Augmented Association Between Blood Pressure and Proteinuria in Hyperuricemic Patients With Nonnephrotic Chronic Kidney Disease

Augmented Association Between Blood Pressure and Proteinuria in Hyperuricemic Patients With... Abstract BACKGROUND Hyperuricemia (HU) may enhance susceptibility to hypertensive renal damage via disrupted autoregulation of glomerular hemodynamics. The effect of HU on the association between blood pressure (BP) and proteinuria remains unknown in patients with chronic kidney disease (CKD). METHODS In total, 109 patients with nonnephrotic CKD (55 men and 54 females) who underwent renal biopsy were recruited. Arteriolar hyalinosis was semiquantitatively assessed via arteriole grading. Correlation between BP and urine protein (UP) level was examined based on the presence of HU, which was defined as the use of urate-lowering drugs or serum uric acid levels of ≥7 and ≥5 mg/dl in males and females, respectively, which were associated with increased risks of hyalinosis in our previous study. RESULTS Median age, BP, estimated glomerular filtration rate, and UP level were 38 years, 124/74 mm Hg, 82 ml/min/1.73 m2, and 0.8 g/gCr, respectively. In patients with HU (n = 59), log-transformed systolic BP (SBP) was significantly correlated with log-transformed UP level (r = 0.49, P < 0.0001); this was not observed in patients without HU (n = 50). Multiple regression analysis (R2 = 0.21, P = 0.0001) revealed that the interaction between HU and log-transformed SBP with respect to proteinuria was significantly correlated with log-transformed UP level (β = 7.0, P = 0.03), independent of age, sex, and potential confounding factors; however, this statistical significance was completely eliminated after adjustment for the arteriolar hyalinosis index. CONCLUSIONS HU potentiates susceptibility to hypertensive glomerular damage via disrupted autoregulation in patients with nonnephrotic CKD. blood pressure, chronic kidney disease, hypertension, hypertensive renal damage, renal arteriolosclerosis, uric acid Hyperuricemia (HU) is associated with chronic kidney disease (CKD) progression,1,2 and many epidemiological studies have confirmed this association.3 Moreover, some interventional studies showed that urate-lowering therapy using allopurinol slows CKD progression.4,5 These findings suggest that HU contributes to the development of renal dysfunction. Epidemiological studies suggested that HU has a greater impact on the renal outcome among individuals with hypertension than among those without it.6 Although the mechanism underlying the association between renal progression and asymptomatic HU, especially in individuals with hypertension, remains to be determined, crystal- independent mechanisms may be involved. An experimental study using a hyperuricemic rat model showed that renal arteriolopathy may be responsible for renal damage and hypertension progression.7,8 We previously revealed that higher uric acid levels were associated with a higher risk for renal arteriolopathy in patients with CKD who underwent renal biopsy.9 Because the disruption of the autoregulation system in afferent arterioles leads to the direct transmission of increased systemic blood pressure (BP) to the glomeruli,10 preglomerular arteriolopathy may augment hypertensive glomerular damage. Thus, we hypothesized that HU potentiates BP-dependent renal damage in association with renal arteriolopathy. Therefore, we conducted a cross-sectional study to examine the association between BP and proteinuria, a marker for glomerular damage in patients with nonnephrotic CKD, with or without HU. METHODS Settings and participants In total, 207 consecutive patients who underwent renal biopsy at the University of the Ryukyus Hospital from 1 January 2003 to 31 December 2007 were included. Patients receiving renin–angiotensin system inhibitors, steroids, or calcineurin inhibitors and those with tubulointerstitial nephritis were excluded because these factors could affect proteinuria levels independent of the systemic BP. Furthermore, patients with nephrotic CKD, which was defined as serum albumin concentrations of <3 g/gCr, were excluded because glomerular permeability rather than BP appeared to be the main determinant of proteinuria in nephrotic CKD. Finally, 109 patients (55 males and 54 females) were included. The study protocol was approved by the ethics review board of the University of the Ryukyus. All patients provided written informed consents for using their clinical and histological data in our analysis. When patients were admitted for renal biopsy, clinicians administered them a lifestyle and medical history questionnaire, collected blood and urine samples, and measured BP. Comorbidities in this analysis were defined as follows. Hypertension was defined as an ambulatory systolic BP (SBP) of ≥140 mm Hg and/or diastolic BP of ≥90 mm Hg, or treatment with antihypertensive drugs Diabetes mellitus was defined as a fasting plasma glucose level of ≥126 mg/dl, 2-hour plasma glucose level of ≥200 mg/dl, or treatment with hypoglycemic agents Dyslipidemia was defined as low-density lipoprotein cholesterol levels of ≥140 mg/dl, high-density lipoprotein cholesterol levels of <40 mg/dl, triglyceride levels of ≥150 mg/dl, or treatment with specific lipid-lowering agents. The baseline height and weight of the patients were recorded, and the body mass index was calculated. Serum creatinine levels were measured using an enzymatic method. The estimated glomerular filtration rate (eGFR) was calculated using the Japanese Society of Nephrology formula11 as follows:  eGFR(ml/min/1.73m2)=194×serumcreatinine−1.094×age−0.287×0.739(if female). Semiquantitative assessment of intrarenal preglomerular vessels In brief, 2–3 layers of smooth muscle cells obtained from preglomerular arterioles, including the afferent arteriole and small interlobular artery, were evaluated. Hyalinosis lesions were identified as pink and amorphous in periodic acid-Schiff-stained arteriolar wall sections. Arteriolar hyalinosis was semiquantitatively assessed in each specimen using a modified grading system established by Bader and Kubo12,13 as follows: grade 0 (G0), no vessel wall hyalinosis; grade 1 (G1), hyalinosis covering less than a quarter of the vessel wall circumference; grade 2 (G2), hyalinosis covering a quarter to half of the vessel wall circumference; and grade 3 (G3), hyalinosis covering more than half of the vessel wall circumference.9 Therefore, the mean grade of renal arteriolar hyalinosis (arteriolar hyalinosis index) was calculated for each patient according to the following formula:  arteriolar hyalinosis index=(n0×0 +n1×1+n2×2+n3×3)/N. Here, n1, n2, and n3 indicate the numbers of arterioles with hyalinosis grades of G1, G2, and G3, respectively, and N indicates the total number of arterioles. Representative microphotographs of each arteriolar hyalinosis grade are shown in our previous report.9 All histological analyses were performed by a single physician who was blinded to all patient data. Statistical analysis The Mann–Whitney or chi-square test was used to analyze the differences between the groups. We previously reported that the uric acid threshold levels, above which the risk for developing hyalinosis in preglomerular arterioles increases, were 5 and 7 mg/dl for females and males, respectively.9 Thus, HU was defined as using urate-lowering drugs or a uric acid level of ≥5 and ≥7 mg/dl in females and males, respectively. Univariate regression analyses were performed to assess the association between log-transformed SBP and log-transformed urine protein (UP) level for the presence of HU. Because we previously confirmed that the association between log-transformed SBP and log-transformed UP is prevalent only among patients with HU, we conducted multiple regression analyses to examine the effect of interaction between log-transformed SBP and HU on log-transformed UP using their interaction term. We adjusted for age, sex, and potential confounding factors, with p values of ≤0.3 for the univariate model. The following covariates were included in the adjusted models: age and sex in model 1 and age, sex, presence of diabetes mellitus, eGFR, and presence of IgA nephropathy in model 2. We further adjusted for a log-transformed hyalinosis index along with the variables used in model 2 (model 3) to examine the association of arteriolar hyalinosis with the interaction between log-transformed SBP and HU. Only for patients with IgA nephropathy, the correlation between log-transformed SBP and log-transformed UP was examined based on the presence of HU to exclude the potential effects of different primary diseases on proteinuria. Moreover, the correlation between log-transformed SBP and log-transformed mean glomerular diameter was examined in patients based on the presence of HU to explore the potential mechanisms for the effect of this interaction on proteinuria. Analyses were performed using the StatView (SAS Institute, Cary, NC) and JMP 10 (SAS Institute) softwares. Continuous data are expressed as median (interquartile ranges) or mean ± SD. For all analyses, a P value of <0.05 was considered to be statistically significant. RESULTS The characteristics of the participants according to their uric acid levels are summarized in Table 1. Significantly older ages; higher prevalence of hypertension, diabetes mellitus, and dyslipidemia; and higher UPs and lower eGFRs were observed in patients with HU than in those without HU. BP levels were comparable between the patient groups. Table 1. Baseline clinical characteristics of patients based on the presence of hyperuricemia   Hyperuricemia (−) (n = 50)  Hyperuricemia (+) (n = 59)  P value  Age, years  32 (20–44)  45 (31–59)  0.004  Male, n (%)  32 (64)  23 (39)  0.02  Body mass index, kg/m2  22.3 (19.4–24.7)  24.8 (21.8–27.5)  0.002  Systolic blood pressure, mm Hg  121 (114–130)  130 (111–140)  0.56  Diastolic blood pressure, mm Hg  74 (68–80)  75 (70–80)  0.63  eGFR, ml/min/1.73 m2  99 (77–119)  69 (49–92)  0.0005  Proteinuria, g/gCr  0.7 (0.3–1.5)  1.2 (0.5–1.7)  0.02  Serum uric acid, mg/dl  5.4 (4.5–6.5)  7.0 (5.9–7.8)  <0.0001  Total cholesterol, mg/dl  196 (169–222)  206 (183–237)  0.10  High-density lipoprotein cholesterol, mg/dl  60 (47–70)  55 (44–68)  0.34  Triglyceride, mg/dl  110 (83–150)  152 (95–232)  0.02  Hypertension, n (%)  12 (24)  27 (46)  0.03  Diabetes mellitus, n (%)  3 (6)  7 (12)  0.47  Dyslipidemia, n (%)  18 (36)  31 (53)  0.12  Smoking status, n (%)  18 (36)  20 (34)  0.98  Urate-lowering drug, n (%)  0 (0)  6 (10)  0.06  Antihypertensive drug, n (%)  2 (4)  7 (12)  0.25  Arteriolar hyalinosis index  0.0 (0.0–0.3)  0.3 (0.0–1.0)  0.004  Mean glomerular size (µm)  156 (140–175)  168 (154–186)  0.02  Maximum glomerular size (µm)  212 (193–239)  226 (208–251)  0.006    Hyperuricemia (−) (n = 50)  Hyperuricemia (+) (n = 59)  P value  Age, years  32 (20–44)  45 (31–59)  0.004  Male, n (%)  32 (64)  23 (39)  0.02  Body mass index, kg/m2  22.3 (19.4–24.7)  24.8 (21.8–27.5)  0.002  Systolic blood pressure, mm Hg  121 (114–130)  130 (111–140)  0.56  Diastolic blood pressure, mm Hg  74 (68–80)  75 (70–80)  0.63  eGFR, ml/min/1.73 m2  99 (77–119)  69 (49–92)  0.0005  Proteinuria, g/gCr  0.7 (0.3–1.5)  1.2 (0.5–1.7)  0.02  Serum uric acid, mg/dl  5.4 (4.5–6.5)  7.0 (5.9–7.8)  <0.0001  Total cholesterol, mg/dl  196 (169–222)  206 (183–237)  0.10  High-density lipoprotein cholesterol, mg/dl  60 (47–70)  55 (44–68)  0.34  Triglyceride, mg/dl  110 (83–150)  152 (95–232)  0.02  Hypertension, n (%)  12 (24)  27 (46)  0.03  Diabetes mellitus, n (%)  3 (6)  7 (12)  0.47  Dyslipidemia, n (%)  18 (36)  31 (53)  0.12  Smoking status, n (%)  18 (36)  20 (34)  0.98  Urate-lowering drug, n (%)  0 (0)  6 (10)  0.06  Antihypertensive drug, n (%)  2 (4)  7 (12)  0.25  Arteriolar hyalinosis index  0.0 (0.0–0.3)  0.3 (0.0–1.0)  0.004  Mean glomerular size (µm)  156 (140–175)  168 (154–186)  0.02  Maximum glomerular size (µm)  212 (193–239)  226 (208–251)  0.006  Abbreviation: eGFR, estimated glomerular filtration rate. View Large Patients without HU had the following underlying kidney diseases [numbers (%)]: IgA nephropathy, 35 (70); primary glomerular diseases other than IgA nephropathy, 4 (8); lupus nephritis or vasculitis, 2 (4); nephrosclerosis, 2 (4); hereditary nephritis, 2 (4); and others, 5 (10). Similarly, patients with HU had the following diseases: IgA nephropathy, 35 (59.3); primary glomerular diseases other than IgA nephropathy, 7 (11.9); lupus nephritis, 1 (1.7); nephrosclerosis, 8 (13.6); hereditary nephritis, 4 (6.8); and others, 4 (6.8). Altogether, IgA nephropathy was the most frequent underlying kidney disease in both patient groups, whereas nephrosclerosis was considerably frequent among patients with HU. Association between BP and UP based on the presence of HU A positive correlation existed between log-transformed SBP and log-transformed UP in patients with HU but not in those without HU (Figure 1). Different definition of HU such as ≥6 or ≥7 mg/dl of uric acid in female did not affect the results. Moreover, there were similar positive correlation even after exclusion of the patients who were treated with diuretics or urate-lowering drugs (data were not shown). While, there were significant negative correlation between SBP and eGFR in both patients with and without HU (data were not shown). Figure 1. View largeDownload slide Association between log-transformed systolic blood pressure and log-transformed urine protein level based on the presence of hyperuricemia. Figure 1. View largeDownload slide Association between log-transformed systolic blood pressure and log-transformed urine protein level based on the presence of hyperuricemia. Effect of interaction between log-transformed SBP and HU on log-transformed UP The interaction between HU and log-transformed SBP remained statistically significant in model 2; however, no statistical significance existed after additional adjustment for the arteriolar hyalinosis index (Table 2). Table 2. Interaction between log-transformed systolic blood pressure and hyperuricemia on log-transformed urine protein level   Model 1  Model 2  Model 3  Adjusted R2 = 0.21  Adjusted R2 = 0.21  Adjusted R2 = 0.11  P < 0.0001  P = 0.0001  P = 0.085    β  SE  P value  β  SE  P value  β  SE  P value  Log (SBP)  −0.08  1.22  0.62  −0.13  1.3  0.45  0.06  2.0  0.83  Hyperuricemia, yes  −6.66  2.9  0.03  −6.84  2.9  0.03  0.37  4.7  0.94  Log(SBP) * hyperuricemia  6.81  1.39  0.03  6.96  1.4  0.03  −0.13  2.2  0.98    Model 1  Model 2  Model 3  Adjusted R2 = 0.21  Adjusted R2 = 0.21  Adjusted R2 = 0.11  P < 0.0001  P = 0.0001  P = 0.085    β  SE  P value  β  SE  P value  β  SE  P value  Log (SBP)  −0.08  1.22  0.62  −0.13  1.3  0.45  0.06  2.0  0.83  Hyperuricemia, yes  −6.66  2.9  0.03  −6.84  2.9  0.03  0.37  4.7  0.94  Log(SBP) * hyperuricemia  6.81  1.39  0.03  6.96  1.4  0.03  −0.13  2.2  0.98  Variables used for adjustment: model 1, log (SBP), hyperuricemia, log (SBP) * hyperuricemia, age, and sex; model 2, model 1 + diabetes mellitus, estimated glomerular filtration rate, IgA nephropathy; model 3, model 2 + log (hyalinosis index). Abbreviation: SBP, systolic blood pressure. View Large Association between BP and UP and mean glomerular diameter based on the presence of HU in patients with IgA nephropathy A significant positive correlation existed between log-transformed SBP and log-transformed UP in patients with both HU and IgA nephropathy (Figure 2). Moreover, log-transformed SBP was correlated with log-transformed mean glomerular diameter in these patients (Figure 3). We further examined the changes in eGFR (%) according to the SBP category by the presence of HU in the patients with IgA nephropathy. The changes in eGFR (%) of the patients with HU was more than twice as high as the change of those without it in each SBP category (<130 mm Hg, −17.2 vs. −3.2; 130–140 mm Hg, −16.0 vs. −6.6; ≥140 mm Hg, −35.5 vs. −18.4, analysis of variance P < 0.0001). Figure 2. View largeDownload slide Association between log-transformed systolic blood pressure and log-transformed urine protein level based on the presence of hyperuricemia among patients with IgA nephropathy. Figure 2. View largeDownload slide Association between log-transformed systolic blood pressure and log-transformed urine protein level based on the presence of hyperuricemia among patients with IgA nephropathy. Figure 3. View largeDownload slide Association between log-transformed systolic blood pressure and log-transformed mean glomerular diameter based on the presence of hyperuricemia among patients with IgA nephropathy. Figure 3. View largeDownload slide Association between log-transformed systolic blood pressure and log-transformed mean glomerular diameter based on the presence of hyperuricemia among patients with IgA nephropathy. DISCUSSION The susceptibility to BP-dependent renal damage is modified in some clinical conditions.14–17 This study revealed that an increased BP was linearly correlated with increased proteinuria among patients with both CKD and HU but not among those with CKD but without HU. Moreover, the interaction between HU and SBP at a higher proteinuria levels remained significant despite adjustment for various confounding factors. These findings suggested that patients with CKD and HU are more susceptible to hypertensive renal damage than those with CKD but without HU. Adjustments for arteriolar hyalinosis index completely eliminated the significance of this interaction, suggesting that arteriolar hyalinosis is responsible for the augmented susceptibility owing to HU. Some mechanisms may be responsible for the positive correlation between BP and proteinuria in patients with both CKD and HU. First, the relatively higher prevalence of hypertension among patients with HU may affect the results. However, absolute BP levels were comparable between the groups, presumably because of an antihypertensive treatment. Thus, hypertension itself may not have affected the results. Second, patients with HU were characterized by a higher prevalence of comorbidities such as diabetes, possibly because diabetes mellitus could be associated with a higher susceptibility to hypertensive renal damage.17 The interaction between HU and BP significantly affected proteinuria despite the adjustment for potential confounding factors such as diabetes mellitus. Thus, HU may be independently associated with augmented BP-dependent glomerular damage. Moreover, HU was negatively correlated with proteinuria, implying that combined high BP and HU may have a fundamental role in increased proteinuria. The causality of HU in increasing the susceptibility to BP-dependent proteinuria could not be determined in this study because of its cross-sectional design. However, previous experimental report suggested that HU plays a causative role in the development of hypertensive renal damage.8 We reported that a higher uric acid level was associated with renal arteriolar hyalinosis.9 In an animal model of HU, hypertension and renal damage were developed in association with renal arteriolopathy, characterized by hyalinosis and medial thickening.8 Additionally, hyalinosis in afferent arterioles is a potential marker for disrupted afferent arteriole autoregulation.18,19 Uric acid may increase the susceptibility to hypertensive renal damage in association with disrupted autoregulation mechanisms due to renal arteriolar hyalinosis. Consistent with this hypothesis, the significance of this interaction was completely eliminated after adjusting for the renal arteriolar hyalinosis index. HU reportedly induces the elevation of glomerular BP in a progressive renal disease model.20 Moreover, xanthine oxidase inhibitor prevents glomerular hypertension even in the presence of systemic hypertension.21 Our findings are consistent with this hypothesis. Our study results may have important clinical implications for patients with CKD. A recent large-scaled epidemiological study showed that high uric acid levels were significantly associated with the incidence of albuminuria.22 In this study, HU coexisting with hypertension had a considerable effect on proteinuria, although HU alone was negatively associated with proteinuria. A previous epidemiological study showed that an association between uric acid level and the incidence of CKD was most prevalent among hypertensive subjects,6 suggesting that HU has a considerable effect on renal progression when accompanied by hypertension. Moreover, the present study may provide a hint to understanding the mechanisms of gender differences in the relationship between incident CKD and uric acid levels.1 Previous, our study showed gender difference in threshold levels of uric acid for arteriolar hyalinosis as 5 mg/dl for females and 7 mg/dl for males.9 Using definition of HU based on this threshold levels, the present study showed clear difference in the relationship between SBP and proteinuria by the presence of HU. These findings suggested even 5 mg/dl of uric acid levels may cause higher susceptibility to hypertensive renal damage in female. Consistent with this hypothesis, augmented relationship between uric acid levels and incident CKD of female are shown to be more definite than that of male.6 This study has some limitations. First, we did not observe actual changes in proteinuria across a wide SBP range in each patient. Therefore, further studies are required to determine the role of HU in hypertensive renal damage. Second, the study included patients with various primary diseases. Hence, the effect of primary diseases on BP may have affected glomerular protein permeability, eventually affecting our study results. Nevertheless, we observed a similar correlation between log-transformed SBP and log-transformed UP only in patients with HU despite limiting the analysis to patients with IgA nephropathy. Moreover, HU was associated with augmentation of greater decline in eGFR according to the SBP category among the patients with IgA nephropathy. Previous study had also demonstrated that patients with HU had greater decline in creatinine clearance than those without it among the patients with IgA nephtopathy.23 Therefore, HU along with hypertension may play a role in progression of CKD, which is independent of primary diseases. Third, the relatively small number of patients with hypertension among those without HU may have affected the ability of our analysis to detect any association between BP and proteinuria. Hypertension is more common in patients without HU than in those with HU.24 Accordingly, it is inevitable that the number of patients with hypertension but without HU would be low. Fourth, a limited specimen volume, characteristic of renal biopsy, may have resulted in a sampling bias. Generally, sampling bias tends to make specific associations listen. Moreover, we observed linear correlations of the hyalinosis grade with age and BP (data not shown), which was consistent with previous autopsy-based study results.13 Therefore, the effects of this bias may be minimal. Finally, since we exclude the patients with renin–angiotensin system inhibitors that could affect proteinuria independent of SBP levels, a large-scale study is needed to elucidate the role of HU in hypertensive renal damage among those with renin–angiotensin system inhibitors. In conclusion, an association between HU and an augmented effect of high BP on proteinuria among patients with nonnephrotic CKD who underwent renal biopsy was observed. Moreover, this association disappeared after adjusting for renal arteriolar hyalinosis. These findings suggest that HU enhances the susceptibility to hypertensive renal damage via disruption of the autoregulation system. Further studies are required to define the role of the interaction between HU and BP in CKD progression. DISCLOSURE The authors declared no conflict of interest. ACKNOWLEDGMENTS The authors are grateful to the nursing staff, medical assistant staff, and nephrologists at Ryukyu University Hospital. REFERENCES 1. Iseki K, Oshiro S, Tozawa M, Iseki C, Ikemiya Y, Takishita S. Significance of hyperuricemia on the early detection of renal failure in a cohort of screened subjects. Hypertens Res  2001; 24: 691– 697. Google Scholar CrossRef Search ADS PubMed  2. Iseki K, Ikemiya Y, Inoue T, Iseki C, Kinjo K, Takishita S. Significance of hyperuricemia as a risk factor for developing ESRD in a screened cohort. Am J Kidney Dis  2004; 44: 642– 650. Google Scholar CrossRef Search ADS PubMed  3. Johnson RJ, Nakagawa T, Jalal D, Sánchez-Lozada LG, Kang DH, Ritz E. Uric acid and chronic kidney disease: which is chasing which? Nephrol Dial Transplant  2013; 28: 2221– 2228. Google Scholar CrossRef Search ADS PubMed  4. Bose B, Badve SV, Hiremath SS, Boudville N, Brown FG, Cass A, de Zoysa JR, Fassett RG, Faull R, Harris DC, Hawley CM, Kanellis J, Palmer SC, Perkovic V, Pascoe EM, Rangan GK, Walker RJ, Walters G, Johnson DW. Effects of uric acid-lowering therapy on renal outcomes: a systematic review and meta-analysis. Nephrol Dial Transplant  2014; 29: 406– 413. Google Scholar CrossRef Search ADS PubMed  5. Kanji T, Gandhi M, Clase CM, Yang R. Urate lowering therapy to improve renal outcomes in patients with chronic kidney disease: systematic review and meta-analysis. BMC Nephrol  2015; 16: 58. Google Scholar CrossRef Search ADS PubMed  6. Obermayr RP, Temml C, Gutjahr G, Knechtelsdorfer M, Oberbauer R, Klauser-Braun R. Elevated uric acid increases the risk for kidney disease. J Am Soc Nephrol  2008; 19: 2407– 2413. Google Scholar CrossRef Search ADS PubMed  7. Mazzali M, Hughes J, Kim YG, Jefferson JA, Kang DH, Gordon KL, Lan HY, Kivlighn S, Johnson RJ. Elevated uric acid increases blood pressure in the rat by a novel crystal-independent mechanism. Hypertension  2001; 38: 1101– 1106. Google Scholar CrossRef Search ADS PubMed  8. Mazzali M, Kanellis J, Han L, Feng L, Xia YY, Chen Q, Kang DH, Gordon KL, Watanabe S, Nakagawa T, Lan HY, Johnson RJ. Hyperuricemia induces a primary renal arteriolopathy in rats by a blood pressure-independent mechanism. Am J Physiol Renal Physiol  2002; 282: F991– F997. Google Scholar CrossRef Search ADS PubMed  9. Kohagura K, Kochi M, Miyagi T, Kinjyo T, Maehara Y, Nagahama K, Sakima A, Iseki K, Ohya Y. An association between uric acid levels and renal arteriolopathy in chronic kidney disease: a biopsy-based study. Hypertens Res  2013; 36: 43– 49. Google Scholar CrossRef Search ADS PubMed  10. Sgouralis I, Layton AT. Theoretical assessment of renal autoregulatory mechanisms. Am J Physiol Renal Physiol  2014; 306: F1357– F1371. Google Scholar CrossRef Search ADS PubMed  11. Matsuo S, Imai E, Horio M, Yasuda Y, Tomita K, Nitta K, Yamagata K, Tomino Y, Yokoyama H, Hishida A; Collaborators developing the Japanese equation for estimated GFR. Revised equations for estimated GFR from serum creatinine in Japan. Am J Kidney Dis  2009; 53: 982– 992. Google Scholar CrossRef Search ADS PubMed  12. Bader H, Meyer DS. The size of the juxtaglomerular apparatus in diabetic glomerulosclerosis and its correlation with arteriolosclerosis and arterial hypertension: a morphometric light microscopic study on human renal biopsies. Clin Nephrol  1977; 8: 308– 311. Google Scholar PubMed  13. Kubo M, Kiyohara Y, Kato I, Tanizaki Y, Katafuchi R, Hirakata H, Okuda S, Tsuneyoshi M, Sueishi K, Fujishima M, Iida M. Risk factors for renal glomerular and vascular changes in an autopsy-based population survey: the Hisayama study. Kidney Int  2003; 63: 1508– 1515. Google Scholar CrossRef Search ADS PubMed  14. Bidani AK, Griffin KA. Pathophysiology of hypertensive renal damage: implications for therapy. Hypertension  2004; 44: 595– 601. Google Scholar CrossRef Search ADS PubMed  15. Bidani AK, Griffin KA. Basic science: hypertensive target organ damage. J Am Soc Hypertens  2015; 9: 235– 7; quiz 238. Google Scholar CrossRef Search ADS PubMed  16. Toto RD, Greene T, Hebert LA, Hiremath L, Lea JP, Lewis JB, Pogue V, Sika M, Wang X; AASK Collaborative Research Group. Relationship between body mass index and proteinuria in hypertensive nephrosclerosis: results from the African American Study of Kidney Disease and Hypertension (AASK) cohort. Am J Kidney Dis  2010; 56: 896– 906. Google Scholar CrossRef Search ADS PubMed  17. Fotheringham J, Odudu A, McKane W, Ellam T. Modification of the relationship between blood pressure and renal albumin permeability by impaired excretory function and diabetes. Hypertension  2015; 65: 510– 516. Google Scholar CrossRef Search ADS PubMed  18. Hill GS, Heudes D, Jacquot C, Gauthier E, Bariéty J. Morphometric evidence for impairment of renal autoregulation in advanced essential hypertension. Kidney Int  2006; 69: 823– 831. Google Scholar CrossRef Search ADS PubMed  19. Zamami R, Kohagura K, Miyagi T, Kinjyo T, Shiota K, Ohya Y. Modification of the impact of hypertension on proteinuria by renal arteriolar hyalinosis in nonnephrotic chronic kidney disease. J Hypertens  2016; 34: 2274– 2279. Google Scholar CrossRef Search ADS PubMed  20. Sánchez-Lozada LG, Tapia E, Santamaría J, Avila-Casado C, Soto V, Nepomuceno T, Rodríguez-Iturbe B, Johnson RJ, Herrera-Acosta J. Mild hyperuricemia induces vasoconstriction and maintains glomerular hypertension in normal and remnant kidney rats. Kidney Int  2005; 67: 237– 247. Google Scholar CrossRef Search ADS PubMed  21. Sánchez-Lozada LG, Tapia E, Soto V, Avila-Casado C, Franco M, Wessale JL, Zhao L, Johnson RJ. Effect of febuxostat on the progression of renal disease in 5/6 nephrectomy rats with and without hyperuricemia. Nephron Physiol  2008; 108: p69– p78. Google Scholar CrossRef Search ADS PubMed  22. Takae K, Nagata M, Hata J, Mukai N, Hirakawa Y, Yoshida D, Kishimoto H, Tsuruya K, Kitazono T, Kiyohara Y, Ninomiya T. Serum uric acid as a risk factor for chronic kidney disease in a Japanese Community - the Hisayama study. Circ J  2016; 80: 1857– 1862. Google Scholar CrossRef Search ADS PubMed  23. Ohno I, Hosoya T, Gomi H, Ichida K, Okabe H, Hikita M. Serum uric acid and renal prognosis in patients with IgA nephropathy. Nephron  2001; 87: 333– 339. Google Scholar CrossRef Search ADS PubMed  24. Kuwabara M, Niwa K, Nishi Y, Mizuno A, Asano T, Masuda K, Komatsu I, Yamazoe M, Takahashi O, Hisatome I. Relationship between serum uric acid levels and hypertension among Japanese individuals not treated for hyperuricemia and hypertension. Hypertens Res  2014; 37: 785– 789. Google Scholar CrossRef Search ADS PubMed  © American Journal of Hypertension, Ltd 2017. All rights reserved. For Permissions, please email: journals.permissions@oup.com http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png American Journal of Hypertension Oxford University Press

Augmented Association Between Blood Pressure and Proteinuria in Hyperuricemic Patients With Nonnephrotic Chronic Kidney Disease

Loading next page...
 
/lp/ou_press/augmented-association-between-blood-pressure-and-proteinuria-in-wZIN3Awq00
Publisher
Oxford University Press
Copyright
© American Journal of Hypertension, Ltd 2017. All rights reserved. For Permissions, please email: journals.permissions@oup.com
ISSN
0895-7061
eISSN
1941-7225
D.O.I.
10.1093/ajh/hpx166
Publisher site
See Article on Publisher Site

Abstract

Abstract BACKGROUND Hyperuricemia (HU) may enhance susceptibility to hypertensive renal damage via disrupted autoregulation of glomerular hemodynamics. The effect of HU on the association between blood pressure (BP) and proteinuria remains unknown in patients with chronic kidney disease (CKD). METHODS In total, 109 patients with nonnephrotic CKD (55 men and 54 females) who underwent renal biopsy were recruited. Arteriolar hyalinosis was semiquantitatively assessed via arteriole grading. Correlation between BP and urine protein (UP) level was examined based on the presence of HU, which was defined as the use of urate-lowering drugs or serum uric acid levels of ≥7 and ≥5 mg/dl in males and females, respectively, which were associated with increased risks of hyalinosis in our previous study. RESULTS Median age, BP, estimated glomerular filtration rate, and UP level were 38 years, 124/74 mm Hg, 82 ml/min/1.73 m2, and 0.8 g/gCr, respectively. In patients with HU (n = 59), log-transformed systolic BP (SBP) was significantly correlated with log-transformed UP level (r = 0.49, P < 0.0001); this was not observed in patients without HU (n = 50). Multiple regression analysis (R2 = 0.21, P = 0.0001) revealed that the interaction between HU and log-transformed SBP with respect to proteinuria was significantly correlated with log-transformed UP level (β = 7.0, P = 0.03), independent of age, sex, and potential confounding factors; however, this statistical significance was completely eliminated after adjustment for the arteriolar hyalinosis index. CONCLUSIONS HU potentiates susceptibility to hypertensive glomerular damage via disrupted autoregulation in patients with nonnephrotic CKD. blood pressure, chronic kidney disease, hypertension, hypertensive renal damage, renal arteriolosclerosis, uric acid Hyperuricemia (HU) is associated with chronic kidney disease (CKD) progression,1,2 and many epidemiological studies have confirmed this association.3 Moreover, some interventional studies showed that urate-lowering therapy using allopurinol slows CKD progression.4,5 These findings suggest that HU contributes to the development of renal dysfunction. Epidemiological studies suggested that HU has a greater impact on the renal outcome among individuals with hypertension than among those without it.6 Although the mechanism underlying the association between renal progression and asymptomatic HU, especially in individuals with hypertension, remains to be determined, crystal- independent mechanisms may be involved. An experimental study using a hyperuricemic rat model showed that renal arteriolopathy may be responsible for renal damage and hypertension progression.7,8 We previously revealed that higher uric acid levels were associated with a higher risk for renal arteriolopathy in patients with CKD who underwent renal biopsy.9 Because the disruption of the autoregulation system in afferent arterioles leads to the direct transmission of increased systemic blood pressure (BP) to the glomeruli,10 preglomerular arteriolopathy may augment hypertensive glomerular damage. Thus, we hypothesized that HU potentiates BP-dependent renal damage in association with renal arteriolopathy. Therefore, we conducted a cross-sectional study to examine the association between BP and proteinuria, a marker for glomerular damage in patients with nonnephrotic CKD, with or without HU. METHODS Settings and participants In total, 207 consecutive patients who underwent renal biopsy at the University of the Ryukyus Hospital from 1 January 2003 to 31 December 2007 were included. Patients receiving renin–angiotensin system inhibitors, steroids, or calcineurin inhibitors and those with tubulointerstitial nephritis were excluded because these factors could affect proteinuria levels independent of the systemic BP. Furthermore, patients with nephrotic CKD, which was defined as serum albumin concentrations of <3 g/gCr, were excluded because glomerular permeability rather than BP appeared to be the main determinant of proteinuria in nephrotic CKD. Finally, 109 patients (55 males and 54 females) were included. The study protocol was approved by the ethics review board of the University of the Ryukyus. All patients provided written informed consents for using their clinical and histological data in our analysis. When patients were admitted for renal biopsy, clinicians administered them a lifestyle and medical history questionnaire, collected blood and urine samples, and measured BP. Comorbidities in this analysis were defined as follows. Hypertension was defined as an ambulatory systolic BP (SBP) of ≥140 mm Hg and/or diastolic BP of ≥90 mm Hg, or treatment with antihypertensive drugs Diabetes mellitus was defined as a fasting plasma glucose level of ≥126 mg/dl, 2-hour plasma glucose level of ≥200 mg/dl, or treatment with hypoglycemic agents Dyslipidemia was defined as low-density lipoprotein cholesterol levels of ≥140 mg/dl, high-density lipoprotein cholesterol levels of <40 mg/dl, triglyceride levels of ≥150 mg/dl, or treatment with specific lipid-lowering agents. The baseline height and weight of the patients were recorded, and the body mass index was calculated. Serum creatinine levels were measured using an enzymatic method. The estimated glomerular filtration rate (eGFR) was calculated using the Japanese Society of Nephrology formula11 as follows:  eGFR(ml/min/1.73m2)=194×serumcreatinine−1.094×age−0.287×0.739(if female). Semiquantitative assessment of intrarenal preglomerular vessels In brief, 2–3 layers of smooth muscle cells obtained from preglomerular arterioles, including the afferent arteriole and small interlobular artery, were evaluated. Hyalinosis lesions were identified as pink and amorphous in periodic acid-Schiff-stained arteriolar wall sections. Arteriolar hyalinosis was semiquantitatively assessed in each specimen using a modified grading system established by Bader and Kubo12,13 as follows: grade 0 (G0), no vessel wall hyalinosis; grade 1 (G1), hyalinosis covering less than a quarter of the vessel wall circumference; grade 2 (G2), hyalinosis covering a quarter to half of the vessel wall circumference; and grade 3 (G3), hyalinosis covering more than half of the vessel wall circumference.9 Therefore, the mean grade of renal arteriolar hyalinosis (arteriolar hyalinosis index) was calculated for each patient according to the following formula:  arteriolar hyalinosis index=(n0×0 +n1×1+n2×2+n3×3)/N. Here, n1, n2, and n3 indicate the numbers of arterioles with hyalinosis grades of G1, G2, and G3, respectively, and N indicates the total number of arterioles. Representative microphotographs of each arteriolar hyalinosis grade are shown in our previous report.9 All histological analyses were performed by a single physician who was blinded to all patient data. Statistical analysis The Mann–Whitney or chi-square test was used to analyze the differences between the groups. We previously reported that the uric acid threshold levels, above which the risk for developing hyalinosis in preglomerular arterioles increases, were 5 and 7 mg/dl for females and males, respectively.9 Thus, HU was defined as using urate-lowering drugs or a uric acid level of ≥5 and ≥7 mg/dl in females and males, respectively. Univariate regression analyses were performed to assess the association between log-transformed SBP and log-transformed urine protein (UP) level for the presence of HU. Because we previously confirmed that the association between log-transformed SBP and log-transformed UP is prevalent only among patients with HU, we conducted multiple regression analyses to examine the effect of interaction between log-transformed SBP and HU on log-transformed UP using their interaction term. We adjusted for age, sex, and potential confounding factors, with p values of ≤0.3 for the univariate model. The following covariates were included in the adjusted models: age and sex in model 1 and age, sex, presence of diabetes mellitus, eGFR, and presence of IgA nephropathy in model 2. We further adjusted for a log-transformed hyalinosis index along with the variables used in model 2 (model 3) to examine the association of arteriolar hyalinosis with the interaction between log-transformed SBP and HU. Only for patients with IgA nephropathy, the correlation between log-transformed SBP and log-transformed UP was examined based on the presence of HU to exclude the potential effects of different primary diseases on proteinuria. Moreover, the correlation between log-transformed SBP and log-transformed mean glomerular diameter was examined in patients based on the presence of HU to explore the potential mechanisms for the effect of this interaction on proteinuria. Analyses were performed using the StatView (SAS Institute, Cary, NC) and JMP 10 (SAS Institute) softwares. Continuous data are expressed as median (interquartile ranges) or mean ± SD. For all analyses, a P value of <0.05 was considered to be statistically significant. RESULTS The characteristics of the participants according to their uric acid levels are summarized in Table 1. Significantly older ages; higher prevalence of hypertension, diabetes mellitus, and dyslipidemia; and higher UPs and lower eGFRs were observed in patients with HU than in those without HU. BP levels were comparable between the patient groups. Table 1. Baseline clinical characteristics of patients based on the presence of hyperuricemia   Hyperuricemia (−) (n = 50)  Hyperuricemia (+) (n = 59)  P value  Age, years  32 (20–44)  45 (31–59)  0.004  Male, n (%)  32 (64)  23 (39)  0.02  Body mass index, kg/m2  22.3 (19.4–24.7)  24.8 (21.8–27.5)  0.002  Systolic blood pressure, mm Hg  121 (114–130)  130 (111–140)  0.56  Diastolic blood pressure, mm Hg  74 (68–80)  75 (70–80)  0.63  eGFR, ml/min/1.73 m2  99 (77–119)  69 (49–92)  0.0005  Proteinuria, g/gCr  0.7 (0.3–1.5)  1.2 (0.5–1.7)  0.02  Serum uric acid, mg/dl  5.4 (4.5–6.5)  7.0 (5.9–7.8)  <0.0001  Total cholesterol, mg/dl  196 (169–222)  206 (183–237)  0.10  High-density lipoprotein cholesterol, mg/dl  60 (47–70)  55 (44–68)  0.34  Triglyceride, mg/dl  110 (83–150)  152 (95–232)  0.02  Hypertension, n (%)  12 (24)  27 (46)  0.03  Diabetes mellitus, n (%)  3 (6)  7 (12)  0.47  Dyslipidemia, n (%)  18 (36)  31 (53)  0.12  Smoking status, n (%)  18 (36)  20 (34)  0.98  Urate-lowering drug, n (%)  0 (0)  6 (10)  0.06  Antihypertensive drug, n (%)  2 (4)  7 (12)  0.25  Arteriolar hyalinosis index  0.0 (0.0–0.3)  0.3 (0.0–1.0)  0.004  Mean glomerular size (µm)  156 (140–175)  168 (154–186)  0.02  Maximum glomerular size (µm)  212 (193–239)  226 (208–251)  0.006    Hyperuricemia (−) (n = 50)  Hyperuricemia (+) (n = 59)  P value  Age, years  32 (20–44)  45 (31–59)  0.004  Male, n (%)  32 (64)  23 (39)  0.02  Body mass index, kg/m2  22.3 (19.4–24.7)  24.8 (21.8–27.5)  0.002  Systolic blood pressure, mm Hg  121 (114–130)  130 (111–140)  0.56  Diastolic blood pressure, mm Hg  74 (68–80)  75 (70–80)  0.63  eGFR, ml/min/1.73 m2  99 (77–119)  69 (49–92)  0.0005  Proteinuria, g/gCr  0.7 (0.3–1.5)  1.2 (0.5–1.7)  0.02  Serum uric acid, mg/dl  5.4 (4.5–6.5)  7.0 (5.9–7.8)  <0.0001  Total cholesterol, mg/dl  196 (169–222)  206 (183–237)  0.10  High-density lipoprotein cholesterol, mg/dl  60 (47–70)  55 (44–68)  0.34  Triglyceride, mg/dl  110 (83–150)  152 (95–232)  0.02  Hypertension, n (%)  12 (24)  27 (46)  0.03  Diabetes mellitus, n (%)  3 (6)  7 (12)  0.47  Dyslipidemia, n (%)  18 (36)  31 (53)  0.12  Smoking status, n (%)  18 (36)  20 (34)  0.98  Urate-lowering drug, n (%)  0 (0)  6 (10)  0.06  Antihypertensive drug, n (%)  2 (4)  7 (12)  0.25  Arteriolar hyalinosis index  0.0 (0.0–0.3)  0.3 (0.0–1.0)  0.004  Mean glomerular size (µm)  156 (140–175)  168 (154–186)  0.02  Maximum glomerular size (µm)  212 (193–239)  226 (208–251)  0.006  Abbreviation: eGFR, estimated glomerular filtration rate. View Large Patients without HU had the following underlying kidney diseases [numbers (%)]: IgA nephropathy, 35 (70); primary glomerular diseases other than IgA nephropathy, 4 (8); lupus nephritis or vasculitis, 2 (4); nephrosclerosis, 2 (4); hereditary nephritis, 2 (4); and others, 5 (10). Similarly, patients with HU had the following diseases: IgA nephropathy, 35 (59.3); primary glomerular diseases other than IgA nephropathy, 7 (11.9); lupus nephritis, 1 (1.7); nephrosclerosis, 8 (13.6); hereditary nephritis, 4 (6.8); and others, 4 (6.8). Altogether, IgA nephropathy was the most frequent underlying kidney disease in both patient groups, whereas nephrosclerosis was considerably frequent among patients with HU. Association between BP and UP based on the presence of HU A positive correlation existed between log-transformed SBP and log-transformed UP in patients with HU but not in those without HU (Figure 1). Different definition of HU such as ≥6 or ≥7 mg/dl of uric acid in female did not affect the results. Moreover, there were similar positive correlation even after exclusion of the patients who were treated with diuretics or urate-lowering drugs (data were not shown). While, there were significant negative correlation between SBP and eGFR in both patients with and without HU (data were not shown). Figure 1. View largeDownload slide Association between log-transformed systolic blood pressure and log-transformed urine protein level based on the presence of hyperuricemia. Figure 1. View largeDownload slide Association between log-transformed systolic blood pressure and log-transformed urine protein level based on the presence of hyperuricemia. Effect of interaction between log-transformed SBP and HU on log-transformed UP The interaction between HU and log-transformed SBP remained statistically significant in model 2; however, no statistical significance existed after additional adjustment for the arteriolar hyalinosis index (Table 2). Table 2. Interaction between log-transformed systolic blood pressure and hyperuricemia on log-transformed urine protein level   Model 1  Model 2  Model 3  Adjusted R2 = 0.21  Adjusted R2 = 0.21  Adjusted R2 = 0.11  P < 0.0001  P = 0.0001  P = 0.085    β  SE  P value  β  SE  P value  β  SE  P value  Log (SBP)  −0.08  1.22  0.62  −0.13  1.3  0.45  0.06  2.0  0.83  Hyperuricemia, yes  −6.66  2.9  0.03  −6.84  2.9  0.03  0.37  4.7  0.94  Log(SBP) * hyperuricemia  6.81  1.39  0.03  6.96  1.4  0.03  −0.13  2.2  0.98    Model 1  Model 2  Model 3  Adjusted R2 = 0.21  Adjusted R2 = 0.21  Adjusted R2 = 0.11  P < 0.0001  P = 0.0001  P = 0.085    β  SE  P value  β  SE  P value  β  SE  P value  Log (SBP)  −0.08  1.22  0.62  −0.13  1.3  0.45  0.06  2.0  0.83  Hyperuricemia, yes  −6.66  2.9  0.03  −6.84  2.9  0.03  0.37  4.7  0.94  Log(SBP) * hyperuricemia  6.81  1.39  0.03  6.96  1.4  0.03  −0.13  2.2  0.98  Variables used for adjustment: model 1, log (SBP), hyperuricemia, log (SBP) * hyperuricemia, age, and sex; model 2, model 1 + diabetes mellitus, estimated glomerular filtration rate, IgA nephropathy; model 3, model 2 + log (hyalinosis index). Abbreviation: SBP, systolic blood pressure. View Large Association between BP and UP and mean glomerular diameter based on the presence of HU in patients with IgA nephropathy A significant positive correlation existed between log-transformed SBP and log-transformed UP in patients with both HU and IgA nephropathy (Figure 2). Moreover, log-transformed SBP was correlated with log-transformed mean glomerular diameter in these patients (Figure 3). We further examined the changes in eGFR (%) according to the SBP category by the presence of HU in the patients with IgA nephropathy. The changes in eGFR (%) of the patients with HU was more than twice as high as the change of those without it in each SBP category (<130 mm Hg, −17.2 vs. −3.2; 130–140 mm Hg, −16.0 vs. −6.6; ≥140 mm Hg, −35.5 vs. −18.4, analysis of variance P < 0.0001). Figure 2. View largeDownload slide Association between log-transformed systolic blood pressure and log-transformed urine protein level based on the presence of hyperuricemia among patients with IgA nephropathy. Figure 2. View largeDownload slide Association between log-transformed systolic blood pressure and log-transformed urine protein level based on the presence of hyperuricemia among patients with IgA nephropathy. Figure 3. View largeDownload slide Association between log-transformed systolic blood pressure and log-transformed mean glomerular diameter based on the presence of hyperuricemia among patients with IgA nephropathy. Figure 3. View largeDownload slide Association between log-transformed systolic blood pressure and log-transformed mean glomerular diameter based on the presence of hyperuricemia among patients with IgA nephropathy. DISCUSSION The susceptibility to BP-dependent renal damage is modified in some clinical conditions.14–17 This study revealed that an increased BP was linearly correlated with increased proteinuria among patients with both CKD and HU but not among those with CKD but without HU. Moreover, the interaction between HU and SBP at a higher proteinuria levels remained significant despite adjustment for various confounding factors. These findings suggested that patients with CKD and HU are more susceptible to hypertensive renal damage than those with CKD but without HU. Adjustments for arteriolar hyalinosis index completely eliminated the significance of this interaction, suggesting that arteriolar hyalinosis is responsible for the augmented susceptibility owing to HU. Some mechanisms may be responsible for the positive correlation between BP and proteinuria in patients with both CKD and HU. First, the relatively higher prevalence of hypertension among patients with HU may affect the results. However, absolute BP levels were comparable between the groups, presumably because of an antihypertensive treatment. Thus, hypertension itself may not have affected the results. Second, patients with HU were characterized by a higher prevalence of comorbidities such as diabetes, possibly because diabetes mellitus could be associated with a higher susceptibility to hypertensive renal damage.17 The interaction between HU and BP significantly affected proteinuria despite the adjustment for potential confounding factors such as diabetes mellitus. Thus, HU may be independently associated with augmented BP-dependent glomerular damage. Moreover, HU was negatively correlated with proteinuria, implying that combined high BP and HU may have a fundamental role in increased proteinuria. The causality of HU in increasing the susceptibility to BP-dependent proteinuria could not be determined in this study because of its cross-sectional design. However, previous experimental report suggested that HU plays a causative role in the development of hypertensive renal damage.8 We reported that a higher uric acid level was associated with renal arteriolar hyalinosis.9 In an animal model of HU, hypertension and renal damage were developed in association with renal arteriolopathy, characterized by hyalinosis and medial thickening.8 Additionally, hyalinosis in afferent arterioles is a potential marker for disrupted afferent arteriole autoregulation.18,19 Uric acid may increase the susceptibility to hypertensive renal damage in association with disrupted autoregulation mechanisms due to renal arteriolar hyalinosis. Consistent with this hypothesis, the significance of this interaction was completely eliminated after adjusting for the renal arteriolar hyalinosis index. HU reportedly induces the elevation of glomerular BP in a progressive renal disease model.20 Moreover, xanthine oxidase inhibitor prevents glomerular hypertension even in the presence of systemic hypertension.21 Our findings are consistent with this hypothesis. Our study results may have important clinical implications for patients with CKD. A recent large-scaled epidemiological study showed that high uric acid levels were significantly associated with the incidence of albuminuria.22 In this study, HU coexisting with hypertension had a considerable effect on proteinuria, although HU alone was negatively associated with proteinuria. A previous epidemiological study showed that an association between uric acid level and the incidence of CKD was most prevalent among hypertensive subjects,6 suggesting that HU has a considerable effect on renal progression when accompanied by hypertension. Moreover, the present study may provide a hint to understanding the mechanisms of gender differences in the relationship between incident CKD and uric acid levels.1 Previous, our study showed gender difference in threshold levels of uric acid for arteriolar hyalinosis as 5 mg/dl for females and 7 mg/dl for males.9 Using definition of HU based on this threshold levels, the present study showed clear difference in the relationship between SBP and proteinuria by the presence of HU. These findings suggested even 5 mg/dl of uric acid levels may cause higher susceptibility to hypertensive renal damage in female. Consistent with this hypothesis, augmented relationship between uric acid levels and incident CKD of female are shown to be more definite than that of male.6 This study has some limitations. First, we did not observe actual changes in proteinuria across a wide SBP range in each patient. Therefore, further studies are required to determine the role of HU in hypertensive renal damage. Second, the study included patients with various primary diseases. Hence, the effect of primary diseases on BP may have affected glomerular protein permeability, eventually affecting our study results. Nevertheless, we observed a similar correlation between log-transformed SBP and log-transformed UP only in patients with HU despite limiting the analysis to patients with IgA nephropathy. Moreover, HU was associated with augmentation of greater decline in eGFR according to the SBP category among the patients with IgA nephropathy. Previous study had also demonstrated that patients with HU had greater decline in creatinine clearance than those without it among the patients with IgA nephtopathy.23 Therefore, HU along with hypertension may play a role in progression of CKD, which is independent of primary diseases. Third, the relatively small number of patients with hypertension among those without HU may have affected the ability of our analysis to detect any association between BP and proteinuria. Hypertension is more common in patients without HU than in those with HU.24 Accordingly, it is inevitable that the number of patients with hypertension but without HU would be low. Fourth, a limited specimen volume, characteristic of renal biopsy, may have resulted in a sampling bias. Generally, sampling bias tends to make specific associations listen. Moreover, we observed linear correlations of the hyalinosis grade with age and BP (data not shown), which was consistent with previous autopsy-based study results.13 Therefore, the effects of this bias may be minimal. Finally, since we exclude the patients with renin–angiotensin system inhibitors that could affect proteinuria independent of SBP levels, a large-scale study is needed to elucidate the role of HU in hypertensive renal damage among those with renin–angiotensin system inhibitors. In conclusion, an association between HU and an augmented effect of high BP on proteinuria among patients with nonnephrotic CKD who underwent renal biopsy was observed. Moreover, this association disappeared after adjusting for renal arteriolar hyalinosis. These findings suggest that HU enhances the susceptibility to hypertensive renal damage via disruption of the autoregulation system. Further studies are required to define the role of the interaction between HU and BP in CKD progression. DISCLOSURE The authors declared no conflict of interest. ACKNOWLEDGMENTS The authors are grateful to the nursing staff, medical assistant staff, and nephrologists at Ryukyu University Hospital. REFERENCES 1. Iseki K, Oshiro S, Tozawa M, Iseki C, Ikemiya Y, Takishita S. Significance of hyperuricemia on the early detection of renal failure in a cohort of screened subjects. Hypertens Res  2001; 24: 691– 697. Google Scholar CrossRef Search ADS PubMed  2. Iseki K, Ikemiya Y, Inoue T, Iseki C, Kinjo K, Takishita S. Significance of hyperuricemia as a risk factor for developing ESRD in a screened cohort. Am J Kidney Dis  2004; 44: 642– 650. Google Scholar CrossRef Search ADS PubMed  3. Johnson RJ, Nakagawa T, Jalal D, Sánchez-Lozada LG, Kang DH, Ritz E. Uric acid and chronic kidney disease: which is chasing which? Nephrol Dial Transplant  2013; 28: 2221– 2228. Google Scholar CrossRef Search ADS PubMed  4. Bose B, Badve SV, Hiremath SS, Boudville N, Brown FG, Cass A, de Zoysa JR, Fassett RG, Faull R, Harris DC, Hawley CM, Kanellis J, Palmer SC, Perkovic V, Pascoe EM, Rangan GK, Walker RJ, Walters G, Johnson DW. Effects of uric acid-lowering therapy on renal outcomes: a systematic review and meta-analysis. Nephrol Dial Transplant  2014; 29: 406– 413. Google Scholar CrossRef Search ADS PubMed  5. Kanji T, Gandhi M, Clase CM, Yang R. Urate lowering therapy to improve renal outcomes in patients with chronic kidney disease: systematic review and meta-analysis. BMC Nephrol  2015; 16: 58. Google Scholar CrossRef Search ADS PubMed  6. Obermayr RP, Temml C, Gutjahr G, Knechtelsdorfer M, Oberbauer R, Klauser-Braun R. Elevated uric acid increases the risk for kidney disease. J Am Soc Nephrol  2008; 19: 2407– 2413. Google Scholar CrossRef Search ADS PubMed  7. Mazzali M, Hughes J, Kim YG, Jefferson JA, Kang DH, Gordon KL, Lan HY, Kivlighn S, Johnson RJ. Elevated uric acid increases blood pressure in the rat by a novel crystal-independent mechanism. Hypertension  2001; 38: 1101– 1106. Google Scholar CrossRef Search ADS PubMed  8. Mazzali M, Kanellis J, Han L, Feng L, Xia YY, Chen Q, Kang DH, Gordon KL, Watanabe S, Nakagawa T, Lan HY, Johnson RJ. Hyperuricemia induces a primary renal arteriolopathy in rats by a blood pressure-independent mechanism. Am J Physiol Renal Physiol  2002; 282: F991– F997. Google Scholar CrossRef Search ADS PubMed  9. Kohagura K, Kochi M, Miyagi T, Kinjyo T, Maehara Y, Nagahama K, Sakima A, Iseki K, Ohya Y. An association between uric acid levels and renal arteriolopathy in chronic kidney disease: a biopsy-based study. Hypertens Res  2013; 36: 43– 49. Google Scholar CrossRef Search ADS PubMed  10. Sgouralis I, Layton AT. Theoretical assessment of renal autoregulatory mechanisms. Am J Physiol Renal Physiol  2014; 306: F1357– F1371. Google Scholar CrossRef Search ADS PubMed  11. Matsuo S, Imai E, Horio M, Yasuda Y, Tomita K, Nitta K, Yamagata K, Tomino Y, Yokoyama H, Hishida A; Collaborators developing the Japanese equation for estimated GFR. Revised equations for estimated GFR from serum creatinine in Japan. Am J Kidney Dis  2009; 53: 982– 992. Google Scholar CrossRef Search ADS PubMed  12. Bader H, Meyer DS. The size of the juxtaglomerular apparatus in diabetic glomerulosclerosis and its correlation with arteriolosclerosis and arterial hypertension: a morphometric light microscopic study on human renal biopsies. Clin Nephrol  1977; 8: 308– 311. Google Scholar PubMed  13. Kubo M, Kiyohara Y, Kato I, Tanizaki Y, Katafuchi R, Hirakata H, Okuda S, Tsuneyoshi M, Sueishi K, Fujishima M, Iida M. Risk factors for renal glomerular and vascular changes in an autopsy-based population survey: the Hisayama study. Kidney Int  2003; 63: 1508– 1515. Google Scholar CrossRef Search ADS PubMed  14. Bidani AK, Griffin KA. Pathophysiology of hypertensive renal damage: implications for therapy. Hypertension  2004; 44: 595– 601. Google Scholar CrossRef Search ADS PubMed  15. Bidani AK, Griffin KA. Basic science: hypertensive target organ damage. J Am Soc Hypertens  2015; 9: 235– 7; quiz 238. Google Scholar CrossRef Search ADS PubMed  16. Toto RD, Greene T, Hebert LA, Hiremath L, Lea JP, Lewis JB, Pogue V, Sika M, Wang X; AASK Collaborative Research Group. Relationship between body mass index and proteinuria in hypertensive nephrosclerosis: results from the African American Study of Kidney Disease and Hypertension (AASK) cohort. Am J Kidney Dis  2010; 56: 896– 906. Google Scholar CrossRef Search ADS PubMed  17. Fotheringham J, Odudu A, McKane W, Ellam T. Modification of the relationship between blood pressure and renal albumin permeability by impaired excretory function and diabetes. Hypertension  2015; 65: 510– 516. Google Scholar CrossRef Search ADS PubMed  18. Hill GS, Heudes D, Jacquot C, Gauthier E, Bariéty J. Morphometric evidence for impairment of renal autoregulation in advanced essential hypertension. Kidney Int  2006; 69: 823– 831. Google Scholar CrossRef Search ADS PubMed  19. Zamami R, Kohagura K, Miyagi T, Kinjyo T, Shiota K, Ohya Y. Modification of the impact of hypertension on proteinuria by renal arteriolar hyalinosis in nonnephrotic chronic kidney disease. J Hypertens  2016; 34: 2274– 2279. Google Scholar CrossRef Search ADS PubMed  20. Sánchez-Lozada LG, Tapia E, Santamaría J, Avila-Casado C, Soto V, Nepomuceno T, Rodríguez-Iturbe B, Johnson RJ, Herrera-Acosta J. Mild hyperuricemia induces vasoconstriction and maintains glomerular hypertension in normal and remnant kidney rats. Kidney Int  2005; 67: 237– 247. Google Scholar CrossRef Search ADS PubMed  21. Sánchez-Lozada LG, Tapia E, Soto V, Avila-Casado C, Franco M, Wessale JL, Zhao L, Johnson RJ. Effect of febuxostat on the progression of renal disease in 5/6 nephrectomy rats with and without hyperuricemia. Nephron Physiol  2008; 108: p69– p78. Google Scholar CrossRef Search ADS PubMed  22. Takae K, Nagata M, Hata J, Mukai N, Hirakawa Y, Yoshida D, Kishimoto H, Tsuruya K, Kitazono T, Kiyohara Y, Ninomiya T. Serum uric acid as a risk factor for chronic kidney disease in a Japanese Community - the Hisayama study. Circ J  2016; 80: 1857– 1862. Google Scholar CrossRef Search ADS PubMed  23. Ohno I, Hosoya T, Gomi H, Ichida K, Okabe H, Hikita M. Serum uric acid and renal prognosis in patients with IgA nephropathy. Nephron  2001; 87: 333– 339. Google Scholar CrossRef Search ADS PubMed  24. Kuwabara M, Niwa K, Nishi Y, Mizuno A, Asano T, Masuda K, Komatsu I, Yamazoe M, Takahashi O, Hisatome I. Relationship between serum uric acid levels and hypertension among Japanese individuals not treated for hyperuricemia and hypertension. Hypertens Res  2014; 37: 785– 789. Google Scholar CrossRef Search ADS PubMed  © American Journal of Hypertension, Ltd 2017. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Journal

American Journal of HypertensionOxford University Press

Published: Apr 1, 2018

There are no references for this article.

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off