Angiology: Open Access
Open Access

Association of Brachial Artery Measures with Estimated GFR>60 mL/min/1.73 m² in a Cross-Sectional Study of the Community-Based Women

Kazumi Fujioka^1*, Minoru Oishi², Tomohiro Nakayama³ and Akira Fujioka^{1 *}Correspondence: Kazumi Fujioka, Department of Dermatology, Fujioka Dermatological Clinic, Tokyo, Japan, Email:

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Introduction

Flow-Mediated Vasodilation (FMD), an endothelium-dependent function, and Nitroglycerin-Mediated Vasodilation (NMD), an endothelium-independent function in the brachial artery is potent procedure for assessing vascular endothelial and Vascular Smooth Muscle Cell (VSMC) function [1]. Patients with severe Chronic Kidney Disease (CKD) have high risk of occurring Cardiovascular Disease (CVD) [2], but it has been reported that subjects with mild kidney dysfunction have also an increased CVD risk in the community-based study [3]. It has been suggested that the increased risk of CVD has been contributed not only to clustering of CV risk factors [4] but also to endothelial dysfunction [5,6] in subjects with CKD. Though the threshold eGFR at which CV risk increases is unclear, expert consensus have proposed a level of <60 mL/min/1.73 m² [7]. Studies have been reported that eGFR is associated with endothelial dysfunction in the community-based subjects [6,8-11]. With regard to the restricting analysis to subject with eGFR>60 mL/min/1.73 m² representing CKD stage 0-2, a few reports has been studied [9-11]. The cardio-renal interrelationship has been suggested under normal conditions [12]. It has been also reported that endothelial dysfunction is considered as one of the major pathophysiological mechanism contributing to the relation of CVD and CKD [6,13,14]. We think that early detection of cardio-renal interaction damage can contribute to the prevention of initiation or precipitation of diseases. According to the experts consensus proposed as a threshold of eGFR>60 mL/min/1.73 m², we evaluate whether early decline in kidney function with eGFR>60 mL/min/1.73 m² value is correlated with brachial artery measures as indicators of the endothelial function. Except the relationship between endothelial dysfunction and eGFR value, Serum Uric Acid (SUA) is also an independent predictor of CKD in subject with eGFR>60 mL/min/1.73 m² [15,16]. Experimentally, some studies indicate that hyperuricemia cause systemic and glomerular hypertension, leading to endothelial dysfunction and contribute to an afferent renal arteriopathy and tubulointerstitial fibrosis in kidney [17-20]. We also add the estimation whether eGFR 60 mL/ min/1.73 m² of renal function is related with SUA. Furthermore, experimental and clinical studies have also indicated the relationship between SUA and endothelial dysfunction [21-25]. Therefore, we have studied whether interrelationship among eGFR>60 mL/ min/1.73 m², FMD and SUA are correlated. Meanwhile, carotid Intima-Media Thickness (IMT) is a marker to assess the largely medial hypertrophy of the vessel [26] and brachial-ankle Pulse Wave Velocity (baPWV) is a predictor to evaluate arterial stiffness [13]. In addition to the evaluation of endothelial function, we added the examinations whether eGFR>60 mL/min/1.73 m² value is correlated with different arterial trees at different sites.

Materials and Methods

Study population

Thirty six women with eGFR>60 mL/min/1.73 m² renal function in community-based population were retrospectively studied in this research (including: 8 cerebral infarction, 9 migraine, 2 cervical spondylosis, and 17 not otherwise). Thirty six subjects who fulfilled eGFR>60 mL/min/1.73 m² value were enrolled in the study between March 2008 and April 2014. All vasoactive medications were withheld for at least a few days. Women patients were allowed to perform ultrasonographic examinations either in luteal or follicular phase. For the FMD examination, patients fasted for 12 hours before the study and they were studied in a quiet, temperature-controlled room. The estimated glomerular filtration rate (eGFR) was calculated using Japanese eGFR equation [27].

Vascular reactivity

FMD of the brachial artery was determined using high resolution B-mode ultrasonographic system (UNEXEX 18G, Japan) with a linear transducer mid-frequency of 7.5 MHz, using the technique described previous report [28,29]. Briefly, this was followed by inflation pneumatic tourniquet of placed around forearm to higher pressure 50 mmHg more than systolic blood pressure and followed by deflation after 5 minutes. The scan was made by the procedure of auto calculation. Fifteen minutes were then allowed for vessel recovery and a further scan at rest was then recorded. An exogenous NO donor, such as a single high dose (0.3 mg) of NTG spray has been given to determine the maximum obtainable vasodilator response, and to serve as a measure of endothelium-independent vasodilation reflecting VSMC function, in accordance with the previous report [1,28,29]. Parameters including FMD, NMD and P-NTGD were expressed as previously described [28,29].

Carotid ultrasonography

The Intima-Media Thickness (IMT) of the bilateral Common Carotid Arteries (CCA) was measured by ultrasonography with a 10 MHz probe using an ultrasound system (Aplio SSA-700A, Toshiba Medical System, Tochigi, Japan). Measurement of IMT were performed on the visible CCA in either the near or the far wall, and maximum IMT was defined as IMT-C max. Measurement IMT were also made within a region free of plaque as previously described [26,28].

Brachial-ankle Pulse Wave Velocity (baPWV) measurement

baPWV was measured using a volume-plethysmographic apparatus (form PWV/ABI; Colin, Co.,Ltd., Komaki, Japan) and Ankle Brachial Pressure Index (ABI) is measured simultaneously by these machines in accordance with a described method [28-30].

Statistical analysis

Numerical variables were expressed as mean ± SD. Spearman’s bi-variable correlation analysis was used to test the relationships between the numerical variables when appropriate. Statistical significance was defined as a p value of less than 0.05. The statistical analyses were performed using the SPSS software package (version 16.0; SPSS Inc., Chicago, IL).

Result

Baseline characteristics of study population are summarized in (Table 1). Mean age of the participants was 55.4 ± 14.4 years (range: 19 to 80 years). Brachial artery measures of the participants were presented (Table 2).

Table 1: The Clinical and Biochemical Characteristics of the Participant (mean ± SD).

Table 2: Brachial Artery Measures (mean ± SD).

Table 3 shows Spearman’s rank correlation coefficients of the brachial artery measures in participants. FMD% was significantly correlated with FMD/NMD ratio (r=0.68, n p<0.001). Significant correlation between FMD% and p-NTGD was recognized (r=-0.37, p=0.03).

Table 3: Spearman’s rank correlation coefficients of the brachial artery measures in participant with eGFR>60 mL/min/1.73 m².

Table 4 shows Spearman’s rank correlation coefficients of the atherosclerotic parameters in participants. Negative correlation between FMD and rtIMT (r=-0.664, p<0.001) and negative correlation between FMD and ltIMT (r=-0.546, p=0.005) were also detected. Positive correlation between rtIMT and rtbaPWV (r=0.432, p=0.027), positive correlation between rtIMT and ltbaPWV (r=0.478, p=0.010), positive correlation between ltIMT and rtbaPWV (r=0.498, p=0.010) and positive correlation between ltIMT and LtbaPWV (r=0.527, p=0.006) were also recognized. Negative correlation between FMD and ltbaPWV(r=-0.417, p=0.020) were observed, but there was no correlation between FMD and rtbaPWV (r=-0.343, p=0.059).

Table 4: Spearman’s rank correlation coefficients of the atherosclerotic parameters in participant with eGFR.60 mL/min/1.73m².

Table 5 shows Spearman’s rank correlation coefficients for FMD, BAD, P-NTGD, NMD and FMD/NMD ratio with clinical and biochemical parameters in participants.

Table 5: Spearman’s rank correlation coefficients for FMD, BAD, P-NTGD, NMD and FMD/NMD with clinical and biochemical parameters in participants with eGFR>60 mL/min/1.73 m².

There was significantly positive correlation between FMD and eGFR (r=0.348, p=0.041; Figure 1) and positive correlation between FMD/NMD ratio and eGFR (r=0.471, p=0.004; Figure 2). Negative correlation between P-NTGD and eGFR (r=-0.405, p=0.016; Figure 3) was recognized. There was weak negative correlation between FMD and SUA (r=-0.340, p=0.045).

Figure 1: Positive correlation between FMD and eGFR was significantly observed.

Figure 2: Significant positive correlation between FMD/NMD ratio and eGFR was shown.

Figure 3: Significant negative correlation between P-NTGD and eGFR was observed.

Table 6 shows Spearman’s rank correlation for carotid IMT, baPWV and Ankle Brachial Pressure Index (ABI) with clinical and biochemical parameters in participants.

Table 6: Spearman’s rank correlation coefficients for IMT, baPWV and ABI with clinical and biochemical parameters in participant with eGFR>60 mL/min/1.73 m².

Negative correlation between eGFR and rt IMT (r=-0.509, p=0.009) was detected, but here was no correlation between eGFR and ltIMT (r=-0.229, p=0.271). Correlation between eGFR and rt baPWV and lt baPWV were not shown. Positive correlation between SUA and rtIMT (r=0.613, p=0.001) and positive correlation between SUA and ltIMT (r=0.638, p=0.001) were also recognized.

Table 7 shows correlation between SUA and other parameters in participant. There was weak negative correlation between SUA and eGFR (r=-0.335, p=0.049).

Table 7: Correlation between serum uric acid and other parameters in the participant with eGFR>60 mL/min/1.73 m²

Discussion

Previous studies have suggested that eGFR is associated with endothelial dysfunction in community-based [6,8,11]. Though the threshold eGFR at which CV risk increases is not clear, expert consensus have proposed a level of < 60 mL/min/1.73 m² [7], namely, the National Kidney Foundation clinical practice guidelines define CKD as the presence of eGFR less than 60 mL/min/1.73 m² with or without kidney damage for at least 3 months [7]. With regard to the restricting analysis to subject with eGFR>60 mL/min/1.73 m², a few reports have been studied [9-11]. The Hoorn Study indicated that the inverse correlation between eGFR and biomarkers of endothelial function, namely plasma Von Willebrand Factor (VWF), soluble Vascular Cell Adhesion Molecule-1 (VCAM-1) and the urinary albumin-creatinine ratio in subjects unselected for CKD in a population-based cohort [6]. The Framingham Heart Study indicated that endothelial dysfunction estimated with FMD is not a major correlate of moderate CKD in subjects with stage 3 CKD, suggesting the focus on other mechanism such as inflammation and arterial stiffness [8]. The Multi-Ethnic Study of Atherosclerosis (MESA) showed no association between FMD and renal function in subjects with eGFR>60 mL/min/1.73 m² [10]. Nerpin et al. reported that eGFR is associated with endothelial function in subjects with normal kidney function, but that this association is mainly explained by confounding CV risk factors [11]. However, Study of Health in Pomerania (SHIP) indicated that FMD was associated with renal dysfunction in females with eGFR>60 mL/min/1.73 m² [9]. They suggest that very mild renal dysfunction is considered as a risk factor for the early atherosclerosis disease process in women [9]. Our data showed that mild renal dysfunction assessed by eGFR value is respectively associated with endothelial function evaluated with FMD, FMD/NMD ratio which represents more sensitive parameter than FMD [31] and P-NTGD [32]. P-NTGD value [32] which is without vascular tone and shows more stable marker than BAD [33]. BAD is the plausible surrogate marker of FMD. Our results indicated that correlation between mild renal dysfunction and endothelial function in the restricting study to subject with >60 mL/min/1.73 m² was shown in women in cross-sectional study.

It has been suggested that the interaction between the heart and the kidney may occur in the setting of processes and diseases such as advanced age, hypertension, diabetes mellitus and atherosclerosis [14]. The cardio-renal interrelationship by fine-turning by neurohumoral activity, namely Atrial Natriuretic Peptide (ANP), Renin-Angiotensin-Aldosterone System (RAAS) and Sympathetic Nervous System (SNS) has been also reported under normal conditions [14]. Our result indicated that the cardio-renal relation may be also observed through endothelial dysfunction under mild renal dysfunction. While, it has been reported that endothelial dysfunction is considered as one of the pathophysiological major mechanism contributing to the relation of CVD and CKD [6,13,14]. Cytogenetically, Shang et al. reported microRNA-92a as a crucial link between CKD and CVD by mediated uremia-impaired endothelial dysfunction [34]. In addition to classic CVD risk factors, it can be suggested that mild renal dysfunction might be a CVD risk factor in women.

Except the correlation between endothelial dysfunction and eGFR, Sonoda et al. reported the SUA as an independent predictor of future development of CKD in subject with eGFR>60 mL/min/1.73 m² [15]. It has been also suggested that SUA was independently related to the eGFR in the subject with eGFR>60 mL/min/1.73 m² [16]. Experimentally, some studies indicated that hyperuricemia causes systemic and glomerular hypertension, leading to endothelial dysfunction and experimental hyperuricemia also contribute to an afferent renal arteriopathy and tubulointerstitial fibrosis in the kidney by activating the RAAS [17-20]. It is plausible that elevated SUA may contribute to endothelial dysfunction, inflammation, oxidative stress and Renin-Angiotensin System (RAS) activation [17] and leading to systemic atherosclerosis and/or reduced eGFR, namely, initiation and progression of CKD. As our data showed the weak inverse relationship between SUA and eGFR, the increased SUA level, even in physiological range, may be a risk factor for impaired eGFR in subjects with mild renal dysfunction.

The evidence of SUA to stimulate oxidant production has already been studied in both adipocytes [35] and VSMC [36]. In addition to these studies, Yu et al. [21] have reported that SUA can induce oxidative stress and activation of local RAS system leading to senescence and apoptosis, showing a mechanism of uric acidinduced human umbilical vein endothelial dysfunction. Clinical studies have also indicated the relationship between SUA and endothelial dysfunction [22-25]. As our data showed a weak inverse correlation between SUA and endothelial function, the raised SUA, even in physiological range, may reflect he endothelial dysfunction.

Kanbay et al. have reported that allopurinol lowering SUA showed decreased SUA level, increased FMD value and increased eGFR level [24]. Our result may suggest that raised SUA level, in physiological range, contribute to both decreased FMD and impaired eGFR. It is putative that the interrelationship among SUA, endothelial dysfunction and eGFR, subsequently leading to systemic and/or renal atherosclerosis.

Meanwhile, atherosclerosis and arteriosclerosis which are different vascular pathologies are present in CKD [13]. It has reported that progressive deterioration of renal function in CKD is related with the uremic toxins, oxidative stress and inflammation, and develop the initiation of endothelial dysfunction and progression of atherosclerosis [13]. Endothelial dysfunction also cause arteriosclerosis, a disease affecting the media of large and middle sized arteries with an increased collagen: elastin ratio, calcification and hyperplasia and hypertrophy of VSMCs, leading to the occurrence of increased arterial stiffness measured by PWV [13]. On the other hand, IMT is a marker which reflects not only early atherosclerosis, but also non-atherosclerotic compensatory remodeling with largely medial hypertrophy [26]. In addition to the endothelial function assessed by brachial artery measures; we add the study whether eGFR>60 mL/min/1.73 m² value is correlated with these indicators. Negative correlation between eGFR and rtIMT was detected, but there was no correlation between eGFR and ltIMT. Correlation between eGFR and baPWV was not shown.

The interrelationship among FMD, IMT and baPWV which are different artery trees at different sites and different indicators of atherosclerosis were also evaluated. Our data suggested correlations between FMD and IMT and between IMT and baPWV, respectively.

Study Limitations

There were some limitations in this study. Our results indicated that correlation between mild renal dysfunction and endothelial function in the restricting study to subject with >60 mL/min/1.73 m² was shown in women in cross-sectional study. But several confounding factors related to endothelial dysfunctions as well as renal dysfunction were present. The differences in risk factors are important to address as they are likely independently related to endothelial dysfunction as well as renal dysfunction. However, our study sample size is relatively small; we did not adjust using confounding factors. Future prospective studies are warranted to obtain more specific conclusion.

Conclusion

It can be suggested that mild renal dysfunction might be a cardiovascular risk factor in women. Though, it should not be distinctly stated just based on the study results.

Acknowledgement

The author appreciates his assistance of Dr. Masahiro Okada. Compliance with ethical standards. Informed consent was obtained from patients and healthy controls in this study and the study was approved by the Ethics Committee of NIihon University School of Medicine.

Conflict of Interest

Authors declare that they have no conflicts of interest.

References

1. Corretti MC, Anderson TJ, Benjamin EJ, Celermajer D, Charbonneau F, Creager MA, et al. Guidelines for the ultrasound assessment of endothelial-dependent flow-mediated vasodilation of the brachial artery: a report of the International Brachial Artery Reactivity Task Force. J Am Coll Cardiol. 2002;39:257-265.
2. Matsushita K, Selvin E, Bash LD, Franceschini N, Astor BC, Coresh J. Change in estimated GFR associates with coronary heart disease and mortality. J Am Soc Nephrol. 2009;20:2617-2624.
3. Soveri I, Arnlov J, Berglund L, Lind L, Fellstrom B, Sundström J. Kidney function and discrimination of cardiovascular risk in middle-aged men. J Intern Med. 2009;266:406-413.
4. Keller CR, Odden MC, Fried LF, Newman AB, Angleman S, Green CA, et al. Kidney function and markers of inflammation in elderly persons without chronic kidney disease: The health, aging, and body composition study. Kidney Int. 2007;71:239-244.
5. Recio-Mayoral A, Banerjee D, Streather C, Kaski JC. Endothelial dysfunction, inflammation and atherosclerosis in chronic kidney disease-a cross-sectional study of predialysis, dialysis and kidney-transplantation patients. Atherosclerosis. 2011;216:446-451.
6. Stam F, van Guldener C, Becker A, Dekker JM, Heine RJ, Bouter LM, et al. Endothelial dysfunction contributes to renal function-associated cardiovascular mortality in a population with mild renal insufficiency: The Hoorn study. J Am Soc Nephrol. 2006;17:537-545.
7. Foundation NK. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am J Kidney Dis. 2002;39:S1-S266.
8. Foster MC, Keyes MJ, Larson MG, Vita JA, Mitchell GF, Meigs JB, et al. Relations of measures of endothelial function and kidney disease: The Framingham Heart Study. Am J Kidney Dis. 2008;52:859-867.
9. Reffelmann T, Krebs A, Ittermann T, Empen K, Hummel A. Mild renal dysfunction as a non-traditional cardiovascular risk factor? -association of cystatin C-based glomerular filtration rate with flow-mediated vasodilation. Atherosclerosis. 2010;211:660-666.
10. Peralta CA, Jacobs Jr DR, Katz R, Ix JH, Madero M, Duprez DA, et al. Association of pulse pressure, arterial elasticity, and endothelial function with kidney function decline among adults with estimated GFR>60mL/min/1.73m2 : The Multi-Ethnic Study of Atherosclerosis(MESA). Am J Kidney Dis. 2011;59:41-49.
11. Neprin E, Ingelsson E, Riserus U, Hermersson-Karlqvist J, Sundstrom J,  Jobs E, et al. Association between glomerular filtration rate and endothelial function in an elderly community cohort. Atherosclerosis. 2012;224:242-246.
12. Boudoulas KD, Triposkiadis F, Parissis J, Butler J, Boudoulas H. The cardio-renal interrelationship. Prog Cardiovasc Dis. 2017;59: 636-648.
13. Moody WE, Edwards NC, Madhani M, Chue CD, Steeds RP, Ferro CJ, et al. Endothelial dysfunction and cardiovascular disease in early-stage chronic kidney disease: cause or association? Atherosclerosis. 2012;223:86-94.
14. Rossi GP, Seccia TM, Barton M, Danser AHJ, de Leeuw PW, Dhaun N, et al. Endothelial factors in the pathogenesis and treatment of chronic kidney disease Part 1: general mechanism: a joint consensus statement from the European Society of Hypertension Working Group on endothelial and endothelial factors and the Japanese Society of Hypertension. J Hypertens. 2018;36:451-461.
15. Sonoda H, Takase H, Dohi Y, Kimura G. Uric acid levels predict future development of chronic kidney disease. Am J Nephrol. 2011;33:352-357.
16. Ji B, Zhang S, Gong L, Wang Z, Ren W, Li Q, et al. The risk factors of mild decline in estimated glomerular filtration rate in a community-based population. Clin Biochem. 2013;46:750-754.
17. Jalal DI, Chonchol M, Chen W, Targher G. Uric acid as a target of therapy in CKD. Am J Kidney Dis. 2013;61:134-146.
18. Mazzali M, Hughes J, Kim YG, Jefferson JA, Kang DH, Gordon KL, et al. Elevated uric acid increases blood pressure in the rat by a novel crystal-independent mechanism. Hypertension. 2001;38:1101-1106.
19. Sanchez-Lozada LG, Tapia E, Lopez-Molina R, Nepomuceno T, Soto V, Avila-Casado C, et al. Effects of acute and chronic L-arginine treatment in experimental hyperuricemia. Am J Physiol. 2007;292:F1238-F1244.
20. Mazzali M, Kanellis J, Han L, Feng L, Xia YY, Chen Q, et al. Hyperuricemia induces a primary renal arteriolopathy in rats by a blood pressure-independent mechanism. Am J Physiol Renal Physiol. 2002;282:F991-F997.
21. Yu MA, Sanchez-Lozada LG, Johnson RJ, Kang DH. Oxidative stress with an activation of the renin-angiotensin system in human vascular endothelial cells as a novel mechanism of uric acid-induced endothelial dysfunction. J Hypertens. 2010;28:1234-1242.
22. Ho WJ, Tsai WP, Yu KH, Tsay PK, Wang CL. Association between endothelial dysfunction and hyperuricaemia. Rheumatology. 2010;49:1929-1934.
23. Kanbay M, Yilmaz MI, Sonmez A, Turgut F, Saglam M, Cakir E, et al. Serum uric acid level and endothelial dysfunction in patients with nondiabetic chronic kidney disease. Am. J Nephrol. 2011;33:298-304.
24. Kanbay M, Huddam B, Azak A, Solak Y, Kadioglu GK, Kirbas I, et al. A randomized study of allopurinol on endothelial function and estimated glomerular filtration rate in asymptomatic hyperuricemic subjects with normal renal function. Clin J Am Soc Nephrol. 2011;6:1887-1894.
25. Tao M, Pi X, Ma X, Shi Y, Zhang Y, Gu H, et al. Relationship between serum uric acid and clustering of cardiovascular disease risk factors and renal disorders among Shanghai population: a multicenter and cross-sectional study. BMJ Open. 2019;9:e025453.
26. Touboul PJ, Hennerici MG, Meairs S, Adams H, Amarenco P, Bornstein N, et al. Mannheim carotid intima-media thickness and plaque consensus (2004-2006-2011). An update on behalf of the advisory board of the 3rd, 4th and 5th watching the risk symposia, at the 13th , 15th and 20th European Stroke Conferences, Mannheim, Germany, 2004, Brussels, Belgium, 2006, and Hamburg, Germany, 2011.Cerebrovasc Dis. 2012;34:290-296.
27. Matsuo S, Imai E, Horio M, Yasuda Y, Tomita K, Nitta K, et al. Revised equations for estimated GFR from serum creatinine in Japan. Am J Kidney Dis. 2009;53:982-992.
28. Fujioka K, Oishi M, Fujioka A, Nakayama T. Increased nitroglycerin-mediated vasodilation in migraineurs without aura in the interictal period. J Med Ultrason. 2018;45:605-610.
29. Fujioka K. Reply to: Endothelium-dependent and independent functions in migraineurs. J Med Ultrason. 2019;46: 169-170.
30. Yamashina A, Tomiyama H, Takeda K, Tsuda H, Arai T, Hirose K, et al. Validity, reproducibility, and clinical significance of noninvasive brachial-ankle pulse wave velocity measurement. Hypertens Res. 2002;25: 359-364.
31. Diaz KM, Veerabhadrappa P, Kashem MA, Feairheller DL, Sturgeon KM, Williamson ST, et al. Relationship of visit-to-visit and ambulatory blood pressure variability to vascular function in African Americans. Hypertens Res. 2012;35:55-61.
32. Chung WB, Hamburg NM, Holbrook M, Shenouda SM, Dohadwala MM, Terry DF, et al. The brachial artery remodels to maintain local shear stress despite the presence of cardiovascular risk factors. Arterioscler Thromb Vasc Biol. 2009;29:606-612.
33. Holewijn S, den Heijer M, Swinkels DW, Stalenhoef FH, de Graaf J. Brachial artery diameter is related to cardiovascular risk factors and intima-media thickness. Eur J Clin Invest. 2009;39:554-560.
34. Shang F, Wang SC, Hsu CY, Miao Y, Martin M, Yin Y, et al. MicroRNA-92a midiates endothlia dysfunction in CKD. J Am Soc Nephrol. 2017;28:3251-3261.
35. Sautin YY, Nakagawa T, Zharikov S, Johnson RJ. Averse effects of the classic antioxidant uric acid in adipocytes: NADPH oxidase-mediated oxidative/nitrosative stress. Am J Physiol Cell Physiol. 2007;293:C584-C596.
36. Corry DB, Eslami P, Yamamoto K, Nyby MD, Makino H, Tuck ML. Uric acid stimulates vascular smooth muscle cell proliferation and oxidative stress via the vascular renin-angiotensin system. J Hypertens. 2008;26:269-275.