A machine learning-assisted model for renal urate underexcretion with genetic and clinical variables among Chinese men with gout

OBJECTIVES

The objective of this study was to develop and validate a prediction model for renal urate underexcretion (RUE) in male gout patients.

METHODS

Men with gout enrolled from multicenter cohorts in China were analyzed as the development and validation data sets. The RUE phenotype was defined as fractional excretion of uric acid (FE_UA) <5.5%. Candidate genetic and clinical features were screened by the least absolute shrinkage and selection operator (LASSO) with 10-fold cross-validation. Machine learning algorithms (stochastic gradient descent (SGD), logistic regression, support vector machine) were performed to construct a predictive classifier of RUE. Models were assessed by the area under the receiver operating characteristic curve (AUC) and the precision-recall curve (PRC).

RESULTS

One thousand two hundred thirty-eight and two thousand twenty-three patients were enrolled as the development and validation cohorts, with 1220 and 754 randomly chosen patients genotyped, respectively. Rs3775948.GG of SLC2A9/GLUT9, rs504915.AA of NRXN2/URAT1, and 7 clinical features (age, hypertension, nephrolithiasis, blood glucose, serum urate, urea nitrogen, and creatinine) were generated by LASSO. Two additional SNP variants (rs2231142.GG of ABCG2 and rs11231463.GG of SLC22A9/OAT7) were selected based on their contributions to gout in the development cohort and their reported effects on renal urate handling. The optimized classifiers yielded AUCs of ~0.914 and PRCs of ~0.980 using these 11 variables. The SGD model was conducted in the validation cohort with an AUC of 0.899 and the PRC of 0.957.

CONCLUSIONS

A prediction model for RUE composed of four SNPs and readily accessible clinical features was established with acceptable accuracy for men with gout.

Clinical classification of hyperuricemia in patients with chronic kidney disease

PURPOSE

Clinical classification of hyperuricemia (HUA) could help to guide therapy of HUA. Studies on the classification of HUA with chronic kidney disease (CKD) are rare. Therefore, we aimed to investigate the classification of HUA with CKD.

METHODS

A cross-sectional study of 428 CKD patients was conducted, including 218 HUA patients. By correlation analysis, the association of 24-h urinary uric acid (24-h Uur), uric acid clearance rate (Cur), the urinary uric acid excretion per kilogram of weight per hour (Eur) and fractional excretion of uric acid (FEur) with estimated glomerular filtration rate (eGFR) was analyzed in the HUA and non-HUA groups. According to Eur combined with Cur and the 24-h Uur combined with FEur, HUA with CKD was classified into underexcretion, renal overload, combined and 'normal' types, which were also stratified by CKD stages.

RESULTS

According to the Eur and Cur, in early CKD (eGFR ≥ 60 mL/min/1.73 m²), the underexcretion type accounted for 83.75%, and the renal overload type accounted for 2.5%. As the CKD stage increased, the proportion of the underexcretion type increased. According to the 24-h Uur and FEur, in early CKD, the underexcretion type accounted for 53.75%, and the renal overload type accounted for 15%. With increasing CKD stages, the proportion of the 'normal' type increased significantly.

CONCLUSION

Different uses of Eur with Cur or 24-h Uur with FEur varied significantly in classifying HUA patients with CKD. Eur + Cur may be more applicable to the classification of HUA patients with CKD, and further research is needed.

Effects of dapagliflozin on serum and urinary uric acid levels in patients with type 2 diabetes: a prospective pilot trial

BACKGROUND

We aimed to evaluate the effects of short-term therapy with dapagliflozin on serum uric acid (SUA) and urinary uric acid (UUA) levels in patients with type 2 diabetes.

METHODS

In this prospective pilot trial, 8 patients with type 2 diabetes mellitus were assigned to the treatment group with dapagliflozin 10 mg once daily for one week, and 7 subjects with normal glucose tolerance were recruited into the control group. Data of anthropometric measurements, SUA, 24-h UUA, fractional excretion of UA (FEUA), serum lipid parameters and 3-h oral glucose tolerance test (OGTT) were collected in both treatment and control groups; all examinations were repeated after treatment. The area under the curve of glucose (AUCGlu) was calculated to reflect the general glucose levels, while insulin resistance and islet β-cell function were reflected by indexes calculated according to the data obtained from the OGTT.

RESULTS

The weight and serum lipid parameters showed no differences before and after treatment with dapagliflozin for one week. We found SUA levels decreased from 347.75 ± 7.75 μmol/L before treatment to 273.25 ± 43.18 μmol/L after treatment, with a statistically significant difference (P = 0.001) and was accompanied by a significant increase in FEUA from 0.009 to 0.029 (P = 0.035); there was a linear correlation between SUA and FEUA levels. Glucose control, insulin sensitivity and islet β-cell function were improved to a certain extent. We also found a positive correlation between the decrease in glucose levels and the improvement in islet β-cell function.

CONCLUSIONS

The SUA-lowering effect of dapagliflozin could be driven by increasing UA excretion within one week of treatment, and a certain degree of improvement in glucose levels and islet β-cell function were observed.Trial registration ClinicalTrials.gov identifier, NCT04014192. Registered 12 July 2019, https://www.clinicaltrials.gov/ct2/show/NCT04014192:term=NCT04014192&draw=2&rank=1. Yes.

[Clinical characteristics and renal uric acid excretion in early-onset gout patients]

Objective: To investigate clinical characteristics and renal uric acid excretion in early-onset gout patients. Methods: Consecutive inpatients with primary gout were recruited between 2013 and 2017. The patients with gout onset younger than 30 were defined as early-onset group while the others were enrolled as control group. Clinical characteristics and uric acid (UA) indicators were compared between two groups. Results: Among 202 recruited patients, the early-onset group included 36 patients (17.8%). Compared with control group, the early-onset group presented more patients with obesity [13 patients (36.1%) vs. 22 patients (13.3%), P<0.05], significantly higher serum UA level [(634±124)μmol/L vs.(527±169)μmol/L] and glomerular load of UA[(7.2±2.8)mg·min(-1)·1.73m(-2) vs. (4.4±2.2)mg·min(-1)·1.73m(-2)] and estimated glomerular filtration rate (GFR) [(83±21)ml·min(-1)·1.73m(-2) vs. (67±21)ml·min(-1)·1.73m(-2)] (all P<0.05), lower fractional excretion of UA [4.4% (3.4%,6.1%) vs. 7.2% (5.2%,9.6%),P<0.05], whereas 24h urinary UA excretion was comparable [(2 788±882)μmol/1.73m(2) vs. (2 645±1 140)μmol/1.73m(2), P=0.274]. Subgroup analysis of patients without chronic kidney disease showed significantly lower fractional excretion of UA in the early-onset group [4.5%(3.3%,6.1%) vs. 6.7% (5.1%,8.7%),P<0.05]. Logistic regression analysis showed that obesity (OR=3.25) and fractional excretion of UA less than 7% (OR=9.01, all P<0.05) were risk factors of gout early onset. Conclusion: The gout patients with early-onset younger than 30 present high serum and glomerular load of uric acid which might be due to obesity and relative under-excretion of renal uric acid.

Urinary excretion of uric acid is negatively associated with albuminuria in patients with chronic kidney disease: a cross-sectional study

Background

Increasing evidence has shown that albuminuria is related to serum uric acid. Little is known about whether this association may be interrelated via renal handling of uric acid. Therefore, we aim to study urinary uric acid excretion and its association with albuminuria in patients with chronic kidney disease (CKD).

Methods

A cross-sectional study of 200 Chinese CKD patients recruited from department of nephrology of Huadong hospital was conducted. Levels of 24 h urinary excretion of uric acid (24-h Uur), fractional excretion of uric acid (FEur) and uric acid clearance rate (Cur) according to gender, CKD stages, hypertension and albuminuria status were compared by a multivariate analysis. Pearson and Spearman correlation and multiple regression analyses were used to study the correlation of 24-h Uur, FEur and Cur with urinary albumin to creatinine ratio (UACR).

Results

The multivariate analysis showed that 24-h Uur and Cur were lower and FEur was higher in the hypertension group, stage 3–5 CKD and macro-albuminuria group (UACR> 30 mg/mmol) than those in the normotensive group, stage 1 CKD group and the normo-albuminuria group (UACR< 3 mg/mmol) (all P < 0.05). Moreover, males had higher 24-h Uur and lower FEur than females (both P < 0.05). Multiple linear regression analysis showed that UACR was negatively associated with 24-h Uur and Cur (P = 0.021, P = 0.007, respectively), but not with FEur (P = 0.759), after adjusting for multiple confounding factors.

Conclusions

Our findings suggested that urinary excretion of uric acid is negatively associated with albuminuria in patients with CKD. This phenomenon may help to explain the association between albuminuria and serum uric acid.

The uricosuric effects of dihydropyridine calcium channel blockers in vivo using urate under-excretion animal models

The purpose of this study was to create novel urate under-excretion animal models using pyrazinamide and to evaluate whether dihydropyridine calcium channel blockers (CCBs) have uricosuric effects in vivo. Adult male ICR mice were treated with pyrazinamide, vehicle (dimethyl sulfoxide: DMSO), or tap water. Thirty minutes later, pyrazinamide-treated mice were given benzbromarone, losartan, nilvadipine, nitrendipine, nifedipine or azelnidipine. Six hours after the second administration, urine (by urinary bladder puncture) and plasma were collected to measure uric acid and creatinine levels, and fractional excretion of uric acid (FEUA) and creatinine clearance (Ccr) were calculated and evaluated. There was no significant difference in the levels of plasma uric acid, plasma creatinine, Ccr, urinary N-acetyl-β-d-glucosaminidase (NAG) and urinary NAG-creatinine ratio between water, DMSO, and pyrazinamide-treated mice. But the FEUA of pyrazinamide-treated mice was significantly lower than water mice. The FEUA was significantly higher in mice taking the dihydropyridine CCBs (nilvadipine, nitrendipine, nifedipine, and high-dose azelnidipine) than in pyrazinamide-treated mice. There was no significant difference in Ccr. Thus, a novel animal model created with PZA administration was useful as a urate under-excretion animal model that was probably URAT1-mediated, and the uricosuric effects of dihydropyridine CCBs were confirmed in vivo.

Genetic variation underlying renal uric acid excretion in Hispanic children: the Viva La Familia Study

Background

Reduced renal excretion of uric acid plays a significant role in the development of hyperuricemia and gout in adults. Hyperuricemia has been associated with chronic kidney disease and cardiovascular disease in children and adults. There are limited genome-wide association studies associating genetic polymorphisms with renal urate excretion measures. Therefore, we investigated the genetic factors that influence the excretion of uric acid and related indices in 768 Hispanic children of the Viva La Familia Study.

Methods

We performed a genome-wide association analysis for 24-h urinary excretion measures such as urinary uric acid/urinary creatinine ratio, uric acid clearance, fractional excretion of uric acid, and glomerular load of uric acid in SOLAR, while accounting for non-independence among family members.

Results

All renal urate excretion measures were significantly heritable (p <2 × 10⁻⁶) and ranged from 0.41 to 0.74. Empirical threshold for genome-wide significance was set at p <1 × 10⁻⁷. We observed a strong association (p < 8 × 10⁻⁸) of uric acid clearance with a single nucleotide polymorphism (SNP) in zinc finger protein 446 (ZNF446) (rs2033711 (A/G), MAF: 0.30). The minor allele (G) was associated with increased uric acid clearance. Also, we found suggestive associations of uric acid clearance with SNPs in ZNF324, ZNF584, and ZNF132 (in a 72 kb region of 19q13; p <1 × 10⁻⁶, MAFs: 0.28–0.31).

Conclusion

For the first time, we showed the importance of 19q13 region in the regulation of renal urate excretion in Hispanic children. Our findings indicate differences in inherent genetic architecture and shared environmental risk factors between our cohort and other pediatric and adult populations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12881-016-0366-3) contains supplementary material, which is available to authorized users.

Identifying Different Causes of Hyponatremia With Fractional Excretion of Uric Acid

BACKGROUND

There is controversy over the prevalence of the syndrome of inappropriate antidiuretic hormone secretion (SIADH) and cerebral or renal salt wasting (RSW), 2 syndromes with identical common clinical and laboratory parameters but different therapies. The traditional approach to the hyponatremic patient relies on volume assessment, but there are limitations to this method.

METHODS

We used an algorithm that relies on fractional excretion of urate (FEurate) to evaluate patients with hyponatremia and present 4 illustrative cases.

RESULTS

Overall, 2 patients had increased FEurate [normal: 4-11%], as is seen in SIADH and RSW. A diagnosis of SIADH was made in 1 patient by correcting the hyponatremia with 1.5% saline and observing a characteristic normalization of an elevated FEurate that is characteristic of SIADH as compared to FEurate being persistently increased in RSW. A patient with T-cell lymphoma had symmetrical leg edema due to lymphomatous obstruction of the inferior vena cava, postural hypotension, pleural effusion, ascites, decreased cardiac output and urine sodium level of 10mmol/L. Saline-induced excretion of dilute urines and undetectable plasma antidiuretic hormone were consistent with RSW. Furosemide, given for presumed heart failure, induced a profound diuresis that required large volumes of fluid resuscitation. A normal FEurate identified a reset osmostat in a transplant patient with a slowly developing pneumocystis carinii pneumonia. A volume-depleted hyponatremic patient with Addison׳s disease had a low FEurate of 1.4%.

CONCLUSIONS

These illustrative cases suggest that an approach to hyponatremia using FEurate may be a useful alternative to traditional volume-based approaches.