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. 2021 Mar 25;16(3):e0249240. doi: 10.1371/journal.pone.0249240

Different clinical impact of hyperuricemia according to etiologies of chronic kidney disease: Gonryo Study

Kimio Watanabe 1,*, Masaaki Nakayama 1,2, Tae Yamamoto 3, Gen Yamada 4, Hiroshi Sato 5, Mariko Miyazaki 6,7, Sadayoshi Ito 7,8
Editor: Ping-Hsun Wu9
PMCID: PMC7993817  PMID: 33765101

Abstract

Background

Hyperuricemia is highly prevalent in chronic kidney disease (CKD) patients, but the evidence for a relationship between uric acid (UA) and clinical outcomes in CKD patients is limited and inconsistent. We hypothesized that UA has a different impact on clinical outcomes according to the underlying disease causing CKD.

Methods

This study prospectively investigated the associations between UA and renal and non-renal outcomes according to the underlying disease causing CKD in 2,797 Japanese patients under the care of nephrologists. The patients were categorized into four groups: primary renal disease (n = 1306), hypertensive nephropathy (n = 467), diabetic nephropathy (n = 275), and other nephropathy (n = 749). The renal outcome was defined as end-stage renal disease (ESRD), and the non-renal outcome was defined as a composite endpoint of cardiovascular events (CVEs) and all-cause mortality.

Results

During a median 4.8-year follow-up, 359 (12.8%) patients reached the renal outcome, and 260 (9.3%) reached the non-renal outcome. In the all-patient analysis, hyperuricemia was not associated with the risks for renal and non-renal outcomes, but in primary renal disease (PRD) and hypertensive renal disease (HTN) patients, hyperuricemia was significantly associated with non-renal outcomes. Per 1 mg/dl higher UA level, multivariable adjusted hazard ratio was 1.248 (95% CI: 1.003 to 1.553) for PRD, and 1.250 (1.035 to 1.510) for HTN. Allopurinol did not reduce the risks for renal and non-renal outcomes, both in all patients and in the subgroup analysis.

Conclusions

The effect of hyperuricemia on clinical outcomes in CKD patients varies according to the underlying disease causing CKD. Hyperuricemia is an independent risk factor for non-renal outcomes in primary renal disease and hypertensive renal disease patients. Allopurinol did not decrease the risks for renal and non-renal outcomes.

Introduction

Previous epidemiological studies of the general population showed the independent effect of hyperuricemia on the risk for renal outcomes, such as development of chronic kidney disease (CKD), or non-renal outcomes, such as cardiovascular events (CVEs) and deaths [1–6]. However, the evidence regarding the relationship between uric acid (UA) and clinical outcomes in CKD patients is limited and inconsistent [7–11].

Other than UA, multiple and specific risk factors including decreased GFR, urinary protein, renal anemia, and CKD-related mineral bone disorder also exist in CKD patients, and differences in the underlying diseases causing CKD, such as glomerulonephritis, hypertensive renal disease, and diabetic nephropathy, might affect clinical outcomes [12–14]. Several studies performed in subpopulations have shown the effect of hyperuricemia on the risk for progression of renal dysfunction [15–17], but how different are the impacts of UA on risks for renal and non-renal outcomes by the underlying disease causing CKD is unknown.

Furthermore, the amount of data on whether allopurinol, a urate-lowering agent, improves renal and non-renal outcomes in CKD is limited and inconsistent [18–23].

Based on this background, the aim of this study was to clarify the effects of hyperuricemia and allopurinol on the risk of renal outcomes, specifically end-stage renal disease (ESRD), and non-renal outcomes, specifically the composite endpoint of CVEs and all-cause mortality, according to the difference in the underlying disease causing CKD in a large, multicenter, prospective, observational cohort study (Gonryo Study).

Methods

Study protocol and ethics statement

The Gonryo CKD cohort is a prospective, observational survey to clarify long-term clinical outcomes of outpatients followed by nephrologists in 11 hospitals, including Tohoku University Hospital in Miyagi Prefecture, which is located in the north-east area of Japan. Between May 2006 and November 2008, 4015 patients who had given their written, informed consent were included and followed until December 2015. The study, which was performed in accordance with the principles of the Helsinki Declaration, was approved by the institutional review board (IRB) of Tohoku University School of Medicine and the respective participating hospitals (Number 2006–10, UMIN000011211). Nephrologists and their assistants in participating hospitals kept a record of each participants’ outcomes once a year in medical records and picked up them for analysis. The National Kidney Foundation Kidney Disease Outcomes Quality Initiative Guidelines were applied to define CKD, and CKD stage was classified by patients’ baseline estimated GFR (eGFR), calculated using the Modification of Diet in Renal Disease (MDRD) study equation for Japanese people: eGFR (mL/min/1.73 m2) = 194 x serum creatinine (-1.094) x age (-0.287) x 0.739 (if female) [24]. Subjects were excluded from the study for the following reasons: no-show (n = 1), eGFR > 60 mL/min/1.73 m2 without proteinuria (n = 837), eGFR > 60 mL/min/1.73 m2 without urine test (n = 94), and no data for serum UA (n = 125). Patients who have continued to use each drug at the time of entry are registered as medication users, and, inclusion criteria as drug user are not set by the length of the administration period. Finally, 2,797 patients meeting the CKD criteria were evaluated in the present study (Fig 1). Hyperuricemia was defined the serum UA level of 7.0 mg/dL or higher regardless of sex. To identify the pathogenetic importance of hyperuricemia for clinical outcomes, all subjects were classified according to the underlying cause of CKD into four categories: primary renal disease (PRD, n = 1,306; biopsy proven in 78.6%); hypertensive nephropathy (HTN, n = 467; biopsy proven in 12.8%); diabetic nephropathy (DN, n = 275; biopsy proven in 17.1%); and other nephropathy (Others, n = 749; biopsy proven in 37.8%). Hypertensive nephropathy was defined by preceding history of hypertension with absence of other possible disorders, including cases with biopsy findings of nephrosclerosis, and diabetic nephropathy was defined by preceding history of diabetes accompanying nephropathy with absence of other possible renal disorders, including cases with biopsy findings of diabetic nephropathy or those who presenting nephropathy with diabetic retinopathy in the absence of other possible disorders. Other nephropathies included vasculitis, polycystic kidney disease, genetic disorder, interstitial nephritis, and CKD of unknown cause. The baseline characteristics of all patients and each group are shown in Table 1.

Fig 1. Patient selection in the present study.

Fig 1

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Table 1. Baseline characteristics of 2,797 CKD patients, overall and by underlying disease causing CKD.

Characteristic Underlying disease causing CKD
Overall PRD HTN DN Others
N 2797 1306 467 275 749
    Age (y) 60.5±16.2 56.0±16.8 70.0±11.6 66.6±12.7 59.9±15.6
    Male 1521 (54.4) 723 (55.4) 269 (57.6) 180 (65.5) 348 (46.6)
CKD stage
    Stage 1+2 1050 (37.5) 625 (47.9) 77 (16.5) 53 (19.3) 295 (39.4)
    Stage 3a 602 (21.5) 265 (20.3) 172 (36.8) 40 (14.5) 125 (16.7)
    Stage 3b 453 (16.2) 196 (15.0) 86 (18.4) 39 (14.2) 132 (17.6)
    Stage 4 403 (14.4) 137 (10.5) 80 (17.1) 59 (21.5) 127 (16.9)
    Stage 5 285 (10.2) 80 (6.1) 52 (11.1) 84 (30.5) 69 (9.2)
CVD and CKD risk factors
    Hypertension 2186 (78.2) 965 (73.9) 467 (100) 249 (90.5) 531 (70.9)
    Diabetes 766 (27.4) 204 (15.6) 149 (31.9) 275 (100) 138 (18.4)
    Cardiac disease 359 (12.8) 106 (8.1) 104 (22.3) 66 (24.0) 83 (11.1)
    Stroke 180 (6.4) 46 (3.5) 56 (11.9) 34 (12.4) 44 (5.9)
    Dyslipidemia 1202 (43.0) 579 (44.3) 195 (41.8) 144 (52.4) 284 (37.9)
    Smoking 455 (16.3) 210 (16.1) 75 (16.1) 57 (20.7) 113 (15.1)
    Creatinine (mg/dL) 1.5±1.4 1.3±1.2 1.6±1.3 2.5±1.9 1.5±1.2
    eGFR (mL/min/1.73 m2) 53.3±29.7 59.9±29.6 44.7±22.6 35.9±26.3 53.5±31.0
    Urinary protein* 1398 (50.0) 642 (49.2) 234 (50.1) 215 (78.2) 307 (40.9)
    Hemoglobin (g/dL) 12.7±2.1 13.1±1.9 12.6±2.2 11.5±2.3 12.5±2.1
    Albumin (g/dL) 4.0±0.5 4.1±0.5 4.1±0.4 3.7±0.6 3.9±0.5
    LDL (mg/dL) 111.5±31.9 110.1±30.9 110.6±30.1 111.5±33.6 114.5±33.9
    SBP (mmHg) 131.4±16.2 129.5±15.2 134.9±17.4 136.9±17.7 130.4±15.9
    DBP (mmHg) 76.7±10.8 77.2±10.3 76.2±11.6 73.9±11.7 77.1±10.7
    PP (mmHg) 54.7±12.7 52.3±11.2 58.7±13.7 62.9±14.6 53.3±11.9
Medication use
    ACE inhibitors or ARBs 1778 (63.6) 819 (62.7) 338 (72.4) 212 (77.1) 409 (54.6)
    Diuretics 447 (15.9) 125 (9.6) 90 (19.3) 129 (46.9) 103 (13.8)
    Allopurinol 691 (24.7) 290 (22.2) 148 (31.7) 64 (23.3) 189 (25.2)
    Statins 963 (34.4) 467 (35.8) 148 (31.7) 119 (43.3) 229 (30.6)
    Steroid 682 (24.4) 419 (32.1) 13 (2.8) 6 (2.2) 224 (29.9)
    Antiplatelets 1265 (45.2) 725 (55.5) 160 (34.3) 115 (41.8) 265 (35.4)
Uric acid
    Total (mg/dL) 6.4±1.7 6.3±1.6 6.5±1.8 7.0±2.1 6.2±1.7
    Male (mg/dL) 6.8±1.6 6.7±1.4 6.9±1.7 7.2±2.0 6.7±1.6
    Female (mg/dL) 5.8±1.8 5.7±1.6 5.9±1.8 6.7±2.2 5.7±1.7
Renal biopsy 1416 (50.6) 1026 (78.6) 60 (12.8) 47 (17.1) 283 (37.8)
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PRD, primary renal disease; HTN, hypertensive renal disease; DN, diabetic nephropathy; CKD, chronic kidney disease; CVD, cardiovascular disease; eGFR, estimated glomerular filtration; LDL, low-density lipoprotein; SBP, systolic blood pressure; DBP, diastolic blood pressure; PP, pulse pressure; ACE, angiotensin-converting enzyme; ARB, angiotensin II receptor blocker.

*Urinary protein means the number and proportion of patients who were positive on the dipstick urinary protein test.

Outcomes and measurements

The study outcomes included ESRD (initiation of hemodialysis or peritoneal dialysis), CVEs, and all-cause mortality. CVEs included angina pectoris, acute myocardial infarction, congestive heart failure, and stroke (cerebral bleeding or infarction). Outcomes were determined from medical records, death certificates, and interviews with attending physicians at the time of the patients’ annual checkups until the fifth-year follow-up. In cases with congestive heart failure, only those who needed admission for treatment were counted. Asymptomatic cerebral infarction or lacunar infarction was not included. Baseline data obtained from medical records at each hospital at the beginning of the study included demographic data, laboratory data, smoking habits, body mass index (BMI), underlying disease causing CKD with information about renal biopsy, comorbid condition (hypertension, diabetes mellitus, dyslipidemia, coronary artery disease, cerebrovascular disease, peripheral artery disease), blood pressure, and heart rate. Laboratory data included blood creatinine, hemoglobin, hematocrit, blood urea nitrogen, UA, albumin, calcium, phosphate, cholesterol, triglycerides, C-reactive protein, and urinary protein by dipstick test for spot urine. Drug use information included angiotensin-converting enzyme (ACE) inhibitors, angiotensin II receptor blockers (ARBs), calcium channel blockers, beta blockers, other antihypertensive agents, loop diuretics, thiazide diuretics, aldosterone antagonists, antidiabetic drugs including insulin, lipid-lowering agents, anti-platelet agents, corticosteroids, activated vitamin D, phosphate binders, erythropoiesis stimulating agents, intravenous or oral iron use, and allopurinol. These data were collected annually from cohort entry until the end of follow-up.

Statistical analysis

Statistical analyses were performed using SPSS version 22.0 (IBM, Tokyo, Japan). Data are shown as means ± standard deviation (SD) for continuous variables, and categorical variables are shown as numbers and percentage. A p value less than 0.05 was considered significant. The Chi-squared test or Fisher’s exact test was used for differences in categorical variables, and analysis of variance (ANOVA) or the Kruskal-Wallis test was used for continuous data. We analyzed UA as a continuous variable and investigated associations between UA per 1 mg/dl higher value with ESRD, CVEs, and all-cause mortality. A Cox proportional hazard model was used to evaluate the relationships between UA and ESRD, CVEs, and all-cause mortality. Analyzed variables included underlying disease of CKD, eGFR, urinary protein, systolic blood pressure, past history of cardiac disease, ACE inhibitor and/or ARB use, diuretic use, statins, antiplatelets, age, sex, smoking habits, BMI, hemoglobin, and albumin. Data were censored at the time of death, initiation of hemodialysis or peritoneal dialysis, or the end of the study in December 2015. Survival analysis was performed using the Kaplan-Meier method with the stratified log-rank test.

Results

Baseline characteristics and the association between UA level and CKD stage

The baseline characteristics of the patients in the present study are summarized in Table 1. A total of 2,797 patients were analyzed, with a mean follow-up of 4.8 years. The mean age of all subjects was 60.5±16.2 years, with men accounting for 54.4%. Mean eGFR was 53.3±29.7 mL/min/1.73 m2, UA was 6.4±1.7 mg/dL, and 24.7% of patients were on allopurinol at the start of the study. In terms of underlying diseases causing CKD, age was higher with HTN, whereas eGFR was lower and baseline uric acid was higher in DN. The UA level was higher in men than in women regardless of the cause of CKD. An increasing trend in both the mean UA level and the proportion of patients with a UA level greater than 8.0 mg/dL was confirmed with increasing CKD stage (Fig 2).

Fig 2. Boxplot of baseline serum uric acid levels by CKD stage according to underlying disease causing CKD.

Fig 2

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PRD, primary renal disease; HTN, hypertensive renal disease; DN, diabetic nephropathy.

Uric acid and renal outcome (ESRD)

A total of 359 patients (12.8%) reached the renal outcome (ESRD). In all subjects, UA was not an independent risk factor for ESRD with the Cox proportional hazard model adjusted for underlying disease causing CKD, eGFR, urinary protein, systolic blood pressure, past history of cardiac disease, ACE inhibitors/ARBs, diuretics, statins, antiplatelets, age, sex, smoking, BMI, hemoglobin, and albumin. In the subgroup analysis, only sex (male) was associated with an increased risk for ESRD (adjusted HR per 1 mg/dl higher UA level was 1.101, [95%CI 1.009–1.202], p = 0.031) (Fig 3A).

Fig 3. Associations of uric acid with renal and non-renal outcomes.

Fig 3

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CI, confidence interval; HR, hazard ratio; PRD, primary renal disease; HTN, hypertensive renal disease; DN, diabetic nephropathy; CVEs, cardiovascular events. †Associations are measured per 1 mg/dl increment of UA using Cox proportional hazard regression. Hazard ratios (HRs) were adjusted for underlying disease of CKD, eGFR, urinary protein, systolic blood pressure, past history of cardiac disease, ACEi/ARBs, diuretics, statins, antiplatelets, allopurinol, age, sex, smoking, body mass index, hemoglobin, albumin.

Uric acid and non-renal outcomes (CVEs and deaths)

There were 260 patients (9.3%) who reached the non-renal outcome (composite endpoint of CVEs and all-cause mortality). In all subjects, UA was not an independent risk factor for the non-renal outcome with the Cox proportional hazard model adjusted for underlying disease causing CKD, eGFR, urinary protein, systolic blood pressure, past history of cardiac disease, ACE inhibitors/ARBs, diuretics, statins, antiplatelets, age, sex, smoking, BMI, hemoglobin, and albumin. In the subgroup analysis, UA was associated with an increased risk for the non-renal outcome in PRD and HTN group. Per 1 mg/dl higher UA level, multivariable adjusted HR was 1.248 (95% CI: 1.003 to 1.553) for PRD, and 1.250 (1.035 to 1.510) for HTN (Fig 3B). UA 6.0 mg/dL in PRD and UA 6.8 mg/dL in HTN are optimal cut off value from ROC analysis. AUC of ROC curve and p-value are 0.611 (95%CI, 0.537–0.685, p = 0.004) in PRD and 0.658 (95%CI, 0.584–0.732, p = 0.012) in HTN. Detailed data are also shown in S1 Table.

Effect of allopurinol on renal and non-renal outcomes

A total of 697 (24.7%) patients were prescribed allopurinol at baseline. The efficacy of allopurinol for preventing renal and non-renal outcomes was not confirmed in both all patients and in the subgroup analysis (Fig 4 and S2 Table). Kaplan-Meier analysis with the stratified log-rank test was performed to determine the efficacy of allopurinol for preventing renal and non-renal outcomes (Fig 5).

Fig 4. Associations of allopurinol with renal and non-renal outcomes.

Fig 4

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CI, confidence interval; HR, hazard ratio; PRD, primary renal disease; HTN, hypertensive renal disease; DN, diabetic nephropathy; CVEs, cardio-vascular events. †Associations are measured per 1 mg/dl increment of UA using Cox proportional hazard regression. Hazard ratios (HRs) were adjusted for underlying disease of CKD, eGFR, urinary protein, systolic blood pressure, past history of cardiac disease, ACEi/ARBs, diuretics, statins, antiplatelets, allopurinol, age, sex, smoking, body mass index, hemoglobin, albumin.

Fig 5. Impact of allopurinol on renal and non-renal outcomes.

Fig 5

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Discussion

The results of this study demonstrated that hyperuricemia is an independent risk factor for non-renal outcomes in primary renal disease and hypertensive renal disease patients, and allopurinol did not decrease the risk in these patients. We analyzed UA as a continuous variable and demonstrated that per 1 mg/dl higher UA level, multivariable adjusted HR was 1.248 (95% CI: 1.003 to 1.553) for PRD, and 1.250 (1.035 to 1.510) for HTN. The strength of the study is that it clarified the long-term prognosis of CKD outpatients followed by nephrologists according to the underlying disease causing CKD in a large-scale, multi-center, prospective cohort. We previously showed the beneficial effect of allopurinol in 178 HTN patients with impaired kidney function (eGFR< 45 mL/min/1.73 m2) during 18.4-month follow-up [25], but this result was not confirmed in the present study. The reason for this discrepancy is that a larger number of variables was included in the present analysis than in the previous study. The number of patients who reached non-renal outcomes in the present study and the previous one was 359 and 28, respectively. The more accurate analysis with adjustment of more variables in the present study showed the efficacy of allopurinol to be unclear.

The potential role of UA in clinical outcomes has been debated for decades [11], and hyperuricemia is thought to have an impact, not large, but certainly related to adverse events in CKD patients based on various previous studies [9, 10, 12–14, 17, 26]. Of course, hyperuricemia is a commonly seen finding in CKD, and it could be a consequence of reduced excretion or diuretic agents [27]. Based on evidence concerning UA and possible links to hypertension, renal disease, and cardiovascular disease [5], hyperuricemia in hypertensive renal disease appears to be an important issue, given the present results. Basic research can help us understand the specific mechanisms of this relationship: higher UA levels cause endothelial dysfunction, activation of the renin-angiotensin aldosterone system, vascular injury, tubulointerstitial inflammation, and elevated blood pressure [9, 28]. In the present study, 63.6% of the patients were taking ACE inhibitors or ARBs at baseline, which could have attenuated the potential effects of hyperuricemia on the activity of the renin-angiotensin system.

IgA nephropathy is the most common primary glomerulonephritis in Japan [29]. Although it has been suggested that IgA nephropathy patients with hyperuricemia have poor renal prognosis [12, 17], the relationship between hyperuricemia in IgA nephropathy patients and non-renal outcome has been unclear. We confirmed that non-renal outcome in PRD is poor in this study, however, the data of detailed classification of PRD is lacking. It is necessary to clarify how the renal and non-renal outcomes differs depending on the type of PRD in the future.

Several animal studies have demonstrated that allopurinol treatment prevented the development of hypertension, structural and functional alterations in the glomerular afferent arteriole, and the ischemic type of renal parenchymal injury via modulation of the renin-angiotensin system and neuronal NO synthase [30, 31]. However, recent multicenter, randomized, double-blind, placebo-controlled trials (RCTs), such as “Febuxostat Versus Placebo Randomized Controlled Trial Regarding Reduced Renal Function in Patients With Hyperuricemia Complicated by Chronic Kidney Disease Stage 3” (FEATHER), the Preventing Early Renal Loss in Diabetes (PERL), and “the Controlled Trial of Slowing of Kidney Disease Progression from the Inhibition of Xanthine Oxidase” (CKD-FIX) failed to demonstrate clinically meaningful benefits of serum urate reduction with allopurinol or febuxostat on kidney function decline, similar to the present results [21, 22, 32]. In addition, the KDIGO (Kidney Disease: Improving Global Outcomes) guideline clinical practice recommendation says that, “there is insufficient evidence to support or refute the use of agents to lower serum uric acid concentrations in people with CKD and either symptomatic or asymptomatic hyperuricemia in order to delay progression of CKD” [33]. On the other hand, hyperuricemia has been shown to be a risk factor for cardiovascular disease, including myocardial infarction and stroke [34]. Based on various findings so far, including the present study, we should carefully consider whether we should treat asymptomatic hyperuricemia and the relevance of lowering uric acid levels. In addition, further studies are needed to clarify which CKD patients, e.g. underlying disease causing CKD, severity of CKD stage, and degree of uric acid elevation, would benefit from treatment.

The present study has several limitations. First, since this was an observational study, it only shows an association between uric acid or allopurinol and clinical outcomes, not a cause and effect relationship. Second, details of the adjustment of allopurinol, such as discontinuation, reduction, and increase, were not available also, the data of switching to other XOR inhibitors, such as febuxostat or topiroxostat in the treatment course is lacking. Third, renal biopsy was performed only 12.8% in HTN group, and 17.1% in DN group, and nearly one-third patients in the HTN group had diabetes mellitus. It is considered difficult to distinguish between nephrosclerosis and DKD in a strict sense without biopsy. So, caution should be taken in interpreting the data.

Conclusions

The effect of hyperuricemia on clinical outcomes in CKD patients varies according to the underlying disease causing CKD. Hyperuricemia is an independent risk factor for non-renal outcomes in primary renal disease and hypertensive renal disease patients, and allopurinol did not decrease the risks for renal and non-renal outcomes.

Supporting information

S1 Table. Associations of uric acid with renal and non-renal outcomes.

(DOCX)

Click here for additional data file. (27.3KB, docx)
S2 Table. Associations of allopurinol with renal and non-renal outcomes.

(DOCX)

Click here for additional data file. (15KB, docx)

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

The authors received no specific funding for this work.

References

  • 1.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(4): 642–50 [PubMed] [Google Scholar]
  • 2.Chonchol M, Shlipak MG, Katz R, Sarnak MJ, Newman AB, Siscovick DS. Relationship of Uric Acid With Progression of Kidney Disease. Am J Kidney Dis 2007; 50(2): 239–47 10.1053/j.ajkd.2007.05.013 [DOI] [PubMed] [Google Scholar]
  • 3.Bellomo G, Venanzi S, Verdura C, Saronio P, Esposito A, Timio M. Association of uric acid with change in kidney function in healthy normotensive individuals. Am J Kidney Dis 2010; 56(2): 264–72 10.1053/j.ajkd.2010.01.019 [DOI] [PubMed] [Google Scholar]
  • 4.Iseki K, Iseki C, Kinjo K. Changes in serum uric acid have a reciprocal effect on eGFR change: A 10-year follow-up study of community-based screening in Okinawa, Japan. Hypertens Res 2013; 36(7): 650–4 10.1038/hr.2013.11 [DOI] [PubMed] [Google Scholar]
  • 5.Feig DI, Kang DH, Johnson RJ. Uric Acid and Cardiovascular Risk Daniel. N Engl J Med 2008; 359(17): 1811–21 10.1056/NEJMra0800885 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Fang J, Alderman MH. Serum uric acid and cardiovascular mortality: The NHANES I Epidemiologic Follow-up Study, 1971–1992. JAMA 2000; 283(18): 2404–10 10.1001/jama.283.18.2404 [DOI] [PubMed] [Google Scholar]
  • 7.Nacak H, Diepen MV, Qureshi AR, Carrero JJ, Stijnen T, Dekker FW. Uric acid is not associated with decline in renal function or time to renal replacement therapy initiation in a referred cohort of patients with Stage III, IV and v chronic kidney disease. Nephrol Dial Transplant 2015; 30(12): 2039–45 10.1093/ndt/gfv225 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Liu WC, Hung CC, Chen SC, Yeh SM, Lin MY, Chiu YW, et al. Association of Hyperuricemia with renal outcomes, cardiovascular disease, and mortality. Clin J Am Soc Nephrol 2012; 7(4): 541–8 10.2215/CJN.09420911 [DOI] [PubMed] [Google Scholar]
  • 9.Jalal DI, Chonchol M, Chen W, Targher G. Uric acid as a target of therapy in CKD. Am J Kid Dis 2013; 61(1): 134–46 10.1053/j.ajkd.2012.07.021 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Hsu CY, Iribarren C, McCulloch CE, Darbinian J, Go AS. Risk factors for end-stage renal disease—25-year follow-up. Arch Intern Med 2009; 169(4): 342–50 10.1001/archinternmed.2008.605 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Johnson RJ, Bakris GL, Borghi C, Chonchol MB, Feldman D,Lanaspa MA, et al. Hyperuricemia, Acute and Chronic Kidney Disease, Hypertension, and Cardiovascular Disease: Report of a Scientific Workshop Organized by the National Kidney Foundation. Am J Kidney Dis 2018; 71(6): 851–65 10.1053/j.ajkd.2017.12.009 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Syrjänen J, Mustonen J, Pasternack A. Hypertriglyceridaemia and hyperuricaemia are risk factors for progression of IgA nephropathy. Nephrol Dial Transplant 2000; 15(1):34–42 10.1093/ndt/15.1.34 [DOI] [PubMed] [Google Scholar]
  • 13.Ficociello LH, Rosolowsky ET, Niewczas MA, Maselli NJ, Weinberg JM, Aschengru A, et al. High-Normal Serum Uric Acid Increases Risk of Early Progressive Renal Function Loss in Type 1 Diabetes. Diabetes Care 2010; 33(6): 1337–43 10.2337/dc10-0227 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Madero M, Sarnak MJ, Wang X, Greene T, Beck GJ, Kusek JW, et al. Uric Acid and Long-term Outcomes in CKD. Am J Kidney Dis 2009; 53(5): 796–803 10.1053/j.ajkd.2008.12.021 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Ficociello LH, Rosolowsky ET, Niewczas MA, Maselli NJ, Weinberg JM, Aschengru A, et al. High-Normal Serum Uric Acid Increases Risk of Early Progressive Renal Function Loss in Type 1 Diabetes. Diabetes Care 2010; 33(6): 1337–43 10.2337/dc10-0227 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Meier-Kriesche HU, Schold JD, Vanrenterghem Y, Halloran PF, Ekberg H. Uric Acid Levels Have No Significant Effect on Renal Function in Adult Renal Transplant Recipients: Evidence from the Symphony Study. Clin J Am Soc Nephrol 2009; 4(10): 1655–60 10.2215/CJN.02700409 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.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(4): 333–9 10.1159/000045939 [DOI] [PubMed] [Google Scholar]
  • 18.Goicoechea M, de Vinuesa SG, Verdalles U, Verde E, Macias N, Santos A, et al. Allopurinol and Progression of CKD and Cardiovascular Events: Long-term Follow-up of a Randomized Clinical Trial. Am J Kidney Dis 2015; 65(4): 543–9 10.1053/j.ajkd.2014.11.016 [DOI] [PubMed] [Google Scholar]
  • 19.Goicoechea M, de Vinuesa SG, Verdalles U, Ruiz-Caro C, Ampuero J, Rincón, et al. Effect of Allopurinol in Chronic Kidney Disease Progression and Cardiovascular Risk. Clin J Am Soc Nephrol 2010; 5(8): 1388–93 10.2215/CJN.01580210 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Fleeman N, Pilkington G, Dundar Y, Dwan K, Boland A, Dickson R, et al. Allopurinol for the treatment of chronic kidney disease: a systematic review. Health Technol Assess 2014; 18(40): 1–77 10.3310/hta18400 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Doria A, Galecki AT, Spino C, Pop-Busui R, Cherney DZ, Lingvay I, et al. Serum Urate Lowering with Allopurinol and Kidney Function in Type 1 Diabetes. N Engl J Med 2020; 382(26): 2493–503 10.1056/NEJMoa1916624 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Badve SV, Pascoe EM, Tiku A, Boudville N, Brown FG, Cass A, et al. Effects of Allopurinol on the Progression of Chronic Kidney Disease. N Engl J Med 2020; 382(26): 2504–13 10.1056/NEJMoa1915833 [DOI] [PubMed] [Google Scholar]
  • 23.Bose B, Badve SV, Hiremath SS, Boudville N, Brown FG, Cass A, et al. Effects of uric acid-lowering therapy on renal outcomes: A systematic review and meta-analysis. Nephrol Dial Transplant 2014; 29(2): 406–13 10.1093/ndt/gft378 [DOI] [PubMed] [Google Scholar]
  • 24.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(6): 982–92 10.1053/j.ajkd.2008.12.034 [DOI] [PubMed] [Google Scholar]
  • 25.Terawaki H, Nakayama M, Miyazawa E, Murata Y, Nakayama K, Matsushima M, et al. Effect of allopurinol on cardiovascular incidence among hypertensive nephropathy patients: The Gonryo study. Clin Exp Nephrol 2013; 17(4): 549–53 10.1007/s10157-012-0742-z [DOI] [PubMed] [Google Scholar]
  • 26.Meier-Kriesche HU, Schold JD, Vanrenterghem Y, Halloran PF, Ekberg H. Uric acid levels have no significant effect on renal function in adult renal transplant recipients: Evidence from the symphony study. Clin J Am Soc Nephrol 2009; 4(10): 1655–60 10.2215/CJN.02700409 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Jing J, Kielstein JT, Schultheiss UT, Sitter T, Titze SI, Schaeffner ES, et al. Prevalence and correlates of gout in a large cohort of patients with chronic kidney disease: The German Chronic Kidney Disease (GCKD) study. Nephrol Dial Transplant 2015; 30(4): 613–21 10.1093/ndt/gfu352 [DOI] [PubMed] [Google Scholar]
  • 28.Nakagawa T, Johnson RJ, Andres-Hernando A, Roncal-Jimenez C, Sanchez-Lozada LG, Tolan DR, et al. Fructose production and metabolism in the kidney. J Am Soc Nephrol 2020; 31(5): 898–906 10.1681/ASN.2019101015 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Sugiyama H, Yokoyama H, Sato H, Saito T, Kohda Y, Nishi S, et al. Japan Renal Biopsy Registry and Japan Kidney Disease Registry: Committee Report for 2009 and 2010. Clin Exp Nephrol 2013; 17(2): 155–73 10.1007/s10157-012-0746-8 [DOI] [PubMed] [Google Scholar]
  • 30.Sánchez-Lozada LG, Tapia E, Santamaría J, Avila-Casado C, Soto V, Nepomuceno T, et al. Mild hyperuricemia induces vasoconstriction and maintains glomerular hypertension in normal and remnant kidney rats. Kidney Int 2005; 67(1): 237–47 10.1111/j.1523-1755.2005.00074.x [DOI] [PubMed] [Google Scholar]
  • 31.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(5): 1101–6 10.1161/hy1101.092839 [DOI] [PubMed] [Google Scholar]
  • 32.Kimura K, Hosoya T, Uchida S, Inaba M, Makino H, Maruyama S, et al. Febuxostat Therapy for Patients With Stage 3 CKD and Asymptomatic Hyperuricemia: A Randomized Trial. Am J Kidney Dis 2018; 72(6): 798–810 10.1053/j.ajkd.2018.06.028 [DOI] [PubMed] [Google Scholar]
  • 33.Levin A, Stevens P, Bilous R, Coresh J, De Francisco A, De Jong P, et al. Kidney disease: Improving global outcomes (KDIGO) CKD work group. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl ernational Supplements. 2013; 10.1038/kisup.2012.73 [DOI] [PubMed] [Google Scholar]
  • 34.Bos MJ, Koudstaal PJ, Hofman A, Witteman JCM, Breteler MMB. Uric acid is a risk factor for myocardial infarction and stroke: The Rotterdam Study. Stroke 2006; 37(6): 1503–7 10.1161/01.STR.0000221716.55088.d4 [DOI] [PubMed] [Google Scholar]

Decision Letter 0

Ping-Hsun Wu

18 Jan 2021

PONE-D-20-34099

Relationships of underlying disease causing chronic kidney disease to hyperuricemia and clinical outcomes: Gonryo study

PLOS ONE

Dear Dr. Kimio Watanabe,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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We look forward to receiving your revised manuscript.

Kind regards,

Ping-Hsun Wu, M.D. PhD.

Academic Editor

PLOS ONE

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The method to link follow-up outcomes should be described. Some important factors are missing in the adjusted model, such as Statin. Please add the potential confounders in the model or acknowledge them as a limitation.

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Reviewer #2: Partly

**********

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Reviewer #2: Yes

**********

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Reviewer #1: Watanabe et al. investigated the effect of hyperuricemia on clinical outcomes in different CKD etiology. Hyperuricemia is an independent risk factor for non-renal outcomes in hypertensive renal disease. I have some comments to improve the study.

1. Primary renal disease was the major cause of CKD in the Gonryo study (2006 -2008). I wondered the proportion of major cause of CKD in Japan.

2. The present in both figures and tables is redundant in the main text. Please move the detailed data of Table to the supplementary material.

3. Page 15, line 203, the full name of “RCT”, “FEATHER”, “PERL”, and “CKD-FIX” should be presented.

4. Since hyperuricemia is associated with non-renal outcomes in hypertensive renal disease patients, a spline function for uric acid level and non-renal outcomes will be interesting to observe the adequate and optimal uric acid cut off value.

5. The observation subjects were enrolled between May 2006 and November 2008 and follow up until December 2015. How to link these participants and recorded their outcomes? Is there any national registry or database to link subjects’ outcomes?

Reviewer #2: The authors demonstrated the association between hyperuricemia and clinical outcomes in CKD patients in a prospective observational cohort study. It has novelty because the authors showed the effects of hyperuricemia varies according to underlying diseases causing CKD. However, there are some issues needed to be clarified.

Major issue:

Q1: The authors should explain in more detail how to classify CKD patients into different categories, especially when patients had more than two underlying diseases causing CKD simultaneously. According to table 1, 149(31.9%) patients in hypertensive nephropathy group(HTN) had diabetes mellitus, and 249(90.5%) patients in diabetic nephropathy group(DN) had hypertension. However, only 12.8% and 17.1% patients in HTN and DN respectively received renal biopsy. Without biopsy, how did the authors judge and confirm the underlying diseases causing CKD?

Q2: Statins have been proven to be effective in the primary and secondary prevention of cardiovascular disease. However, statins were not adjusted in the evaluation of non-renal outcomes (CVEs and deaths) in the present study. Meanwhile, information about the use of antiplatelet agents was not available. The lack of these important factors may cause biases in evaluation of CVE.

Minor issue:

Q3: What is the definition of hyperuricemia? What is the cut-point value of hyperuricemia used in the current study? Was the hyperuricemia defined according to the initial single laboratory data or the average of serial blood exams during follow-up? Were patients divided into quartiles according to serum UA level? The authors should define hyperuricemia more clearly.

Q4: How to define medication use? Did a single prescription of medication fit the definition of medication use? Or a continuous use of a drug for a period of time could be regarded as medication use. The authors should define medication use more clearly.

Q5: In the current study, allopurinol did not decrease the risks for renal and non-renal outcomes. However, information about the use of other UA lowering agents, such as febuxostat and benzbromarone, was not available. That may lead to biases when evaluating the effects of UA lowering agent and clinical outcomes. Is it possible to consider all the UA lowering agents in the current study?

Q6: The title of the present study “ Relationships of underlying disease causing chronic kidney disease to hyperuricemia and clinical outcomes “ was a little bit confusing. Could the authors make it more clear?

**********

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2021 Mar 25;16(3):e0249240. doi: 10.1371/journal.pone.0249240.r002

Author response to Decision Letter 0

8 Feb 2021

Additional Editor Comments:

The method to link follow-up outcomes should be described. Some important factors are missing in the adjusted model, such as Statin. Please add the potential confounders in the model or acknowledge them as a limitation.

[Response]

National registry or database to link subjects’ outcomes do not exist in Japan. Nephrologists and their assistants in eleven participating hospitals in Miyagi Prefecture kept a record of each participants’ outcomes once a year in medical records and picked up them for analysis. Regarding this point, we added the following comment in Methods section.

Line 80-81, Nephrologists and their assistants in participating hospitals kept a record of each participants’ outcomes once a year in medical records and picked up them for analysis.

Following your comment, we re-analyzed the adjusted model adding statins and antiplatelets as the potential confounders. Please, see figures and tables (Fig. 3 and 4, S1 and S2 Table). As the result of re-analysis, we identified primary renal disease (PRD) patients also have the risk for non-renal outcomes. Therefore, we modified manuscript as follows.

Line 40-43, but in primary renal disease (PRD) and hypertensive renal disease (HTN) patients, hyperuricemia was significantly associated with non-renal outcomes on multivariate Cox proportional analysis (adjusted hazard ratio [95% confidence interval] PRD, 1.248 [1.003 – 1.553]; HTN, 1.250 [1.035 – 1.510]).

Line 47, Hyperuricemia is an independent risk factor for non-renal outcomes in primary renal disease and hypertensive renal disease patients.

Line 172-173, In the subgroup analysis, only PRD and HTN was were associated with an increased risk for the non-renal outcome (HR 1.250, 95%CI 1.035-1.510, p=0.020 adjusted HR [95% Cl] PRD, 1.248 [1.003 – 1.553]; HTN, 1.250 [1.035 – 1.510]) (Figure 3-b).

Line 187-189, The results of this study demonstrated that hyperuricemia is an independent risk factor for non-renal outcomes in primary renal disease and hypertensive renal disease patients, and allopurinol did not decrease the risk in these patients.

Line 247-249, Hyperuricemia is an independent risk factor for non-renal outcomes in primary renal disease and hypertensive renal disease patients, and allopurinol did not decrease the risks for renal and non-renal outcomes.

Line 211-216, IgA nephropathy is the most common primary glomerulonephritis in Japan [29]. Although it has been suggested that IgA nephropathy patients with hyperuricemia have poor renal prognosis [12, 17], the relationship between hyperuricemia in IgA nephropathy patients and non-renal outcome was unclear. We confirmed that non-renal outcome in PRD is poor in this study, however, the data of detailed classification of PRD is lacking. It is necessary to clarify how the renal and non-renal outcomes differs depending on the type of PRD in the future.

[29] Sugiyama H, Yokoyama H, Sato H, Saito T, Kohda Y, Nishi S, et al. Japan Renal Biopsy Registry and Japan Kidney Disease Registry: Committee Report for 2009 and 2010. Clin Exp Nephrol 2013; 17(2): 155-73

Reviewer #1: Watanabe et al. investigated the effect of hyperuricemia on clinical outcomes in different CKD etiology. Hyperuricemia is an independent risk factor for non-renal outcomes in hypertensive renal disease. I have some comments to improve the study.

1. Primary renal disease was the major cause of CKD in the Gonryo study (2006 -2008). I wondered the proportion of major cause of CKD in Japan.

[Response to 1]

Unfortunately, there are no Japanese patients’ data showing the proportion of major cause of CKD. Since the Gonryo study targets only CKD patients who had been followed by nephrologist, the proportion of nephritis patients is thought to be relatively high compared to the actual situation. The most common primary cause of renal failure among new dialysis patients was diabetic nephropathy (43.8%), followed by chronic glomerulonephritis (32.4%) in the nationwide survey conducted at the end of 2013 in Japan*. Based on the result, it is expected that there would actually be more DN/DKD patients compared to our result in Table1.

*Ikuto M, Shigeru N, Satoshi O, Naoki K, Norio H, Takayuki H, et al. An Overview of Regular Dialysis Treatment in Japan (As of 31 December 2013). Ther Apher Dial 2015; 19(6): 540-74

2. The present in both figures and tables is redundant in the main text. Please move the detailed data of Table to the supplementary material.

[Response to 2]

We moved the detailed data of Table (Table 2 and 3) to the supplementary material (S1 and S2 Table).

3. Page 15, line 203, the full name of “RCT”, “FEATHER”, “PERL”, and “CKD-FIX” should be presented.

[Response to 3]

We corrected the sentence which you pointed out as follows.

Line 221-227, However, recent RCTs, such as FEATHER, PERL, and CKD-FIX, However, recent multicenter, randomized, double-blind, placebo-controlled trials (RCTs), such as “Febuxostat Versus Placebo Randomized Controlled Trial Regarding Reduced Renal Function in Patients With Hyperuricemia Complicated by Chronic Kidney Disease Stage 3” (FEATHER), the Preventing Early Renal Loss in Diabetes (PERL), and “the Controlled Trial of Slowing of Kidney Disease Progression from the Inhibition of Xanthine Oxidase” (CKD-FIX) failed to demonstrate clinically meaningful benefits of serum urate reduction with allopurinol or febuxostat on kidney function decline, similar to the present results [21][22][32].

4. Since hyperuricemia is associated with non-renal outcomes in hypertensive renal disease patients, a spline function for uric acid level and non-renal outcomes will be interesting to observe the adequate and optimal uric acid cut off value.

[Response to 4]

We detected that UA 6.0 mg/dL in PRD and UA 6.8 mg/dL in HTN are optimal cut off value from ROC analysis. Regarding this point, we added the following comment in Result section.

Line 174-176, UA 6.0 mg/dL in PRD and UA 6.8 mg/dL in HTN are optimal cut off value from ROC analysis. AUC of ROC curve and p-value are 0.611 (95%CI, 0.537-0.685, p=0.004) in PRD and 0.658 (95%CI, 0.584-0.732, p=0.012) in HTN.

5. The observation subjects were enrolled between May 2006 and November 2008 and follow up until December 2015. How to link these participants and recorded their outcomes? Is there any national registry or database to link subjects’ outcomes?

[Response to 5]

National registry or database to link subjects’ outcomes do not exist in Japan. Nephrologists and their assistants in eleven participating hospitals in Miyagi Prefecture kept a record of each participants’ outcomes once a year in medical records and picked up them for analysis. Regarding this point, we added the following comment in Methods section.

Line 80-81, Nephrologists and their assistants in participating hospitals kept a record of each participants’ outcomes once a year in medical records and picked up them for analysis.

Reviewer #2: The authors demonstrated the association between hyperuricemia and clinical outcomes in CKD patients in a prospective observational cohort study. It has novelty because the authors showed the effects of hyperuricemia varies according to underlying diseases causing CKD. However, there are some issues needed to be clarified.

Major issue:Q1: The authors should explain in more detail how to classify CKD patients into different categories, especially when patients had more than two underlying diseases causing CKD simultaneously. According to table 1, 149(31.9%) patients in hypertensive nephropathy group(HTN) had diabetes mellitus, and 249(90.5%) patients in diabetic nephropathy group(DN) had hypertension. However, only 12.8% and 17.1% patients in HTN and DN respectively received renal biopsy. Without biopsy, how did the authors judge and confirm the underlying diseases causing CKD?

[Response to Q1]

Patients were classified according to one of four underlying renal diseases diagnosed by the attending physicians at the participating hospitals. Hypertensive nephropathy was defined by preceding history of hypertension with absence of other possible disorders, including cases with biopsy findings of nephrosclerosis, and diabetic nephropathy was defined by preceding history of diabetes accompanying nephropathy with absence of other possible renal disorders, including cases with biopsy findings of diabetic nephropathy or those who presenting nephropathy with diabetic retinopathy in the absence of other possible disorders. Following your suggestion, we added the detailed explanation in the methods section.

Line 95-100, Hypertensive nephropathy was defined by preceding history of hypertension with absence of other possible disorders, including cases with biopsy findings of nephrosclerosis, and diabetic nephropathy was defined by preceding history of diabetes accompanying nephropathy with absence of other possible renal disorders, including cases with biopsy findings of diabetic nephropathy or those who presenting nephropathy with diabetic retinopathy in the absence of other possible disorders.

Q2: Statins have been proven to be effective in the primary and secondary prevention of cardiovascular disease. However, statins were not adjusted in the evaluation of non-renal outcomes (CVEs and deaths) in the present study. Meanwhile, information about the use of antiplatelet agents was not available. The lack of these important factors may cause biases in evaluation of CVE.

[Response to Q2]

Following your comment, we re-analyzed the adjusted model adding statins and antiplatelets as the potential confounders. As the result of re-analysis, we identified primary renal disease (PRD) patients also have the risk for non-renal outcomes. Please, see figures and tables (Fig. 3 and 4, S1 and S2 Table). Also we modified the manuscript.

Minor issue:Q3: What is the definition of hyperuricemia? What is the cut-point value of hyperuricemia used in the current study? Was the hyperuricemia defined according to the initial single laboratory data or the average of serial blood exams during follow-up? Were patients divided into quartiles according to serum UA level? The authors should define hyperuricemia more clearly.

[Response to Q3]

First of all, hyperuricemia in this report was defined the serum uric acid level of 7.0 mg/dL or higher regardless of sex. Regarding this point, we added the following comment in Methods section.

Line 91, Hyperuricemia was defined the serum UA level of 7.0 mg/dL or higher regardless of sex.

And we demonstrate 1-mg/dL increase in uric acid level is associated with a hazard ratio of 1.250 [1.035 – 1.510] for non-renal outcome in hypertensive renal disease patients. In this analysis, we used uric acid level at the time of enrollment as continuous variable. And we detected that UA 6.0 mg/dL in PRD and UA 6.8 mg/dL in HTN are optimal cut off value from ROC analysis. Regarding this point, we added the following comment in Result section.

Line 174-176, UA 6.0 mg/dL in PRD and UA 6.8 mg/dL in HTN are optimal cut off value from ROC analysis. AUC of ROC curve and p-value are 0.611 (95%CI, 0.537-0.685, p=0.004) in PRD and 0.658 (95%CI, 0.584-0.732, p=0.012) in HTN.

Q4: How to define medication use? Did a single prescription of medication fit the definition of medication use? Or a continuous use of a drug for a period of time could be regarded as medication use. The authors should define medication use more clearly.

[Response to Q4]

Patients who have continued to use allopurinol at the time of entry were registered as medication users. Therefore, inclusion criteria as drug user are not set by the length of the administration period. Regarding this point, we added the following comment in Methods section.

Line 88-90, Patients who have continued to use each drug at the time of entry are registered as medication users, and inclusion criteria as drug user are not set by the length of the administration period.

Q5: In the current study, allopurinol did not decrease the risks for renal and non-renal outcomes. However, information about the use of other UA lowering agents, such as febuxostat and benzbromarone, was not available. That may lead to biases when evaluating the effects of UA lowering agent and clinical outcomes. Is it possible to consider all the UA lowering agents in the current study?

[Response to Q5]

In the current study, UA level and allopurinol users are extracted and analyzed only at the time of entry (from 2006 to 2008). And very few patients were using uric acid lowering agents other than allopurinol. For this reason, febuxostat, which has been available since 2011 in Japan, or benzbromarone are not considered in this analysis. Of course, it is expected that there are not a few cases in which allopurinol was switched to febuxostat or topiroxostat during the course of treatment, and possibility of bias is considered, so this point was added to the limitation.

Line 240-242, Second, details of the adjustment of allopurinol, such as discontinuation, reduction, and increase, were not available, also, the data of switching to other XOR inhibitors, such as febuxostat or topiroxostat in the treatment course is lacking.

Q6: The title of the present study “ Relationships of underlying disease causing chronic kidney disease to hyperuricemia and clinical outcomes “ was a little bit confusing. Could the authors make it more clear?

[Response to Q6]

We changed the title of the present study from “Relationships of underlying disease causing chronic kidney disease to hyperuricemia and clinical outcomes” to “Different clinical impact of hyperuricemia according to etiologies of chronic kidney disease: Gonryo Study”.

Attachment

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Decision Letter 1

Ping-Hsun Wu

5 Mar 2021

PONE-D-20-34099R1

Different clinical impact of hyperuricemia according to etiologies of chronic kidney disease: Gonryo Study

PLOS ONE

Dear Dr. Kimio Watanabe,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Apr 19 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Ping-Hsun Wu, M.D. PhD.

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments (if provided):

The clinical classification of CKD etiology could be described clearly. A suggestion for the revised method and result section for adding statin and the anti-platelet variable was considered.

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Reviewers' comments:

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Comments to the Author

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Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

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Reviewer #1: Yes

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: No

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Reviewer #1: Yes

Reviewer #2: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: (No Response)

Reviewer #2: Q1: The authors added the definition of HTN and DN in the revised manuscript. However, the authors did not mention about how to classify if a patient had both diabetes mellitus and hypertension simultaneously. As shown in Table 1, nearly one-third patients in the HTN group had diabetes mellitus. Why were these patients regarded as HTN rather than DN? Since low biopsy rate in patients from HTN and DN groups, more convincing and detailed classification criteria to differentiate HTN from DN should be described. Otherwise, the authors should mention that misclassification is possible and the data should be interpreted with caution in the limitation section.

Q2: Since the authors analyzed UA as a continuous variable, and the relationship between UA and clinical outcomes was demonstrated as hazard ratios per 1 mg/dl greater UA level, they should mention this clearly in the Methods section, and described the results more precisely in the manuscript (Abstract, Results section, Discuss section, and caption of figures)

Q3: The authors re-analyzed the HR after taking statin and anti-platelet into consideration in the revised manuscript. In the Statistical analysis sections and Results section, adjusting for statin and anti-platelet should be mentioned. Please make sure that all corresponding description in the manuscript have been modified.

Q4: In line 172-173, The sentence "In the subgroup analysis, PRD and HTN was associated with an increased risk for the non-renal outcome" was confusing. Please make it more clear.

**********

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Reviewer #2: No

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PLoS One. 2021 Mar 25;16(3):e0249240. doi: 10.1371/journal.pone.0249240.r004

Author response to Decision Letter 1

8 Mar 2021

Reviewer #1: (No Response)

Reviewer #2: Q1: The authors added the definition of HTN and DN in the revised manuscript. However, the authors did not mention about how to classify if a patient had both diabetes mellitus and hypertension simultaneously. As shown in Table 1, nearly one-third patients in the HTN group had diabetes mellitus. Why were these patients regarded as HTN rather than DN? Since low biopsy rate in patients from HTN and DN groups, more convincing and detailed classification criteria to differentiate HTN from DN should be described. Otherwise, the authors should mention that misclassification is possible and the data should be interpreted with caution in the limitation section.

[Response]

Patients who have not had renal biopsy and who have both hypertension and diabetes at the same time were classified as either HTN or DN by the attending physicians’ judgment based on the medical history, urine test and presence or absence of diabetic retinopathy. Hypertensive nephropathy was defined by preceding history of hypertension with absence of other possible disorders, including cases with biopsy findings of nephrosclerosis, and diabetic nephropathy was defined by preceding history of diabetes accompanying nephropathy with absence of other possible renal disorders, including cases with biopsy findings of diabetic nephropathy or those who presenting nephropathy with diabetic retinopathy in the absence of other possible disorders. However, biopsy rate is low in HTN and DN. And it is considered difficult to distinguish between HTN and DN in a strict sense without biopsy finding. We think this point is considered as the limitation of this study, so we added the following comments.

Line 247-250 (Discussion) Third, renal biopsy was performed in 50.6% of all patients, and only 12.8% of hypertensive renal disease patients. Third, renal biopsy was performed only 12.8% in HTN group, and 17.1% in DN group, and nearly one-third patients in the HTN group had diabetes mellitus. It is considered difficult to distinguish between HTN and DN in a strict sense without biopsy. So, caution should be taken in interpreting the data.

Q2: Since the authors analyzed UA as a continuous variable, and the relationship between UA and clinical outcomes was demonstrated as hazard ratios per 1 mg/dl greater UA level, they should mention this clearly in the Methods section, and described the results more precisely in the manuscript (Abstract, Results section, Discuss section, and caption of figures)

[Response]

We modified the manuscript about description for relationship between UA and clinical outcomes as follows.

Line 42-43, (Abstract) on multivariate Cox proportional analysis (adjusted hazard ratio [95% confidence interval] PRD, 1.248 [1.003 – 1.553]; HTN, 1.250 [1.035 – 1.510]). Per 1 mg/dl higher UA level, multivariable adjusted hazard ratio was 1.248 (95% CI: 1.003 to 1.553) for PRD, and 1.250 (1.035 to 1.510) for HTN.

Line 139-141, (Methods) We analyzed UA as a continuous variable and investigated associations between UA per 1 mg/dl higher value with ESRD, CVEs, and all-cause mortality.

Line 166-167 (Results) risk for ESRD (adjusted HR per 1 mg/dl higher UA level was 1.101, [95%CI 1.009-1.202], p=0.031)

Line 174-177 (Results) In the subgroup analysis, UA was associated with an increased risk for the non-renal outcome in PRD and HTN group. PRD and HTN was associated with an increased risk for the non-renal outcome (adjusted HR [95% Cl] PRD, 1.248 [1.003 – 1.553]; HTN, 1.250 [1.035 – 1.510]) Per 1 mg/dl higher UA level, multivariable adjusted HR was 1.248 (95% CI: 1.003 to 1.553) for PRD, and 1.250 (1.035 to 1.510) for HTN.

Line 192-194 (Discussion) We analyzed UA as a continuous variable and demonstrated that per 1 mg/dl higher UA level, multivariable adjusted HR was 1.248 (95% CI: 1.003 to 1.553) for PRD, and 1.250 (1.035 to 1.510) for HTN.

Legends for Figure 3, Adjusted for underlying disease of CKD, eGFR, urinary protein, systolic blood pressure, past history of cardiac disease, ACEis/ARBs, diuretics, statins, antiplatelets, allopurinol, age, sex, smoking, body mass index, hemoglobin, albumin. Associations are measured per 1 mg/dl increment of UA using Cox proportional hazard regression. Hazard ratios (HRs) were adjusted for underlying disease of CKD, eGFR, urinary protein, systolic blood pressure, past history of cardiac disease, ACEi/ARBs, diuretics, statins, antiplatelets, allopurinol, age, sex, smoking, body mass index, hemoglobin, albumin.

Legends for Figure 4, Adjusted for underlying disease of CKD, eGFR, urinary protein, systolic blood pressure, past history of cardiac disease, ACEis/ARBs, diuretics, statins, antiplatelets, allopurinol, age, sex, smoking, body mass index, hemoglobin, albumin. Associations are measured per 1 mg/dl increment of UA using Cox proportional hazard regression. Hazard ratios (HRs) were adjusted for underlying disease of CKD, eGFR, urinary protein, systolic blood pressure, past history of cardiac disease, ACEi/ARBs, diuretics, statins, antiplatelets, allopurinol, age, sex, smoking, body mass index, hemoglobin, albumin.

Q3: The authors re-analyzed the HR after taking statin and anti-platelet into consideration in the revised manuscript. In the Statistical analysis sections and Results section, adjusting for statin and anti-platelet should be mentioned. Please make sure that all corresponding description in the manuscript have been modified.

[Response]

We checked all corresponding description in the manuscript and modified as follows.

Line 142-145 (Methods) Analyzed variables included underlying disease of CKD, eGFR, urinary protein, systolic blood pressure, past history of cardiac disease, ACE inhibitor and/or ARB use, diuretic use, statins, antiplatelets, age, sex, smoking habits, BMI, hemoglobin, and albumin.

Line 162-166 (Results) In all subjects, UA was not an independent risk factor for ESRD with the Cox proportional hazard model adjusted for underlying disease causing CKD, eGFR, urinary protein, systolic blood pressure, past history of cardiac disease, ACE inhibitors/ARBs, diuretics, statins, antiplatelets, age, sex, smoking, BMI, hemoglobin, and albumin.

Line 171-174 (Results) In all subjects, UA was not an independent risk factor for the non-renal outcome with the Cox proportional hazard model adjusted for underlying disease causing CKD, eGFR, urinary protein, systolic blood pressure, past history of cardiac disease, ACE inhibitors/ARBs, diuretics, statins, antiplatelets, age, sex, smoking, BMI, hemoglobin, and albumin.

Q4: In line 172-173, The sentence "In the subgroup analysis, PRD and HTN was associated with an increased risk for the non-renal outcome" was confusing. Please make it more clear.

[Response]

We modified the sentence as follows according to the suggestion.

Line 174-176, In the subgroup analysis, PRD and HTN was associated with an increased risk for the non-renal outcome UA was associated with an increased risk for the non-renal outcome in PRD and HTN group

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Decision Letter 2

Ping-Hsun Wu

15 Mar 2021

Different clinical impact of hyperuricemia according to etiologies of chronic kidney disease: Gonryo Study

PONE-D-20-34099R2

Dear Dr. Kimio Watanabe,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Ping-Hsun Wu, M.D. PhD.

Academic Editor

PLOS ONE

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Reviewer #2: All comments have been addressed

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Reviewer #2: Yes

**********

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Reviewer #2: Yes

**********

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Reviewer #2: No

**********

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Acceptance letter

Ping-Hsun Wu

17 Mar 2021

PONE-D-20-34099R2

Different clinical impact of hyperuricemia according to etiologies of chronic kidney disease: Gonryo Study

Dear Dr. Watanabe:

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    Supplementary Materials

    S1 Table. Associations of uric acid with renal and non-renal outcomes.

    (DOCX)

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    S2 Table. Associations of allopurinol with renal and non-renal outcomes.

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