Oxalobacter formigenes reduce the risk of kidney stones in patients exposed to oral antibiotics: a case-control study

Lifestyle Factors and the Microbiome in Urolithiasis: A Narrative Review

Urolithiasis represents one of the most common urologic diseases, and its incidence demonstrates, globally, an increasing trend. The application of preventive measures is an established strategy to reduce urolithiasis-related morbidity, and it is based mostly on the adaptation of lifestyle factors and pharmacotherapy. Furthermore, other research areas demonstrate promising results, such as the research on the microbiome. In the current review, we searched for the latest data on lifestyle-based prevention and microbiome alterations in urolithiasis patients. The majority of the proposed lifestyle measures are already included in the urological guidelines, while additional factors, such as vitamin D supplementation, seem to have a putative positive effect. From the microbiome studies, several microbial composition patterns and metabolic pathways demonstrated an inhibiting or promoting role in lithogenesis. Up to the present, stone prevention has not shown satisfying results, which suggests that lifestyle measures are not adequate. Moreover, microbiome studies are prone to bias, since microbes are strongly affected by numerous clinical factors, while the analysis procedures are not standardized yet. Analysis standardization and data pooling from extensive registration of clinical and microbiome data are essential steps in order to improve the existing prevention strategy with targeted microbiome manipulations.

Causal relationship between gut microbiota and androgenetic alopecia: A Mendelian randomization study

Recent studies have found a strong correlation between gut microbiota and the risk of skin diseases and proposed a "gut-skin axis." Androgenetic alopecia (AGA) is the most common type of alopecia, and androgen plays an important role in its pathogenesis. It has been found that the gut microbiome is closely related to androgens; however, whether this relationship is causal or merely coincidental remains uncertain. To address this issue, Mendelian randomization (MR) analysis was performed to explore the association between gut microbiota and AGA. Genome-wide association studies (GWAS) have compiled summary statistics of the gut microbiota, including 211 taxa (131 genera, 35 families, 20 orders, 16 classes, and 9 phyla), with data from MiBioGen's comprehensive study. We collected genetic associations with AGA from the IEU OpenGWAS project. We performed MR Analyses to assess the causal relationship between the genetically predicted gut microbiota and AGA. In order to verify the reliability of the findings, we systematically performed sensitivity analyses and heterogeneity tests and performed a heterogeneity test. MR Analysis provides important evidence for the causal relationship between genetically predicted gut microbiota and AGA. Lachnospiraceae UCG008 (OR = 0.939, 95%CI 0.175-0.775, P < .01), Oxalobacte (OR = 0.932, 95%CI 0.896-0.969, P < .01) would reduce the risk of AGA. Eubacterium rectale group (OR = 1.102, 95%CI 1.025-1.186, P < .01), Roseburia (OR = 1.183, 95%CI 1.048-1.336, P < .01) would increase the risk of AGA. Further sensitivity and heterogeneity analyses confirmed the robustness of these results. The results of this study indicate that there is a potential genetic susceptibility between gut microbiota and AGA, and screen out protective and risk factors. These results provide a theoretical basis for the prevention and treatment of AGA by regulating gut microbiota.

MNNMDA: Predicting human microbe-disease association via a method to minimize matrix nuclear norm

Identifying the potential associations between microbes and diseases is the first step for revealing the pathological mechanisms of microbe-associated diseases. However, traditional culture-based microbial experiments are expensive and time-consuming. Thus, it is critical to prioritize disease-associated microbes by computational methods for further experimental validation. In this study, we proposed a novel method called MNNMDA, to predict microbe-disease associations (MDAs) by applying a Matrix Nuclear Norm method into known microbe and disease data. Specifically, we first calculated Gaussian interaction profile kernel similarity and functional similarity for diseases and microbes. Then we constructed a heterogeneous information network by combining the integrated disease similarity network, the integrated microbe similarity network and the known microbe-disease bipartite network. Finally, we formulated the microbe-disease association prediction problem as a low-rank matrix completion problem, which was solved by minimizing the nuclear norm of a matrix with a few regularization terms. We tested the performances of MNNMDA in three datasets including HMDAD, Disbiome, and Combined Data with small, medium and large sizes respectively. We also compared MNNMDA with 5 state-of-the-art methods including KATZHMDA, LRLSHMDA, NTSHMDA, GATMDA, and KGNMDA, respectively. MNNMDA achieved area under the ROC curves (AUROC) of 0.9536 and 0.9364 respectively on HDMAD and Disbiome, better than the AUCs of compared methods under the 5-fold cross-validation for all microbe-disease associations. It also obtained a relatively good performance with AUROC 0.8858 in the combined data. In addition, MNNMDA was also better than other methods in area under precision and recall curve (AUPR) under the 5-fold cross-validation for all associations, and in both AUROC and AUPR under the 5-fold cross-validation for diseases and the 5-fold cross-validation for microbes. Finally, the case studies on colon cancer and inflammatory bowel disease (IBD) also validated the effectiveness of MNNMDA. In conclusion, MNNMDA is an effective method in predicting microbe-disease associations.

Availability

The codes and data for this paper are freely available at Github https://github.com/Haiyan-Liu666/MNNMDA.

Etiology, urine metabolic risk factors, and urine oxalate patterns in patients with significant hyperoxaluria and recurrent nephrolithiasis

PURPOSE

American Urology Association guidelines recommend genetic testing for patients with recurrent stones and urine oxalate > 75 mg/day. The goal of this study was to examine the treatment of patients in this category in a large multidisciplinary adult stone clinic.

METHODS

Patients were evaluated from a single institution between 2006 and 2019. Those with at least one level of urinary oxalate excretion (uOx) above 75 mg/day were identified. A chart review identified enteric risk factors and genetic testing results. Patients without an identifiable enteric cause were considered idiopathic.

RESULTS

A total of 4229 separate 24-h urine collections in 1302 patients were reviewed. At least one measurement of uOx above 75 mg/day was found in 103 (7.9%) patients. Enteric hyperoxaluria (EH) was seen in 28 (27%) and idiopathic hyperoxaluria (IH) in 76 (74%). 20 (71%) patients in the EH group had undergone gastric bypass. The median uOx was significantly higher level in the EH group (121.0 vs. 93.0 mg/day). For the entire cohort, there was a drop in uOx (- 33.8 mg/day) with medical and dietary therapy after a follow-up of 46.6 months. The final oxalate was higher in EH (88.9 vs. 60.1 mg/day). Only one patient had referral for genetic testing and was found to have primary hyperoxaluria type 2.

CONCLUSIONS

The most common cause of significant hyperoxaluria in patients with recurrent nephrolithiasis remains idiopathic. Patients with IH have more significant improvement in uOx compared to EH; however, both groups had hyperoxaluria at last follow-up. Rate of genetic testing is low despite guideline recommendations.