Uric Acid Stone Formation Research Articles

Weight loss intervention reduces the risk of kidney stone formation in a rat model of metabolic syndrome.

To investigate the effect of weight loss intervention on the urinary stone risk parameters in a rat model of metabolic syndrome. In a prevention study, 4-week-old male Otsuka Long-Evans Tokushima "Fatty" rats were randomly assigned to three groups: control, food-restricted and food-restricted + exercise-trained groups. In a treatment study, 24-week-old male Otsuka Long-Evans Tokushima "Fatty" rats that had already developed type 2 diabetes were randomly assigned to the same three groups. Blood and 24-h urine chemistry were measured after 16 weeks. In both studies, food-restricted and food-restricted + exercise-trained rats showed significantly higher urinary pH and higher excretion of urinary citrate than control rats. In the prevention study, ion-activity products of calcium oxalate in the food-restricted and food-restricted + exercise-trained groups were significantly lower than that of control rats. In the treatment study, ion-activity products of calcium oxalate index in food-restricted + exercise-trained rats was significantly lower than that of control rats. Weight loss intervention seems to reduce the risk of uric acid stone formation by improving low urine pH and calcium oxalate stone formation by increasing urinary citrate excretion. The present study provides the first theoretical evidence to support weight loss intervention programs for nephrolithiasis patients with metabolic syndrome.

The association of metabolic syndrome and urolithiasis.

There has been an increasing prevalence of kidney stones over the last 2 decades worldwide. Many studies have indicated a possible association between metabolic syndrome and kidney stone disease, particularly in overweight and obese patients. Many different definitions of metabolic syndrome have been suggested by various organizations, although the definition by the International Diabetes Federation (IDF) is universally considered as the most acceptable definition. The IDF definition revolves around 4 core components: obesity, dyslipidemia, hypertension, and diabetes mellitus. Several hypotheses have been proposed to explain the pathophysiology of urolithiasis resulting from metabolic syndrome, amongst which are the insulin resistance and Randall's plaque hypothesis. Similarly the pathophysiology of calcium and uric acid stone formation has been investigated to determine a connection between the two conditions. Studies have found many factors contributing to urolithiasis in patients suffering from metabolic syndrome, out of which obesity, overweight, and sedentary lifestyles have been identified as major etiological factors. Primary and secondary prevention methods therefore tend to revolve mainly around lifestyle improvements, including dietary and other preventive measures.

Type 2 diabetes mellitus and renal stones.

Background:The incidence of urinary stone disease has shown a steep rise in recent decades along with marked modifications in dietary habits and life- style. There has been an increased prevalence of urinary stone disease in patients with diabetes. We took up this study to determine the association of diabetes mellitus with kidney stones in patients undergoing surgical treatment.Materials and Methods:Patients presenting with renal stones for surgical management formed the study group. Body mass index (BMI) was calculated by noting the weight and height of the patient. The extracted stone/stone fragments were analyzed to determine the chemical composition. Urinary pH was similarly noted in all.Results:The mean BMI among the diabetics was 26.35 ± 5.20 (range 17.75-35.60), whereas the mean BMI among the non-diabetics was 23.41 ± 2.85 (range 17.71-31.62) (P < 0.0004). The incidence of uric acid calculi in the diabetics was significantly high (P < 0.03). The mean urinary pH among the diabetics was 5.61 ± 0.36 and among the non-diabetics was 6.87 ± 0.32, which was significantly lower (P < 0.000044).Conclusions:There is a strong association between type 2 diabetes and uric acid stone formation. There is also a strong association between diabetes mellitus, BMI, and also with lower urinary pH.

Does 24-Hour Urine Supersaturation Predict Stone Composition?

Background: The aim of the study was to evaluate the correlation between 24-hour urine supersaturation (SS) levels and the crystalline stone composition. Methods: We retrospectively reviewed the results of stone analysis of 386 patients who had completed 24-hour urine stone risk profiles within 2 months of stone analysis. Patients were characterized as calcium oxalate (CAOX), calcium phosphate (CAPH) or uric acid (UA) stone formers based on the predominant component (> 60%) of their stone. Patients with < 50% of one stone composition were characterized as a mixed stone former. Sensitivity, specificity and accuracy of the 24-hour urine SS for predicting the corresponding stone component were calculated. Results: The distribution of stone compositions was 235 (61%) CAOX, 98 (25%) CAPH, 35 (9%) UA and 18 (5%) mixed stone group. At predominant stone mineral concentration ? 60%, the accuracy of 24-hour urine SS for predicting the predominant stone composition was 52.5% for CAOX, 70% for CAPH and 67% for UA group. Even when the predominant stone mineral concentration was ? 90%, the accuracy of SS did not improve: COAX (49%, P = 0.6641), CAPH (77%, P = 0.361) and UA (67%, P = 0.9593). Conclusions: Twenty-four-hour urine SS has a poor accuracy to predict the predominant stone composition. Accuracy is highest for patients with CAPH stones. World J Nephrol Urol. 2015;4(1):169-172 doi: http://dx.doi.org/10.14740/wjnu206w

100% Uric Acid Stone Formers: What Makes Them Different?

To identify what risk factors on 24-hour urinalysis, if any, predispose patients to have higher percentages of uric acid (UA) stone composition in their stones, with specific emphasis on patients with pure UA stones. We retrospectively identified 308 patients from review of a kidney stone analysis database. Patients were grouped according to the percentage UA composition: 10%-20%, 30%-50%, 60%-90%, and 100% UA. Data were extracted from 24-hour urine collections and serum chemistries. Patients taking allopurinol, citrates, or thiazide diuretics were excluded. The percentage UA stone composition increased as patients became older (P= .05) or heavier (P<.001). Gender did not impact the percentage of UA in stones. Although a higher serum UA level was associated with higher UA stone composition (P<.0006), urinary UA levels did not correlate (P= .1). In contrast, urinary pH correlated significantly with higher UA stone composition (P= .03). Older and heavier patients with higher serum UA levels are more likely to have a pure UA stone. This information combined with traditional predictors (urine pH, radiopacity of stone, and Hounsfield units) may help identify those most likely to respond to dissolution therapy.

Aggregation of Nano- and Micro-Crystallites in Urine of Uric Acid Stone Formers and Healthy Controls

The aggregation of urine crystallites with different sizes in the urines of 5 cases of uric acid (UA) calculi patients and 5 cases of healthy controls were comparatively investigated by means of nanoparticle size analyzer. Different sizes of urine crystallites were obtained by filtrating the urine through microporous membrane with different pore sizes (0.22, 0.45, 1.2, 3, and 8 μm), respectively. The average particle size () increased rapidly with placement time (t) in the lithogenic patients. The values of the urine crystallites of the controls increased more slowly with t. When t was increased, the autocorrelation curves in the two types of urine crystallites became less smooth and the decay of the correlation curve became slower, and decay time of different sizes of urine crystallites both for the calculi patients and the controls increased. These results indicated that the urine crystallites of the controls were more stable than those of the patients. The rapid aggregation of urine crystallites may be an important factor affecting the growth of crystallites in UA stone patients.

Prevalence of Metabolic Syndrome in Patients with Uric Acid and Calcium–based Kidney Stones

The aim of the study was to investigate the prevalence of metabolic syndrome in patients with uric acid and calcium–based kidney stones and to investigate the relationship between metabolic syndrome and type of kidney stone using infrared spectroscopy to evaluate the chemical composition of kidney stones Sixty patients with urolithiasis were examined. Metabolic syndrome was diagnosed according to clinical and laboratory criteria. Weight, height, body mass index, waist circumference, and blood pressure of patients were measured. Blood tests were performed. Concentrations of total cholesterol, low density lipoprotein cholesterol, high density lipoprotein cholesterol, triglycerides, glucose and uric acid in blood, were analyzed. The kidney stones of patients were removed and the composition of each kidney stone was analyzed using Fourier transform infrared spectroscopy. Metabolic syndrome was diagnosed in 55% of the patients; 86.7% of patients with uric acid (UA) kidney stones and 44.4% of patients with calcium (Ca) based stones had metabolic syndrome. All patients diagnosed with metabolic syndrome were overweight or obese. Even though there were no statistically significant differences observed concerning the anthropometrical measures and arterial blood pressure (BP) between the UA stone formers and Ca–based stone formers, the results show a trend that failed to reach significance: higher waist size, BMI and arterial BP means in the group of patients with UA stones than in the patients with Ca–based stones. No statistically significant differences in lipid profile between the groups were found. Concentration of UA in blood serum was significantly higher in patients with UA kidney stones than it was in patients with Ca–based kidney stones. Significant positive correlation between triglycerides and serum UA concentrations, as well as body mass index and serum UA concentration, and negative correlation between concentrations of high-density lipoprotein cholesterol and UA was found. Conclusion: Metabolic syndrome was more prevalent in patients with uric acid stones than in the patients with calcium–based kidney stones, even though this relationship was not statistically significant, most likely because of the limited number of patients investigated.

Association of serum biochemical metabolic panel with stone composition.

To determine the association of the basic metabolic panel with stone type. The present study was a retrospective review of 492 stone formers with both stone composition analysis and basic metabolic panel available. Analysis of a basic metabolic panel across stone types was carried out using Fisher's exact test and analysis of variance. Multinomial logistic regression was used to predict stone type based on a basic metabolic panel. A total of 272 (55%) patients had predominantly calcium oxalate stones, 100 (21%) had uric acid stones, 93 (19%) had calcium phosphate stones, 16 (3%) had mixed stones and 11 (2%) had other types of stones. Uric acid stone formers had the highest serum glucose, blood urea nitrogen and creatinine levels. Calcium oxalate stone formers had the highest serum sodium. No significant differences in mean serum calcium levels across different stone types were identified. The predicted risk of uric acid stone over the other stone types increased with an increase in serum glucose and decreased with an increase in carbon dioxide levels. The predicted risk of calcium oxalate stones increased with an increase in serum sodium and chloride levels. The predicted risk of calcium phosphate and oxalate stones over the other stone types increased with an increase in serum calcium levels. The overall accuracy of the basic metabolic panel alone to predict stone type was 59%. A basic metabolic panel alone or in combination with 24-h urinalysis and demographics does not accurately predict stone type. However, it can be used in combination with other variables to predict stone composition.

Comparison of the Metabolic Profile of Mixed Calcium Oxalate/Uric Acid Stone Formers to That of Pure Calcium Oxalate and Pure Uric Acid Stone Formers

To compare the metabolic profile of patients who form mixed calcium oxalate (CaOx)/uric acid (UA) stones to those of pure CaOx and pure UA stone formers. We performed a retrospective review of 232 patients, with both stone composition analysis and 24-hour urine collection, seen between March 2002 and April 2012. Analysis of 24-hour urine constituents across the 3 stone groups (pure UA, pure CaOx, and mixed CaOx/UA) was performed using univariate analysis of variance and multivariate linear regression models adjusting for clinical and demographic factors and 24-hour urine collection elements. A total of 27 patients (11.6%) had mixed CaOx/UA, 122 (52.6%) had pure CaOx, and 83 (35.8%) had pure UA calculi. Univariate analysis demonstrated significant differences between mixed CaOx/UA patients and pure CaOx patients for urine pH (mixed, 5.63 ± 0.49 vs pure, CaOx 5.93 ± 0.51; P= .009) and supersaturation (SS) UA (mixed, 1.84 ± 1.09 vs pure, CaOx 1.26 ± 0.93; P= .01), and a significant difference between mixed CaOx/UA patients and pure UA patients for SS CaOx (mixed, 7.18 ± 4.23 vs pure, UA 4.90 ± 2.96; P= .005). Multivariate analysis demonstrated that mixed CaOx/UA patients had no significant difference in SS CaOx as compared with pure CaOx patients (difference,-0.27; P= .66), whereas at the same time had no significant difference in SS UA as compared with pure UA patients (-0.07; P=.69). The metabolic profile of patients who form mixed CaOx/UA stones demonstrates abnormalities that promote both CaOx and UA stone formation. Dietary and medical management for this group of patients should address treatment of both defects.

Dyslipidemia and Kidney Stone Risk: Torricelli FC, De SK, Gebreselassie S, et al. J Urol 2014;191:667–72.

This retrospective chart review sought to examine the effect that the metabolic syndrome has on the risk of developing nephrolithiasis. It accomplished this by examining the lipid profile and 24-h urinalysis in patients with kidney stones and observing whether or not the components of the lipid profile were associated with certain components of the urinalysis that were then associated with urinary uric acid formation and thus, formation of uric acid stones. There were 2442 patients with nephrolithiasis who were studied. Associations between various components of the lipid panel and urinalysis were observed utilizing multivariate analysis to account for demographic data, body mass index, diabetes, and hypertension as possible confounders. High total cholesterol (TC) was associated with elevated urinary potassium (p = 0.021) and calcium (p = 0.049). Low high-density lipoprotein (HDL) was associated with higher urinary sodium (p < 0.001), oxalate (p = 0.007), and uric acid (p < 0.001), and lower urinary pH (p = 0.003). Increased non-HDL was associated with increased urinary pH and uric acid (p < 0.001 each). High triglycerides (TG) were associated with high urinary sodium (p < 0.001), oxalate (p = 0.012), uric acid (p < 0.001), and lower urinary pH (p < 0.001). Of the 2442 patients with renal stones, 1761 had an abnormal lipid profile and 661 had a normal lipid profile. Interestingly, there was no significant difference between these groups and uric acid stone formation with multivariate analysis. On multivariate analysis, examining individual components of the lipid profile, TC (p = 0.006) and TGs (p < 0.001) were associated with uric acid stones. Linear regression showed non-HDL associated with higher urinary sodium (p = 0.011) and uric acid (p < 0.001) and TGs associated with higher uric acid (p = 0.017) and lower urinary pH (p = 0.005).

Protein expression of urate transporters in renal tissue of patients with uric acid nephrolithiasis.

URAT1 and GLUT9 are two primary urate transporters involved in the renal urate handling. Renal urate underexcretion was reported in uric acid stone formers (UASF) in previous clinical studies. The aim of this study was to investigate the clinical features and possible impact of protein expression of URAT1 and GLUT9 in renal tissues of patients with uric acid (UA) nephrolithiasis. 23 UASF, 27 patients with calcium oxalate (CaOx) stones, and 22 normal controls were enrolled in this study. Clinical data revealed that older age of onset, high plasma UA concentration, low urinary PH, and relative renal urate underexcretion were associated with UASF. By immunohistochemical or western blotting analysis, a significant increase in the relative expression quantity of URAT1 in renal tissue of UASF was found compared to patients with CaOx nephrolithiasis and normal controls. In conclusion, our results suggested that upregulated URAT1 protein expression might contribute to the relative urate underexcretion from the kidney of UASF.

PD32-01 SUCCESS OF DIABETIC CONTROL AS MEASURED BY HEMOGLOBIN A1C IS DIRECTLY ASSOCIATED WITH 24HR URINARY RISK FACTORS FOR URIC ACID STONE FORMATION

You have accessJournal of UrologyStone Disease: Evaluation II1 Apr 2014PD32-01 SUCCESS OF DIABETIC CONTROL AS MEASURED BY HEMOGLOBIN A1C IS DIRECTLY ASSOCIATED WITH 24HR URINARY RISK FACTORS FOR URIC ACID STONE FORMATION Sara Best, Jonathan Shiau, Rachel Bell, and Kristina Penniston Sara BestSara Best More articles by this author , Jonathan ShiauJonathan Shiau More articles by this author , Rachel BellRachel Bell More articles by this author , and Kristina PennistonKristina Penniston More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2014.02.2272AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES In an era of rising obesity rates, patients must simultaneously manage multiple medical comorbidities. Ideally, several medical problems could be treated with the same strategy, cutting down the complexity of compliance in these patients. It is unknown if glycemic control improves urinary risk factors for stone disease. Patients with diabetes mellitus (DM) are known to have a propensity for lower urine pH and a higher prevalence of uric acid calculi. We examined the influence of hemoglobin A1c (HgbA1c), a measure of long-term DM control, on 24hr urine values. METHODS We queried an approved institutional database containing 540 stone formers with known stone composition and metabolic studies. We identified 85 patients who had undergone both HgbA1c and 24hr urine testing. 24hr urine measures thought to be pertinent to uric acid-related nephrolithiasis included pH, citrate, calcium, sulfate, and uric acid supersaturation (UA SS). Absolute 24hr urinary uric acid was not included in the analysis due to misleading values related to likely precipitation at low pH in some of the cohort. Variables were compared using Fisher’s exact tests, Spearman Correlation and ANOVA. RESULTS Mean patient age was 57 years and 62% of patients were male. Mean BMI was 31.5kg.m2. 29% of the cohort had stones containing some component of uric acid. In our cohort, we confirmed that stone formers with stones containing any uric acid had higher mean HgbA1c than those with other stone types (6.8% vs 6.1%, p = 0.009). As expected, uric acid stone formers had a significantly lower mean urine pH (5.6 vs 6.3, p<0.0001) and higher mean uric acid supersaturation (2.5 vs 1.3, p=0.0003). We found a significant relationship between HgbA1c and 24hr urine pH (R=-0.320, p=0.006). There was also a trend between HgbA1c and UA SS (R=0.222, p=0.059). HgbA1c was not significantly correlated with urinary citrate (p=0.48), calcium (p=0.63), or sulfate (p=0.11). In our cohort, pH was also correlated with sulfate (R=-0.336, p=0.002) and UA SS (R=-0.889, p<0.0001). Citrate was correlated with calcium (R=0.370, p=0.0005) and sulfate was correlated with UA SS (R=0.292, p=0.009). CONCLUSIONS Our study finds that successful glycemic control (lower HgbA1c) is associated with reduced severity of 24hr urinary risk factors for uric acid stone formation.. Our study suggests that better diabetic management may reduce the likelihood of uric acid nephrolithiasis and supports the inclusion of diabetes control as a component of the multidisciplinary medical management of stone forming patients. © 2014FiguresReferencesRelatedDetails Volume 191Issue 4SApril 2014Page: e836 Advertisement Copyright & Permissions© 2014MetricsAuthor Information Sara Best More articles by this author Jonathan Shiau More articles by this author Rachel Bell More articles by this author Kristina Penniston More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

MP25-17 THE EFFECT OF INCREASED VISCERAL FAT AREA AND BODY-MASS INDEX ON 24 HOUR URINE COLLECTION

You have accessJournal of UrologyStone Disease: Basic Research II1 Apr 2014MP25-17 THE EFFECT OF INCREASED VISCERAL FAT AREA AND BODY-MASS INDEX ON 24 HOUR URINE COLLECTION Ethan Fram, Saman Moazami, Mira Herman, Ilir Agalliu, and Joshua Stern Ethan FramEthan Fram More articles by this author , Saman MoazamiSaman Moazami More articles by this author , Mira HermanMira Herman More articles by this author , Ilir AgalliuIlir Agalliu More articles by this author , and Joshua SternJoshua Stern More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2014.02.319AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES The prevalence of obesity in the United States is increasing and with it the incidence of urinary stone disease. Obesity effects the composition of many urinary solutes. Visceral fat has been independently associated with many metabolic disturbances previously linked solely to obesity. We sought to evaluate the impact that visceral fat may have on urinary solutes, urinary volume, and serum uric acid in a cohort of patients with urolithiasis who were treated using ureteroscopy and laser lithotripsy (URS). METHODS We performed a retrospective review of an IRB-approved database of patients who had undergone URS at our institution in the last seven years. 24 hour urine collection results, stone characteristics, and patient demographics were recorded. VFA was calculated using pre-operative CT scanning using a slice taken at the level of the umbilicus (TeraRecon, Aquarius iNtuition workstation). Multivariate regression models were used to predict outcomes. RESULTS We identified 237 patients who met our criteria. The patients represented an ethnically diverse population with high prevalence of comorbidities. Upon multivariate analysis increasing BMI was found to predict high total quantity and concentration of a number of solutes, while VFA was associated with increasing 24-hour urine total quantities of sodium and creatinine (Table 1). Another multivariate analysis demonstrated that visceral fat area predicts uric acid stone formation (OR 1.007, p = .021). Neither visceral fat area nor BMI predicted other stone types. Finally, white ethnicity was associated with approximately 2.5 times as many uric acid stones than expected (X2 = 28.115, p = .031). CONCLUSIONS VFA was weakly associated with 24 hour urine total quantities of sodium and creatinine. In corroboration with previous studies, high BMI increased the quantity and concentration of urinary solutes important to stone formation, including citrate, oxalate, phosphate, and uric acid. The prediction of uric acid stone formation by VFA and disproportionate burden of uric acid stones on those of white ethnicity observed agrees with prior research from our institution in a different subset of our patient population. This data suggest that both visceral and subcutaneous fat are integral to the development of stone disease and deserve further study. Single Models VFA Beta Standard Error p BMI Beta Standard Error p Combined Models VFA Beta Standard Error p BMI Beta Standard Error p Citrate 0.002 0.001 0.094 0.029 0.010 0.000 0.002 0.001 0.128 0.026 0.010 0.007 Oxalate † 0.002 0.001 0.044 0.030 0.010 0.002 0.002 0.001 0.060 0.028 0.010 0.004 Calcium* 0.002 0.001 0.043 0.006 0.010 0.556 0.002 0.001 0.076 0.003 0.010 0.765 Creatinine 0.004 0.001 0.001 0.033 0.009 0.000 0.004 0.001 0.000 0.029 0.009 0.001 Sodium 0.003 0.001 0.008 0.031 0.010 0.003 0.003 0.001 0.022 0.030 0.010 0.004 Phosphate 0.002 0.002 0.348 0.043 0.016 0.007 0.001 0.002 0.480 0.039 0.016 0.017 Uric Acid 0.001 0.001 0.478 0.027 0.010 0.006 0.000 0.001 0.790 0.030 0.010 0.004 Volume 0.002 0.001 0.154 0.003 0.010 0.796 0.001 0.001 0.215 0.002 0.010 0.877 Serum Uric Acid* 0.002 0.002 0.317 0.022 0.014 0.120 0.001 0.002 0.529 0.020 0.015 0.193 Citrate Concentration 0.000 0.001 0.904 0.021 0.010 0.030 0.000 0.001 0.894 0.020 0.010 0.049 Oxalate Concentration ‡ 0.000 0.001 0.822 0.023 0.010 0.021 0.000 0.001 0.737 0.022 0.010 0.028 Calcium Concentration* 0.001 0.001 0.621 0.008 0.009 0.386 0.001 0.001 0.635 0.007 0.010 0.482 Creatinine Concentration 0.001 0.001 0.443 0.024 0.010 0.015 0.001 0.001 0.278 0.022 0.010 0.026 Sodium Concentration 0.002 0.001 0.080 0.028 0.010 0.006 0.002 0.001 0.090 0.027 0.010 0.008 Phosphate Concentration -0.002 0.001 0.247 0.020 0.013 0.136 -0.002 0.002 0.247 0.020 0.014 0.159 Uric Acid Concentration -0.001 0.001 0.472 0.030 0.010 0.003 -0.001 0.001 0.361 0.032 0.010 0.002 * Adjusted for CKD † Adjusted for CAD ‡ Adjusted for HTN Multiple linear regression predicting quartiles of dependent variable. All models included age and sex, as well as any disease state observed to be significant on univariate analysis. Single models included either VFA or BMI, while combined models included both. © 2014FiguresReferencesRelatedDetails Volume 191Issue 4SApril 2014Page: e273 Advertisement Copyright & Permissions© 2014MetricsAuthor Information Ethan Fram More articles by this author Saman Moazami More articles by this author Mira Herman More articles by this author Ilir Agalliu More articles by this author Joshua Stern More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

Epidemiology and clinical pathophysiology of uric acid kidney stones

There is global diversity in the prevalence of uric acid (UA) nephrolithiasis. UA nephrolithiasis comprises 8-10 % of all kidney stones in the United States. However, its prevalence is higher in patients with type 2 diabetes mellitus and those with obesity. Three significant urinary abnormalities have been described as the main etiologic factors for the development of UA nephrolithiasis; low urinary pH, hyperuricosuria and low urinary volume. However, an unduly acidic urine below the ionization constant of uric acid (pKa < 5.5) increases the urinary content of undissociated uric acid and thereby uric acid precipitation. Previous studies have shown the two major pathogenic mechanisms for unduly urinary pH are increased net acid excretion (NAE) and reduced renal ammonium (NH4 (+)), with a combination resulting in overly acidic urine. The impaired ammonium excretion has been demonstrated in a steady state in 24-hour urine and also following an oral ammonium chloride (NH4Cl) challenge to amplify ammoniogenic defects in this population. Similar abnormalities have been disclosed in normal populations and also in T2DM populations without kidney stones. To date, the underlying mechanism of increased acid production, source and nature of putative organic acid anions have not been fully elucidated. One plausible mechanism is the production of organic acid by intestinal and aerobic metabolism. This may occur in obese, diabetic and uric acid stone formers due to the differences in gut microflora.

Role of insulin resistance in uric acid nephrolithiasis.

Metabolic syndrome has been implicated in the pathogenesis of uric acid stones. Although not completely understood, its role is supported by many studies demonstrating increased prevalence of uric acid stones in patients with metabolic syndrome and in particular insulin resistance, a major component of metabolic syndrome. This review presents epidemiologic studies demonstrating the association between metabolic syndrome and nephrolithiasis in general as well as the relationship between insulin resistance and uric acid stone formation, in particular. We also review studies that explore the pathophysiologic relationship between insulin resistance and uric acid nephrolithiasis.

Body Fat Content and Distribution and Urinary Risk Factors for Nephrolithiasis

Obesity is associated with a higher risk of nephrolithiasis. However, it is not known whether higher body fat mass or abnormal fat distribution influences stone risk independent of dietary factors. In this cross-sectional study, non-stone-forming men with no known kidney disease and with a wide range of body weight collected a 24-hour urine specimen while consuming a fixed metabolic diet. They underwent dual-energy x-ray absorptiometry to assess body composition and fat distribution. Urinary risk factors for nephrolithiasis and urine saturation with respect to calcium oxalate and uric acid (assessed as supersaturation index [SI]) were correlated with various measures of adiposity. Study participants included 21 men with a mean age of 52.1 years, mean weight of 91.1 kg, and mean total fat mass of 24.3 kg. Twenty-four-hour urine pH and SI uric acid were more closely correlated with fat mass than with lean mass or total body weight. Both 24-hour urine pH and SI uric acid were also significantly correlated with truncal fat mass but not with leg fat mass. Moreover, there was a significant negative correlation between truncal/leg fat mass and NH4(+)/net acid excretion ratio (R=-0.62; P=0.009). However, there was no significant association between SI calcium oxalate and body weight, lean mass, fat mass, trunk fat mass, or leg fat mass. The association between 24-hour urine pH and SI uric acid and various measures of adiposity suggest that total body fat and trunk fat are more strongly associated with risk factors for uric acid stone formation than are total body weight and lean body mass. Under a controlled metabolic diet, adiposity is not associated with risk factors for calcium oxalate stones. Further studies are needed to confirm these findings in larger populations that include women and patients who form stones.

Renal ammonium excretion after an acute acid load: blunted response in uric acid stone formers but not in patients with type 2 diabetes

Idiopathic uric acid nephrolithiasis is characterized by elevated urinary net acid excretion and insufficient buffering by ammonium, resulting in excessively acidic urine and titration of the relatively soluble urate anion to insoluble uric acid. Patients with type 2 diabetes have similar changes in urinary pH, net acid excretion, and ammonium in 24-h urine collections at baseline, even after controlling for dietary factors, and are at increased risk for uric acid nephrolithiasis. However, not all patients with type 2 diabetes develop kidney stones, suggesting that uric acid stone formers may have additional urinary defects, perhaps not apparent at baseline. We performed a metabolic study of 14 patients with idiopathic uric acid nephrolithiasis, 13 patients with type 2 diabetes, and 8 healthy control subjects of similar body mass index. After equilibration on a fixed diet for 5 days, subjects were given a single oral acid load (50 meq ammonium chloride), and urine was collected hourly for 4 h. Uric acid stone formers had a lower ammonium excretory response to acute acid loading compared with diabetic and nondiabetic nonstone formers, suggesting that an ammonium excretory defect unique to uric acid stone formers was unmasked by the acid challenge. The Zucker diabetic fatty rat also did not show impaired urinary ammonium excretion in response to acute acid challenge. A blunted renal ammonium excretory response to dietary acid loads may contribute to the pathogenesis of idiopathic uric acid nephrolithiasis.

Mass Spectrometric Study of Stone Matrix Proteins of Human Bladder Stones

To evaluate the mechanisms of bladder uric acid stone (BUAS) formation by analyzing BUAS stone matrix proteins, with mass spectrometry (MS). Stone matrix proteins were extracted from 5 pure BUASs. The obtained proteins were analyzed with reverse phase liquid chromatography-tandem MS. The acquired data were investigated against a Swiss Prot human protein database, using Matrix Science Mascot. The identified proteins were submitted to UniProtKB website for gene ontology analysis to define their correlation. They were also submitted to Metacore platform and Kyoto Encyclopedia of Genes and Genomes website for pathway analysis. MS-determined protein expressions were validated by immunoblot. The liquid chromatography-tandem MS analysis identified 58-226 proteins in the 5 BUASs (450 proteins). Metacore software analysis suggests that inflammation might play an important role for BUAS formation. The analysis of endogenous metabolic pathways revealed that these proteins were categorized into glycerophospholipid or glycosphingolipid biosynthesis. Four of 5 identified proteins selected for validation, including uromodulin, S100P, Histone 4, and nucleophosmin, can be validated in the immunoblot data. Our results suggest that inflammatory process and lipid metabolism might play a role in the formation of BUAS. Whether these inflammatory responses are the etiology of stone formation or whether they result from local damage by stone irritation is uncertain.

Property changes of urinary nanocrystallites and urine of uric acid stone formers after taking potassium citrate

The property changes of urinary nanocrystallites in 20 cases of uric acid (UA) stone formers after 1week of potassium citrate (K3cit) intake were comparatively studied by X-ray diffraction analysis, Fourier transform infrared spectroscopy, nanoparticle size analysis, and transmission electron microscopy. Before K3cit intake, the urinary crystallites mainly contained UA and calcium oxalate. After K3cit intake, the components changed to urate and UA; the qualities, species, and amounts of aggregated crystallites decreased; urine pH, citrate, and glycosaminoglycan excretions increased; and UA excretion, Zeta potential, and crystallite size decreased. The stability of crystallites followed the order: controls>patients after taking K3cit>patients before taking K3cit. Therefore, the components of urinary stones were closely related to the components of urinary crystallites.

Effects of Visceral Fat Area and Other Metabolic Parameters on Stone Composition in Patients Undergoing Percutaneous Nephrolithotomy

Obesity is a risk factor for metabolic syndrome and urolithiasis, particularly uric acid stones. As estimated by visceral fat area, visceral obesity is a more specific measure of the risk of metabolic syndrome than body mass index. We investigated the effects of visceral fat area and other metabolic factors on uric acid stone formation in patients treated with percutaneous nephrolithotomy. We retrospectively reviewed the records of 269 patients who underwent percutaneous nephrolithotomy. Visceral fat area was measured in each patient on a CT axial slice at the umbilical level using the Aquarius iNtuition fat analysis tool. Analysis was performed to determine the effect of visceral fat area and other comorbidities on uric acid stone formation. Of the 269 patients analyzed there was no difference in baseline comorbidities between uric acid and nonuric acid stone formers. Patients with uric acid stones had a significantly higher mean visceral fat area (209.3 vs 161.9 cm², p = 0.001), and rates of hypertension (67.4% vs 47.3%) and coronary artery disease (14.3% vs 4.6%, each p = 0.011). On logistic regression analysis hypertension (OR 2.16, 95% CI 1.05-4.45, p = 0.04) and a high visceral fat area (OR 3.64, 95% CI 1.22-10.85, p = 0.02) were independent risk factors for uric acid stones. As a marker of visceral obesity, visceral fat area contributes to the risk of metabolic syndrome and urolithiasis. Uric acid stone formers showed a significantly higher hypertension rate and mean visceral fat area, which were independent risk factors for uric acid urolithiasis. Evaluating these characteristics in stone formers may facilitate a tailored metabolic assessment and treatment plan.