Endogenous Nitric Oxide Synthase Inhibitors, Arterial ...

Endogenous Nitric Oxide Synthase Inhibitors, Arterial Hemodynamics, and Subclinical Vascular Disease The PREVENCION Study Julio A. Chirinos, Robert David, J. Alexander Bralley, Humberto Zea-Díaz, Edgar Munõz-Atahualpa, Fernando Corrales-Medina, Carolina Cuba-Bustinza, Julio Chirinos-Pacheco, Josefina Medina-Lezama

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Abstract—Endogenous NO synthase inhibitors (end-NOSIs) have been associated with cardiovascular risk factors and atherosclerosis. In addition, end-NOSIs may directly cause hypertension through hemodynamic effects. We aimed to examine the association between end-NOSI asymmetrical dimethylarginine (ADMA) and N-guanidino-monomethylarginine (NMMA), subclinical atherosclerosis, and arterial hemodynamics. We studied 922 adults participating in a population-based study (PREVENCION Study) and examined the correlation between end-NOSI/L-arginine and arterial hemodynamics, carotid-femoral pulse wave velocity, and carotid intima-media thickness using linear regression. ADMA, NMMA, and L-arginine were found to be differentially associated with various classic cardiovascular risk factors. ADMA and NMMA (but not L-arginine) were significant predictors of carotid intima-media thickness, even after adjustment for cardiovascular risk factors, C-reactive protein, and renal function. In contrast, ADMA and NMMA did not predict carotid-femoral pulse wave velocity, blood pressure, or hemodynamic abnormalities. Higher L-arginine independently predicted systolic hypertension, higher central pulse pressure, incident wave amplitude, central augmented pressure, and lower total arterial compliance but not systemic vascular resistance or cardiac output. We conclude that ADMA and NMMA are differentially associated with cardiovascular risk factors, but both end-NOSIs are independent predictors of carotid atherosclerosis. In contrast, they are not associated with large artery stiffness, hypertension, or hemodynamic abnormalities. Our findings are consistent with a role for asymmetrical arginine methylation in atherosclerosis but not in large artery stiffening, hypertension, or long-term hemodynamic regulation. L-Arginine is independently associated with abnormal pulsatile (but not resistive) arterial hemodynamic indices, which may reflect abnormal L-arginine transport, leading to decreased intracellular bioavailability for NO synthesis. (Hypertension. 2008;52:1051-1059.) Key Words: asymmetrical dimethylarginine 䡲 hypertension 䡲 atherosclerosis 䡲 arterial stiffness 䡲 hemodynamics

M

ultiple studies have demonstrated the important role of NO in endothelial physiology and the pathogenesis of vascular disease and hypertension. NO synthase (NOS) produces citrulline and NO from L-arginine.1,2 However, methylated arginine derivatives are normally produced endogenously and competitively inhibit NOS, including asymmetrical dimethylarginine (ADMA) and N-guanidinomonomethyl-arginine (NMMA).1– 4 Increased circulating ADMA has been associated with various cardiovascular risk factors and cardiovascular disease in clinical populations.1– 4 However, there is uncertainty regarding the relationship between ADMA and hypertension. Although it appears that administration of exogenous ADMA produces an acute increase in blood pressure, changes in cardiac output, systemic vascular resistance, and arterial stiffness,5–7 whether circulating levels of endogenous NOS inhibitors (end-NOSIs) are associated with these abnormalities is unknown. Furthermore,

recent studies suggest that ADMA affects central pressure augmentation.7,8 However, previous studies that assessed the relationship between ADMA and hypertension did not evaluate central arterial pressure and indices of pulsatile and resistive hemodynamics. Another issue that requires further investigation is the association between end-NOSIs and subclinical vascular disease. Although ADMA has consistently been shown to correlate with carotid intima-media thickness (c-IMT) in populations with clinical cardiovascular disease, 2 recent studies yielded conflicting results, one showing an independent positive association between ADMA and c-IMT in older adults from the community,9 with the other demonstrating an inverse relationship between c-IMT and ADMA among middle-aged individuals,10 raising the issue of whether inhibition of inducible NOS may be protective in early atherosclerosis. Therefore, data derived from probabilistic,

Received July 23, 2008; first decision August 11, 2008; revision accepted September 17, 2008. From the University of Pennsylvania (J.A.C.), Philadelphia; Metametrix Clinical Laboratory (R.D., J.A.B.), Duluth, Ga; and Santa Maria Catholic University School of Medicine (H.Z-D., E.M-A., F.C-M., C.C-B., J.C-P., J.M-L.). AQP, Peru. Correspondence to Julio A. Chirinos, Division of Cardiology, 8B111, Philadelphia VA Medical Center, 3900 Woodland Ave, Philadelphia, PA 19104. E-mail [email protected] © 2008 American Heart Association, Inc. Hypertension is available at http://hypertension.ahajournals.org

DOI: 10.1161/HYPERTENSIONAHA.108.120352

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population-based samples of unselected adults over a wide age range are needed to reduce selection bias and more definitively assess the association between ADMA and c-IMT, as well as other markers of subclinical vascular disease, such as carotid-femoral pulse wave velocity (cfPWV), a measure of large artery stiffness. Furthermore, no studies analyzing the correlates of NMMA (another endogenous end-NOSI) in the general population are available to date. In a population-based study, we aimed to do the following: (1) examine the association between various cardiovascular risk factors and end-NOSIs, as well as the natural substrate for NOS, L-arginine; (2) examine the independent association between increased levels of end-NOSIs and 2 different markers of subclinical vascular disease with proven prognostic value in the general population (c-IMT and cf-PWV); and (3) examine the correlation between end-NOSIs, central arterial pressure, and systemic hemodynamics. Downloaded from http://hyper.ahajournals.org/ by guest on June 19, 2018

Methods Study Population and Sampling Design The objectives, design, and details regarding the sampling strategy of the PREVENCION Study have been published previously.11 PREVENCION is a population-based study undertaken in Arequipa, Peru. The sampling strategy was probabilistic, multistage, clustered, and stratified according to geographic location and socioeconomic status and based on the most recent population and household national census. The sample included adults aged 20 to 80 years, with an overall participation rate of 85.3%. After initial contact with participants at their household, a comprehensive evaluation was performed at the study headquarters. The study was approved by the Santa Maria Catholic University Human Research Committee, and participants gave informed consent. ADMA, NMMA, and L-arginine were measured in 922 randomly selected subjects from the study cohort (467 women and 455 men). Of these, 767 subjects (365 men and 392 women) had hemodynamic measurements, and 557 subjects (268 women and 289 men) had measurements of c-IMT.

Blood Pressure and Laboratory Measurements Blood pressure was measured with the auscultatory method, as described previously,11 and hypertension was defined according to the Seventh Report of the Joint National Committee for the Diagnosis, Evaluation, and Treatment of High Blood Pressure. Biochemical measurements were performed after an overnight fast, as described previously.11 Diabetes mellitus was defined as fasting blood glucose ⱖ126 mg/dL or pharmacological treatment for diabetes. Serum creatinine was measured by a kinetic compensated Jaffe assay in a Cobas Mira analyzer (Roche), and creatinine clearance was estimated with the Cockcroft-Gault equation. C-reactive protein (CRP) was measured using a high-sensitivity assay (Kamiya Biomedical). Serum samples were frozen at ⫺70°C and shipped to Metametrix Clinical Laboratory for blinded measurements of ADMA, NMMA, and L-arginine by 2 of the authors (R.D. and J.A.B.). L-Arginine, ADMA, and NMMA were analyzed by liquid chromatography-mass spectrometry after a derivitization procedure. In this method, acetonitrile and 15N2-arginine (internal standard) are added to serum/ plasma for protein precipitation. After centrifugation, the supernatant is extracted and added to n-butanol and acetyl chloride. Butylation of the carboxylic acid occurs on heating. The solvent is then evaporated and the dried material reconstituted in mobile phase A. Analytes are retained on a reverse-phase C-18 column with ammonium acetate buffer (mobile phase A), eluted by gradient addition of acetonitrile with formic acid (mobile phase B), and detected in electrospray positive ion mode. The within-run and between-run coefficients

of variation for these measurements were ⬍8% and ⬍12%, respectively.

Measurements of c-IMT High-resolution B-mode carotid ultrasonography was performed with a linear-array, 10-MHz transducer in B mode (Sonosite Titan, Sonosite). With the subject in the supine position, images were obtained bilaterally from the anterior, posterior, and lateral views, with the head tilted slightly upward in the midline position. The transducer was manipulated so that the near and far walls of the common carotid artery were parallel to the transducer footprint, and the lumen diameter was maximized in the longitudinal plane. A region 1 cm proximal to the carotid bulb was identified, and blinded measurements of c-IMT of the near and far walls were performed, including plaques if present in this area, using semiautomated Sonocalc software (Sonosite).

Measurements of cf-PWV Aortic pulse wave velocity is the most robust and reproducible index of large artery stiffness and an independent predictor of cardiovascular risk.12 We measured cf-PWV from simultaneous recordings of arterial flow waves from the right carotid artery and the right femoral artery at the groin, using nondirectional transcutaneous Doppler flow probes (IMEX Dop II, 8 mHz, Nicolet Vascular Inc). The time delay (⌬time) between the onset of flow at the carotid and femoral sites (foot of the velocity signal at each site) was measured offline over 5 to 10 consecutive cardiac cycles and averaged. The distance between the suprasternal notch and the carotid recording point was subtracted from the sum of the distance between the suprasternal notch and pubic symphysis plus the distance between the pubic symphysis and the femoral recording point. Pulse wave velocity was calculated as distance/⌬time. Two trained observers measured the time delay, and an additional observer evaluated data quality for systematic bias, reproducibility, and consistency through blinded measurements in digitally stored recordings. The interobserver and intraobserver coefficients of variation were ⬍5%.

Pulse Waveform Analysis Using a commercially available system (SphygmoCor Px, AtCor Medical), the radial artery pressure wave was recorded with a high-fidelity Millar applanation tonometer (Millar Instruments) and calibrated with auscultatory brachial blood pressure measurements. The aortic pressure wave form was obtained from the radial pressure wave form using the generalized transfer function of the SphygmoCor device.8,13 The merging point of the incident and the reflected wave (inflection point) was identified on the aortic pressure waveform. The first and second systolic peaks (P1 and P2) of the derived aortic pressure waveform were recorded. Augmented pressure was calculated as P2⫺P1. Aortic augmentation index was defined as augmented pressure expressed as a percentage of aortic pulse pressure. Aortic incident wave amplitude was calculated by subtracting diastolic blood pressure from the pressure at the first systolic peak. Total arterial compliance was calculated with the area method.12

Impedance Cardiography Impedance cardiography (ICG) uses changes in thoracic electric impedance to estimate changes in blood volume in the aorta.14 After placement of 4 dual sensors on a patient’s neck and chest, a low-amplitude, high-frequency alternating current is delivered from the 4 outer sensors, and the 4 inner sensors detect instantaneous changes in voltage. According to Ohm’s law, when a constant current is applied to the thorax, the changes in voltage are directly proportional to the changes in measured impedance. Changes from thoracic electric impedance occur because of changes in lung volumes with respiration and changes in the volume and velocity of blood in the great vessels. The rapidly changing component of chest impedance is filtered to remove the respiratory variation, leaving impedance changes attributable to ventricular ejection, which have been shown to correlate well with stroke volume measured with

Chirinos et al Table 1.

NOS Inhibitors, Vascular Disease, and Hypertension

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General Characteristics of Study Subjects

Variable

Men (n⫽455)

Women (n⫽467)

P

Age, y

54.1 (52.3 to 55.7)

55.3 (53.7 to 56.8)

0.25

93.8

92.1

0.53

5.7

7.3

Race to ethnicity, % Mestizos/Amerindian* White Black

0.4

Current smoking, %

21.6 (17.9 to 25.8)

0.6 8.7 (6.4 to 11.8)

⬍0.001

Body height, cm

167 (167 to 168)

154 (154 to 155)

⬍0.001

Body weight, kg

75.2 (73.9 to 76.5)

64.8 (63.6 to 64.0)

⬍0.001

Waist circumference, cm

94.8 (93.8 to 95.8)

89.6 (88.4 to 90.8)

⬍0.001

Body mass index, kg/m2

26.8 (26.4 to 27.1)

27.4 (26.9 to 27.8)

0.03

Hypertension, %

29.6 (25.4 to 34.2)

37.1 (32.6 to 42.0)

0.02

5.3 (3.6 to 7.7)

5.8 (4.0 to 8.4)

0.73

Diabetes mellitus, %


Total cholesterol, mg/dL

199 (196 to 203)

206 (202 to 210)

0.008

LDL cholesterol, mg/dL

115 (112 to 118)

122 (118 to 125)

0.002

Triglycerides, mg/dL

191 (182 to 201)

168 (161 to 176)

⬍0.001

48 (47 to 49)

52 (51 to 53)

⬍0.001

HDL cholesterol, mg/dL ADMA, ␮mol/L

0.81 (0.79 to 0.84)

0.82 (0.79 to 0.86)

0.44

NMMA, ␮mol/L

0.16 (0.15 to 0.18)

0.18 (0.16 to 0.20)

0.01 0.16

L-Arginine,

␮mol/L

139.3 (131.6 to 146.9)

146.0 (136.9 to 155.2)

CRP, mg/L

2.48 (2.15 to 2.81)

2.81 (2.52 to 3.10)

0.28

Estimated GFR, mL/min

90.6 (87.7 to 63.4)

81.7 (79.1 to 84.3)

⬍0.001

cf-PWV, m/s

10.3 (9.9 to 10.7)

10.6 (10.1 to 11.0)

0.59

Aortic incident wave amplitude, mm Hg

24.8 (23.8 to 25.8)

23.2 (22.4 to 23.9)

0.008

9.3 (8.6 to 10.0)

12.9 (12.0 to 13.7)

⬍0.001

Aortic augmentation index, %

25.8 (24.5 to 27.0)

32.3 (31.2 to 33.4)

⬍0.001

Cardiac output, L/min

5.50 (5.38 to 5.62)

4.70 (4.63 to 4.85)

⬍0.001

Aortic augmented pressure, mm Hg

Cardiac index, L/min per m2

2.97 (2.92 to 3.02)

2.93 (2.86 to 2.99)

0.29

Systemic vascular resistance, dyne 䡠 s 䡠 cm⫺5

1185 (1149 to 1221)

1396 (1348 to 1444)

⬍0.001

Systemic vascular resistance index, dyne 䡠 s 䡠 m2 䡠 cm⫺5

2152 (2099 to 2205)

2217 (2150 to 2285)

0.13

95% CIs are shown in parentheses. GFR indicates glomerular filtration rate. *Subjects are mixed Amerindian and white.

pulmonary artery thermodilution.14,15 In turn, ICG-derived stroke volume allows for the computation of cardiac output and systemic vascular resistance. We performed ICG using a Bio-Z device (Cardiodynamics Inc). For the calculation of systemic vascular resistance, this ICG device used brachial mean arterial pressure measured with an automated oscillometric sphygmomanometer, which is integrated in the device. All of the measurements of cf-PWV, radial tonometry, and ICG procedures were performed between 8 and 11 AM after a resting period of 10 minutes in a quiet room and included prohibitions on smoking, meals, alcohol, and beverages containing caffeine before measurement.12

Statistical Analysis Continuous variables are presented as means, whereas proportions are presented as frequencies and percentages, with 95% CIs. Analyses presented here are unweighted. Linear regression was used to assess predictors of end-NOSI, cf-PWV, c-IMT, and hemodynamic variables. Variables were logarithmically transformed as appropriate to improve normality in regression models. Backward stepwise regression was performed to identify independent predictors of ADMA, NMMA, and L-arginine, with P⬍0.10 used as the cutoff for retaining variables the models. In contrast, because we wanted to assess whether ADMA, NMMA, and L-arginine predict subclinical

vascular disease and hemodynamic variables independent of all of the other risk factors, we forced all of the covariates of interest in these regression models. Tests were 2-tailed, and statistical significance was defined as ␣⬍0.05. SPSS version 13.0 for Windows and its complex samples module were used for statistical analyses.

Results General characteristics of study participants are shown in Table 1.

ADMA, NMMA, and L-Arginine Levels and Cardiovascular Risk Factors Table 2 shows regression models examining predictors of ADMA, NMMA, and L-arginine. For stepwise regression, terms in the initial models included age, gender, smoking, waist circumference, hypertension, diabetes mellitus, highdensity lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, CRP, and estimated creatinine clearance. LDL cholesterol and CRP were selected in stepwise regression as independent significant predictors of higher ADMA levels, whereas LDL cholesterol and gender were

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December 2008 Table 2. Cardiovascular Risk Factors as Predictors of ADMA, NMMA, and L-Arginine in Unadjusted and Stepwise Regression Models Models/Predictors

Estimate (␤)

95% CI

P

Predictors of ADMA, nmol/L Unadjusted Age*

15.81

3.58 to 28.04

0.01

Male gender

⫺19.57

⫺51.93 to 12.79

0.24

Current smoking

⫺15.48

⫺62.44 to 31.49

0.52

HDL cholesterol†

⫺9.19

⫺26.27 to 7.89

0.29

LDL cholesterol†

11.05

4.90 to 17.21

⬍0.001

Diabetes mellitus

55.62

⫺5.90 to 117.14

0.08

2.34

⫺31.67 to 36.36

49.74

12.71 to 86.76

0.009

⫺8.17

⫺14.44 to ⫺1.92

0.01

Age*

12.98

⫺1.47 to 27.42

0.08

LDL cholesterol†

11.44

0.46 to 1.83

0.001

(log) CRP

38.09

1.33 to 74.84

0.04

Hypertension (log) CRP Creatinine clearance†

0.89

Stepwise regression (multivariate analysis) Downloaded from http://hyper.ahajournals.org/ by guest on June 19, 2018

Predictors of (log) NMMA Unadjusted Age*

0.006

⫺0.008 to 0.002

Male gender

⫺0.06

Current smoking

⫺0.024

⫺0.076 to 0.028

HDL cholesterol†

⫺0.02

⫺0.04 to 0.01

LDL cholesterol† Diabetes mellitus Hypertension (log) CRP Creatinine clearance†

0.024

⫺0.09 to ⫺0.03

0.017 to 0.031

0.41 ⬍0.001 0.37 0.16 ⬍0.001

0.04

⫺0.03 to 0.11

0.27

⫺0.005

⫺0.05 to 0.03

0.81

⫺0.04 to 0.06

0.74

0.009 ⫺0.01

⫺0.016 to ⫺0.003

0.005

Stepwise regression (multivariate analysis) LDL cholesterol†

0.023

0.016 to 0.03

⬍0.001

⫺0.042 to 0.001

0.06

HDL cholesterol†

⫺0.02

Male gender

⫺0.055

⫺0.09 to ⫺0.02

Age*

⫺0.02

⫺0.029 to ⫺0.010

⬍0.001

Male gender

⫺0.049

⫺0.076 to ⫺0.022

⬍0.001

Current smoking

⫺0.007

⫺0.049 to 0.035

HDL cholesterol†

0.028

0.013 to 0.042

LDL cholesterol†

0.003

⫺0.008 to 0.002

0.23

Diabetes mellitus

⫺0.012

⫺0.063 to 0.039

0.63

Hypertension

⫺0.024

⫺0.054 to 0.005

0.10

(log) CRP

0.036

0.005 to 0.068

0.02

Creatinine clearance†

0.06

0.005 to 0.12

0.03

⫺0.024

⫺0.034 to ⫺0.013

⬍0.001

0.016 to 0.049

⬍0.001

0.002

Predictors of (log) L-arginine Unadjusted

0.74 ⬍0.001

Stepwise regression (multivariate analysis) Age* HDL cholesterol† Male gender (log) CRP

0.032 ⫺0.043 0.047

*Estimates are per 10-year increase. †Estimates are per 10-mg/dL increase or 10-mL/min increase.

⫺0.073 to ⫺0.013

0.006

0.017 to 0.078

0.002

Chirinos et al Table 3.


ADMA and NMMA as Predictors of c-IMT Models Including ADMA

Models Including (log) NMMA

Models/Predictors

Standardized Estimate

95% CI


P

Univariate analysis

0.15

0.01

0.12

0.02

Age

0.61

⬍0.001

0.62

⬍0.001

Male gender

0.03

0.58

0.04

0.39

Current smoking

0.05

0.07

0.05

0.06

HDL cholesterol

0.01

0.59

0.02

0.61

LDL cholesterol

0.15

⬍0.001

0.13

⬍0.001

Multivariate model

Diabetes mellitus

0.07

0.03

0.08

0.03

Hypertension

0.088

0.02

0.09

0.02


Waist circumference

0.04

0.21

0.06

0.14

ADMA or (log) NMMA

0.092

0.008

0.11

0.001

(log) CRP

0.004

0.88

0.007

0.81

Creatinine clearance

0.032

0.60

0.04

0.53

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Table 4 shows standardized estimates from regression models analyzing ADMA, NMMA, and L-arginine as predictors of cf-PWV, central pulse pressure, aortic incident wave amplitude, aortic augmented pressure, aortic augmentation index, pulse pressure amplification, total arterial compliance, systemic vascular resistance, and cardiac output. It should be noted that these indices represent different physiological hemodynamic parameters and are not simply redundant measures of vascular compliance. Except for a modest but significant independent relationship between NMMA and aortic augmentation index, ADMA and NMMA did not predict any of these variables. In contrast, L-arginine was an independent predictor of central pulse pressure, incident wave amplitude, augmented pressure, and total arterial compliance but not of augmentation index (Table 4). L-Arginine did not predict cardiac output or systemic vascular resistance, regardless of whether these were indexed for body surface area. These findings did not appreciably change when restricted only to subjects free of antihypertensive medication use.

Discussion independent predictors of NMMA. Age, gender, HDL cholesterol, and CRP were independent predictors of L-arginine.

ADMA, NMMA, and L-Arginine as Predictors of c-IMT As shown in Table 3, higher ADMA and NMMA predicted higher c-IMT in univariate analysis and after adjustment for age, gender, current smoking, HDL and LDL cholesterol, waist circumference, diabetes mellitus, hypertension, CRP, and creatinine clearance. Analysis of standardized estimates revealed that age was the strongest predictor of c-IMT, followed by LDL cholesterol. The value of the standardized estimates for ADMA and NMMA were comparable to or higher than that of hypertension and higher than those of diabetes mellitus and current smoking. In contrast, L-arginine was not a significant predictor of c-IMT in univariate or multivariate analyses (data not shown).

ADMA, NMMA, and L-Arginine as Predictors of Blood Pressure, cf-PWV, and Hemodynamic Parameters We analyzed the relationship among ADMA, NMMA, and L-arginine as predictors of brachial systolic and diastolic blood pressure treated as continuous variables in subjects free of antihypertensive medication use. After adjustment for age, gender, current smoking, HDL cholesterol, LDL cholesterol, waist circumference, diabetes mellitus, CRP, and creatinine clearance, neither NMMA (standardized ␤⫽⫺0.058; P⫽0.14) nor ADMA (standardized ␤⫽⫺0.063; P⫽0.06) were significant predictors of systolic blood pressure. In contrast, higher L-arginine levels independently predicted higher systolic blood pressure (standardized ␤⫽0.13; P⫽0.003). L-Arginine did not predict diastolic blood pressure (standardized ␤⫽0.002; P⫽0.96), nor did NMMA (standardized ␤⫽0.014; P⫽0.74) or ADMA (standardized ␤⫽⫺0.014; P⫽0.74).

We report on the relationship between end-NOSIs and cardiovascular risk factors, carotid atherosclerosis, large artery stiffness, and systemic hemodynamics in a large populationbased sample of adults. We found that age, LDL cholesterol, and CRP were independent predictors of higher ADMA levels. In contrast, LDL cholesterol and gender were independent predictors of higher NMMA, whereas age, gender, CRP, and HDL cholesterol levels were independent predictors of L-arginine levels. Importantly, ADMA and NMMA were significant predictors of higher c-IMT and remained significant predictors after adjustment for cardiovascular risk factors. In contrast, end-NOSIs were not associated with large artery stiffness, hypertension, or various hemodynamic indices, whereas L-arginine was associated with systolic hypertension and pulsatile hemodynamic abnormalities but not with determinants of mean arterial pressure. Our study confirms previous data regarding the association between c-IMT and ADMA and, to our knowledge, is the first study to examine the correlates of NMMA, to demonstrate an independent association between NMMA and c-IMT, and to assess the relationship between both end-NOSIs and large artery stiffness, as well as detailed hemodynamic parameters in the general population.

End-NOSIs and Cardiovascular Risk Factors We found ADMA and NMMA to be differentially associated with cardiovascular risk factors. Our observation of increasing levels of ADMA with aging are consistent with previous data.16 ADMA and NMMA correlated positively with LDL cholesterol, which is in line with animal studies.17,18 Interestingly, end-NOSIs did not correlate with smoking or diabetes mellitus. Data regarding associations with diabetes mellitus and smoking have been mixed from previous animal and human studies,17,19 –24 suggesting that these associations are affected by the selection and characteristics of the population studied.

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Table 4. ADMA, NMMA, and L-Arginine as Predictors of cf-PWV and Hemodynamic Parameters Univariate Analysis

Multivariate Analysis*


P Value

ADMA

0.07

0.05

0.008

(log) NMMA

0.07

0.07

0.04

0.23

⫺0.03

0.48

⫺0.02

0.54

0.93

⬍0.01

0.99

0.35

⫺0.01

0.001

0.98

0.09

0.03

0.44

⫺0.02

0.005

⫺0.06

Models/Predictors


P Value

(Log) carotid-femoral pulse wave velocity (m/s)

(log) L-arginine

0.82

(Log) Aortic pulse pressure, mm Hg ADMA (log) NMMA (log) L-arginine

0.004 ⫺0.04

0.70 0.002

Aortic incident wave amplitude, mm Hg ADMA (log) NMMA

⫺0.10

0.46 0.06

0.03

0.46

0.11

⬍0.001

ADMA

0.02

0.62

0.03

0.31

(log) NMMA

0.003

0.94

0.01

0.57

⫺0.001

0.98

0.07

0.003

ADMA

0.05

0.22

0.02

0.43

(log) NMMA

0.08

0.04

0.05

0.03

⫺0.05

0.23

0.02

0.33

ADMA

⫺0.06

0.13

⫺0.03

0.29

(log) NMMA

⫺0.07

0.08

⫺0.04

0.13

0.06

0.10

⫺0.01

0.63

ADMA

⫺0.07

0.15

⫺0.002

0.64

(log) NMMA

⫺0.04

0.37

⫺0.001

0.97

0.04

0.31

⫺0.08

0.03

ADMA

⫺0.06

0.17

⫺0.002

0.96

(log) NMMA

⫺0.02

0.56

0.01

0.78

0.04

0.34

⫺0.09

0.02 0.71

(log) L-arginine (Log) Aortic augmented pressure, mm Hg


(log) L-arginine Aortic augmentation index, %

(log) L-arginine (Log) Pulse pressure amplification, %

(log) L-arginine (Log) Total arterial compliance, mL/mm Hg

(log) L-arginine (Log) SV/CPP ratio

(log) L-arginine (Log) Systemic vascular resistance, dyne 䡠 s 䡠 m2 䡠 cm⫺5 ADMA (log) NMMA (log) L-arginine

0.03

0.39

⫺0.01.

⫺0.004

0.92

0.002

0.95

0.05

0.24

0.02

0.69 0.98

(Log) Systemic vascular resistance index, dyne 䡠 s 䡠 m2 䡠 cm⫺5 ADMA

0.05

0.17

0.001

⫺0.02

0.70

0.02

0.67

0.04

0.36

0.04

0.33

ADMA

⫺0.05

0.24

⫺0.03

0.34

(log) NMMA

⫺0.02

0.72

0.04

0.30

(log) L-arginine

⫺0.03

0.47

0.03

0.45 0.34

(log) NMMA (log) L-arginine Cardiac Output, L/min

Cardiac index, n L/min per m2 0.06

0.16

⫺0.04

(log) NMMA

⬍0.01

0.88

⫺0.05

0.25

(log) L-arginine

⬍0.01

0.91

0.02

0.63

ADMA

*Adjusted for age, gender, estimated creatinine clearance, body height, LDL-cholesterol, HDL-cholesterol, current smoking, diabetes mellitus, waist circumference, and C-reactive protein. For incident wave amplitude, models also included mean arterial pressure. For cf-PWV, aortic augmentation index, augmented pressure, central pulse pressure, and pulse pressure amplification, models also adjusted for mean arterial pressure and heart rate.

Chirinos et al


Carotid Atherosclerosis


Previous studies have reported increased ADMA levels in association with cardiovascular disease,25–27 cardiovascular risk factors,17,22,23,28 –30 endothelial dysfunction,31 and adverse cardiovascular outcomes in clinical populations.20,24,32–34 A recent community-based study reported an association between ADMA and c-IMT among individuals ⬎40 years of age,9 whereas a smaller study in younger individuals reported a negative correlation.10 The authors of the latter study suggested a possible protective effect of ADMA in early stages of atherosclerosis because of inhibition of inducible NOS, which is involved in inflammation and atherosclerosis. We examined a probabilistic population-based sample of unselected adults over a wide age range (20 to 80 years) and found that both ADMA and NMMA predict c-IMT independent of classic cardiovascular risk factors, CRP, and renal function. In multivariate models, ADMA and NMMA were third only to age and LDL cholesterol as predictors of c-IMT. c-IMT is an intermediate phenotype for early atherosclerosis, correlates with the presence of more advanced atherosclerosis (including coronary artery disease), and independently predicts the risk of cardiovascular events.35 Our results suggest that ADMA and NMMA are important markers of cardiovascular risk in the general population and are consistent with a role for asymmetrical arginine methylation in atherosclerosis.

Large Artery Stiffness, Hypertension, and Arterial Hemodynamics ADMA and NMMA were not independently associated with large artery stiffness or the presence of hypertension. In contrast, L-arginine was associated with increased peripheral systolic (but not diastolic) blood pressure. Because there is significant variability in the degree of pulse (and systolic) pressure amplification between the aorta and the brachial artery, which is strongly affected by wave reflections,12 we also evaluated central systolic and pulse pressure, as well as various parameters of pulsatile and steady arterial hemodynamics. L-Arginine was a significant independent predictor of various parameters of pulsatile arterial hemodynamics, including central pulse pressure, incident wave amplitude, augmented pressure, and total arterial compliance (Table 4), but not of cardiac output or resistive vascular load. Finally, except for a modest but significant relationship between NMMA and augmentation index, end-NOSI levels did not predict any of these hemodynamic variables. Our results demonstrate that circulating levels of endNOSI are not strongly associated with blood pressure or hemodynamic abnormalities. Previous data indicate that ADMA infusions cause vasoconstriction and increased peripheral vascular resistance.5,6 However, acute infusion of ADMA that led to a marked increase in circulating levels elevated mean arterial pressure only slightly.6 ADMA infusions were shown to increase the aortic augmentation index, a marker of arterial wave reflections.7 NOS inhibition has also been associated with decreased renal sodium excretion.36,37 However, mice that overexpress dimethylarginine dimethylaminohydrolase and have chronically low endogenous ADMA levels did not exhibit a significant difference in

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mean arterial pressure, cardiac output, and systemic vascular resistance but did demonstrate a significant (albeit modest) difference in systolic blood pressure.38 Collectively, these studies suggested prohypertensive effects of acute ADMA administration, with uncertainty about the association among endogenous inhibitors of NOS, blood pressure, and hemodynamic variables. Our results indicate that, in unselected human adults, end-NOSI levels are not associated with hypertension or hemodynamic abnormalities, suggesting that acute effects of NOS inhibition are not sustained after prolonged exposure to high-circulating levels of (endogenous) ADMA/NMMA. An intriguing finding was the association between L-arginine and abnormal pulsatile arterial hemodynamics (but not with the determinants of mean arterial pressure), which mediated an independent positive relationship between elevated L-arginine and systolic blood pressure. An association between L-arginine and hypertension has been suggested in 2 smaller previous studies.39,40 This apparently paradoxical association may be attributable to abnormalities in L-arginine transport via system y⫹, which may limit intracellular availability or L-arginine for NO synthesis.39,40 This transport system has been shown to be abnormal in hypertension.41 In addition, it is possible that abnormalities in the degradation of L-arginine underlie this association, because animal studies suggest that expression or activity of arginases may be altered in hypertension.41,42 It is possible that increased L-arginine leads to an increase in arginine metabolites, such as ornithine, with may have adverse vascular effects. This later explanation may also underlie the effect of L-arginine supplementation, which lead to increase plasma L-arginine but impaired vascular function in a recent clinical trial.43 However, L-arginine metabolism is complex, and multiple other mechanisms may underlie our observations. This should be the focus of further research.

Limitations Our study is limited by its cross-sectional design, which cannot prove a cause-effect relationship. We did not measure symmetrical dimethylarginine, an alternatively methylated arginine molecule that does not inhibit NOS. c-IMT measurements were not available in all of the subjects, and the study could not address any racial differences regarding the studied correlations.

Perspectives ADMA and NMMA are differentially associated with various classic cardiovascular risk factors and subclinical inflammation. However, both are independent predictors of subclinical atherosclerosis. In addition, despite the acute hemodynamic effects of exogenous NOS inhibitor administration, there is no association between levels of endogenous ADMA or NMMA and large artery stiffness, hypertension, or pulsatile or resistive hemodynamic abnormalities. Our findings are consistent with a role for asymmetrical arginine methylation in atherosclerosis but not in large artery stiffening, hypertension, or long-term hemodynamic regulation. In contrast, there is an independent positive association between L-arginine and systolic hypertension, as well as abnormalities in various indices of

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Hypertension

December 2008

pulsatile (but not resistive) arterial hemodynamics, which may reflect abnormal L-arginine transport (leading to decreased intracellular bioavailability for NOS) or abnormal catabolism of L-arginine in systolic hypertension. Additional studies are required to assess the prognostic value of end-NOSIs in the general population and to assess whether interventions to decrease these levels may be beneficial in subjects at risk for cardiovascular disease. Additional mechanistic studies are also needed to explore the association between L-arginine and abnormal pulsatile hemodynamics.

Sources of Funding This work was supported by the Santa Maria Research Institute. J.A.C. is supported by American Heart Association National Research Award 0885031N and National Institutes of Health grant RO1-HL080076-02.

Disclosures Downloaded from http://hyper.ahajournals.org/ by guest on June 19, 2018

J.M-L. received modest research support from Sonosite, Inc. J.M-L. and J.A.C. received modest research support from Cardiodynamics, Inc, and Atcor Medical, Inc. R.D. is an employee of and J.A.B. owns stock (more than $10 000 worth) and is an employee of Metametrix Clinical Laboratory, which provides commercial services for measurements of asymmetrical dimethylarginine and other biomarkers.

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Endogenous Nitric Oxide Synthase Inhibitors, Arterial Hemodynamics, and Subclinical Vascular Disease: The PREVENCION Study Julio A. Chirinos, Robert David, J. Alexander Bralley, Humberto Zea-Díaz, Edgar Muñoz-Atahualpa, Fernando Corrales-Medina, Carolina Cuba-Bustinza, Julio Chirinos-Pacheco and Josefina Medina-Lezama Downloaded from http://hyper.ahajournals.org/ by guest on June 19, 2018

Hypertension. 2008;52:1051-1059; originally published online October 13, 2008; doi: 10.1161/HYPERTENSIONAHA.108.120352 Hypertension is published by the American Heart Association, 7272 Greenville Avenue, Dallas, TX 75231 Copyright © 2008 American Heart Association, Inc. All rights reserved. Print ISSN: 0194-911X. Online ISSN: 1524-4563

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