smoking status and use of contraceptives. In contrast, hsCRP levels were not influenced by the CRP +1444CNT polymorphism. However, including an interaction term in the regression analysis revealed an interaction between the two polymorphisms with respect to their association with hsCRP levels (p = 0.018, R2 = 33.4%, df = 1), women carrying both the CC genotype of the AGTR1 polymorphism and the CC genotype of the CRP polymorphism displaying the lowest serum levels of hsCRP. Apart from a weak association between WHR and the AGTR1 polymorphism, no associations between the anthropometric and metabolic traits and the two studied polymorphisms were observed. 4. Discussion In the present study, the A allele of the AGTR1 polymorphism +1166ANC was dose-dependently associated with higher hsCRP levels. No significant association was found between serum hsCRP levels and the CRP polymorphism +1444CNT per se, but we did obtain evidence for a gene–gene interaction between AGTR1 and CRP to be of importance for hsCRP levels. Our results are well in line with previous reports showing AngII to have AGTR1-mediated pro-inflammatory effects (for refs, see [25,41]) involving the induction of pro-inflammatory cytokines, adhesion molecules, and chemokines [42–45]. Our observed association between the +1166ANC polymorphism in the AGTR1 gene and hsCRP gains support from a previous study by Sezer and co-workers in which a similar observation was made [46]. Since this possible relationship was not the issue of their study, it was however only mentioned, without presentation of any data. The influence exerted by AngII and AGTR1 on inflammation has previously been suggested to be independent of their influence on blood pressure [47,48]. The present study is in support of this hypothesis as no significant relationship was found between the AGTR1 +1166ANC SNP and common parameters related to CVD (with the exception of a borderline association with WHR). In addition, the association between the polymorphism and hsCRP remained significant when controlling for blood pressure. The +1166ANC polymorphism is located in an untranslated region of AGTR1 but is associated with a number of phenotypes, e.g. essential hypertension [32,34–36,49,50], diastolic blood pressure [51], coronary vasomotion [52], hypercholesterolemia [33], and AngII response [53]. Martin et al. [54] recently presented a possible explanation for why this silent polymorphism appears to influence receptor expression by showing that it is situated in a cis-regulated site that is recognized by microRNA (miR-155) capable of silencing gene expression. The C allele
of the SNP was found to prevent this microRNA from interacting with the site resulting in increased expression of AGTR1. Most studies have shown that the CC genotype or the presence of a C allele displays a negative effect on CVD risk factors. In contrast, other studies have associated the AA genotype with negative anthropometric and metabolic parameters including higher BMI and fasting glucose [55] as well as insulin resistance [56]. In accordance with our results, some other studies however have failed to detect any association between the +1166ANC polymorphism and metabolic traits [57,58]. The disparate findings with respect to this AGTR1 polymorphism on the one hand, and vascular functions and various anthropometric/metabolic parameters on the other, may be due to the fact that the studied populations have differed with respect to illness (some comprising healthy individuals and some patients with CVD or metabolic disorders), age, gender and ethnicity. Further studies are thus warranted in order to shed light on these possible relationships. In several studies, the T allele of the +1444CNT polymorphism of the CRP gene has been associated with higher serum hsCRP levels [17,19,59– 62], and also with a larger CRP response following an inflammatory stimulus [18]. In contrast to these studies, a Japanese report showed opposite results, as homozygotes for the C allele displayed elevated hsCRP levels compared to T-carriers [63]. Yet another study reported no significant association between this polymorphism and levels of hsCRP [14]. Despite the lack of association between serum hsCRP levels per se and the CRP polymorphism in our study, a significant interaction between the AGTR1 and CRP polymorphisms was found. Thus, in the presence of the AGTR1 CC-genotype, women carrying the CC genotype of the CRP polymorphism displayed the lowest hsCRP levels, which is well in line with the many previous studies suggesting the T allele to be associated with higher hsCRP levels. The divergent results obtained from studies on the possible influence of CRP genotype on hsCRP levels may be explained by the fact that the influence of confounding factors has not always been taken into account, as well as by the influence of gene–gene interactions, such as the one found in our study. Other genes that have been reported to influence hsCRP levels [64] include those coding for interleukin-6 [65], tumour necrosis factor (TNF)-alpha [66], the leptin receptor [67], and various genes involved in beta-adrenergic transmission [12]. Whether these genes interact with the CRP gene remains to be investigated. Our study is faced with certain limitations. Firstly, hsCRP levels should preferably be measured on several occasions in order to exclude cases of falsely elevated concentrations; however, in the present study, the analyses were based on results obtained from one measurement only. Secondly, hsCRP levels are known to be affected by a series of confounding factors (see Introduction), of which many, but not all, were assessed and taken into account. Thirdly, the studied population was of a relatively moderate size. However, the fact that all subjects were of the same age and the same gender probably enhanced the statistical power of the study. To summarize, we found an association between the +1166ANC polymorphism in the AGTR1 gene and serum levels of hsCRP in women, further supporting the association between the RAS and inflammation. This association was independent of CVD risk factors such as BMI, blood pressure and blood lipids.
Acknowledgements The authors gratefully acknowledge the technical assistance of Gunilla Bourghardt and Inger Oscarsson.
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Regulatory Peptides j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / r e g p e p
Association between the AGTR1 polymorphism +1166ANC and serum levels of high-sensitivity C-reactive protein☆ Petra Suchankova a,⁎, Susanne Henningsson a, Marie Olsson a, Fariba Baghaei b, Roland Rosmond b, Göran Holm b, Elias Eriksson a, Agneta Ekman a a b
Institute of Neuroscience and Physiology, Department of Pharmacology, University of Gothenburg, P.O. Box 431, SE-405 30 Gothenburg, Sweden Institute of Medicine, Department of Metabolism and Cardiovascular Research, University of Gothenburg, Gothenburg, Sweden
a r t i c l e
i n f o
Article history: Received 11 April 2008 Received in revised form 2 November 2008 Accepted 2 November 2008 Available online 6 November 2008 Keywords: Angiotensin II (AngII) Angiotensin II type 1 receptor (AGTR1) High-sensitivity C-reactive protein (hsCRP) Inflammation Renin–angiotensin system (RAS) +1444CNT polymorphism +1166ANC polymorphism
a b s t r a c t Genetic factors have been shown to influence high-sensitivity C-reactive protein (hsCRP) levels, however, which genes that are involved in this process remains to be clarified. The renin–angiotensin system (RAS) is of importance for the regulation of inflammation, and blockade of angiotensin II type 1 receptors (AGTR1) influences hsCRP levels. These findings prompted us to investigate whether a polymorphism in the AGTR1 gene may influence hsCRP levels. Additionally, a polymorphism in the CRP gene that has previously been shown to influence hsCRP levels was genotyped. Serum levels of hsCRP were measured in 270 42-year-old women recruited from the population registry. Two single nucleotide polymorphisms were analysed: +1166ANC and +1444CNT of the AGTR1 and CRP gene, respectively. The A allele of the AGTR1 polymorphism +1166ANC was dose-dependently associated with higher hsCRP levels (p = 0.014, adjusted for confounding factors and multiple comparisons). hsCRP levels were not significantly influenced by the CRP +1444CNT genotype; however, an interaction between the two studied polymorphisms with respect to hsCRP levels was observed (p = 0.018). The significant association between the AGTR1 polymorphism and hsCRP levels, which appears to be independent of anthropometric and metabolic traits, is yet another indication of a direct influence of RAS on inflammation. © 2008 Elsevier B.V. All rights reserved.
1. Introduction C-reactive protein (CRP) is a sensitive indicator of inflammation, the levels of which rise dramatically in response to inflammatory stimuli. The emergence of high-sensitivity methods for measuring low levels of CRP (i.e. hsCRP) in serum has led to accumulating evidence that modestly elevated levels of hsCRP, tentatively reflecting lowgrade inflammation, are an independent risk factor for cardiovascular disease (CVD) in both women and men [1–6]. Even though levels of hsCRP are known to be associated with lifestyle factors (e.g. exercise, smoking, estrogen use), sociodemographic factors (e.g. ethnicity, age, education, economic status), body mass index (BMI), and blood pressure (for refs, see [7–9]), family and twin studies suggest that genetic factors also contribute to interindividual differences in hsCRP levels [10–12]. In this vein, different single nucleotide polymorphisms (SNPs) [13–19], as well as one dinucleotide repeat polymorphism [20], in the CRP gene, have been shown to be associated with baseline hsCRP levels. ☆ Sponsorship: This study was supported by the Medical Research Council (8668), Torsten and Ragnar Söderberg's Foundation and Swedish Brain Power. ⁎ Corresponding author. Tel.: +46 31 786 34 48; fax: +46 31 786 30 65. E-mail address: [email protected] (P. Suchankova). 0167-0115/$ – see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.regpep.2008.11.001
The renin–angiotensin system (RAS) consists of an enzymatic cascade that results in the formation of angiotensin II (AngII). This peptide hormone acts as a potent vasoconstrictor and exerts its effects mainly through the activation of angiotensin II type 1 receptors (AGTR1). AngII is consistently linked to the pathogenesis of atherosclerosis (for refs, see [21]) and is believed to be involved in the development of both hypertension and insulin resistance [22]. Recent studies have demonstrated that AngII is important also for inflammation [23–25], and variations in the gene of both angiotensin converting enzyme [26] and angiotensinogen [27] have been associated with proneness for inflammation. Additionally, it has been demonstrated that treatment with AGTR1 blockers [28,29], as well as angiotensin converting enzyme inhibitors [30,31], decrease serum levels of hsCRP. One SNP in the 3′-untranslated region (3′UTR) of the AGTR1 gene (+1166ANC, ID: rs5186) has previously been associated with CVD [32,33] and essential hypertension [34–36]. Given the apparent influence of AGTR1 on hsCRP, and the fact that hsCRP levels are also associated with CVD, we aimed to explore to what extent this polymorphism is associated with elevated serum hsCRP levels in healthy subjects. To this end, hsCRP levels as well as this SNP were assessed in a population consisting of 270 women that were all at the age of 42 and recruited from the population registry. We also analysed
P. Suchankova et al. / Regulatory Peptides 152 (2009) 28–32
an SNP in the 3′UTR of the CRP gene itself (+1444CNT, ID: rs1130864) that has previously been reported to exert an effect on serum hsCRP [17–19]. 2. Methods 2.1. Subjects All women born on uneven days in the year of 1956 and living in Gothenburg, Sweden, constituted the primary cohort (n =1137); this population-based group had originally been recruited for a study of obesity, anthropometrics, and cardiovascular risk factors [37]. Reported self-measurements of body weight, height, and circumference ratio over the waist and hips (WHR) were completed and returned by 80% of the original cohort. WHR was then used for a selection of 450 women in total with low, median or high WHR. Of these women, 270 (60%) volunteered to provide blood samples for analyses and genotyping. At the time of blood sampling, an anthropometric examination recording weight, length and WHR were performed. The women also self-reported smoking habits. At the time of the investigation the participants were 42 years old. All participating women gave their informed consent and the study protocol was approved by the ethical committee of Göteborg University. 2.2. Determination of anthropometric and metabolic traits Venous blood samples were obtained between 0800 h and 1000 h after an overnight fast in the follicular phase of the menstrual cycle. Serum samples were stored at −80 °C until analysis. Measurement of anthropometric and metabolic traits has previously been described by Henningsson et al. [38]. hsCRP levels were determined by means of a high-sensitivity double-antibody ELISA purchased from Immundiagnostik A, Bensheim, Germany. The inter-assay and intra-assay coefficients of variance were 6.0% and 0.1–4.6%, respectively. 2.3. Genotyping Human genomic DNA was extracted from blood samples using the QIAamp DNA Blood Mini Kit (Qiagen, Hilden, Germany). The analysis of the A/C polymorphism at position 1166 in the 3′UTR region of the AGTR1 gene in the studied population has been described by Olsson et al. [39]. The CRP polymorphism chosen for genotyping was previously identified by Brull et al. [17] and is located in the 3′UTR of the CRP gene. This SNP was analysed by polymerase chain reaction (PCR) amplification using 5′-CTG GTC TGG GAG CTC GTT AAC TA-3′ and 5′-GCG CTT CCT TCT CAG CTC TT-3′ as the forward and reverse primer, respectively. The PCR was performed using HotstarTaq polymerase from Qiagen and GeneAmp PCR System 9700 (Applied Biosystems, Foster City, CA). A total volume of 20 µL containing 0.3 µM primers, 1.5 mM MgCl2, approximately 50 ng DNA and 200 μM of each dNTP was used. An initial 15 min denaturation step at 95 °C was followed by 41 cycles of 15 s at 95 °C, 30 s at 63 °C and 15 s at 72 °C. Once the cycles were completed the reaction was incubated at 72 °C for 7 min and then left at 4 °C. The PCR-product was genotyped using a Pyrosequencer PSQ 96 and the PSQ 96 SNP Reagent Kit (Pyrosequencing, Uppsala, Sweden). To identify the polymorphism +1444CNT, 15 pmol of the sequencing primer 5'-AAT TCT GAT TCT TTT GGA C-3′ was used. A total of 20 µL of PCR product was used for pyrosequencing in accordance with the manufacturer's instructions. 2.4. Statistical analysis Associations between serum levels of hsCRP (log normalised values of hsCRP were used) and genotypes were assessed using linear regression with BMI, WHR, systolic and diastolic blood pressure, levels of high-density lipoprotein (HDL), levels of low-density lipoprotein
29
(LDL), hypertensive drug treatment, smoking status and the use of hormonal contraceptives as covariates. Additionally, an interaction term was added to the regression analysis in order to investigate whether the two studied polymorphisms interact with each other with regards to hsCRP levels. The relationship between anthropometric and metabolic traits on the one hand and serum levels of hsCRP on the other was investigated using Pearson product–moment correlation coefficient. All measured values are expressed as mean ± SD. Corrections for multiple comparisons were made using the Bonferroni technique (pvalues were multiplied with the number of analyses performed). The significance level was set to α = 0.05. The statistical analysis was carried out using the statistical software package SPSS for Windows (Version 13.0, SPSS, Chicago, IL, USA). 3. Results Neither the AGTR1 +1166ANC nor the CRP +1444CNT polymorphism distribution differed significantly from Hardy–Weinberg equilibrium (p = 0.47 and p = 0.12), and both genotype frequencies (Table 1) were in line with previously published data [17,18,34,40]. The mean serum level of hsCRP in the studied women was 1.84 ± 2.82 mg/L (median: 0.82 mg/L). Seven women had hsCRP levels above 10 mg/L, which may be indicative of an ongoing infection or inflammation; however, all women were included in the analyses since exclusion of these women did not change the results substantially. 34% of the studied women were smokers, 8% were being treated with hypertensive medication and 10% used hormonal contraceptives. There was a positive correlation between serum levels of hsCRP on the one hand and BMI and WHR on the other, and a negative correlation between hsCRP and HDL. In addition, a weak positive correlation was seen between serum levels of hsCRP and systolic blood pressure (Table 2). Table 1 Anthropometric and metabolic traits according to the AGTR1 +1166ANC and CRP +1444CNT genotype Pa +1166ANC n = 270 % BMI, kg/m2 WHR Systolic BP⁎, mm Hg Diastolic BP⁎, mm Hg HDL, mM LDL, mM hsCRP, mg/L +1444CNT n = 270 % BMI, kg/m2 WHR Systolic BP⁎, mm Hg Diastolic BP⁎, mm Hg HDL, mM LDL, mM hsCRP, mg/L
AA 130 48 24.9 ± 4.3 0.82 ± 0.07 110 ± 14
AC 111 41 24.7 ± 4.0 0.80 ± 0.07 111 ± 15
CC 29 11 24.4 ± 5.3 0.78 ± 0.07 108 ± 14
ns 0.01 ns
64 ± 9
65 ± 10
64 ± 12
ns
1.57 ± 0.38 2.99 ± 0.68 2.01 ± 2.92 CC 131 49 24.9 ± 4.7 0.80 ± 0.07 111 ± 15
1.61 ± 0.44 3.2 ± 0.80 1.72 ± 2.88 TC 106 39 24.4 ± 3.7 0.81 ± 0.07 109 ± 13
1.70 ± 0.41 2.92 ± 0.58 1.48 ± 2.07 TT 33 12 25.3 ± 4.5 0.82 ± 0.08 110 ± 15
ns ns 0.006
ns ns ns
65 ± 10
64 ± 9
66 ± 9
ns
1.57 ± 0.38 3.07 ± 0.71 1.85 ± 2.53
1.61 ± 0.37 3.08 ± 0.72 1.82 ± 3.36
1.67 ± 0.58 3.08 ± 0.82 1.84 ± 1.95
ns ns ns
Pb
R2 (%)
Pc
ns
0.002
31.5
ns
29.3
0.014
BMI, body mass index; WHR, waist to hip ratio; BP, blood pressure; HDL, high-density lipoprotein; LDL, low-density lipoprotein; hsCRP, high-sensitivity C-reactive protein; ns, non significant. All data are reported as mean ± SD. Pa = Significant levels obtained by linear regression without any adjustments. df = 1 for all tests. Pb = Significant levels obtained by linear regression with adjustments made for BMI, WHR, systolic and diastolic blood pressure, HDL, LDL, hypertensive drug treatment, smoking status and contraceptive treatment. df = 10. Pc = Bonferroni corrected P-value. ⁎mean obtained from two independent measurements, n = 267.
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Table 2 Correlations between hsCRP levels and anthropometric and metabolic traits, respectively
2
BMI, kg/m WHR Systolic BP⁎, mm Hg Diastolic BP⁎, mm Hg HDL, mM LDL, mM
n
Correlation
Pa
Pb
270 270 267 267 270 270
0.405 0.241 0.126 0.107 −0.216 0.116
b0.001 b0.001 0.039 ns b0.001 ns
b0.001 b0.001 ns ns 0.002 ns
Pa = Significant levels obtained by Pearson product–moment correlation without any adjustments. Pb = Bonferroni corrected P-value. ⁎mean obtained from two independent measurements.
When hsCRP levels were analysed with regard to the two studied polymorphisms, a significant association was found between the AGTR1 polymorphism and hsCRP, carriers of the A allele displaying higher hsCRP serum levels (Table 1). This association remained significant also when controlling for the confounding factors BMI, WHR, systolic and diastolic blood pressure, HDL and LDL levels, hypertensive drug treatment, smoking status and use of contraceptives. In contrast, hsCRP levels were not influenced by the CRP +1444CNT polymorphism. However, including an interaction term in the regression analysis revealed an interaction between the two polymorphisms with respect to their association with hsCRP levels (p = 0.018, R2 = 33.4%, df = 1), women carrying both the CC genotype of the AGTR1 polymorphism and the CC genotype of the CRP polymorphism displaying the lowest serum levels of hsCRP. Apart from a weak association between WHR and the AGTR1 polymorphism, no associations between the anthropometric and metabolic traits and the two studied polymorphisms were observed. 4. Discussion In the present study, the A allele of the AGTR1 polymorphism +1166ANC was dose-dependently associated with higher hsCRP levels. No significant association was found between serum hsCRP levels and the CRP polymorphism +1444CNT per se, but we did obtain evidence for a gene–gene interaction between AGTR1 and CRP to be of importance for hsCRP levels. Our results are well in line with previous reports showing AngII to have AGTR1-mediated pro-inflammatory effects (for refs, see [25,41]) involving the induction of pro-inflammatory cytokines, adhesion molecules, and chemokines [42–45]. Our observed association between the +1166ANC polymorphism in the AGTR1 gene and hsCRP gains support from a previous study by Sezer and co-workers in which a similar observation was made [46]. Since this possible relationship was not the issue of their study, it was however only mentioned, without presentation of any data. The influence exerted by AngII and AGTR1 on inflammation has previously been suggested to be independent of their influence on blood pressure [47,48]. The present study is in support of this hypothesis as no significant relationship was found between the AGTR1 +1166ANC SNP and common parameters related to CVD (with the exception of a borderline association with WHR). In addition, the association between the polymorphism and hsCRP remained significant when controlling for blood pressure. The +1166ANC polymorphism is located in an untranslated region of AGTR1 but is associated with a number of phenotypes, e.g. essential hypertension [32,34–36,49,50], diastolic blood pressure [51], coronary vasomotion [52], hypercholesterolemia [33], and AngII response [53]. Martin et al. [54] recently presented a possible explanation for why this silent polymorphism appears to influence receptor expression by showing that it is situated in a cis-regulated site that is recognized by microRNA (miR-155) capable of silencing gene expression. The C allele
of the SNP was found to prevent this microRNA from interacting with the site resulting in increased expression of AGTR1. Most studies have shown that the CC genotype or the presence of a C allele displays a negative effect on CVD risk factors. In contrast, other studies have associated the AA genotype with negative anthropometric and metabolic parameters including higher BMI and fasting glucose [55] as well as insulin resistance [56]. In accordance with our results, some other studies however have failed to detect any association between the +1166ANC polymorphism and metabolic traits [57,58]. The disparate findings with respect to this AGTR1 polymorphism on the one hand, and vascular functions and various anthropometric/metabolic parameters on the other, may be due to the fact that the studied populations have differed with respect to illness (some comprising healthy individuals and some patients with CVD or metabolic disorders), age, gender and ethnicity. Further studies are thus warranted in order to shed light on these possible relationships. In several studies, the T allele of the +1444CNT polymorphism of the CRP gene has been associated with higher serum hsCRP levels [17,19,59– 62], and also with a larger CRP response following an inflammatory stimulus [18]. In contrast to these studies, a Japanese report showed opposite results, as homozygotes for the C allele displayed elevated hsCRP levels compared to T-carriers [63]. Yet another study reported no significant association between this polymorphism and levels of hsCRP [14]. Despite the lack of association between serum hsCRP levels per se and the CRP polymorphism in our study, a significant interaction between the AGTR1 and CRP polymorphisms was found. Thus, in the presence of the AGTR1 CC-genotype, women carrying the CC genotype of the CRP polymorphism displayed the lowest hsCRP levels, which is well in line with the many previous studies suggesting the T allele to be associated with higher hsCRP levels. The divergent results obtained from studies on the possible influence of CRP genotype on hsCRP levels may be explained by the fact that the influence of confounding factors has not always been taken into account, as well as by the influence of gene–gene interactions, such as the one found in our study. Other genes that have been reported to influence hsCRP levels [64] include those coding for interleukin-6 [65], tumour necrosis factor (TNF)-alpha [66], the leptin receptor [67], and various genes involved in beta-adrenergic transmission [12]. Whether these genes interact with the CRP gene remains to be investigated. Our study is faced with certain limitations. Firstly, hsCRP levels should preferably be measured on several occasions in order to exclude cases of falsely elevated concentrations; however, in the present study, the analyses were based on results obtained from one measurement only. Secondly, hsCRP levels are known to be affected by a series of confounding factors (see Introduction), of which many, but not all, were assessed and taken into account. Thirdly, the studied population was of a relatively moderate size. However, the fact that all subjects were of the same age and the same gender probably enhanced the statistical power of the study. To summarize, we found an association between the +1166ANC polymorphism in the AGTR1 gene and serum levels of hsCRP in women, further supporting the association between the RAS and inflammation. This association was independent of CVD risk factors such as BMI, blood pressure and blood lipids.
Acknowledgements The authors gratefully acknowledge the technical assistance of Gunilla Bourghardt and Inger Oscarsson.
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