Prediction and causal inference of hyperuricemia using gut microbiota.

Hyperuricemia (HUA) is a symptom of high blood uric acid (UA) levels, which causes disorders such as gout and renal urinary calculus. Prolonged HUA is often associated with hypertension, atherosclerosis, diabetes mellitus, and chronic kidney disease. Studies have shown that gut microbiota (GM) affect these chronic diseases. This study aimed to determine the relationship between HUA and GM. The microbiome of 224 men and 254 women aged 40 years was analyzed through next-generation sequencing and machine learning. We obtained GM data through 16S rRNA-based sequencing of the fecal samples, finding that alpha-diversity by Shannon index was significantly low in the HUA group. Linear discriminant effect size analysis detected a high abundance of the genera Collinsella and Faecalibacterium in the HUA and non-HUA groups. Based on light gradient boosting machine learning, we propose that HUA can be predicted with high AUC using four clinical characteristics and the relative abundance of nine bacterial genera, including Collinsella and Dorea. In addition, analysis of causal relationships using a direct linear non-Gaussian acyclic model indicated a positive effect of the relative abundance of the genus Collinsella on blood UA levels. Our results suggest abundant Collinsella in the gut can increase blood UA levels.

Gut Microbiota Characterization in Patients with Asymptomatic Hyperuricemia: probiotics increased.

Asymptomatic hyperuricemia (AH) is an early stage of gout. Emerging evidence shows that the intestinal microbiota is related to gout. However, the relationship between AH and the intestinal microbiota is poorly understood. Therefore, the aim of the current study was to explore the possible correlation between AH and intestinal flora. We compared the intestinal microbial communities of AH (45 cases) and healthy subjects (45 cases) by 16S rRNA gene sequencing and clustering analysis on the incorporated population. Intestinal-type clustering can be divided into two groups, and significant differences in the proportion of AH are found among different bowel types. Alpha diversity indices were higher in the AH group than in the control group, and beta diversity indices also showed significant differences. A total of 19 genera were found different between the AH group and the control group. Compared with the control group, some probiotics are increased in the AH population. Two groups were ranked by importance of bacteria. We found the different bacteria partially coincided with the important bacteria, and the joint diagnosis level of the important bacteria was good. Conclusion: There were significant differences in the composition of intestinal biota between AH patients and healthy subjects. Some probiotics increased in AH.

Protective effects of tuna meat oligopeptides (TMOP) supplementation on hyperuricemia and associated renal inflammation mediated by gut microbiota.

Recently, interest in using whole food-derived mixtures to alleviate chronic metabolic syndrome through potential synergistic interactions among different components is increasing. In this study, the effects and mechanisms of tuna meat oligopeptides (TMOP) on hyperuricemia and associated renal inflammation were investigated in mice. Dietary administration of TMOP alleviated hyperuricemia and renal inflammation phenotypes, reprogramed uric acid metabolism pathways, inhibited the activation of NLRP3 inflammasome and TLR4/MyD88/NF-κB signaling pathways, and suppressed the phosphorylation of p65-NF-κB. In addition, TMOP treatments repaired the intestinal epithelial barrier, reversed the gut microbiota dysbiosis and increased the production of short-chain fatty acids. Moreover, the antihyperuricemia effects of TMOP were transmissible by transplanting the fecal microbiota from TMOP-treated mice, indicating that the protective effects were at least partially mediated by the gut microbiota. Thus, for the first time, we clarify the potential effects of TMOP as a whole food derived ingredient on alleviating hyperuricemia and renal inflammation in mice, and additional efforts are needed to confirm the beneficial effects of TMOP on humans.

Hyperuricemia is associated with impaired intestinal permeability in mice.

Hyperuricemia is associated with many metabolic diseases. However, the underlying mechanism remains unknown. The gut microbiota has been demonstrated to play significant roles in the immunity and metabolism of the host. In the present study, we constructed a hyperuricemic mouse model to investigate whether the metabolic disorder caused by hyperuricemia is related to intestinal dysbiosis. A significantly increased intestinal permeability was detected in hyperuricemic mice. The difference in microflora between wild-type and hyperuricemic mice accompanies the translocation of gut microbiota to the extraintestinal tissues. Such a process is followed by an increase in innate immune system activation. We observed increased LPS and TNF-α levels in the hyperuricemic mice, indicating that hyperuricemic mice were in a state of low-grade systemic inflammation. In addition, hyperuricemic mice presented early injury of parenteral tissue and disordered lipid metabolism. These findings suggest that intestinal dysbiosis due to an impaired intestinal barrier may be the key cause of metabolic disorders in hyperuricemic mice. Our findings should aid in paving a new way of preventing and treating hyperuricemia and its complications.NEW & NOTEWORTHY Hyperuricemia is associated with many metabolic diseases. However, the underlying mechanism remains unknown. We constructed a hyperuricemic mouse model to explore the relationship between intestinal dysbiosis and metabolic disorder caused by hyperuricemia.

Analysis of Oral Microbiota Revealed High Abundance of Prevotella Intermedia in Gout Patients.

BACKGROUND/AIMS: Microbes reside in a number of body sites, including the oral cavity, and are associated with the progression of many systemic diseases. In this study, we aimed to investigate the effects of gout and hyperuricemia (HUA) on the composition of oral microbiomes. METHODS: Analysis of the oral microbiota from 12 gout patients, 11 HUA patients, and 19 healthy control subjects was performed using a deep sequencing approach, and validation of significant changes in Prevotella intermedia and Serratia marcescens in new patient cohorts was performed using quantitative PCR (qPCR). RESULTS: Our analysis indicated that both gout and HUA significantly altered the composition of the oral microbiome in patients. Patients with gout or HUA had significantly greater levels of salivary Prevotella intermedia but significantly lower levels of Serratia marcescens than healthy control subjects. CONCLUSION: We demonstrated the association between the oral microbiome and gout and HUA for the first time. In particular, 16S sequencing and qPCR analysis revealed significantly higher levels of oral Prevotella intermedia in gout/HUA patients, which suggests that these patients might be at risk for the development of periodontitis.