The role of microbiome: a novel insight into urolithiasis

Potassium sodium hydrogen citrate intervention on gut microbiota and clinical features in uric acid stone patients

The high recurrence rate of renal uric acid stone (UAS) poses a significant challenge for urologists, and potassium sodium hydrogen citrate (PSHC) has been proven to be an effective oral dissolution drug. However, no studies have investigated the impact of PSHC on gut microbiota and its metabolites during stone dissolution therapy. We prospectively recruited 37 UAS patients and 40 healthy subjects, of which 12 patients completed a 3-month pharmacological intervention. Fasting vein blood was extracted and mid-stream urine was retained for biochemical testing. Fecal samples were collected for 16S ribosomal RNA (rRNA) gene sequencing and short chain fatty acids (SCFAs) content determination. UAS patients exhibited comorbidities such as obesity, hypertension, gout, and dyslipidemia. The richness and diversity of the gut microbiota were significantly decreased in UAS patients, Bacteroides and Fusobacterium were dominant genera while Subdoligranulum and Bifidobacterium were poorly enriched. After PSHC intervention, there was a significant reduction in stone size accompanied by decreased serum uric acid and increased urinary pH levels. The abundance of pathogenic bacterium Fusobacterium was significantly downregulated following the intervention, whereas there was an upregulation observed in SCFA-producing bacteria Lachnoclostridium and Parasutterella, leading to a significant elevation in butyric acid content. Functions related to fatty acid synthesis and amino acid metabolism within the microbiota showed upregulation following PSHC intervention. The correlation analysis revealed a positive association between stone pathogenic bacteria abundance and clinical factors for stone formation, while a negative correlation with SCFAs contents. Our preliminary study revealed that alterations in gut microbiota and metabolites were the crucial physiological adaptation to PSHC intervention. Targeted regulation of microbiota and SCFA holds promise for enhancing drug therapy efficacy and preventing stone recurrence. KEY POINTS: • Bacteroides and Fusobacterium were identified as dominant genera for UAS patients • After PSHC intervention, Fusobacterium decreased and butyric acid content increased • The microbiota increased capacity for fatty acid synthesis after PSHC intervention.

Discovery of 2,8-dihydroxyadenine in HUA patients with uroliths and biomarkers for its associated nephropathy

Currently, it is acknowledged that gout is caused by uric acid (UA). However, some studies have revealed no correlation between gout and UA levels, and growing evidence suggests that 2,8-dihydroxyadenine (2,8-DHA), whose structural formula is similar to UA but is less soluble, may induce gout. Hence, we hypothesized that uroliths from hyperuricemia (HUA) patients, which is closely associated with gout, may contain 2,8-DHA. In this study, 2,8-DHA in uroliths and serum of HUA patients were determined using HPLC. Moreover, bioinformatics was used to investigate the pathogenic mechanisms of 2,8-DHA nephropathy. Subsequently, a mouse model of 2,8-DHA nephropathy established by the gavage administration of adenine, as well as a model of injured HK-2 cells induced by 2,8-DHA were used to explore the pathogenesis of 2,8-DHA nephropathy. Interestingly, 2,8-DHA could readily deposit in the cortex of the renal tubules, and was found in the majority of these HUA patients. Additionally, the differentially expressed genes between 2,8-DHA nephropathy mice and control mice were found to be involved in inflammatory reactions. Importantly, CCL2 and IL-1β genes had the maximum degree, closeness, and betweenness centrality scores. The expressions of CCL2 and IL-1β genes were significantly increased in the serum of 24 HUA patients with uroliths, indicating that they may be significant factors for 2,8-DHA nephropathy. Further analysis illustrated that oxidative damage and inflammation were the crucial processes of 2,8-DHA renal injury, and CCL2 and IL-1β genes were verified to be essential biomarkers for 2,8-DHA nephropathy. These findings revealed further insights into 2,8-DHA nephropathy, and provided new ideas for its diagnosis and treatment.

Identification of Two Clusters in Renal Pelvis Urobiome of Unilateral Stone Formers Using 2bRAD-M

Urolithiasis is a common urological disease with increasing incidence and a high recurrence rate, whose etiology is not fully understood. The application of sequencing and culturomics has revealed that urolithiasis is closely related to the urinary microbiome (urobiome), shedding new light on the pathogenesis of stone formation. In this study, we recruited 30 patients with unilateral stones and collected their renal pelvis urine from both sides. Then, we performed 2bRAD-M, a novel sequencing technique that provides precise microbial identification at the species level, to characterize the renal pelvis urobiome of unilateral stone formers in the both sides. We first found that the urobiome in the stone side could be divided into two clusters (Stone1 and Stone2) based on distance algorithms. Stone2 harbored higher microbial richness and diversity compared to Stone1. The genera Cupriavidus and Sphingomonas were overrepresented in Stone1, whereas Acinetobacter and Pseudomonas were overrepresented in Stone2. Meanwhile, differential species were identified between Stone1 and Stone2. We further constructed a random forest model to discriminate two clusters which achieved a powerful diagnostic potential. Moreover, the urobiome of the non-stone side (Control1/2) was compared with that of the stone side (Stone1/2). Stone1 and Control1 showed different microbial community distributions, while Stone2 was similar to Control2 based on diversity analysis. We also identified differentially abundant species among all groups. We assumed that there might be different mechanisms of how microbiota contribute to stone formation in two clusters. Our findings might assist in the selection of suitable medical treatments for urolithiasis.

Oxalate (dys)Metabolism: Person-to-Person Variability, Kidney and Cardiometabolic Toxicity

Oxalate is a metabolic end-product whose systemic concentrations are highly variable among individuals. Genetic (primary hyperoxaluria) and non-genetic (e.g., diet, microbiota, renal and metabolic disease) reasons underlie elevated plasma concentrations and tissue accumulation of oxalate, which is toxic to the body. A classic example is the triad of primary hyperoxaluria, nephrolithiasis, and kidney injury. Lessons learned from this example suggest further investigation of other putative factors associated with oxalate dysmetabolism, namely the identification of precursors (glyoxylate, aromatic amino acids, glyoxal and vitamin C), the regulation of the endogenous pathways that produce oxalate, or the microbiota's contribution to oxalate systemic availability. The association between secondary nephrolithiasis and cardiovascular and metabolic diseases (hypertension, type 2 diabetes, and obesity) inspired the authors to perform this comprehensive review about oxalate dysmetabolism and its relation to cardiometabolic toxicity. This perspective may offer something substantial that helps advance understanding of effective management and draws attention to the novel class of treatments available in clinical practice.

Outpatient Antibiotic Use is Not Associated with an Increased Risk of First-Time Symptomatic Kidney Stones

SIGNIFICANCE STATEMENT

Antibiotics modify human microbiomes and may contribute to kidney stone risk. In a population-based case-control study using 1247 chart-validated first-time symptomatic kidney stone formers and 4024 age- and sex-matched controls, the risk of kidney stones was transiently higher during the first year after antibiotic use. However, this risk was no longer evident after adjustment for comorbidities and excluding participants with prior urinary symptoms. Findings were consistent across antibiotic classes and the number of antibiotic courses received. This suggests that antibiotics are not important risk factors of kidney stones. Rather, kidney stones when they initially cause urinary symptoms are under-recognized, resulting in antibiotic use before a formal diagnosis of kidney stones ( i.e. , reverse causality).

BACKGROUND

Antibiotics modify gastrointestinal and urinary microbiomes, which may contribute to kidney stone formation. This study examined whether an increased risk of a first-time symptomatic kidney stone episode follows antibiotic use.

METHODS

A population-based case-control study surveyed 1247 chart-validated first-time symptomatic kidney stone formers with a documented obstructing or passed stone (cases) in Olmsted County, Minnesota, from 2008 to 2013 and 4024 age- and sex-matched controls. All prescriptions for outpatient oral antibiotic use within 5 years before the onset of symptomatic stone for the cases and their matched controls were identified. Conditional logistic regression estimated the odds ratio (OR) of a first-time symptomatic kidney stone across time after antibiotic use. Analyses were also performed after excluding cases and controls with prior urinary tract infection or hematuria because urinary symptoms resulting in antibiotic prescription could have been warranted because of undiagnosed kidney stones.

RESULTS

The risk of a symptomatic kidney stone was only increased during the 1-year period after antibiotic use (unadjusted OR, 1.31; P = 0.001), and this risk was attenuated after adjustment for comorbidities (OR, 1.16; P = 0.08). After excluding cases and controls with prior urinary symptoms, there was no increased risk of a symptomatic kidney stone during the 1-year period after antibiotic use (unadjusted OR, 1.04; P = 0.70). Findings were consistent across antibiotic classes and the number of antibiotic courses received.

CONCLUSIONS

The increased risk of a first-time symptomatic kidney stone with antibiotic use seems largely due to both comorbidities and prescription of antibiotics for urinary symptoms. Under-recognition of kidney stones that initially cause urinary symptoms resulting in antibiotic use may explain much of the perceived stone risk with antibiotics ( i.e. , reverse causality).

Exploring the characteristics of gut microbiome in patients of Southern Fujian with hypocitraturia urolithiasis and constructing clinical diagnostic models

PURPOSE

Hypocitraturia is an important cause of urolithiasis. Exploring the characteristics of the gut microbiome (GMB) of hypocitriuria urolithiasis (HCU) patients can provide new ideas for the treatment and prevention of urolithiasis.

METHODS

The 24 h urinary citric acid excretion of 19 urolithiasis patients was measured, and patients were divided into the HCU group and the normal citrate urolithiasis (NCU) group. The 16 s ribosomal RNA (rRNA) was used to detect GMB composition differences and construct operational taxonomic units (OTUs) coexistence networks. The key bacterial community was determined by Lefse analysis, Metastats analysis and RandomForest analysis. Redundancy analysis (RDA) and Pearson correlation analysis visualized the correlation between key OTUs and clinical features and then established the disease diagnosis model of microbial-clinical indicators. Finally, PICRUSt2 was used to explore the metabolic pathway of related GMB in HCU patients.

RESULTS

The alpha diversity of GMB in HCU group was increased and Beta diversity analysis suggested significant differences between HCU and NCU groups, which was related to renal function damage and urinary tract infection. Ruminococcaceae_ge and Turicibacter are the characteristic bacterial groups of HCU. Correlation analysis showed that the characteristic bacterial groups were significantly associated with various clinical features. Based on this, the diagnostic models of microbiome-clinical indicators in HCU patients were constructed with the areas under the curve (AUC) of 0.923 and 0.897, respectively. Genetic and metabolic processes of HCU are affected by changes in GMB abundance.

CONCLUSION

GMB disorder may be involved in the occurrence and clinical characteristics of HCU by influencing genetic and metabolic pathways. The new microbiome-clinical indicator diagnostic model is effective.