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. 2021 Jan 27;16(1):e0244106. doi: 10.1371/journal.pone.0244106

The effect of baseline serum uric acid on chronic kidney disease in normotensive, normoglycemic, and non-obese individuals: A health checkup cohort study

Young-Bin Son 1, Ji Hyun Yang 1, Myung-Gyu Kim 1, Sang Kyung Jo 1, Won Yong Cho 1, Se Won Oh 1,*
Editor: Cheng Hu2
PMCID: PMC7840038  PMID: 33503029

Abstract

Introduction

The independent role of serum uric acid (SUA) on kidney disease is controversial due to its association with metabolic syndrome. The objective of this study was to investigate the association of baseline SUA with development of chronic kidney disease and eGFR decline in normotensive, normoglycemic and non-obese individuals during follow up period.

Materials and methods

We included non-hypertensitive, non-diabetic, and non-obese 13,133 adults with estimated glomerular filtration rate (eGFR) ≥ 60ml/min/1.73m2 who had a voluntary health check-up during 2004–2017.

Results

SUA was positively related to adjusted means of systolic blood pressure (SBP), triglyceride, body mass index, and body fat percent. SUA was inversely associated with high density lipoprotein HDL (P for trend ≤0.001). SUA was an independent risk factor for the development of diabetes, hypertension, and obesity. During 45.0 [24.0–76.0] months of median follow up, the highest quartiles of SUA showed significant risks of 30% eGFR decline compared than the lowest quartile (RR:3.701; 95% CI: 1.504–9.108). The highest quartile had a 2.2 fold (95% CI: 1.182–4.177) increase in risk for incident chronic kidney disease (CKD).

Conclusions

SUA is an independent risk factor for the development of diabetes, hypertension, and obesity in the healthy population. High SUA is associated with increased risk of CKD development and eGFR decline in participants with intact renal function.

Introduction

Uric acid has been suggested as a potentially modifiable risk factor for chronic kidney disease (CKD) [1–3]. Tubulointerstitial precipitation of uric acid can lead to renal damage [4]. Regardless of uric acid crystal, animal studies have shown that uric acid causes vascular smooth muscle cell proliferation in afferent arteriole, tubulointerstitial inflammation, insterstitial fibrosis, and eventually renal dysfunction [5].

However, recent clinical studies did not show consistent results about the effect of uric acid on renal outcomes. Some small controlled clinical studies have reported that urate lowering therapy could slow CKD progression [6–9]. In contrast, other studies did not show the beneficial effect of urate lowering therapy in patients with diabetic nephropathy, IgA nephropathy, or CKD stage 3 [10–12]. A recent large scaled clinical trial has reported that urate lowering therapy does not reduce the decline of renal function in CKD 3 patients. However, it has significant benefits for those whom serum creatinine level is lower than median or in patients without proteinuria [13].

On the other hand, increasing intake of purine and fructose diet can cause hyperuricemia and obesity [14]. Hyperuricemia is associated with insulin resistance, hypertension (HTN), and diabetes mellitus (DM) [15–18]. These metabolic factors can lead to renal damage and they are confounders when analyzing the effect of uric acid on renal outcome.

Therefore, we planned longitudinal studies for assessing development of CKD according to baseline serum uric acid (SUA) in participants who had intact renal function. We investigated the effect of SUA in participants who did not have metabolic abnormalities such as DM, HTN or obesity to assess the independent association between SUA and renal outcome.

Materials and methods

Participants

Participants were those who underwent general health check-up during 2004–2017 in Korea University Anam Hospital. We included 55,098 participants aged ≥18 years with estimated glomerular filtration rate (eGFR) ≥ 60 ml/min/1.73m2. Among them, we exclude 38,103 participants whose serum creatinine were checked only one time and 3,562 participants who had HTN (N = 2,743), DM (N = 797) or obesity (N = 492) (Fig 1). We divided 13,133 participants into gender-specific quartile groups according to serum uric acid. This study was approved by the Institutional Review Board of Korea University Anam Hospital Clinical Trial Center (IRB No. 2019AN0181). It was conducted in accordance with the Declaration of Helsinki. Institutional review board approved that informed consent is not necessary because this is a retrospective study.

Fig 1. Selection of study population.

Fig 1

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Measurements

Blood samples after an 8-hour fast were collected year-round and immediately processed, refrigerated, and transported (in cold storage) to the laboratory for analysis within 12 hours: serum uric acid, creatinine, hemoglobin (Hb), white blood cell (WBC), aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), bilirubin, protein, albumin, glucose, cholesterol, triglyceride (TG), high density lipoprotein (HDL), low density lipoprotein (LDL), C-reactive protein (CRP) were measured. Measurement of serum creatinine was performed using Toshiba Neo (Toshiba Medical System Co, Otawara, Japan) between 2004 and Nov. 2012 or Beckman Coulter AU5811, 5821 (Diamond Diagnostics, Holliston, MA, USA) between Dec. 2012 and Nov. 2018. Serum creatinine was measured with the Jaffe kinetic method (Jan. 2004—Nov. 2012, CLINIMATE Creatinine sekisui, Sekisui Medical Co. Ltd., Tokyo, Japan; Dec. 2012—Nov. 2018; Beckman Creatinine, Beckman Coulter, Inc., USA). GFR was estimated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation [19]. Urine protein was measured by dipstick urinalysis. Results are reported using a semiquantitative scale from negative to 4+.

Definitions

HTN was defined as the presence of either (i) systolic BP (SBP) ≥ 140 mmHg or diastolic BP (DBP) ≥ 90 mmHg or (ii) diagnostic code of hypertension. DM was defined as participants who fulfilled at least one of the following three criteria: (i) fasting blood glucose (FBS) ≥126 mg/dL; (ii) HbA1c ≥ 6.5%; (iii) diagnostic code of diabetes. Body mass index (BMI) was calculated based on weight and height (kg/m2). Obesity was defined as BMI ≥ 30 kg/m2. Proteinuria was defined as dipstick urinalysis above 1+. Decline of renal function was defined as 30% of decrease of follow up eGFR compared to baseline eGFR. Incident CKD was defined as the incidence of eGFR decline below 60 ml/min/1.73m2. Body fat and muscle percent were measured using bioelectrical impedance analysis (InBody770, InBody Co, Ltd., Seoul, Korea). Malignancy was defined as presence of “C” code in electronic medical record.

Statistical analysis

All analyses were performed using SPSS software (SPSS version 25.0, Chicago, IL, USA). Data are presented as mean ± standard deviation (SD) for continuous variables and as percentage for categorical variables. Differences were analyzed using Chi-square test for categorical variables and analysis of variance (ANOVA) for continuous variables. Adjusted means and 95% confidence intervals (95% CIs) of SBP, TG, HDL, BMI, body fat percent and FBS were calculated using analysis of covariance to adjust independent factors related to SUA and post-hoc analysis was used to correct for multiple comparisons. Risks and 95% CIs of development of HTN, DM, obesity, decline in eGFR, and incident CKD were calculated using cox regression analysis. A P value < 0.05 was considered statistically significant.

Results

Baseline characteristics of participants

Baseline characteristics of participants are described in Table 1. The study cohort had an average age of 44.5 ± 10.2 years, an eGFR of 92.2 ± 13.6 ml/min/1.73 m2, and a uric acid level of 5.2 ± 1.4 mg/dL. Males accounted for 54.5%. Higher SUA levels were significantly associated with younger age and higher levels of hemoglobin, protein, albumin, and liver enzymes such as AST, ALT, and ALP. Higher SUA was also associated with higher WBC and CRP but lower eGFR. Higher SUA was related to higher BMI, BP, FBS and dyslipidemia such as higher total cholesterol, TG, LDL, and lower HDL (Table 1).

Table 1. Baseline characteristics of study population.

Uric acid
1st (N = 3230) 2nd (N = 3118) 3rd (N = 3419) 4th (N = 3366)
Age (years) 45.5±10.0 44.6±10.2 43.8±10.0 44.1±10.3 <0.001
BMI (kg/m2) 22.6±2.7 22.9±2.6 23.3±2.7 24.0±2.7 <0.001
Men (%) 1718 (53.2) 1738 (55.7) 1858 (54.3) 1842 (54.7) 0.223
SBP (mmHg) 111±11 111±11 112±11 113±11 <0.001
DBP (mmHg) 68±9 68±9 69±9 70±9 <0.001
Uric acid 3.9±0.9 4.9±0.9 5.5±1.0 6.5±1.2 <0.001
eGFR (mL/min/1.73 m2) 95.1±13.3 93.3±13.5 91.8±13.3 88.7±13.6 <0.001
Hb (g/dL) 14.0±1.7 14.3±1.5 14.4±1.5 14.5±1.4 <0.001
WBC (1000/μL) 5.6±1.6 5.7±1.5 5.8±1.5 6.0±1.5 <0.001
AST (IU/L) 22.3±14.0 22.9±20.0 22.9±12.2 24.4±12.4 <0.001
ALT (IU/L) 21.0±23.1 22.3±25.2 23.0±16.9 26.4±22.9 <0.001
ALP (IU/L) 54.4±17.2 54.8±16.3 55.4±17.1 56.9±17.1 <0.001
Bilirubin 0.81±0.36 0.84±0.38 0.84±0.38 0.85±0.36 0.001
Protein 7.2±0.4 7.2±0.4 7.2±0.4 7.3±0.4 <0.001
Albumin 4.5±0.3 4.5±0.3 4.5±0.3 4.6±0.3 <0.001
Glucose (mg/dL) 90.5±9.2 90.2±9.4 90.5±9.3 91.2±9.9 <0.001
Cholesterol(mg/dL) 180.7±31.7 183.7±32.0 185.9±31.3 192.3±34.2 <0.001
TG (mg/dL) 105.7±64.9 112.6±66.2 120.9±76.9 140.9±95.7 <0.001
HDL (mg/dL) 55.7±13.5 54.2±12.7 53.8±12.8 52.4±13.1 <0.001
LDL (mg/dL) 106.2±27.8 109.4±28.6 111.7±28.6 116.9±31.7 <0.001
CRP 1.2±3.3 1.2±2.8 1.3±2.5 1.7±3.9 <0.001
Malignancy (%) 174 (5.4) 149 (4.8) 184 (5.4) 190 (5.6) 0.462
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Abbreviations: BMI (body mass index), systolic blood pressure (SBP), diastolic blood pressure (DBP), estimated glomerular filtration rate (eGFR), hemoglobin (Hb), white blood cell (WBC), aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), triglyceride (TG), high density lipoprotein (HDL), low density lipoprotein (LDL), C-reactive protein (CRP), diabetes mellitus (DM), and hypertension (HTN).

Association of SUA with metabolic disorders at baseline

Associations of SUA with SBP, TG, HDL, BMI, body fat percent, and FBS were evaluated after adjusting for multiple factors at baseline. SBP was positively related to SUA (P for trend = 0.001). Adjusted SBP of 4th quartile was significantly higher than that of the 1st quartile (112.1 ± 0.2 mmHg vs. 111.4 ± 0.2 mmHg, P = 0.003) (Fig 2A).

Fig 2. Association of Serum Uric Acid (SUA) with metabolic disorders.

Fig 2

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A. The highest quartile had significantly higher of systolic blood pressure (SBP) than the lowest quartile (P = 0.003). B. The 3rd and the highest quartiles had significantly higher triglyceride (TG) than the lowest quartile (P< 0.001). C. The 2nd, 3rd, and the highest quartiles had significantly higher high density lipoprotein (HDL) than the lowest quartile (P< 0.001). D. The 2nd, 3rd, and the highest quartiles had significantly higher BMI than the lowest quartile (P ≤0.024). E. The 2nd, 3rd, and the highest quartiles had significantly higher body fat percent than the lowest quartile (P ≤0.009). Body fat percent was measured in 3,682 participants. F. FBS was not associated with SUA (P >0.05). *P < 0.05 vs. the lowest uric acid quartile. SBP, TG, HDL, BMI, body fat percent, and FBS were adjusted by age, hemoglobin, white blood cell count, estimated glomerular filtration rate, serum albumin, aspartate aminotransferase, alanine aminotransferase, total cholesterol, and low density lipoprotein. Adjusted means and 95% confidence intervals (95% CIs) of SBP, TG, HDL, BMI, body fat percent and FBS were calculated using analysis of covariance to adjust independent factors related to SUA.

TG, BMI, and body fat percent had positive relations with SUA (P for trend < 0.001). The TG of the 3rd or 4th quartile was significantly higher than that of the 1st quartile (P <0.001) (Fig 2B). Adjusted means of BMI and body fat percent were higher in the 3rd, and 4th quartiles than those of the lowest quartile (P ≤ 0.024) (Fig 2D and 2E). SUA was inversely associated with HDL (P for trend < 0.001). HDL of the 2nd, 3rd, and 4th quartiles were significantly lower than those of the lowest quartile (P < 0.01) (Fig 2C). Adjusted FBS was not associated with SUA (Fig 2F).

Development of diabetes, hypertension, and obesity according to SUA quartiles

During 45.0 [24.0–76.0] months of follow up period, we analyzed the incidence of new onset DM, HTN, and obesity. DM, HTN, and obesity were developed in 341 (2.6%), 765 (5.8%), and 124 (0.9%) participants, respectively. The 3rd, and 4th quartiles of SUA showed higher risk for the development of DM than the lowest quartile by multivariate analysis (RR: 1.805, 95% CI: 1.305–2.498; RR: 1.767, 95% CI: 1.279–2.442, respectively). SUA was related to the development of HTN and obesity. The 3rd and 4th quartiles had higher risk of the development of HTN (RR: 1.285, 95% CI: 1.038–1.590 and RR: 1.302, 95% CI: 1.051–1.614) than the lowest quartile. The highest quartile of SUA was related to the development of obesity (RR: 1.792, 95% CI: 1.028–3.121) (Table 2).

Table 2. Risks for the development of hypertension, diabetes, and obesity according to the quartiles of baseline serum uric acid level.

HTN DM Obesity
RR 95% CI P RR 95% CI P RR 95% CI P
1st reference reference reference
2nd 0.987 0.788–1.234 0.906 1.165 0.832–1.631 0.373 0.801 0.403–1.591 0.526
3rd 1.285 1.038–1.590 0.022 1.805 1.305–2.498 <0.001 1.188 0.652–2.165 0.575
4th 1.302 1.051–1.614 0.016 1.767 1.279–2.442 0.001 1.792 1.028–3.121 0.039
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Abbreviations: hypertension (HTN), diabetes mellitus (DM)/

Relative risks (RR) and 95% confidence intervals (95% CIs) of development hypertension, diabetes and obesity were calculated using cox regression analysis.

Risks were adjusted by age, sex, systolic blood pressure, body mass index, estimated glomerular filtration rate, hemoglobin, white blood cell, low density lipoprotein, aspartate aminotransferase, alanine aminotransferase, fasting blood sugar, serum albumin, total cholesterol and malignancy.

Higher SUA related to worse renal outcomes

A total of 47 (0.4%) participants had 30% decline in eGFR during the follow up period. The highest quartile of SUA was significantly associated with 30% decline in eGFR in unadjusted and age- and sex- adjusted analysis. When risks were adjusted by multiple factors, the highest quartiles of SUA showed significant risks of 3.7 fold in 30% eGFR decline compared to corresponding risk of the lowest quartile (RR: 3.701, 95% CI: 1.504–9.108).

Incident CKD was developed in 101 (0.8%) participants. Models 1 and 2 showed significant associations of incident CKD with 4th quartiles of SUA. Model 3 showed that the highest SUA quartile had a 2.2 -fold (95% CI: 1.182–4.177, P = 0.013) increase in risk for incident CKD compared to the lowest quartile (Table 3).

Table 3. Risks for the incidence of GFR decline and CKD development according to the quartiles of baseline serum uric acid level.

Decline in eGFR of 30%
Model 1 Model 2 Model 3
RR 95% CI P RR 95% CI P RR 95% CI P
1st reference reference reference
2nd 0.518 0.151–1.770 0.294 0.515 0.151–1.763 0.291 0.603 0.173–2.098 0.427
3rd 1.702 0.679–4.267 0.257 1.736 0.692–4.354 0.239 2.098 0.814–5.406 0.125
4th 3.011 1.292–7.019 0.011 3.067 1.316–7.153 0.009 3.701 1.504–9.108 0.004
Development of CKD
Model 1 Model 2 Model 3
RR 95% CI P RR 95% CI P RR 95% CI P
1st reference reference reference
2nd 0.975 0.458–2.076 0.947 0.931 0.436–1.986 0.853 0.732 0.340–1.575 0.425
3rd 1.274 0.624–2.601 0.505 1.428 0.699–2.917 0.329 0.803 0.385–1.677 0.560
4th 3.964 2.168–7.249 <0.001 4.853 2.643–8.910 <0.001 2.222 1.182–4.177 0.013
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Abbreviations: estimated glomerular filtration rate (eGFR), chronic kidney disease (CKD).

Relative risks (RR) and 95% confidence intervals (95% CIs) of decline in eGFR, and incident CKD were calculated using cox regression analysis.

Model 1: Unadjusted.

Model 2: adjusted by age, sex.

Model 3: adjusted by age, sex, systolic blood pressure, body mass index, estimated glomerular filtration rate, hemoglobin, white blood cell, low density lipoprotein, aspartate aminotransferase, alanine aminotransferase, fasting blood sugar, serum albumin, total cholesterol and malignancy.

Discussion

In this study, SUA was associated with BMI, BP, dyslipidemia, and development of DM, HTN and obesity. High SUA is associated with increased risk of the development of DM, although SUA was not associated with FBS cross-sectionally. SUA was associated with decline in renal function and development of CKD. Interestingly, the risk of decline in renal function according to SUA was significant in participants without DM, HTN, and obesity.

The hypothesis that uric acid is a possible factor for renal disease is not new. Epidemiologic studies demostrated elevated serum uric acid as a risk factor for the development of acute and chronic kidney disease, hypertension, and diabetes [20]. A meta-analysis of 15 cohort studies showed that the relative risk of CKD was 1.22 per 1 mg/dL serum uric level increment [21]. SUA is an independent risk factor of cardiovascular disease and mortality [22, 23]. Animal experiments have reported that increases in serum uric acid by inhibiting urate oxidase can increase renal renin and decrease plasma nitrate, resulting in vasoconstriction and hypertension [24, 25]. Early hypertension is reversible by lowering uric acid. However, prolonged hyperuricemia can lead to activation of inflammatory mediators and grow factors, vascular smooth muscle cell proliferation, and vascular wall thickening. Reduction of SUA is insufficient to control high blood pressure in a prolonged state of hyperuricemia [5, 25, 26].

Accordingly, we hypothesized that SUA might be modifiable risk factor of renal outcome in participants without chronic vascular damage. Therefore, the association of SUA with renal outcome in participants with intact renal function was analyzed and significant risks were observed in participants with higher baseline SUA. A recent randomized trial did not demonstrate the improvement of renal function by urate lowering therapy in stage 3 CKD with asymptomatic hyperuricemia [13]. However, subgroup analysis showed significant benefit of uric acid lowering therapy in patients without proteinuria and with higher renal function [13]. An observational study in 3,885 individuals with CKD stages 2–4 also showed that SUA was an independent risk factor for kidney failure only in earlier stages of CKD, but not associated with kidney failure in late stages of CKD [3]. A previous cohort study demonstrated that SUA is related to the new development of hypertension, but not to the incidence of CKD [27]. In this study, SUA is no longer an independent risk factor to predict the incidence of CKD by multivariate analysis and SUA is affected by the confounding effect of eGFR.

However, whether SUA is an independent risk factor for renal function decline remains unclear because metabolic profile at baseline is significant worse in participants with higher SUA. Hyperuricemia is related to obesity and insulin resistance [15, 16]. Increase intake of fructose and purine diet can cause hyperuricemia [14]. Plasma uric acid is elevated in obese mice due to production and secretion of uric acid in adipose tissue by increased production of xanthine oxidoreductase [28]. In addition, higher levels of circulating insulin can inhibit the excretion of uric acid through the kidney [29, 30]. To eliminate the effect of metabolic factors, we investigated the effect of SUA on renal outcome in participants without DM, HTN, and obesity. These associations of SUA with renal outcome was significant in such subjects without metabolic abnormalities. SUA is associated with systemic inflammatory markers in children with asymptomatic hyperuricemia [31]. Hyperuricemia causes increased of monocyte chemoattractant protein-1 and primes monocyte trafficking in gout patients [32]. In this study, we observed SUA was independently associated with inflammatory markers such as WBC and CRP. SUA is associated with increased arterial stiffness and decreased renal function in normotensive individuals [33]. Irrespective of metabolic abnormalities, SUA might contribute to the development of CKD by increasing inflammation and vascular stiffness.

The relationship of FBS with SUA remains controversial. Many studies have reported positive relationships between serum glucose and SUA [14–16, 18]. One study on 11,183 with normal glucose tolerance has demonstrated that a U-shape relationship between SUA and FBS [34]. By contrast, SUA is inversely related to FBS in studies conducted on healthy population [35, 36]. The third National Health and Nutrition Examination Survey showed that SUA levels were negatively associated with type 2 DM [35]. The relationship between SUA and FBS is currently unclear. Approximately 70% of uric acid is excreted by the kidney. Among freely filtered uric acid through glomerulus, 90% is reabsorbed through proximal tubule [37]. Low SUA was observed in participants treated with sodium glucose cotransporter 2 inhibitors. Such low SUA may be due to increased excretion of uric acid in proximal renal tubule by increased glycosuria [38, 39]. In our study, cross-sectional analysis revealed that SUA was not associated with FBS after the adjustment. Uricosuric effect in participants with high amount of glycosuria could affect the cross-sectional relationship between SUA and FBS. However, and the incidence of DM was increased in participants with higher SUA in accordance with increased development of obesity after a long-term follow up.

This study has several limitations. First, we did not have data of medications. Therefore, the prevalence of HTN, DM, and dyslipidemia might have been underestimated. Second, this study was performed on a healthy population. The association of SUA with renal outcome could be different in CKD patients. Third, we included the participants who measured serum creatinine two times, and the defining CKD could be overestimated because there is a possibility that we included the participants who had a transient impairment of renal function at the follow up study. Finally, this study only investigated Koreans. However, data were analyzed cross-sectionally and longitudinally. In addition, we could investigate temporal relationship of SUA with metabolic abnormalities and renal outcomes. We also investigated the relationship of SUA with renal outcomes in participants without metabolic abnormalities.

In conclusion, high SUA is an independent risk factor for the development of diabetes, hypertension, and obesity in the healthy population. High SUA is associated with increased risk of CKD development and eGFR decline in participants with intact renal function.

Acknowledgments

We would like to thank Hyeon Jin Min and Bong Gyun Sun for the contribution of this work.

Data Availability

There are ethical restrictions on sharing a de-identified data set. The ethics committee in Korea University Anam Hospital do not approve that the patient’s data be open to the public. The data is only available to the researchers whose research proposal has been examined and approved the ethics committee of Korea University Anam Hospital. If other researchers would like to access the data, they should submit their research proposal in the homepage (http://ctc.kumc.or.kr/).

Funding Statement

This study is supported by a Korea University Grant (Grant No. K2008381)

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Decision Letter 0

Dulce Elena Casarini

5 Aug 2020

PONE-D-20-13895

Serum uric acid and risk of chronic kidney disease in normotensive, normoglycemic, and non-obese individuals

PLOS ONE

Dear Dr.  Se Won Oh 

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.

It would be important for the authors to try to revise the comments made by this editor and regarding the statistics observed by one of the referees with whom I agree that it will certainly improve the study.

The study was well conducted but the authors need to analyze some points that I consider to be important in the manuscript, and that, if modified, will contribute to improving the text. Suggestions:

- the summary would need to be reformulated as it does not make it clear that it isis a follow-up study;

- in methods it would be necessary to describe the power of the sample used in the study and also it is important to describe in the results all the variables used;

- what were the analyzes carried out in order to verify if the ANOVA test is suitable for the study, and it would also be important to consider if the results obtained do not depend only on the high number of individuals collected in the study, therefore, they are really representative of the studied population, and,  

- when looking for risk calculation I believe it is better to use logistic regression analysis.

I hope that the authors will consider the suggestions made by the referees and this editor revising the manuscript..

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We look forward to receiving your revised manuscript.

Kind regards,

Dulce Elena Casarini, PhD, FAHA

Academic Editor

PLOS ONE

Additional Editor Comments:

The study was well conducted but the authors need to analyze some points that I consider to be important in the manuscript, and that, if modified, will contribute to improving the text.

Suggestions:

- the summary would need to be reformulated as it does not make it clear that it isis a follow-up study;

- in methods it would be necessary to describe the power of the sample used in the study and also it is important to describe in the results all the variables used;

- what were the analyzes carried out in order to verify if the ANOVA test is suitable for the study, and it would also be important to consider if the results obtained do not depend only on the high number of individuals collected in the study, therefore, they are really representative of the studied population, and,

- when looking for risk calculation I believe it is better to use logistic regression analysis.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

**********

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

Reviewer #1: Yes

Reviewer #2: No

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. 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: Dear authors

Congratulations

You -the authors of the current research studied the association between serum uric acid levels and declining of renal function in individuals without comorbidities from Korea. You observed that SUA is an independent risk factor for declining eGFR, even in individuals with a normal range of renal function and without metabolic disorder. Despite being a retrospective study, you show interesting data showing the relationship that was the objective of the current research.

But, I need to make some small comments, such as...

In page 4

materials and methods

-It is necessary a figure with flowchart showing enrolment and exclusion criterias of individuals in this study.

In page 7; the results part

Higher SUA related to worse renal outcomes

I guess is better to describe:

-When risks were adjusted by multiple factors, the highest quartiles of SUA showed significant risks of 3.7 fold in eGFR decline compared to corresponding risk of the lowest quartile (RR: 3.701, 95% CI: 1.504-9.108).

-It is correct to assume that "...highest SUA quartile had a 2.222-fold (95% CI: 1.182-4.177, P =0.013) increase in risk for incident CKD...".

I see that is better "...highest quartile had a 2.2 fold (95% CI: 1.182-4.177) increase in risk for incident chronic kidneyd isease (CKD)".

Reviewer #2: This is an interesting paper and appears to have approached an important question regarding whether high levels of uric acid can be associated with loss in the renal function in adult population. However, there are several important issues that require clarification.

1) The title does not reflect the findings of the manuscript. It is not clear that this is a follow-up study. After the follow-up, there are already hypertensive and metabolically unhealthy individuals. Therefore, the title is inappropriate.

2) Please, do not use abbreviations in the summary section

3) The summary is not adequate. It is not clear in the aim section that this is a follow-up study.

4) Describe how the patients were recruited so that the reader can determine how representative this sample is of the population. For example, were these consecutive patients presenting to the Center?

5) Blood pressure data cannot be represented in decimals, please correct.

6) In the methodology section, it is important to describe all the variables present in the results.

7) Were normality tests performed?

8) How was the body fat percentage obtained?

9) What diagnostics were done to check that ANOVA fit and that results were not dependent on only the high number of individuals?

10) Wouldn't it be more informative to examine the baseline data by correlation analysis.

11) In Table 1, it appears that many variables do not show a linear trend across the quartiles of uric acid (e.g. Hb, AST, ALT, ALP, bilirubin, protein, albumin, glucose). This contradicts the claim that there is a linear trend (P < 0.001).

12) It would be more appropriate to perform logistic regression for the risk calculation

13) It would be appropriate to perform Poisson Regression

14) Results (Figures): The graphic quality is very poor.

15) The discussion section is very simple and could be better detailed.

16) The conclusion is confusing and speculative.

**********

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2021 Jan 27;16(1):e0244106. doi: 10.1371/journal.pone.0244106.r002

Author response to Decision Letter 0

18 Oct 2020

Dear reviewers

Thank you for your thoughtful comments regarding our manuscript. We took your comments seriously and revised our manuscript again.

Reviewer #1: Dear authors

Congratulations

You -the authors of the current research studied the association between serum uric acid levels and declining of renal function in individuals without comorbidities from Korea. You observed that SUA is an independent risk factor for declining eGFR, even in individuals with a normal range of renal function and without metabolic disorder. Despite being a retrospective study, you show interesting data showing the relationship that was the objective of the current research.

But, I need to make some small comments, such as...

In page 4

materials and methods

-It is necessary a figure with flowchart showing enrolment and exclusion criterias of individuals in this study.

Thank you for your correction. I added flowchart of study population.

In page 7; the results part

Higher SUA related to worse renal outcomes

I guess is better to describe:

-When risks were adjusted by multiple factors, the highest quartiles of SUA showed significant risks of 3.7 fold in eGFR decline compared to corresponding risk of the lowest quartile (RR: 3.701, 95% CI: 1.504-9.108).

-It is correct to assume that "...highest SUA quartile had a 2.222-fold (95% CI: 1.182-4.177, P =0.013) increase in risk for incident CKD...".

I see that is better "...highest quartile had a 2.2 fold (95% CI: 1.182-4.177) increase in risk for incident chronic kidneyd isease (CKD)".

Thank you for your correction. I changed the manuscript as your suggestions.

Reviewer #2: This is an interesting paper and appears to have approached an important question regarding whether high levels of uric acid can be associated with loss in the renal function in adult population. However, there are several important issues that require clarification.

1) The title does not reflect the findings of the manuscript. It is not clear that this is a follow-up study. After the follow-up, there are already hypertensive and metabolically unhealthy individuals. Therefore, the title is inappropriate.

Thank you for your comments. I changed the title as “The effect of baseline serum uric acid on chronic kidney disease in normotensive, normoglycemic, and non-obese individuals: A health checkup cohort study.”

2) Please, do not use abbreviations in the summary section

Thank you for your correction. I added full terminology before the use of abbreviations in the abstract section.

3) The summary is not adequate. It is not clear in the aim section that this is a follow-up study.

Thank you for your comments. I added the comments regarding follow-up study in the abstract section.

4) Describe how the patients were recruited so that the reader can determine how representative this sample is of the population. For example, were these consecutive patients presenting to the Center?

Korea University Anam Hospital is a tertiary hospital and has a health checkup center. Participants voluntarily came to the hospital and performed general health checkup. Among them, approximately 30.8% of participants retested health checkup voluntarily.

5) Blood pressure data cannot be represented in decimals, please correct.

I corrected blood pressure data in table 1.

6) In the methodology section, it is important to describe all the variables present in the results.

Thank you for your comments. I added about the description of all the variables in the methodology section.

7) Were normality tests performed?

We performed normality tests in all variables in this study. As previous studies documented (Am J Med. 1965; 39: 242-51, J Clin Hypertens (Greenwich). 2017 Jan;19(1):45-50), serum uric acid was not normally distributed and skewed to the high value end of the scale ( Kolmogorov-Smirnov test, P >0.05).

Average= 5.21; standard deviation= 1.375; N= 13,133

7) How was the body fat percentage obtained?

We measured total body fat mass and lean body mass using bioelectrical impedance analysis (InBody770, InBody Co, Ltd., Seoul, Korea). And fat percentage was calculated based on body weight (fat mass/ body weight *100).

8) What diagnostics were done to check that ANOVA fit and that results were not dependent on only the high number of individuals?

Only the high values of serum uric acid (the highest quartile of serum uric acid) showed a significant risk increase for development of chronic kidney disease and eGFR decline, and other groups of serum uric acid (1st, 2nd 3rd quartile of serum uric acid) was not associated with development of chronic kidney disease and eGFR decline. We analyzed these results using cox regression analysis. ANOVA was not used.

9) Wouldn't it be more informative to examine the baseline data by correlation analysis.

I re-examined baseline data by correlation analysis between serum uric acid with many variables.

Serum uric acid was positively associated with systolic blood pressure (P<0.001, r=0.289), diastolic blood pressure (P<0.001, r=0.304), body mass index (P<0.001, r=0.363), white blood cell count (P<0.001, r=0.218), hemoglobin (P<0.001, r=0.565), serum protein (P<0.001, r=0.125), albumin (P<0.001, r=0.221), AST (P<0.001, r=0.136), ALT (P<0.001, r=0.230), ALP (P<0.001, r=0.173), bilirubin (P<0.001, r=0.236), total cholesterol (P<0.001, r=0.147), fasting blood glucose (P<0.001, r=0.168), triglyceride (P<0.001, r=0.331), LDL (P<0.001, r=0.190), and C-reactive protein (P<0.001, r=0.067). In addition, serum uric acid was negatively correlated with eGFR (P<0.001, r=-0.283) and HDL (P<0.001, r=-0.299).

10) In Table 1, it appears that many variables do not show a linear trend across the quartiles of uric acid (e.g. Hb, AST, ALT, ALP, bilirubin, protein, albumin, glucose). This contradicts the claim that there is a linear trend (P < 0.001).

In table 1, you can see the mean values such as Hb, AST, ALT, ALP, bilirubin, protein, albumin and glucose are increased according to the increase of uric acid quartiles. There is a linear trend between the quartiles of uric acid and following variables: age, body mass index, systolic blood pressure, diastolic blood pressure, eGFR, hemoglobin, white blood cell count, AST, ALT, ALP, bilirubin, protein, albumin, glucose, cholesterol, TG, HDL, LDL and CRP (P for trend ≤ 0.001).

11) It would be more appropriate to perform logistic regression for the risk calculation.

In table 2 and 3, we used cox regression analysis because logistic analysis cannot adjust the follow up time period. We wanted to evaluate the risk for the development of HTN, DM, obesity, and renal outcomes during follow up period. In figure 1, we used analysis of covariance to investigate the association of baseline serum uric acid with SBP, TG, HDL, BMI, body fat percent, and FBS because dependent variables were all continuous variables. Dependent variable of logistic analysis should be categorical variable.

12) It would be appropriate to perform Poisson Regression.

Unfortunately, I cannot understand fully about your comment. The dependent variables such as the development of hypertension, diabetes, obesity, eGFR decline or chronic kidney disease were “dichotomous” scale (none or presence). The events could occur only one time during follow up period and participants got a disease state after the events. However, the poisson regression may be more appropriate when the dependent variables is “count scale”: more than zero or greater.

13) Results (Figures): The graphic quality is very poor.

Thank you for your comment. I corrected the graphic.

14) The discussion section is very simple and could be better detailed.

Thank you for your comments. I added following sentences in the discussion section.

15) The conclusion is confusing and speculative.

Thank you for your comments. I corrected the conclusions as follows.

: In conclusion, high SUA is an independent risk factor for the development of diabetes, hypertension, and obesity in the healthy population. High SUA is associated with increased risk of CKD development and eGFR decline in participants with intact renal function.

Thank you for your consideration.

Sincerely,

Se Won Oh

Associate professor

Division of Nephrology, Department of Internal Medicine, Korea University Anam Hospital, Korea University College of Medicine

73, Inchon-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea; Tel: 82-2-920-6260; e-Mail: hisy81@hanmail.net

Attachment

Submitted filename: response_reviewers.docx

Click here for additional data file. (188KB, docx)

Decision Letter 1

Cheng Hu

3 Dec 2020

The effect of baseline serum uric acid on chronic kidney disease in normotensive, normoglycemic, and non-obese individuals: A health checkup cohort study

PONE-D-20-13895R1

Dear Dr. Oh,

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.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Cheng Hu

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

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Reviewer #1: The authors answered all doubts and questions made to them about the current manuscript. The authors aligned the title with the objectives and the conclusion. They made a new chart. They managed to mitigate the statistical deficiency. They managed to improve the discussion of the manuscript. In my opinion, the manuscript is now ready to be published.

Reviewer #2: (No Response)

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Reviewer #1: No

Reviewer #2: No

Acceptance letter

Cheng Hu

13 Jan 2021

PONE-D-20-13895R1

The effect of baseline serum uric acid on chronic kidney disease in normotensive, normoglycemic, and non-obese individuals: A health checkup cohort study

Dear Dr. Oh:

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on behalf of

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Associated Data

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

    Supplementary Materials

    Attachment

    Submitted filename: response_reviewers.docx

    Click here for additional data file. (188KB, docx)

    Data Availability Statement

    There are ethical restrictions on sharing a de-identified data set. The ethics committee in Korea University Anam Hospital do not approve that the patient’s data be open to the public. The data is only available to the researchers whose research proposal has been examined and approved the ethics committee of Korea University Anam Hospital. If other researchers would like to access the data, they should submit their research proposal in the homepage (http://ctc.kumc.or.kr/).

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