Early Inflammatory and Metabolic Changes in Association With AGTR1 Polymorphisms in Prehypertensive Subjects

Abstract

BACKGROUND

The Seventh Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure in 2003 created a prehypertension category for persons with blood pressures ranging from systolic blood pressure (SBP) of 120–139 mm Hg or diastolic blood pressure (DBP) from 80 to 89 mm Hg, due to increased risk of cardiovascular disease.

METHODS

Our study utilized the University of California-San Diego (UCSD) Twin Hypertension Cohort. We measured comprehensive plasma cholesterol levels and metabolic (glucose, insulin, leptin) and inflammatory markers (interleukin-6 (IL-6), C-reactive protein (CRP), free fatty acids) to determine the differences between normotensive and prehypertensive subjects. Additionally, we determined whether angiotensin II receptor type-1 (AGTR1) polymorphisms, previously associated with hypertension, could predict prehypertension.

RESULTS

A total of 455 white subjects were included in the study (mean age 37.1 years). Prehypertensive subjects were older with greater body mass index (BMI) than the normotensives, and after adjusting for sex and age, had greater plasma glucose, insulin, and IL-6. The common AGTR1 A1166C (rs5186) polymorphism in the 3′-UTR region, particularly the presence of the 1166C allele, which fails to downregulate gene expression, predicted greater likelihood of being in the prehypertension group and higher SBP. A lesser-studied polymorphism in intron-2 of AGTR1 (A/G; rs2276736) was associated with plasma high-density lipoprotein (HDL) and apolipoprotein A-1. In a subgroup analysis of nonobese subjects (N = 405), similar associations were noted.

CONCLUSION

Prehypertensive subjects already exhibit early pathophysiologic changes putting them at risk of future cardiovascular disease, and AGTR1 may also contribute to this increased risk. Further investigation is needed to confirm these findings and the precise molecular mechanisms of action.

Cardiovascular and all-cause mortality is directly related to blood pressure, even for blood pressure as low as 115/75 mm Hg.¹ Given increased disease risk even in subjects with “high-normal” blood pressures, the Seventh Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC-7) in 2003 created a prehypertension category for persons with blood pressures ranging from systolic blood pressure (SBP) of 120–139 mm Hg or diastolic blood pressure (DBP) from 80 to 89 mm Hg.² Many of the pathophysiologic mechanisms that play a role in hypertension may already be deranged in prehypertensive subjects,³ including inflammatory pathways that result in elevated C-reactive protein (CRP)⁴ and interleukin-6 (IL-6),⁵ as well as metabolic pathways that result in elevated glucose and insulin levels.⁶ However, conclusions are often confounded due to obesity and presence of the metabolic syndrome and other cardiovascular disease risk factors.

Undoubtedly, hypertension is influenced by heredity with family history highly predictive of future hypertension. Large genome-wide association studies have revealed principally minor associations⁷ perhaps not surprising in light of a number of challenges including the definition of hypertension used.⁸ Despite the continuum of disease and cardiovascular risk with blood pressure, few studies have investigated genetic influences in prehypertensive subjects. Candidate genes from the renin–angiotensin system (RAS) pathway, which play a primary role in vascular tone, hypertension, and sodium and water excretion, have been implicated as contributors to genetic hypertension. In particular, the angiotensin II receptor type-1 gene (AGTR1)⁹ has been frequently studied given that its gene product is the primary receptor for angiotensin II, especially in the heart and the kidney. AGTR1, a G-protein coupled receptor, is the target of pharmacologic intervention and has been studied in a number of medical conditions including heart failure¹⁰ and stroke.¹¹ The A1166C polymorphism in the 3′-untranslated region (UTR) of the gene, which affects receptor expression,¹² has been extensively investigated in hypertension,¹³ but there is also evidence that it influences the metabolic syndrome.¹⁴

Hypertension has previously been associated with inflammation and metabolic changes as well as common AGTR1 genetic polymorphisms. The aim of our study was to determine whether such changes and genetic polymorphisms are noted in young prehypertensive subjects, who do not yet have evidence of diabetes or cardiovascular disease.

METHODS

Subjects

The University of California-San Diego (UCSD) twin/family study has previously been described,¹⁵ with 878 recruited subjects. After excluding hypertensives (defined as self-reported, on blood pressure–lowering medication, or measured SBP ≥140 or DBP ≥90 mm Hg; N = 192), diabetics (self-reported, on glucose-lowering medication, or fasting plasma glucose ≥126 mg/dl; N = 4), and nonwhite subjects (by self-identification; N = 227) to decrease likelihood of admixture confounding genetic associations, 455 subjects from 220 families, including 347 twins, met criteria for this study. None of the subjects reported history of cardiovascular disease. As shown in Table 1, 74.5% were female, with 44% reporting a family history of hypertension. Brachial cuff blood pressures (mm Hg) were measured in seated subjects in triplicate using a DynaPulse oscillometric device (PulseMetric, San Diego, CA) as previously described and validated,¹⁶ with SBP/DBP measured as K1/K4. Using these triplicate measurements, we classified 53.2% in the prehypertensive range (120 ≤ SBP < 140 or 80 ≤ DBP < 90). Subjects were instructed to fast for at least 6 h before evaluation. Fasting plasma and blood samples were collected from each subject.

Table 1.

Demographic characteristics of the study cohort, overall percentages, and differences by blood pressure status

Characteristic	N	Overall, N (%)	Normotensives, N (%)	Prehypertensives, N (%)	P value (Unadj)	P valuea (sex/age adjusted)	P valuea (sex, age, BMI, heart rate, and smoking adjusted)
Blood pressure status	455	—	213 (46.8)	242 (53.2)	—	—	—
Sex (male/female)	455	116 (25.5)/339 (74.5)	42 (19.7)/171 (80.3)	74 (30.6)/168 (69.4)	0.008	0.0021	0.0004
Family history of hypertension (yes/no)	414	200 (44.0)/214 (53.2)	92 (46.9)/104 (53.1)	108 (49.5)/110 (50.5)	0.60	0.46	0.19
Smoking history (yes/no)	433	57 (13.2)/376 (86.8)	21 (10.5)/179 (89.5)	36 (15.5)/197 (84.6)	0.032	0.026	0.049

AGTR1 genotypes	N	Major allele homozygotes (genotype N)	Heterozygotes	Minor allele homozygotes	Minor allele frequency	HWE χ2	P value
Intron-2, (A/G) rs2276735	435	A/A 203	A/G 183	G/G 49	0.32	0.63	0.43
Exon 4, Leu191Leu, rs5182	436	C/C 130	C/T 199	T/T 107	0.47	3.2	0.08
3′UTR, A1166C, rs5186	439	A/A 227	A/C 178	C/C 34	0.28	0.012	0.91

Normal (SBP <120 mm Hg and DBP <80 mm Hg) vs. prehypertensive (SBP 120–139 mm Hg or DBP 80–89 mm Hg). N = 455 from 220 families, including 347 twins. Family history of hypertension refers to first degree relative diagnosed at <60 years of age. Bold values signify differences by blood pressure status, P < 0.05.

^aWhen evaluating sex differences by blood pressure status, sex is not included in the model. When evaluating smoking, the fully adjusted model does not include smoking.

AGTR1, angiotensin II receptor type-1; BMI, body mass index; DBP, diastolic blood pressure; HWE, Hardy–Weinberg equilibrium; SBP, systolic blood pressure; 3′-UTR, 3′-untranslated region of gene; χ², χ² analysis.

A subgroup analysis was also performed in nonobese subjects (defined as body mass index (BMI) <30 kg/m²; N = 405).

Measurements of plasma inflammatory and metabolic markers

All plasma markers were determined in a standardized form and calibrated to the appropriate reference laboratory.

Metabolic markers (glucose, insulin, leptin, free fatty acids)

Plasma glucose was measured using a glucose oxidase (O₂ Electrode) technique on an LX20 auto analyzer from the UCSD clinical laboratory (Beckman-Coulter, Brea, CA). Initially, insulin (in ~92% of samples) and leptin (in ~72% of samples) were measured by radioimmunoassay using Linco Research kits (Charleston, NC, now Millipore, Billerica, MA). Subsequently, insulin (in ~8% of samples) and leptin (in ~28% of samples) were measured together by multiplex (2-plex) double antibody sandwich electrochemiluminescence immunoassays (ECLIA) developed by Meso Scale Discovery (Gaithersburg, MD) using monoclonal capture antibodies. See Supplementary Methods online for more details. Sample concentrations were back fitted from standard curves generated with a 4-parameter logistic curve fit model with 1/y² weighting. Standard back-calculated recoveries were 90–110%. Calibrators and sample duplicate CVs ranged from 0.12 to 7.9%. Spike recovery for insulin and leptin (N = 3 samples) was 90–105%. The insulin and leptin levels (N = 100 samples in duplicate) using radioimmunoassay and ECLIA were highly correlated, with R² = 0.99. The quantitative insulin sensitivity check index (QUICKI) was determined by QUICKI = 1/[log (fasting insulin, IU/ml) + log (fasting glucose, mg/dl)].¹⁷

Free fatty acids were determined by a modified colorimetric enzymatic assay from Wako Chemicals (Richmond, VA), which primarily measured nonesterified fatty acids. The within- and between-run precisions were <2.7 and 5.2% respectively. The linear range of the assay is 0–2.0 mmol/l.

Inflammatory markers (IL-6, CRP)

IL-6 was quantitated by sandwich ECLIA on a Sector Imager-2400 using a Quantiglo kit from R&D Systems (Minneapolis, MN). Intra- and interassay CVs were ~3 and ~10% respectively, with a lower limit of detection (LLOD) of <0.2 pg/ml.

CRP was measured in two phases; ~91% of the samples were determined by the ALPCO (American Laboratory Products, Windham, NH) diagnostic human CRP enzyme-linked immunosorbent assay (#30-9710s), as previously described.¹⁸ In ~9% of samples, CRP was determined using singleplex ECLIA from Meso Scale Discovery, similar to insulin and leptin measurements, except that the samples were prediluted 1:200 with sample dilution buffer provided by Meso Scale Discovery before incubation. CRP results (N = 36 samples in duplicate) by ECLIA were compared to immunoturbidimetric assay (R² = 0.99) and enzyme-linked immunosorbent assay (R² = 0.97). Sample and quality control imprecisions ranged from 0.17 to 7.3%. Spike recoveries for CRP by Meso Scale Discovery ECLIA method were 89–109%.

Lipids and apolipoproteins A-1 and B

Total cholesterol, triglycerides, high-density lipoprotein (HDL), and low-density lipoprotein were measured in ~72% of subjects using enzymatic techniques on an ABA-200 (Abbott Biochromatic Analyzer; Abbott Laboratories, Irving, TX). Low-density lipoprotein and HDL were measured according to the standardized procedures of the Lipid Research Clinics Program.¹⁹ Quantification of apolipoprotein B, apolipoprotein A-1, and HDL subfractions was made as outlined by Young et al.,²⁰ Hogle et al.,²¹ and Gidez et al.²² respectively. The remaining ~28% of samples had total cholesterol, HDL, and triglycerides determined by the UCSD Clinical Chemistry laboratory using an enzymatic colorimetric technique on a Cobas 6000 Analyzer (Roche, Indianapolis, IN). Low-density lipoprotein was then calculated using the Friedewald equation.

Genotyping

Genomic DNA was isolated from blood leukocytes, as has been previously described²³ using PureGene DNA extraction kits (Gentra Systems, Minneapolis, MN). AGTR1 polymorphisms, rs5186, rs5182, and rs2276736 were selected from public databases (www.ncbi.nlm.nih.gov) from varying regions of the gene, 3′-UTR, exon 4, and intron-2, respectively. The polymorphisms were scored using one of two techniques. The first was a two-stage assay (N = 314). In stage one, PCR primers flanking the polymorphism were used to amplify the target region from 5 ng of genomic DNA. In stage two, an oligonucleotide primer flanking the variant was annealed to the amplified template, and extended across the variant base. The mass of the extension product (wild type vs. variant) was scored by matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (low-mass allele vs. high-mass allele). The second technique (N = 383) was determined as part of a whole genome array (Ilumina 610 Quad-array) matched by reference SNP (RefSNP) data. Of subjects (N = 309) that were scored using both techniques, concordance was >99%, with <1% (N = 3) having 1 or more SNPs discordant.

Linkage disequilibrium (LD) was determined using one subject per family on Haploview Software (http://www.broadinstitute.org/haploview/haploview; Boston, MA).²⁴

Subjects were volunteers from Southern California, and each gave informed, written consent; the protocol was approved by the UCSD San Diego Human Research Protection Program.

Statistical analysis

Descriptive and inferential statistics (mean ± s.d.) were computed across all of the twins, using generalized estimating equations (GEEs; PROC GENMOD), in SAS 9.1 (SAS Institute, Cary, NC), to take into account intratwin-pair correlations.²⁵ Least square means are described as mean ± s.e. of the mean in the tables. Most measures were normally distributed; however, plasma triglycerides, CRP, IL-6, leptin, and insulin were skewed, and log-transformation was performed with presentation of geometric means. Results are reported as P values that are unadjusted, sex- and age-adjusted, and finally in a fully adjusted model, which includes the covariates: sex, age, body mass index, heart rate, and smoking history. We also adjusted additionally for the biochemical traits that were measured in different laboratories.

Statistical power for genetic study was determined using the online instrument G*Power 3 (http://www.psycho.uniduesseldorf.de/abteilungen/aap/gpower3/literature).²⁶ Our sample size of >400 has >95% power to detect an effect size of 0.20 for α = 0.05, df = 2.

RESULTS

Tables 1 (percentiles) and 2 (means) show demographic information for the 455 Caucasian subjects, with a mean age of 37.1 ± 14.6 years, who were included in this study. 74.5% were female, and 53.2% were prehypertensive. A family history of hypertension was reported by 44.0% of subjects. Mean blood pressure was 120.3/73.9 mm Hg and BMI was 24.6 ± 4.8 kg/m².

Table 1 indicates that prehypertensive subjects are more likely to be male (P = 0.008) and smokers (P = 0.032). Table 2 notes the differences in demographic characteristics and inflammatory and metabolic markers by blood pressure status (normotensive vs. prehypertensive). Prehypertensive subjects were older (P = 0.0009), had greater BMI (P = 0.0003, sex- and age-adjusted), as shown in Figure 1a, had greater heart rate (P = 0.0038, sex- and age-adjusted) and had greater IL-6 and leptin concentrations (P = 0.0003 and 0.0001, respectively, after sex and age adjustment), shown in Figure 1b. Plasma insulin and glucose levels were also higher in the prehypertensive group (P = 0.0018 and P = 0.018 after sex and age adjustment, respectively), and thus QUICKI, a marker of insulin sensitivity, was greater in the normotensive group (P = 0.0006 after sex and age adjustment), though after adjustment for BMI, smoking, and heart rate these associations were no longer significant.

Table 2.

Baseline demographic mean information, overall, and stratified by blood pressure status

Characteristics	N	Overall	Normotensives	Prehypertensives	P value (Unadj)	P valuea (sex/age adjusted)	P valuea (sex, age, BMI, heart rate, and smoking adjusted)
Anthropometric measures and blood pressures
Age (years)	455	37.1 ± 0.7	34.5 ± 0.9	39.4 ± 1.1	0.0009	0.0002	0.0029
SBP (mm Hg)	423	120.3 ± 0.5	111.4 ± 0.5	127.6 ± 0.4	<0.0001	<0.0001	<0.0001
DBP (mm Hg)	423	73.9 ± 0.4	69.8 ± 0.5	77.7 ± 0.5	<0.0001	<0.0001	<0.0001
Heart rate (bpm)	431	69.1 ± 0.6	68.0 ± 0.9	70.0 ± 0.8	0.044	0.0038	0.034
MAP (mm Hg)	431	87.6 ± 0.4	82.2 ± 0.5	92.3 ± 0.5	<0.0001	<0.0001	<0.0001
BMI (kg/m2)	452	24.6 ± 0.2	23.6 ± 0.4	25.6 ± 0.4	<0.0001	0.0003	0.0014
Lipid measurements
Cholesterol (mg/dl)	329	175.2 ± 2.0	176.7 ± 3.1	175.5 ± 2.7	0.73	0.34	0.23
HDL (mg/dl)	329	50.7 ± 0.9	52.0 ± 1.3	49.6 ± 1.2	0.045	0.063	0.29
LDL (mg/dl)	326	104.0 ± 1.7	104.7 ± 2.6	104.6 ± 2.2	0.98	0.51	0.54
Triglycerideb (mg/dl)	329	104.7 ± 3.7	101.9 ± 5.6	108.6 ± 5.4	0.32	0.53	0.91
Apolipoprotein A-1 (mg/dl)	247	137.3 ± 1.7	138.4 ± 2.6	136.4 ± 2.4	0.44	0.37	0.21
Apolipoprotein B (mg/dl)	246	74.3 ± 1.3	74.8 ± 2.0	74.8 ± 1.8	0.99	0.56	0.41
Inflammatory and metabolic markers
CRPb (μg/ml)	441	1.99 ± 0.14	1.87 ± 0.22	2.18 ± 0.21	0.051	0.047	0.76
Free fatty acids (mmol/l)	356	0.48 ± 0.012	0.47 ± 0.016	0.49 ± 0.019	0.34	0.38	0.64
IL-6b (pg/ml)	425	1.6 ± 0.10	1.4 ± 0.1	1.8 ± 0.2	0.0002	0.0003	0.040
Leptinb (ng/ml)	334	11.7 ± 0.6	10.4 ± 0.9	13.1 ± 0.9	0.0049	0.0001	0.73
Glucose (mg/dl)	397	80.4 ± 0.5	78.5 ± 0.8	82.0 ± 0.7	0.002	0.018	0.11
Insulinb (μU/ml)	339	13.3 ± 0.6	11.9 ± 0.9	14.7 ± 1.1	0.0039	0.0018	0.086
QUICKI	343	0.35 ± 0.002	0.35 ± 0.003	0.34 ± 0.003	0.0011	0.0006	0.057

Normal (SBP ±120 mm Hg and DBP ±80 mm Hg) vs. prehypertension (SBP 120–139 mm Hg or DBP 80–89 mm Hg). Three models are noted, the first is unadjusted, second adjusted for sex and age, and the full model adjusted for sex, age, body mass index, hear rate, and smoking history. Bold values signify P ± 0.05. Means ± s.e. are reported.

^aFor dependent variables included in the adjusted models, no adjustment for that variable is made, for example for BMI, the fully adjusted model includes only sex, age, and smoking history.

^bLog transformation performed for normalization with presentation of geometric means.

BMI, body mass index; bpm, beats per minute; CRP, C-reactive protein; DBP, diastolic blood pressure; HDL, high-density lipoprotein; IL-6, interleukin-6; LDL, low-density lipoprotein; MAP, mean arterial pressure; QUICKI, quantitative insulin sensitivity check index; SBP, systolic blood pressure.

Figure 1.

Differences in characteristics by blood pressure status (normal vs. prehypertensive). (a) Age and body mass index (BMI). Prehypertensive subjects were older with greater BMI, P = 0.0009 and P < 0.0001, respectively. BMI was still significant after adjustment for sex and age. Age is shown on the x-axis and BMI on the y-axis. Mean ± s.e. is graphed. (b) Plasma leptin and IL-6. Prehypertensive subjects had greater leptin and IL-6 levels than normotensives, after sex and age adjustment P = 0.0001 and P = 0.0003, respectively. Statistics were performed on log-transformed values for normalization, with presentation of geometric means (with s.e. bars). IL-6 is shown on the x-axis and leptin on the y-axis. IL, interleukin.

In subgroup analysis of nonobese subjects (N = 405), similarly, prehypertension was associated before and after sex and age adjustment with higher heart rate (P = 0.0061), BMI (P = 0.0006), IL-6 (P = 0.0059), leptin (P = 0.0008), glucose (P = 0.048), and insulin (P = 0.016).

For the genetic associations, Table 1 indicates the frequencies for each of the three polymorphisms investigated within our cohort. All were in Hardy–Weinberg equilibrium, and were only in partial LD with one another, rs5182 and rs5186 (r² = 0.37), rs2276736 and rs5186 (r² = 0.02). Table 3 shows blood pressure, metabolic, and inflammatory characteristics stratified by AGTR1 polymorphism. There was no association of age or BMI with any of the three polymorphisms. SBP was associated with the AGTR1 3′-UTR A1166C (rs5186) polymorphism such that the presence of the minor allele, 1166C, at either 1 or 2 copies was associated with higher SBP, recessive model, P = 0.0005, sex- and age-adjusted, as shown in Figure 2a. Similarly, Figure 2b shows the percentages of subjects within each blood pressure group by A1166C genotype, noting that subjects with prehypertension are more likely to carry the minor allele 1166C, P = 0.0061 after sex and age adjustment.

Table 3.

Results of association studies of AGTR1 polymorphisms (rs5186 and rs2276736) with blood pressure and inflammatory/metabolic markers

	rs 5186 (3′-UTR, A1166C)				rs 2276736 (intron-2, A/G)
	Additive models		Recessive models		Additive models		Recessive models
Association of AGTR1 polymorphisms	P value (Unadj)	P value (age/sex adj)	P value (Unadj)	P value (age/sex adj)	P value (Unadj)	P value (age/sex adj)	P value (Unadj)	P value (age/sex adj)
Anthropometric measures and blood pressure
SBP (mm Hg)	0.016	0.0023	0.0042	0.005	NS	NS	NS	NS
DBP (mm Hg)	NS	NS	NS	NS	NS	NS	NS	NS
MAP (mm Hg)	NS	NS	NS	NS	NS	NS	NS	NS
Heart rate (bpm)	NS	NS	NS	NS	NS	NS	NS	NS
BMI (kg/m2)	NS	NS	NS	NS	NS	NS	NS	NS
Lipid measurements
Cholesterol (mg/dl)	NS	NS	NS	NS	NS	NS	NS	NS
HDL (mg/dl)	NS	NS	NS	NS	0.027	NS	0.012	0.039
LDL (mg/dl)	NS	NS	NS	NS	NS	NS	NS	NS
Triglycerideb (mg/dl)	NS	NS	NS	NS	NS	NS	NS	NS
Apolipoprotein A-1(mg/dl)	NS	NS	NS	NS	0.012	0.033	0.0071	0.020
Apolipoprotein B (mg/dl)	NS	NS	NS	NS	NS	NS	NS	NS
Inflammatory and metabolic markers
CRPb (μg/ml)	NS	NS	NS	NS	NS	NS	NS	NS
Free fatty acids (mmol/l)	NS	NS	NS	NS	0.031	0.045	NS	NS
IL-6b (pg/ml)	NS	NS	NS	NS	NS	NS	NS	NS
Leptinb (ng/ml)	NS	NS	NS	NS	NS	NS	0.032	NS
Glucose (mg/dl)	NS	NS	NS	NS	NS	NS	NS	NS
Insulinb (μU/ml)	NS	NS	NS	NS	NS	NS	NS	NS
QUICKI	NS	NS	NS	NS	NS	NS	NS	NS

AGTR1 Leu191Leu (rs5182) was not associated with any of the traits. Additive (For example, A/A vs. A/G vs. G/G) and recessive models (For example, A/A vs. A/G and G/G) are noted for each polymorphism, both unadjusted and adjusted for sex and age. Bold values signify P < 0.05. Results are consistent with observations that multiple blocks of linkage disequilibrium (LD) result in different associations based upon location of each polymorphism (LD between these two SNPS is minimal with r² = 0.02).

^bLog-transformation performed for normalization with presentation of geometric means.

AGTR1, angiotensin II receptor type-1; BMI, body mass index; bpm, beats per minute; CRP, C-reactive protein; DBP, diastolic blood pressure; HDL, high-density lipoprotein; IL-6, interleukin-6; LDL, low-density lipoprotein; MAP, mean arterial pressure; QUICKI, quantitative insulin sensitivity check index; SBP, systolic blood pressure; SNP, single-nucleotide polymorphism; 3′-UTR, 3′-untranslated region of gene.

Figure 2.

Angiotensin II receptor type-1 (AGTR1) polymorphism A1166C is associated with systolic blood pressure (SBP) and prehypertensive status. (a). SBP. Subjects with at least one 1166C allele, either as a heterozygote or a homozygote of this minor allele have greater SBP than those wild-type homozygous (A1166/A1166), P = 0.0005 after age and sex adjustment. Mean ± s.e. is graphed. (b) Prehypertensive status. Similarly, subjects with at least one 1166C allele (as heterozygote or homozygote minor alleles), have greater likelihood of being prehypertensive, P = 0.0061 after age and sex adjustment.

The AGTR1 intron-2 polymorphism, (A/G, rs2276736) was not associated with blood pressure, but after sex and age adjustment, associations in an additive model were noted with free fatty acids (P = 0.045) and apolipoprotein A-1 (P = 0.033), noted in Table 3. Recessive models for HDL cholesterol and apolipoprotein A-1 indicated that the wild-type homozygotes (A/A) have the highest plasma levels of these metabolic traits (sex- and age-adjusted, P = 0.039 and P = 0.020, respectively). Figure 3 shows the relationship in that wild-type homozygotes (A/A) have greater concentrations of both apolipoprotein A-1 and HDL cholesterol.

Figure 3.

Angiotensin II receptor type-1 (AGTR1) polymorphism in Intron-2 (A/G; rs2276736) associates with plasma high-density lipoprotein (HDL) and apolipoprotein A-1 levels. Shown in a recessive model, subjects with at least one minor allele G (A/G or G/G) have lower HDL and apolipoprotein A-1 levels than wild-type homozygotes (A/A), P = 0.039 and P = 0.020, respectively, after sex and age adjustment. Apolipoprotein A-1 is shown on the x-axis and HDL on the y-axis. Mean ± s.e. are shown.

AGTR1 Leu191Leu (rs5182) was not associated with any of the traits in our study, consistent with the incomplete LD with either rs5186 (r² = 0.37) or rs2276736 (r² = 0.02) and the multiple LD structure within AGTR1 (www.hapmap.org).

In the subgroup analysis of nonobese subjects, the association between the AGTR1 3′-UTR polymorphism at A1166C and SBP was maintained (recessive model, P = 0.001, sex- and age-adjusted). However, the polymorphism was also associated with plasma triglyceride levels in an additive model (P = 0.022, sex- and age-adjusted). The AGTR1 intron-2 polymorphism was additionally associated with plasma leptin in the nonobese subgroup (recessive model, P = 0.0094, sex and age-adjusted).

In further adjusting the plasma characteristics measured using different assays (CRP, insulin, lipids, leptin), there were no significant differences in the results for any of the analyses.

DISCUSSION

Our study found that prehypertensive subjects already show signs of altered inflammatory and metabolic markers, compared with their normotensive controls, and that polymorphisms within the AGTR1 gene may contribute to these abnormalities. We found that young, white prehypertensive subjects are older and have greater BMI, but after multivariate adjustment for confounders, they also continued to have greater heart rate and IL-6 levels. Additionally, the commonly studied AGTR1 3′-UTR polymorphism A1166C is associated with SBP and prehypertension, though we found that the lesser-studied polymorphism A/G in intron-2 (rs2276736) was associated with plasma HDL and apolipoprotein A-1. This is the first study to our knowledge that has associated the AGTR1 gene and its A1166C polymorphism with prehypertension.

Prehypertension was initially categorized in 2003 by JNC-7 in order to classify those at high risk of the future development of hypertension.² Though only lifestyle modifications such as weight loss and exercise were recommended as treatment,² the syndrome was recognized as a major health concern that was growing in frequency.²⁷ The prevalence of prehypertension, at ~30%, is greater than that of hypertension and such subjects already had an intermediate risk of cardiovascular disease and mortality compared with normotensives and hypertensives.²⁸ Many predictors of prehypertension have already been revealed, which include traditional cardiovascular risk factors, such as obesity, elevated fasting glucose, and cholesterol levels²⁹ as well as novel factors such as CRP and homocysteine.⁵ Because of the high degree of correlation among such traits, much influenced by BMI and obesity, true causative associations have been difficult to determine due to possible confounding. For example, CRP correlated with prehypertension in previous studies,⁵ but may be confounded by obesity, in up to 24% of the prehypertensive subjects. In this cohort, prehypertensive subjects displayed elevation of IL-6, a known inducer of CRP production, even after adjustment for many possible confounders. IL-6 has been independently associated with coronary heart disease mortality in models including both inflammatory markers and the metabolic syndrome.³⁰ Our study also demonstrates that traditional metabolic indicators, such as fasting glucose and insulin levels, are already elevated in subjects classified as prehypertensive when compared to normotensive controls, though it may be attributed to increased BMI and heart rate as adjusting for such confounders reduced the association. Heart rate has been previously associated with metabolic syndrome,³¹ as a marker of sympathetic and parasympathetic imbalance. This suggests a role for sympathetic activity as a pathogenetic factor for the observed inter-relationships and differences between prehypertensive and normotensive subjects. When limiting our study to nonobese subjects (N = 405; BMI <30 kg/m²), the associations of prehypertension and glucose, insulin, and leptin were maintained. A similar study conducted in Spain also concluded that prehypertension was associated with insulin resistance.⁶

Given angiotensin II's broad spectrum of actions as an autocrine, endocrine, and intracrine transmitter with AGTR1 as its primary target in cardiovascular disease, AGTR1 has been extensively studied.³² The most extensively studied polymorphism is A1166C (rs5186),¹³ which is not in a coding region, but is in the 3′-UTR and has been shown to influence mRNA transcript stability.³³ In particular, human micro-RNA, hsa-miR-155, appears to differentially interact with the AGTR1 3′-UTR based on variation at the A1166C polymorphism, such that when the major allele A1166 is present, gene expression is downregulated.¹² Yet when 1166C is present, downregulation does not occur, resulting in increased AGTR1 levels.

Here, we note that the presence of the 1166C allele is associated with higher mean SBP even in subjects that are not yet hypertensive. Similarly, the Cardiovascular Health Study found this allele to be associated with SBP³⁴ and a recent longitudinal prospective study noted that the 1166C allele was associated with incident hypertension.¹⁴ Previous case–control studies have also noted correlation between 1166C and hypertension,^35,36 though a meta-analysis of 38 articles was unable to reach a sound conclusion largely due to “methodologic weaknesses,” and heterogeneity of studies.¹³ Many of the studies were small and underpowered, and thus failed to detect associations.

AGTR1, both receptor and gene, has been studied for associations with the metabolic syndrome. Various mechanisms may play a role in the relationships between the AGTR1 receptor, angiotensin II, and components of the metabolic syndrome. For example, hypercholesterolemia may upregulate AGTR1 expression, shown in vascular smooth muscle cells.³⁷ Some studies have suggested that the AGTR1 A1166C polymorphism may predict incident or prevalent metabolic syndrome,^14,38 which is consistent with our hypertension results.

Although the AGTR1 intronic polymorphism (A/G) rs2276736 has not been extensively studied and its function is unknown, we found that it was associated with plasma HDL and apolipoprotein A-1 levels (Figure 3) in a recessive model. One previous study found that this polymorphism, as well as others in the AGTR1 gene, was associated with nonalcoholic fatty liver disease in Japanese patients.³⁹ One possibility is that this polymorphism, in a separate LD block from the others studied here, may tag the promoter region of the gene. Relationships have been noted between angiotensin II and HDL levels. Angiotensin II may induce HDL scavenger receptor class B type-1 resulting in an increase in HDL uptake by adipocytes.⁴⁰ Further investigation is necessary to determine whether the AGTR1 polymorphism in intron-2 is functional and how it may perturb angiotensin II signaling, which may subsequently affect HDL concentrations. As the primary protein scaffold of HDL and an important part of cholesterol metabolism, it is consistent that apolipoprotein A-1 levels are associated with the polymorphism as well, though the effects of angiotensin II and the receptor levels on apolipoprotein A-1 have not been studied.

In our subgroup analyses of nonobese subjects, additional associations were noted with the AGTR1 polymorphisms, such that the A1166C polymorphism was also associated with plasma triglyceride levels in an additive model (P = 0.022, sex- and age-adjusted) and the intron-2 polymorphism was additionally associated with plasma leptin in the nonobese subgroup (recessive model, P = 0.0094, sex- and age-adjusted). One explanation is that this genetic variation may contribute to the basal levels, but as subjects become obese, other neurohormonal and environmental factors may confound the associations and reduce their significance.

We must acknowledge limitations of our study. We used casual blood pressures in triplicate to classify blood pressure status. The use of ambulatory BP would have allowed us to identify subjects with white-coat or masked hypertension. Our cohort was overrepresented in female Caucasian subjects; thus results may not be readily generalizable to the population at large. However, we deliberately defined a group of Caucasian subjects without hypertension or diabetes in order to detect differences that are not confounded by genetic admixture. A strength of our cohort design, in evaluating twins and their families, is that we can also determine heritability of traits, to assess the proportion of phenotypic variation that is attributable to genetic variation. The heritability of such metabolic and inflammatory traits from our cohort has previously been reported:^15,18 these metabolic and inflammatory traits are highly heritable, with SBP and DBP nearing ~50% heritability, and plasma leptin and triglyceride levels over ~60%.

Another limitation of our study is in evaluating a number of genotypes, one must consider whether results are influenced by multiple comparisons. However, the three genotypes are in incomplete LD, and thus not independent observations. In utilizing the conservative Bonferroni correction for each genotype (target P = 0.05/3 = 0.017), SBP remains associated with the A1166C genotype.

In conclusion, our study found that healthy prehypertensive subjects already display increased metabolic and inflammatory markers compared to those with normal blood pressure. As such traits are highly heritable, we also determined that genetic variation within the AGTR1 gene, particularly the commonly studied functional 3′-UTR polymorphism A1166C, influences not only blood pressure but also HDL levels in this cohort. Further investigation is needed to confirm these results and determine more precise molecular mechanisms.