The Relationship between ADMA and Anthropometric Indicators,

Glucose, Lipid, and Inflammatory Parameters in Obese People

M. Aron Pase

, Dharma Lindarto

*, Brama Ihsan Sazli

Department of Internal Medicine, Faculty of Medicine, Universitas Sumatera Utara,

H. Adam Malik Hospital, Jalan Bunga Lau No 17, Medan 20136, Indonesia

Keywords: Asymmetrical dimethylarginine, Obesity, Cardiovascular Risk Factor.

Abstract: Asymmetric dimethylarginine (ADMA) is an endogenous inhibitor of nitric oxide production and involved

in various pathological processes, especially processes involving cardiovascular risk. The purpose of this

study was to analyze the correlation between ADMA and anthropometric, glucose, lipid, and inflammatory

parameters. The study was a cross-sectional study of 45 obese subjects at H. Adam Malik Hospital. Blood

tests were carried out after 8-10 hours of aging against cardiovascular risk parameters: anthropometry (body

weight, BMI, and WC), glucose (FPS, PPS, HbA1C, Fasting Insulin, and HOMA-IR), lipid (LDL-C, HDL-

C, TG, and sd-LDL), and inflammation (ApoB and hs-CRP) parameters. Results: Of the 45 subjects, the

average age was 41.69 ± 5.69 years old, and the average BMI was 33.09 ± 5.05 (Obesity I). ADMA was

also found to be correlated significantly with FPG, HBA1c, and TG parameters [r=-0.506, p=0.001; r=-

0.334, p=0.013, dan r = -0.315. p=0.017, respectively]. In obesity, ADMA correlated significantly with

cardiovascular risk parameters: FPG, HbA1C, and TG.

1 INTRODUCTION

Asymmetrical dimethylarginine (ADMA) is an

endogenous inhibitor of nitric oxide synthase (NO)

which appears as a risk marker for various disease

conditions including end-stage kidney failure

(Zoccali et al., 2001), liver failure (Tsikas et al.,

2003), heart failure (Kielsten et al., 2003), diabetes

(Lin et al., 2002), pre-eclampsia (Sayyidou et

al.,2003), and atherosclerotic (Boger et al., 1997). It

has been observed that ADMA is positively

correlated with NO serum concentration and body

mass index (BMI) (Borgeraas et al., 2016).

Inflammation measured by C-reactive protein

(CRP) is another strong risk marker for predicting

cardiovascular death and complications including

inflammatory diseases (Goodson et al., 2005), sepsis

(Lobo et al., 2005), lung disease (Man et al., 2006),

and coronary heart disease (Blake & Ridker, 2002).

The interaction between ADMA and CRP is a

problem of cardiovascular disease because both

ADMA and CRP factors are involved in endothelial

dysfunction in humans (Baylis, 2006).

Obesity increases the risk of morbidity due to

hypertension, dyslipidemia, T2DM, coronary heart

disease (CHD), stroke, gallbladder disease,

osteoarthritis, sleep apnea, respiratory disorders, and

certain types of cancer. Obesity is also associated

with an increased risk of all causes of death due to

cardiovascular disease (CVD) (National Institute of

Health, 1998). Obesity is caused by abnormal or

excessive fat accumulation due to metabolic

disorders (Colak et al., 2010). According to previous

research, the main determinant of obesity is insulin

resistance which is associated with endothelial

dysfunction (El Assar et al., 2016). Obesity can

trigger the activity of tumor necrosis factor in α

proinflammatory cytokine, which then inhibits the

insulin receptor substrate 1 in the insulin signaling

pathway (Peraldi et al., 1996).

Based on several studies, ADMA has a positive

correlation with cardiovascular risk factors in

prediabetes (Eliana et al., 2011), angina pectoris

(Borgeraas et al., 2016), IGT, and obesity (Huang et

al., 2018). Therefore, the aim of this study was to

investigate the correlation between ADMA and

anthropometric, glucose, lipid, and inflammatory

parameters in obesity

Pase, M., Lindarto, D. and Sazli, B.

The Relationship between ADMA and Anthropometric Indicators, Glucose, Lipid, and Inﬂammatory Parameters in Obese People.

DOI: 10.5220/0009848500240029

In Proceedings of the 2nd International Conference on Tropical Medicine and Infectious Disease (ICTROMI 2019), pages 24-29

ISBN: 978-989-758-469-5

2 MATERIALS AND METHODS

The study design was a cross-sectional study by

recruiting 45 nurses (female and male) at H. Adam

Malik Hospital aged 30-55 years who met the

criteria for obesity (WHO, 2000) and signed an

informed consent form. Subjects were excluded

from the study if they had secondary illness or

obesity that could affect markers of metabolic

disorders, lipid profiles, and inflammations such as

pregnancy or lactation, acute infection, anemia,

menopause, diabetes or hypertension, cardiovascular

disease, chronic kidney disease or liver dysfunction,

smoking, consuming corticosteroids, estrogen, beta-

adrenergic receptor agonists, nitrates, or other

vasodilator agents (Kelm et al., 2002). Venous blood

samples were collected from the subjects in the

morning after 8-10 hours of fasting combined with

ethylenediaminetetraacetate (EDTA) containing

heparin, then centrifuged.

Prior to the commencement of the study, the

study protocol was reviewed and approved by the

Institutional Research Ethics Board.

2.1 Biochemical Analysis

Serum glucose levels, HDL cholesterol (HDL-C),

and triglycerides (TG) were measured by the

enzymatic colorimetric method while Apo-B and hs-

CRP levels were measured by the immunoassay

method with Hitachi Modular analyzer using the

Roche Diagnostic kit. Insulin levels were measured

by the chemiluminescence immunoassay method

using the DPC Immulite-I analyzer (Diagnostic

Products Corp, Los Angeles, CA, USA) kit.

The HbA1c values were measured using the

High-Performance Liquid Chromatography (HPLC)

method which was in accordance with the American

Diabetes Association standard (American Diabetes

Association, 2010). ADMA levels were examined

using ELISA method with a normal range of 0.4-

0.75 μmol/L (80-150 ng/mL) (Miyazaki et al.,

1999). The HOMA-IR formula = [(fasting glucose

serum (mmol / l) x fasting insulin (μU / ml) / 22,5]

was used to determine the index of insulin resistance

(Matthews et al., 1985).

2.2 Statistical Analysis

The mean and standard deviation were summarized

as descriptive statistics. The Shapiro-Wilk test was

used to determine whether a variable was normally

distributed. The parametric test was performed on

variables with normal distribution, whereas the

nonparametric test was performed on variables with

the abnormal distribution. Furthermore, the Pearson

and Spearman test were used to evaluate the

correlation between variables according to the

variable distribution. P < 0.05 was accepted as an

indication of statistical significance. SPSS for

Windows 22.0 was used for the statistical analysis.

3 RESULTS

From the 45 obese subjects who met the inclusion

criteria, the average age was 41.69 ± 5.69 years, and

the average BMI was 33.09 ± 5.05 (Obesity I).

Table 1. shows the characteristics of the research

subjects in terms of anthropometric, glucose, lipid,

inflammatory parameters in obesity, while Table 2.

shows the correlation analysis between ADMA and

the subject parameters. There was a significant

correlation between the levels of ADMA and fasting

blood glucose (FBG), HbA1c, and TG.

The Relationship between ADMA and Anthropometric Indicators, Glucose, Lipid, and Inﬂammatory Parameters in Obese People

Table 1: Baseline Characteristic of Obese Subjects.

Parameters Total (mean±SD); n=45

Age (years) 41.69±5.69

Body weight (Kg) 78.79±13.26

BMI (kg/m

) 33.09±5.05

WC (cm) 96.34±9.33

ADMA (umol/l) 0.82±0.13

FPG (mg/dl) 86.00±10.94

PPG (mg/dl) 109.84±28.56

HbA1C (%) 5.56±0.56

Fasting Insulin (μIU/mL) 9.52±7.32

HOMA-IR 1.24±0.91

LDL-C (mg/dl) 137.51±33.51

HDL-C (mg/dl) 47.06±12.84

TG (mg/dl) 151.22±57.31

sd-LDL (mg/dl) 1.34±0.26

ApoB (g/L) 104.31±18.41

hs-CRP (mg/L) 3.64±2.38

Table 2: Relationship Between ADMA and Anthropometry, Glucose, Lipid, and Inflammation Parameters.

Parameters r P

Age (year) -0.057 0.356

Body weight (Kg) -0.056 0.407

BMI (kg/m

) -0.117 0.445

WC (cm) -0.100 0.256

FPS (mg/dl) -0.506 0.001*

PPS (mg/dl) -0.230 0.064

HbA1C (%) -0.334 0.013*

Fasting Insulin (μIU/mL) -0.102 0.255

HOMA-IR -0.225 0.069

LDL-C (mg/dl) -0.149 0.165

HDL-C (mg/dl) 0.154 0.157

TG (mg/dl) -0.315 0.017*

sd-LDL (mg/dl) -0.042 0.392

ApoB (g/L) -0.168 0.135

hs-CRP (mg/L) -0.059 0.351

Abbreviations: BMI, body mass index; WC, waist circumference; ADMA, asymmetric

dimethylarginine; FPG, fasting plasma glucose; PPG, postprandial plasma glucose;

HbA1c, glycosylated hemoglobin; HOMA-IR: homeostasis model assessment of insulin

resistance;; LDL-C, low density lipoprotein cholesterol; HDL-C, high density lipoprotein

cholesterol; TG, triglycerides; ApoB: apolipoprotein B; sd-LDL: small dense-LDL; CRP,

C-reactive protein;

* p<0.05.

Abbreviations: BMI, body mass index; WC, waist circumference; FPG, fasting plasma glucose;

PPG, postprandial plasma glucose; HbA1c, glycosylated hemoglobin; HOMA-IR: homeostasis

model assessment of insulin resistance; LDL-C, low density lipoprotein cholesterol; HDL-C, high

density lipoprotein cholesterol; TG, triglycerides; ApoB: apolipoprotein B; sd-LDL: small dense-

LDL; CRP, C-reactive protein;

* p<0.05.

ICTROMI 2019 - The 2nd International Conference on Tropical Medicine and Infectious Disease

4 DISCUSSION

ADMA is believed to be a mediator that affects the

risk of atherosclerosis. Several clinical studies have

shown that increased ADMA is present in the

conditions of chronic kidney insufficiency,

dyslipidemia, hypertension, diabetes mellitus, and

hyperhomocysteinemia, and other conditions

(Landim, Casella & Chagas, 2009). The presence of

cardiovascular disease risk factors, especially

atherosclerotic disease will induce functional and

morphological changes in endothelium, become

easily inflamed, thrombosis, and vasoconstriction

(Vita & Keaney, 2002). The dysfunctional

endothelium can be detected by an imbalance

between widening and constricting factors,

procoagulant factors, and anticoagulant factors

which stimulate and inhibit the development and

proliferation of cells (Rubanyi, 1993).

Other clinical evidence also supported that

increased plasma ADMA was associated with

decreased NO synthesis (Boger et al.,1998). Plasma

ADMA levels can change rapidly in response to

changes in the risk factors. In diabetic patients, a few

hours after high-fat eating, plasma ADMA level

increases, and vasodilation is reduced (Fard et al.,

2000). In low body mass index (BMI) condition,

each 0.1 μmol/L increase in the plasma ADMA level

was associated with an increased risk of acute

myocardial infarct (AMI) with HR (95% CI) 1.21

(1.08-1.35) and cardiovascular death 1.30 (1.13-

1.49) (Hoy et al., 2007). ADMA level was 0.40-0.77

mol/L for the entire population, 0.41-0.79 mol/L

for men, 0.38-0.73 mol/L for women under 45

years old, and 0.41-0.84 mol/L for women above

45 years old (Hoy et al., 2007). Past studies showed

that plasma ADMA levels were higher in obesity

(McLaughlin et al., 2006). In this study, ADMA

levels were 0.82 ± 0.13 mol/L.

Based on several previous studies, plasma

ADMA levels were associated with the risk of AMI

and cardiovascular death (Borgeraas et al.,2016),

unchanged with weight loss in obesity (Rudofsky et

al.,2011), hypertension and insulin resistance

(Perticone et al., 2010), resistance insulin at the

beginning of diabetes (Nakhjayani et al., 2010),

HOMA-IR in prehypertension (Novianti et al.,

20013), BMI in overweight (Eid et al, 2004), and

HOMA-IR in obesity (Hidayat et al., 2011). In this

study, ADMA had a significant correlation with

FPG, HbA1c, and TG parameters [r = -0.506, p =

0.001; r = -0.334, p = 0.013, and r = -0.315. p =

0.017, respectively] in obesity.

5 CONCLUSION

The association between ADMA and increased

cardiovascular risks was related to glucose

metabolism, lipid, and insulin resistance with

various unknown mechanisms. Thus, further and

extensive research should be done to determine the

role of ADMA in the risk of cardiovascular disease.

CONFLICT OF INTERESTS

The authors declare that there is no conflict of

interests regarding the publication of this paper.

REFERENCES

Baylis C. 2006. Arginine, arginine analogs and nitric

oxide production in chronic kidney disease. Nat Clin

Pract Nephrol, 4, pp. 209-20.

Blake GJ, Ridker PM. 2002. Inflammatory Bio-Markers

And Cardiovascular Risk Prediction. J Intern Med,

252, pp. 283-94.

Boger RH, Bode-Boger SM, Thiele W, Junker W,

Alexander K, Frolich JC. 1997. Biochemical Evidence

For Impaired Nitric Oxide Synthesis In Patients With

Peripheral Arterial Occlusive Disease. Circulation, 95,

pp. 2068-74.

Böger RH1, Bode-Böger SM, Szuba A, Tsao PS, Chan JR,

Tangphao O, et al. 1998. Asymmetric

dimethylarginine (ADMA): a novel risk factor for

endothelial dysfunction: its role in

hypercholesterolemia. Circulation, 98(18), pp. 1842-7.

Borgeraas H, Hertel JK, Svingen GVT, Pedersen ER,

Seifert R, Nygård O, et al. 2016. Association between

Body Mass Index, Asymmetric Dimethylarginine and

Risk of Cardiovascular Events and Mortality in

Norwegian Patients with Suspected Stable Angina

Pectoris. PLoS ONE, 11(3), pp. 1-13.

Colak A, Coker I, Diniz G, Karademirci İ, Hanci T &

Bozkurt U. 2010. Interleukin 6 and tumor necrosis

factor alpha levels in women with and without glucose

metabolism disorders. Turkish Journal of

Biochemistry, 3(35), pp. 190-4.

Eid HMA, Arnesen H, Hjerkinn EM, Lyberg T, Seljeflot I.

2004. Relationship Between Obesity, Smoking, and

the Endogenous Nitric Oxide Synthase Inhibitor,

Asymmetric Dimethylarginine Metabolism, 53(12),

pp. 1574-9.

El Assar M, Angulo J, Santos Ruiz M, Adana RD,

Pindado JC, Sánchez Ferrer ML, et al. 2016.

Asymmetric dimethylarginine (ADMA) Elevation

And Arginase Up-Regulation Contribute To

Endothelial Dysfunction Related To Insulin Resistance

In Rats And Morbidly Obese Humans. Journal of

Physiology, 594(11), pp. 3045-60.

The Relationship between ADMA and Anthropometric Indicators, Glucose, Lipid, and Inﬂammatory Parameters in Obese People

Eliana F, Suwondo P, Makmun LH, Harbuwono DS.

2011. ADMA as a Marker of Endothelial Dysfunction

in Prediabetic Women. Acta Med Indones-Indones J

Intern Med, 43(2), pp. 92-8.

Fard A1, Tuck CH, Donis JA, Sciacca R, Di Tullio MR,

Wu HD, et al. 2000. Acute elevations of plasma

asymmetric dimethylarginine and impaired endothelial

function in response to a high-fat meal in patients with

type 2 diabetes. Arterioscler Thromb Vasc Biol, 20(9),

pp. 2039-44.

Goodson NJ, Symmons DP, Scott DG, Bunn D, Lunt M,

Silman AJ. 2005. Baseline levels of C-reactive Protein

And Prediction Of Death From Cardiovascular

Disease In Patients With Inflammatory Polyarthritis: a

ten-year follow-up study of a primary care-based

inception cohort. Arthritis Rheum, 52, pp. 2293-99.

Hidayat A, Wijaya A, Alrasyid H. 2011. Correlation

between IL-6, hsCRP, ET-1, ADMA and HOMA-IR in

Central Obese Men. Indones Biomed J, 3(1), pp. 43-50.

Hov G, Sagen E, A. Bigonah & Sberg AA. 2007. Health-

associated reference values for arginine, asymmetric

dimethylarginine (ADMA) and symmetric

dimethylarginine (SDMA) measured with high-

performance liquid chromatography G. Scand J Clin

Lab Invest, 67, pp. 868-76.

Huang S, Xu Y, Peng WF, Cheng J, Li HH, Shen LS, Xia

LL. 2018. A Correlational Study Between Serum

Asymmetric Dimethylarginine Level And Impaired

Glucose Tolerance Patients Associated With Obesity.

J Cell Physiol, pp. 1-6.

Kelm M. 2002. Flow-mediated dilatation in human

circulation: Diagnostic and Therapeutic Aspects. Am J

Physiol Heart Circ Physiol, 282, pp. 1-5.

Kielstein JT, Bode-Boger SM, Klein G, Graf S, Haller H,

Fliser D. 2003. Endogenous Nitric Oxide Synthase

Inhibitors And Renal Perfusion In Patients With Heart

Failure. Eur J Clin Invest, 33, pp. 370-5.

Landim MBP, Casella Filho A, Chagas ACP. 2009.

Asymmetric dimethylarginine (ADMA) and

Endothelial Dysfunction: Implications for

Atherogenesis. Clinics, 64(5), pp. 471-8.

Lin KY, Ito A, Asagami T, Tsao PS, Adimoolam

S, Kimoto M, et al. 2002. Impaired Nitric Oxide

Synthase Pathway In Diabetes Mellitus: Role of

Asymmetric Dimethylarginine and Dimethylarginine

Dimethylaminohydrolase. Circulation, 106, pp. 987-

92.

Lobo SM, Lobo FR, Bota DP, Lopes-Ferreira F, Soliman

HM, Mélot C et al. 2003. C-reactive Protein Levels

Correlate With Mortality And Organ Failure In

Critically Ill Patients. Chest, 123, pp. 2043–9.

Man P, Connett JE, Anthonisen NR, Wise RA, Tashkin

DP, Sin DD. 2006. C-reactive protein and mortality in

mild to moderate chronic obstructive pulmonary

disease. Thorax, 61(10), pp. 849-53.

Matthews DR, Hosker JP, Rudenski AS, Naylor BA,

Treacher DF, et al. 1985. Homeostasis model

assessment: insulin resistance and β-cell function from

fasting plasma glucose and insulin concentrations in

man. Diabetologia, 28, pp. 412–9.

McLaughlin T, Stuhlinger M, Lamendola C, Abbasi F,

Bialek J, Reaven GM, et al. 2006. Plasma asymmetric

dimethylarginine concentrations are elevated in obese

insulin-resistant women and fall with weight loss. J

Clin Endocrinol Metab, 91, pp. 1896–900.

Miyazaki H, Matsuoka H, Cooke JP, Usui M, Ueda S,

Okuda S, et al. 1999. Endogenous Nitric Oxide

Synthase Inhibitor: A Novel Marker Of

Atherosclerosis. Circulation, 99, pp. 1141-6.

Nakhjavani M, Karimi-Jafari H, Esteghamati A,

Khalilzadeh O, Asgarani F, Ghadiri-Anari A. 2010.

ADMA is a correlate of insulin resistance in early-

stage diabetes independent of hs-CRP and body

adiposity. Annales d’Endocrinologie, 71, pp. 303-8.

National Institutes of Health. 1998. Clinical Guidelines on

the Identification, Evaluation, and Treatment of

Overweight and Obesity in Adults; The Evidence

Report. Obes Res, 6(2), pp. 51S–209S.

Novianti ME, Bakri S, Arief M, Sandra F. 2013.

Correlation between HOMA-IR with ADMA in

Prehypertension. Indones Biomed J, 5(3), pp. 169-72.

Peraldi P, Hotamisligil GS, Buurman WA, White MF &

Spiegelman BM. 1996. Tumor necrosis factor (TNF)

alpha inhibits insulin signaling through stimulation of

the p55 TNF receptor and activation of

sphingomyelinase. Journal of Biological Chemistry,

271(22), pp. 13018-22.

Perticone F, Sciacqua A, Maio R, Perticone M, Galiano

Leone G, Bruni R, et al. 2010. Endothelial

dysfunction, ADMA and insulin resistance in essential

hypertension. Int J Cardiol, 142(3), pp. 236-41.

Rubanyi GM. 1993. The role of the endothelium in

cardiovascular homeostasis and diseases. J Cardiovasc

Pharmacol, 22(4), pp. S1-S4.

Rudofsky G, Roeder E, Merle T, Hildebrand M, Nawroth

PP, Wolfrum C. 2011. Weight Loss Improves

Endothelial Function Independently of ADMA

Reduction in Severe Obesity. Horm Metab Res, 43,

pp. 343-8.

Savvidou MD, Hingorani AD, Tsikas D, Frolich JC,

Vallance P, Nicolaides KH. 2003. Endothelial

Dysfunction And Raised Plasma Concentrations Of

Asymmetric Dimethylarginine In Pregnant Women

Who Subsequently Develop Pre-Eclampsia. Lancet,

36, pp. 1511-7.

American Diabetes Association. 2010. Standards of

Medical Care in Diabetes. Diabetes Care, 33, pp. S11-

61.

Tsikas D, Rode I, Becker T, Nashan B, Klempnauer J,

Frolich JC. 2003. Elevated plasma and urine levels of

ADMA and 15(S)-8-iso-PGF2alpha in end-stage liver

disease. Hepatology, 38, pp. 1063-4.

Vita JA, Keaney Jr JF. 2002. Endothelial function: a

barometer for cardiovascular risk? Circulation, 106,

pp. 640-2.

WHO. Obesity: Preventing and managing the global

epidemic. Report of a WHO Consultation. WHO

Technical Report Series 894. Geneva: WHO,2000.

Zoccali C, Bode-Boger S, Mallamaci F, Benedetto

F, Tripepi G, Malatino L, et al. 2001. Plasma

ICTROMI 2019 - The 2nd International Conference on Tropical Medicine and Infectious Disease

Concentration of Asymmetrical Dimethylarginine And

Mortality In Patients With End-Stage Renal Disease: a

Prospective Study. Lancet, 358, pp. 2113-7.

The Relationship between ADMA and Anthropometric Indicators, Glucose, Lipid, and Inﬂammatory Parameters in Obese People