Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2013 Oct 10.
Published in final edited form as: Clin Chem. 2009 Jun 18;55(8):1539–1545. doi: 10.1373/clinchem.2009.124263

Asymmetric Dimethylarginine Reference Intervals Determined with Liquid Chromatography–Tandem Mass Spectrometry: Results from the Framingham Offspring Cohort

Edzard Schwedhelm 1,*, Vanessa Xanthakis 2, Renke Maas 1,3, Lisa M Sullivan 2,4, Friedrich Schulze 1, Ulrich Riederer 5, Ralf A Benndorf 1, Rainer H Böger 1, Ramachandran S Vasan 4,6
PMCID: PMC3794429  NIHMSID: NIHMS494923  PMID: 19541865

Abstract

BACKGROUND

Accumulating evidence links higher circulating asymmetric dimethylarginine (ADMA) to greater risk of cardiovascular disease (CVD). Relatively small differences in ADMA concentrations between healthy individuals and those with disease underscore the need to formulate reference intervals that may aid risk stratification of individuals.

METHODS

We formulated reference intervals for plasma ADMA concentrations using a community-based reference sample from the Framingham Offspring Study consisting of 1126 nonsmoking individuals [mean (SD) age 56 (9) years; 60% women] who were free of clinical CVD, hypertension, diabetes, and obesity and who attended a routine examination at which ADMA was assayed. ADMA concentrations were determined using a validated tandem mass spectrometry–liquid chromatography assay.

RESULTS

In the study sample, the mean ADMA concentration was 0.52 (0.11) μmol/L, and the reference limits were 0.311 and 0.732 (2.5th and 97.5th percentile). The sex-specific reference limits were 0.310 and 0.745 in men and 0.313 and 0.721 μmol/L in women. In multivariable regression analysis, ADMA plasma concentrations were positively correlated with age and total plasma homocysteine (both P < 0.001).

CONCLUSIONS

Reference limits calculated for circulating ADMA in our large community-based healthy reference sample confirm the previous observation of a relatively narrow distribution of concentrations. This suggests a tight physiological control of ADMA plasma concentrations, presumably by dimethylarginine dimethylaminohydrolase (DDAH) metabolism of ADMA.

Increased plasma concentrations of the endogenous inhibitor of nitric oxide synthase (NOS)7 asymmetric dimethylarginine (ADMA) are associated with endothelial dysfunction and subclinical atherosclerosis (1–3), which are key precursors of overt cardiovascular disease (CVD) (4). Evidence for ADMA being causally related to CVD comes from both case-control (5) and prospective cohort (6 –9) studies. These associations of ADMA with CVD risk have been observed in community-dwelling individuals free of prior CVD (6, 7), as well as in people with preexisting overt CVD (8, 9).

It is worth noting that whereas the relative risk for CVD associated with the top tertile of ADMA relative to the lowest is 2.4 in the MONICA/KORA (Monitoring of Cardiovascular Disease/Cooperative Health Research in the Region of Augsburg) sample of 9796 apparently healthy men and women ages 25–74 years (7), the highest tertile included people with ADMA >0.85 μmol/L compared to the lowest tertile, which included people with ADMA <0.70 μmol/L. This exemplifies the narrowness of the distribution of plasma ADMA concentrations in selected populations. Therefore, formulation of reference limits for ADMA in the general population may facilitate the definition of increased ADMA concentrations.

The Framingham Heart Study is one of the largest population-based studies to identify risk predictors for cardiovascular morbidity and mortality. Within the Offspring Cohort of this study, we were able to show that ADMA is a risk predictor for total mortality (10). In this context, we now investigate the distribution of ADMA in a reference sample consisting of nonsmoking Framingham Offspring Cohort participants who were free of overt CVD, hypertension, diabetes, and obesity. These individuals underwent measurements of plasma ADMA using a validated liquid chromatography–tandem mass spectrometry (LC-MS/MS) assay (11). This LC-MS/MS– based assay was chosen because it has previously demonstrated high accuracy and precision (11, 12), factors that are a prerequisite for the determination of reliable reference limits. In addition, we evaluated the cross-sectional correlates of ADMA concentrations in this large community-based sample.

Materials and Methods

STUDY SAMPLE

The design and selection criteria of the original Framingham Heart Study have been described (13). Of the 3532 participants who attended the sixth examination cycle (1995 through 1998), we excluded 212 participants from the present investigation for the following reasons: 15 had a serum creatinine concentration >176 μmol/l (2.0 mg/dL), 79 had missing ADMA, and 118 had missing covariate data. From eligible participants, we excluded all nonhealthy individuals in a stepwise exclusion procedure (Fig. 1). After exclusion of 39 outliers [ADMA outliers were defined as values <Q1 − 1.5*IQR or >Q3 − 1.5*IQR (IQR, interquartile range), according to Solberg and Lahti (14)], 1126 participants made up the reference sample. The ADMA distribution of the reference population is depicted in Fig. 2. Alternatively, we used a more relaxed definition of outlier identification to generate a second expanded range reference population (ADMA outliers were defined as values <Q1 − 3*IQR or >Q3 + 3*IQR). This expanded range reference population included 1162 participants after exclusion of 3 outliers (see Supplemental Fig. 1, which accompanies the online version of this article at www.clinchem.org/content/vol55/issue8).

Fig. 1. Study design of The Framingham Heart Study, 6th examination cycle (1995–1998), offspring cohort.

Fig. 1

Open in a new tab

Nonhealthy participants were excluded from the reference population by a stepwise exclusion procedure. *Not eligible for the following reasons: serum creatinine concentration >176 mmol/L (n = 15), missing ADMA (n = 79), and missing covariate data (n = 118).

Fig. 2. Histogram of plasma ADMA with reference interval.

Fig. 2

Open in a new tab

ADMA was determined from EDTA plasma samples using LC-MS/MS and stable isotope dilution with [2H6]ADMA.

At the sixth examination cycle, all attendees underwent standardized measurements of blood pressure (BP), anthropometry, medical history, physical examination, and assessment of laboratory parameters (15, 16). Hypertension was defined as increased BP [systolic blood pressure (SBP) >140 mmHg or diastolic blood pressure (DBP) >90 mmHg] or use of antihypertensive medication. Obesity was defined as body mass index (BMI) ≥30 kg/m2. Preexisting CVD was defined as prior coronary heart disease (myocardial infarction, stable or unstable angina), cerebrovascular disease (stroke or transient ischemic attack), peripheral vascular disease (intermittent claudication), or heart failure. Diabetes was defined as fasting glucose ≥ 7 mmol/L (126 mg/dL) or antidiabetic medication. We used the Modification of Diet in Renal Disease (MDRD) equation to calculate an estimated glomerular filtration rate (eGFR): 186.3 × (serum creatinine)−1.154 × age−0.203 × (0.742 for women). The study protocol was approved by the Institutional Review Board of the Boston University Medical Center and the Ethics Committee of the Hamburg Board of Physicians. All participants provided written informed consent.

BLOOD SAMPLE COLLECTION AND ANALYSIS

At the sixth examination cycle, phlebotomy was performed (typically between 0800 and 0900) on fasting participants, who were supine for approximately 5–10 min. Blood was immediately centrifuged, and plasma/serum were separated and stored at −80 °C until assayed. Blood lipids were analyzed in the Framingham Heart Study laboratory with automated enzymatic assays. High-sensitivity C-reactive protein (hsCRP) and total homocysteine were measured as described (17, 18).

MEASUREMENT OF PLASMA ADMA CONCENTRATION

We performed mass spectrometric measurement of ADMA using a validated high-throughput LC-MS/MS assay that is commercially available (DLD Diagnostika) as described (11, 12). In brief, proteins were precipitated with methanol using 96-well 0.20-μm microfiltration plates precoated with 40 pmol [2H6]ADMA (internal standard). After centrifugation, the micro-filtrates were dried, and analytes were converted to their butyl ester derivatives. We performed subsequent analyses using a Chirobiotic T, 20×1.0 mm i.d., microbore guard column (Astec) connected to a Varian 1200L Triple Quadrupole MS (Varian) in the positive electrospray ionization (ESI+) mode. The sample run time was 1.6 min with intra- and interassay precision of 3.2% and 4.4%, respectively.

STATISTICAL ANALYSES

We used the SAS statistical program (SAS Institute) for statistical analyses. A 2-sided P value of <0.05 indicated statistical significance. Data are presented as mean (SD) or mean (SE) unless otherwise indicated.

We calculated reference limits according to the recommendations of the IFCC as described (19, 20). ADMA concentrations were normally distributed in our sample (assessed by histograms and normal probability plots), and we analyzed ADMA as a continuous variable (without transformation) and as categorical variable (quartiles). We constructed multivariable linear regression models with stepwise forward selection (significance criterion for entry into the model, P < 0.1) of variables using the following candidate covariates: age, sex, BMI, SBP, DBP, total/HDL cholesterol ratio, triglycerides, alcohol consumption, hsCRP, eGFR, and total homocysteine.

Results

The characteristics of our reference sample are displayed in Table 1. The mean age of the participants was 56 years; 60% were women. Women had lower values for DBP, total/HDL cholesterol ratio, total homocysteine, fasting glucose, SBP, BMI (all P < 0.001), LDL cholesterol (P < 0.01), and triglycerides (P < 0.01). The mean ADMA concentration in the overall reference sample was 0.52 (0.11) μmol/L [median (IQR) 0.51 (0.45– 0.59), reference limits 0.311 and 0.732 (2.5th and 97.5th percentile, and 95% CI 0.302– 0.319 and 0.724 – 0.741, respectively]. Plasma ADMA concentrations were similar in men [0.53 (0.11) μmol/L, median (IQR) 0.51 (0.45– 0.60) μmol/L] and women [0.52 (0.10) μmol/L, median (IQR) 0.50 (0.45– 0.58) μmol/L]. The sex-specific 2.5th and 97.5th percentile reference limits were 0.310 and 0.745 in men and 0.313 and 0.721 μmol/L in women. The histogram of the ADMA distribution in the reference sample is depicted in Fig. 2. In the subgroup of women before menopause [mean age 47 (5) years], ADMA was 0.49 (0.08) μmol/L compared with postmenopausal women, 0.53 (0.11) μmol/L [mean age 61 (8) years, P < 0.001]. A correlation between age and ADMA was found in women (unadjusted Pearson r = 0.14, P < 0.001) as well as in men (r = 0.15, P = 0.0017) (Fig. 3). Also, a correlation between ADMA and homocysteine existed in the reference sample (unadjusted Pearson r = 0.12, P < 0.001) (Fig. 4).

Table 1.

Clinical characteristics of the reference sample.a

Women Men
n 669 455
Age, years 56 (9) 56 (9)
BMI, kg/m2 24.4 (2.8) 26.2 (2.3)
SBP, mmHg 116 (12) 120 (10)
DBP, mmHg 71 (8) 74 (7)
Fasting glucose, mmol/L 5.0 (0.44) 5.4 (0.44)
LDL cholesterol, mmol/L 3.18 (0.93) 3.36 (0.85)
Total/HDL cholesterol ratio 3.52 (1.12) 4.53 (1.31)
Triglycerides, mmol/L 1.20 (0.64) 1.31 (0.71)
eGFR, mL/min 88 (23) 89 (28)
hsCRP, mg/L 1.30 (0.59–3.2) 1.06 (0.59–2.4)
Total homocysteine, μmol/L 8.27 (2.54) 9.95 (3.41)
Alcohol consumption, drinks per week 1.48 (2.24) 3.28 (3.98)
Open in a new tab
a

Data are mean (SD) or median (Q3–Q1). eGFR was calculated using the MDRD formula.

Fig. 3. Association between age and ADMA in men and women.

Fig. 3

Open in a new tab

Data represent mean (SE). The unadjusted relationship between age and ADMA was significant for both men and women (Pearson r = 0.15 and r = 0.14 in men and women, respectively; P < 0.002 for both).

Fig. 4. Association between quartiles (Q) of plasma ADMA and total homocysteine.

Fig. 4

Open in a new tab

Data represent mean (SE). The unadjusted relationship between ADMA and homocysteine was significant for pooled sex (Pearson r = 0.12, P < 0.001).

The results of the multivariable regression model are shown in Table 2. We included all candidate variables in a stepwise selection procedure (cutoff for model entry P < 0.1) and created a final model. Data for men and women were combined, since ADMA concentrations were similar. In the final regression model, age, total homocysteine, and eGFR were positively associated with ADMA, whereas DBP was inversely related to ADMA. Sex, alcohol intake, SBP, blood lipids, BMI, and hsCRP were not associated with plasma ADMA concentration in our sample. We also calculated stepwise selection and regression procedures forcing sex into the model. These models produced the same set of significant variables (age, homocysteine, eGFR, and DBP) for the final model and also a very similar magnitude of each β-coefficient and P value (data not shown). Thus, neither stepwise selection nor inclusion of sex had an impact on the multivariable regression procedure output.

Table 2.

Multivariable regression of ADMA plasma concentrations in the reference sample.a

Variable β (SE) P
Age, per 1 year increase 0.0017 (0.0003) <0.001
Homocysteine, per 1 μmol/L increase 0.0038 (0.0010) <0.001
GFR, per 1 mL/min increase 0.0003 (0.0001) 0.017
DBP, per 1 mmHg increase −0.0008 (0.0004) 0.036
Open in a new tab
a

Candidate variables that were considered for model entry were age, sex, BMI, SBP, DBP, total/HDL cholesterol ratio, alcohol consumption, triglycerides, GFR, homocysteine, and CRP. All regression coefficients (β estimates) represent the estimated mean change in ADMA (μmol/L) per 1-unit increase in the corresponding covariate.

Discussion

Experimental and clinical data suggest that increased ADMA concentrations are associated with greater CVD risk (5–9). For individual risk stratification, it is a prerequisite to define reliable reference intervals (21). In the present analysis of a large community-based reference sample, we defined the 95% ADMA reference interval from 0.311– 0.732 μmol/L (2.5th and 97.5th percentiles) in a reference sample without CVD, diabetes, obesity, smoking, or hypertension. The relatively narrow distribution of ADMA concentration has been observed in other cohorts (22) and suggests a tight physiological control of ADMA in vivo, presumably by dimethylarginine dimethylaminohydrolase (DDAH) metabolism of ADMA (23–25). ADMA plasma concentrations increase by 0.0017 μmol/L for each year increase in age (β, Table 2), after adjusting for other variables in the model. This is consistent with a similar increase reported in a smaller sample of men (26). This association between age and ADMA was evident in women and men (Fig. 3, unadjusted relations). In line with this finding, premenopausal women had lower ADMA concentrations than postmenopausal women. This confirms previous reports (27, 28) and may reflect the influence of estrogens on ADMA concentrations (29, 30). Estrogens enhance DDAH gene expression by promoter activation (31). When menopausal status is considered as a candidate variable in the stepwise procedure, however, this variable does not meet the P < 0.1 entry selection criterion. Thus, the most likely explanation for the observed difference in ADMA in pre- and postmenopausal women is the different age in these 2 subgroups. This observation is substantiated by previous data from a smaller cohort where younger women (mean age 31 years) had as much as 23% lower ADMA plasma concentrations compared with older women (mean age 62 years) (27).

The finding of a positive association between plasma ADMA and total homocysteine is consistent with recent clinical and experimental studies (26, 32, 33). In our analyses, we observed an increase of ADMA plasma concentrations of 0.0038 μmol/L per 1 μmol/L increase of homocysteine (Table 2). Homocysteine is known to interact with DDAH activity by modification of enzyme redox status and protein stability (34). Despite this biochemical interaction, clinical studies of homocysteine lowering have noted only minor effects on plasma ADMA concentrations (35). Nevertheless, both substances (homocysteine and ADMA) were found to be associated with intimal-medial thickness in other cohorts (36 –38). This suggests that both biomolecules act hand in hand in impairing endothelial function.

Besides age and total homocysteine, ADMA was influenced by eGFR and DBP in our cohort of healthy individuals (Table 2). It is well known that ADMA is increased in patients with renal function impairment, as well as in patients with increased blood pressure (39 – 41). In contrast to previous reports from various patient populations, renal function was neither impaired nor was blood pressure increased in our reference sample. The weak positive association between ADMA plasma concentrations and eGFR may thus point to a physiological regulation mechanism of renal filtration, or it may be a chance finding due to the comparatively narrow range of renal function levels included in our study. In line with this interpretation, the positive association observed between ADMA and eGFR is further weakened for the expanded-range reference population (online Supplemental Tables 1 and 2). Under pathophysiologic conditions, however, impaired renal excretory function or impaired renal DDAH activity may dominate and explain the inverse associations between ADMA and eGFR found in most previous studies.

Also, the unexpected weak negative association between ADMA and DBP in our healthy reference cohort was further weakened when the relation was examined in the expanded-range reference population (online Supplemental Table 1) with the stepwise multivariable regression model (online Supplemental Table 2). Again, under pathophysiological conditions, impaired DDAH activity may become predominant. In consequence, ADMA degradation is impaired, ADMA accumulates, and blood pressure increases. This association is clearly evidenced by gene polymorphism studies and genetically modified animal models (23–25, 42).

STRENGTHS AND LIMITATIONS

The large community-based reference sample and the quantification of ADMA plasma concentrations by a validated LC-MS/MS method are strengths of our investigation. We acknowledge several limitations, however. We evaluated a community-based reference sample of white, middle-aged individuals of European descent. Caution must be exercised in extrapolating these results to other populations of different ethnicity or with a different age range. Also, from our epidemiological data, no functional conclusions of the observed associations can be made.

Conclusions

We have formulated reference limits for plasma ADMA concentrations using a large community-based reference sample. The relatively narrow distribution of ADMA concentration suggests a tight physiological control of ADMA plasma concentrations, presumably by DDAH metabolism of ADMA.

Supplementary Material

Figure 1
Legend

Acknowledgments

Research Funding: This work was supported through NIH/National Heart, Lung, and Blood Institute contracts N01-HC-25195, N01HV28178, and 2K24HL04334 (R.S. Vasan) and by the Deutsche Forschungsgemeinschaft grant Bo 1431/4-1 (R.H. Böger).

Role of Sponsor: The funding organizations played no role in the design of study, choice of enrolled patients, review and interpretation of data, or preparation or approval of manuscript.

Footnotes

7

Nonstandard abbreviations: NOS, nitric oxide synthase; ADMA, asymmetric dimethylarginine; CVD, cardiovascular disease; MONICA/KORA, Monitoring of Cardiovascular Disease/Cooperative Health Research in the Region of Augsburg; LC-MS/MS, liquid chromatography–tandem mass spectrometry; IQR, interquartile range; BP, blood pressure; SBP, systolic BP; DBP, diastolic BP; BMI, body mass index; MDRD, Modification of Diet in Renal Disease; eGFR, estimated glomerular filtration rate; hsCRP, high-sensitivity C-reactive protein; DDAH, dimethylarginine dimethylaminohydrolase.

Author Contributions: All authors confirmed they have contributed to the intellectual content of this paper and have met the following 3 requirements: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; and (c) final approval of the published article.

Authors’ Disclosures of Potential Conflicts of Interest: Upon manuscript submission, all authors completed the Disclosures of Potential Conflict of Interest form. Potential conflicts of interest:

Employment or Leadership: None declared.

Consultant or Advisory Role: None declared.

Stock Ownership: None declared.

Honoraria: None declared.

Expert Testimony: None declared.

Other remuneration: E. Schwedhelm, R. Maas, and R.H. Böger are named as inventors on patents related to ADMA assays and receive royalties from these.

References

  • 1.Böger RH. Asymmetric dimethylarginine (ADMA): a novel risk marker in cardiovascular medicine and beyond. Ann Med. 2006;38:126–36. doi: 10.1080/07853890500472151. [DOI] [PubMed] [Google Scholar]
  • 2.Böger RH, Bode-Böger SM, Szuba A, Tsao PS, Chan JR, Tangphao O, et al. Asymmetric dimethylarginine (ADMA): a novel risk factor for endothelial dysfunction: its role in hypercholesterolemia. Circulation. 1998;98:1842–7. doi: 10.1161/01.cir.98.18.1842. [DOI] [PubMed] [Google Scholar]
  • 3.Juonala M, Viikari JS, Alfthan G, Marniemi J, Kähönen M, Taittonen L, et al. Brachial artery flow-mediated dilation and asymmetrical dimethylarginine in the Cardiovascular Risk in Young Finns study. Circulation. 2007;116:1367–73. doi: 10.1161/CIRCULATIONAHA.107.690016. [DOI] [PubMed] [Google Scholar]
  • 4.Hansson GK. Inflammation, atherosclerosis, and coronary artery disease. N Engl J Med. 2005:1685–95. doi: 10.1056/NEJMra043430. [DOI] [PubMed] [Google Scholar]
  • 5.Schulze F, Lenzen H, Hanefeld C, Bartling A, Osterziel KJ, Goudeva L, et al. Asymmetric dimethylarginine is an independent risk factor for coronary heart disease: results from the multi-center Coronary Artery Risk Determination investigating the Influence of ADMA Concentration (CARDIAC) study. Am Heart J. 2006;152:493, e1–8. doi: 10.1016/j.ahj.2006.06.005. [DOI] [PubMed] [Google Scholar]
  • 6.Valkonen VP, Päivä H, Salonen JT, Lakka TA, Lehtimäki T, Laakso J, Laaksonen R. Risk of acute coronary events and serum concentration of asymmetrical dimethylarginine. Lancet. 200;358:2127–8. doi: 10.1016/S0140-6736(01)07184-7. [DOI] [PubMed] [Google Scholar]
  • 7.Maas R, Schulze F, Baumert J, Löwel H, Hamraz K, Schwedhelm E, et al. Asymmetric dimethylarginine, smoking, and risk of coronary heart disease in apparently healthy men: prospective analysis from the population-based Monitoring of Trends and Determinants in Cardiovascular Disease/Ko-operative Gesundheitsforschung in der Region Augsburg study and experimental data. Clin Chem. 2007;53:693–701. doi: 10.1373/clinchem.2006.081893. [DOI] [PubMed] [Google Scholar]
  • 8.Schnabel R, Blankenberg S, Lubos E, Lackner KJ, Rupprecht HJ, Espinola-Klein C, et al. Asymmetric dimethylarginine and the risk of cardiovascular events and death in patients with coronary artery disease: results from the AtheroGene Study. Circ Res. 2005:e53–9. doi: 10.1161/01.RES.0000181286.44222.61. [DOI] [PubMed] [Google Scholar]
  • 9.Meinitzer A, Seelhorst U, Wellnitz B, Halwachs-Baumann G, Boehm BO, Winkelmann BR, März W. Asymmetrical dimethylarginine independently predicts total and cardiovascular mortality in individuals with angiographic coronary artery disease (the Ludwigshafen Risk and Cardiovascular Health study) Clin Chem. 2007;53:273–83. doi: 10.1373/clinchem.2006.076711. [DOI] [PubMed] [Google Scholar]
  • 10.Böger RH, Sullivan LM, Schwedhelm E, Wang TJ, Maas R, Benjamin EJ, et al. Plasma asymmetric dimethylarginine and incidence of cardiovascular disease and death in the community. Circulation. 2009;119:1592–600. doi: 10.1161/CIRCULATIONAHA.108.838268. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Schwedhelm E, Tan-Andresen J, Maas R, Riederer U, Schulze F, Böger RH. Liquid chromatography-tandem mass spectrometry method for the analysis of asymmetric dimethylarginine in human plasma. Clin Chem. 2005;51:1268–71. doi: 10.1373/clinchem.2004.046037. [DOI] [PubMed] [Google Scholar]
  • 12.Schwedhelm E, Maas R, Tan-Andresen J, Schulze F, Riederer U, Böger RH. High-throughput liquid chromatographic-tandem mass spectrometric determination of arginine and dimethylated arginine derivatives in human and mouse plasma. J Chromatogr B Analyt Technol Biomed Life Sci. 2007;851:211–9. doi: 10.1016/j.jchromb.2006.11.052. [DOI] [PubMed] [Google Scholar]
  • 13.Dawber TR, Kannel WB, Revotskie N, Stokes J, III, Kagan A, Gordon T. Some factors associated with the development of coronary heart disease: six years’ follow-up experience in the Framingham study. Am J Public Health Nations Health. 1959;49:1349–56. doi: 10.2105/ajph.49.10.1349. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Solberg HE, Lahti A. Detection of outliers in reference distributions: performance of Horn’s algorithm. Clin Chem. 2005;51:2326–32. doi: 10.1373/clinchem.2005.058339. [DOI] [PubMed] [Google Scholar]
  • 15.Vasan RS, Benjamin EJ, Larson MG, Leip EP, Wang TJ, Wilson PW, Levy D. Plasma natriuretic peptides for community screening for left ventricular hypertrophy and systolic dysfunction: the Framingham Heart Study. JAMA. 2002;288:1252–9. doi: 10.1001/jama.288.10.1252. [DOI] [PubMed] [Google Scholar]
  • 16.Kannel WB, Wolf PA, Garrison RJ, editors. Some risk factors related to the annual incidence of cardiovascular disease and death in pooled repeated biennial measurements: Framingham Heart Study, 30-year follow-up. Bethesda, MD: National Heart, Lung, and Blood Institute; Feb, 1987. The Framingham Study: an epidemiological investigation of cardiovascular disease. Section 34. (NIH publ. no. 87–2703) [Google Scholar]
  • 17.Vasan RS, Sullivan LM, Roubenoff R, Dinarello CA, Harris T, Benjamin EJ, et al. Framingham Heart Study. Inflammatory markers and risk of heart failure in elderly subjects without prior myocardial infarction: the Framingham Heart Study. Circulation. 2003;107:1486–91. doi: 10.1161/01.cir.0000057810.48709.f6. [DOI] [PubMed] [Google Scholar]
  • 18.Vasan RS, Beiser A, D’Agostino RB, Levy D, Selhub J, Jacques PF, et al. Plasma homocysteine and risk for congestive heart failure in adults without prior myocardial infarction. JAMA. 2003;289:1251–7. doi: 10.1001/jama.289.10.1251. [DOI] [PubMed] [Google Scholar]
  • 19.Scientific Committee, Clinical Section, Expert Panel on Theory of Reference Values (EPTRV) and International Committee for Standardization in Haematology (ICSH) Standing Committee on Reference Values. Approved recommendation (1987) on the theory of reference values. Part 5. Statistical treatment of collected reference values. Determination of reference limits. Clin Chim Acta. 1987;170:S13–32. [Google Scholar]
  • 20.Fallang A, Larsen S, Horsberg TE. Upper susceptibility threshold limits with confidence intervals: a method to identify normal and abnormal population values for laboratory toxicological parameters, based on acetylcholinesterase activities in sea lice. Pest Manag Sci. 2006;62:208–13. doi: 10.1002/ps.1145. [DOI] [PubMed] [Google Scholar]
  • 21.Horn PS, Pesce AJ, Copeland BE. A robust approach to reference interval estimation and evaluation. Clin Chem. 1998;44:622–31. [PubMed] [Google Scholar]
  • 22.Teerlink T. HPLC analysis of ADMA and other methylated L-arginine analogs in biological fluids. J Chromatogr B Analyt Technol Biomed Life Sci. 2007;851:21–9. doi: 10.1016/j.jchromb.2006.07.024. [DOI] [PubMed] [Google Scholar]
  • 23.Dayoub H, Achan V, Adimoolam S, Jacobi J, Stuehlinger MC, Wang BY, et al. Dimethylarginine dimethylaminohydrolase regulates nitric oxide synthesis: genetic and physiological evidence. Circulation. 2003;108:3042–7. doi: 10.1161/01.CIR.0000101924.04515.2E. [DOI] [PubMed] [Google Scholar]
  • 24.Leiper J, Nandi M, Torondel B, Murray-Rust J, Malaki M, O’Hara B, et al. Disruption of methyl-arginine metabolism impairs vascular homeostasis. Nat Med. 2007;13:198–203. doi: 10.1038/nm1543. [DOI] [PubMed] [Google Scholar]
  • 25.Palm F, Onozato ML, Luo Z, Wilcox CS. Dimethyl-arginine dimethylaminohydrolase (DDAH): expression, regulation, and function in the cardiovascular and renal systems. Am J Physiol Heart Circ Physiol. 2007;293:H3227–45. doi: 10.1152/ajpheart.00998.2007. [DOI] [PubMed] [Google Scholar]
  • 26.Meinitzer A, Puchinger M, Winklhofer-Roob BM, Rock E, Ribalta J, Roob JM, et al. Reference values for plasma concentrations of asymmetrical dimethylarginine (ADMA) and other arginine metabolites in men after validation of a chromatographic method. Clin Chim Acta. 2007;384:141–8. doi: 10.1016/j.cca.2007.07.006. [DOI] [PubMed] [Google Scholar]
  • 27.Schulze F, Maas R, Freese R, Schwedhelm E, Silberhorn E, Böger RH. Determination of a reference value for N(G), N(G)-dimethyl-L-arginine in 500 subjects. Eur J Clin Invest. 2005;35:622–6. doi: 10.1111/j.1365-2362.2005.01561.x. [DOI] [PubMed] [Google Scholar]
  • 28.Hov GG, Sagen E, Bigonah A, Asberg A. Health-associated reference values for arginine, asymmetric dimethylarginine (ADMA) and symmetric dimethylarginine (SDMA) measured with high-performance liquid chromatography. Scand J Clin Lab Invest. 2007;67:868–76. doi: 10.1080/00365510701429836. [DOI] [PubMed] [Google Scholar]
  • 29.Teerlink T, Neele SJ, de Jong S, Netelenbos JC, Stehouwer CD. Oestrogen replacement therapy lowers plasma levels of asymmetrical dimethylarginine in healthy postmenopausal women. Clin Sci (Lond) 2003;105:67–71. doi: 10.1042/CS20020309. [DOI] [PubMed] [Google Scholar]
  • 30.Post MS, Verhoeven MO, van der Mooren MJ, Kenemans P, Stehouwer CD, Teerlink T. Effect of hormone replacement therapy on plasma levels of the cardiovascular risk factor asymmetric dimethylarginine: a randomized, placebo-controlled 12-week study in healthy early post-menopausal women. J Clin Endocrinol Metab. 2003;88:4221–6. doi: 10.1210/jc.2003-030584. [DOI] [PubMed] [Google Scholar]
  • 31.Holden DP, Cartwright JE, Nussey SS, Whitley GS. Estrogen stimulates dimethylarginine dimethylaminohydrolase activity and the metabolism of asymmetric dimethylarginine. Circulation. 2003;108:1575–80. doi: 10.1161/01.CIR.0000091083.61609.DF. [DOI] [PubMed] [Google Scholar]
  • 32.Wang J, Sim AS, Wang XL, Salonikas C, Naidoo D, Wilcken DE. Relations between plasma asymmetric dimethylarginine (ADMA) and risk factors for coronary disease. Atherosclerosis. 2006;184:383–8. doi: 10.1016/j.atherosclerosis.2005.05.002. [DOI] [PubMed] [Google Scholar]
  • 33.Stühlinger MC, Oka RK, Graf EE, Schmölzer I, Upson BM, Kapoor O, et al. Endothelial dysfunction induced by hyperhomocyst(e)inemia: role of asymmetric dimethylarginine. Circulation. 2003;108:933–8. doi: 10.1161/01.CIR.0000085067.55901.89. [DOI] [PubMed] [Google Scholar]
  • 34.Stühlinger MC, Tsao PS, Her JH, Kimoto M, Balint RF, Cooke JP. Homocysteine impairs the nitric oxide synthase pathway: role of asymmetric dimethylarginine. Circulation. 2002;104:2569–75. doi: 10.1161/hc4601.098514. [DOI] [PubMed] [Google Scholar]
  • 35.Schmitt B, Wolters M, Kressel G, Hülsmann O, Ströhle A, Kühn-Velten WN, et al. Effects of combined supplementation with B vitamins and antioxidants on plasma levels of asymmetric dimethylarginine (ADMA) in subjects with elevated risk for cardiovascular disease. Atherosclerosis. 2007;193:168–76. doi: 10.1016/j.atherosclerosis.2006.06.007. [DOI] [PubMed] [Google Scholar]
  • 36.Kelemen LE, Anand SS, Hegele RA, Stampfer MJ, Rosner B, Willett WC, et al. Associations of plasma homocysteine and the methylenetetrahydrofolate reductase C677T polymorphism with carotid intima media thickness among South Asian, Chinese and European Canadians. Atherosclerosis. 2004;176:361–70. doi: 10.1016/j.atherosclerosis.2004.06.003. [DOI] [PubMed] [Google Scholar]
  • 37.Furuki K, Adachi H, Matsuoka H, Enomoto M, Satoh A, Hino A, et al. Plasma levels of asymmetric dimethylarginine (ADMA) are related to intima-media thickness of the carotid artery: an epidemiological study. Atherosclerosis. 2007;191:206–10. doi: 10.1016/j.atherosclerosis.2006.03.022. [DOI] [PubMed] [Google Scholar]
  • 38.Nanayakkara PW, Teerlink T, Stehouwer CD, Allajar D, Spijkerman A, Schalkwijk C, et al. Plasma asymmetric dimethylarginine (ADMA) concentration is independently associated with carotid intima-media thickness and plasma soluble vascular cell adhesion molecule-1 (sVCAM-1) concentration in patients with mild-to-moderate renal failure. Kidney Int. 2005;68:2230–6. doi: 10.1111/j.1523-1755.2005.00680.x. [DOI] [PubMed] [Google Scholar]
  • 39.Zoccali C, Bode-Böger S, Mallamaci F, Benedetto F, Tripepi G, Malatino L, et al. Plasma concentration of asymmetrical dimethylarginine and mortality in patients with end-stage renal disease: a prospective study. Lancet. 2001;358:2113–7. doi: 10.1016/s0140-6736(01)07217-8. [DOI] [PubMed] [Google Scholar]
  • 40.Kielstein JT, Böger RH, Bode-Böger SM, Frölich JC, Haller H, Ritz E, Fliser D. Marked increase of asymmetric dimethylarginine in patients with incipient primary chronic renal disease. J Am Soc Nephrol. 2002;13:170–6. doi: 10.1681/ASN.V131170. [DOI] [PubMed] [Google Scholar]
  • 41.Perticone F, Sciacqua A, Maio R, Perticone M, Maas R, Boger RH, et al. Asymmetric dimethylarginine, L-arginine, and endothelial dysfunction in essential hypertension. J Am Coll Cardiol. 2005;46:518–23. doi: 10.1016/j.jacc.2005.04.040. [DOI] [PubMed] [Google Scholar]
  • 42.Valkonen VP, Tuomainen TP, Laaksonen R. DDAH gene and cardiovascular risk. Vasc Med. 2005;10 (Suppl 1):S45–8. doi: 10.1191/1358863x05vm600oa. [DOI] [PubMed] [Google Scholar]

Associated Data

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

Supplementary Materials

Figure 1
NIHMS494923-supplement-Figure_1.ppt (106.5KB, ppt)
Legend
NIHMS494923-supplement-Legend.doc (40.5KB, doc)

RESOURCES