The impact of short-chain fatty acid-producing bacteria of the gut microbiota in hyperuricemia and gout diagnosis.

INTRODUCTION/OBJECTIVES: Persistent hyperuricemia is a key factor in gout; however, only 13.5% of hyperuricemic individuals manifest the disease. The gut microbiota could be one of the many factors underlying this phenomenon. We aimed to assess the difference in taxonomic and predicted functional profiles of the gut microbiota between asymptomatic hyperuricemia (AH) individuals and gout patients. METHODS: The V3-V4 region of the 16S rRNA gene of the gut microbiota of AH individuals, gout patients, and controls was sequenced. Bioinformatic analyses were carried out with QIIME2 and phyloseq to determine the difference in the relative abundance of bacterial genera among the study groups. Tax4fun2 was used to predict the functional profile of the gut microbiota. RESULTS: AH individuals presented a higher abundance of butyrate- and propionate-producing bacteria than gout patients; however, the latter had more bacteria capable of producing acetate. The abundance of Prevotella genus bacteria was not significantly different between the patients but was higher than that in controls. This result was corroborated by the functional profile, in which AH individuals had less pyruvate oxidase abundance than gout patients and less abundance of an enzyme that regulates glutamate synthetase activation than controls. CONCLUSION: We observed a distinctive taxonomic profile in AH individuals characterized by a higher abundance of short-chain fatty acid-producing bacteria in comparison to those observed in gout patients. Furthermore, we provide scientific evidence that indicates that the gut microbiota of AH individuals could provide anti-inflammatory mediators, which prevent the appearance of gout flares. Key Points • AH and gout patients both have a higher abundance of Prevotella genus bacteria than controls. • AH individuals' gut microbiota had more butyrate- and propionate-producing bacteria than gout patients. • The gut microbiome of AH individuals provides anti-inflammatory mediators that could prevent gout flares.

Inflammasome Genes Polymorphisms and Susceptibility to Gout. Is There a Link?

ABSTRACT Background: The inflammatory response in gout disease is induced by the activation of NLR family pyrin domain-containing 3 (NLPR3) signaling pathway mediated by IL-1β release. Objective: The objective of the study was to determine the association between single nucleotide polymorphisms (SNPs) within NLRP3 inflammasome genes and gout susceptibility. Methods: Mexican patients with gout from the National Rehabilitation Institute and General Hospital of Mexico were enrolled. A healthy control group was also included. We analyzed the frequency and allelic distribution of eight SNPs from seven different genes within the NLRP3 inflammasome signaling pathway: TLR4 rs2149356, CD14 rs2569190, NLRP3 rs3806268, NLRP3 rs10754558, CARD8 rs2043211, IL-1β rs1143623, P2RX7 rs3751142, and PPARGC1B rs45520937 SNPs. Results: We found that the SNP rs45520937 of PPARGC1B was associated with the risk of developing gout when it was analyzed using the dominant model (Odds ratio [OR] = 2.30; 95% confidence interval [CI]: 1.09-4.86; p = 0.030), and it is proposed that the adaptor molecule CD14 rs2569190 polymorphism could be associated with a lower risk of gout under an additive model (OR= 0.41;95% CI: 0.16-1.05; p = 0.064). No significant associations were identified for the remaining SNPs. Conclusion: Our findings suggest that the PPARGC1B rs45520937 SNP is associated with gout susceptibility.

Inflammasome genes polymorphisms and susceptibility to gout. Is there a link?

Background: The inflammatory response in gout disease is induced by the activation of NLR family pyrin domain-containing 3 (NLPR3) signaling pathway mediated by IL-1ß release. Objective: The objective of the study was to determine the association between single nucleotide polymorphisms (SNPs) within NLRP3 inflammasome genes and gout susceptibility. Methods: Mexican patients with gout from the National Rehabilitation Institute and General Hospital of Mexico were enrolled. A healthy control group was also included. We analyzed the frequency and allelic distribution of eight SNPs from seven different genes within the NLRP3 inflammasome signaling pathway: TLR4 rs2149356, CD14 rs2569190, NLRP3 rs3806268, NLRP3 rs10754558, CARD8 rs2043211, IL-1ß rs1143623, P2RX7 rs3751142, and PPARGC1B rs45520937 SNPs. Results: We found that the SNP rs45520937 of PPARGC1B was associated with the risk of developing gout when it was analyzed using the dominant model (Odds ratio [OR] = 2.30; 95% confidence interval [CI]: 1.09-4.86; p = 0.030), and it is proposed that the adaptor molecule CD14 rs2569190 polymorphism could be associated with a lower risk of gout under an additive model (OR= 0.41;95% CI: 0.16-1.05; p = 0.064). No significant associations were identified for the remaining SNPs. Conclusion: Our findings suggest that the PPARGC1B rs45520937 SNP is associated with gout susceptibility.

Taxonomic variations in the gut microbiome of gout patients with and without tophi might have a functional impact on urate metabolism.

OBJECTIVE: To evaluate the taxonomic composition of the gut microbiome in gout patients with and without tophi formation, and predict bacterial functions that might have an impact on urate metabolism. METHODS: Hypervariable V3-V4 regions of the bacterial 16S rRNA gene from fecal samples of gout patients with and without tophi (n = 33 and n = 25, respectively) were sequenced and compared to fecal samples from 53 healthy controls. We explored predictive functional profiles using bioinformatics in order to identify differences in taxonomy and metabolic pathways. RESULTS: We identified a microbiome characterized by the lowest richness and a higher abundance of Phascolarctobacterium, Bacteroides, Akkermansia, and Ruminococcus_gnavus_group genera in patients with gout without tophi when compared to controls. The Proteobacteria phylum and the Escherichia-Shigella genus were more abundant in patients with tophaceous gout than in controls. Fold change analysis detected nine genera enriched in healthy controls compared to gout groups (Bifidobacterium, Butyricicoccus, Oscillobacter, Ruminococcaceae_UCG_010, Lachnospiraceae_ND2007_group, Haemophilus, Ruminococcus_1, Clostridium_sensu_stricto_1, and Ruminococcaceae_UGC_013). We found that the core microbiota of both gout groups shared Bacteroides caccae, Bacteroides stercoris ATCC 43183, and Bacteroides coprocola DSM 17136. These bacteria might perform functions linked to one-carbon metabolism, nucleotide binding, amino acid biosynthesis, and purine biosynthesis. Finally, we observed differences in key bacterial enzymes involved in urate synthesis, degradation, and elimination. CONCLUSION: Our findings revealed that taxonomic variations in the gut microbiome of gout patients with and without tophi might have a functional impact on urate metabolism.

Common gene variants interactions related to uric acid transport are associated with knee osteoarthritis susceptibility.

BACKGROUND: The presence of genetic variants in uric acid (UA) transporters can be associated with hyperuricemia, and therefore with an increased risk of monosodium urate (MSU) crystal precipitation. The inflammatory process triggered by these crystals leads to cartilage damage, which, in turn, could promote knee osteoarthritis (KOA). OBJECTIVE: To determine whether genetic polymorphisms of the UA transporters and their interactions are associated with KOA. MATERIALS AND METHODS: Two hundred forty-three unrelated Mexican-mestizo individuals were recruited for this case-control study. Ninety-three of them were KOA patients but without gout, and one hundred and fifty healthy individuals with no symptoms or signs of KOA were recruited as controls. Forty-one single-nucleotide polymorphisms (SNPs) involved in the UA transporters were genotyped with OpenArray technology in a QuantStudio 12K flex-System with both cases and controls. RESULTS: After adjusting by age, gender, BMI, and ancestry, significant associations were found for eight SNPs: rs1260326 (GCKR), rs780093 (GCKR), rs17050272 (INHBB), rs1471633 (PDZK1), rs12129861 (PDZK1), rs7193778 (IGF1R), rs17786744 (STC1), and rs1106766 (R3HDM2). With respect to gene-gene interactions, the pairwise interactions of rs112129861 (PDZK1) and rs7193778 (IGF1R); rs17050272 (INHBB) and rs1106766 (R3HDM2); rs1106766 (R3HDM2) and rs780093 (GCKR); rs1260326 (GCKR) and rs17786744 (STC1); and rs17786744 (STC1) and rs1106766 (R3HDM2) make it possible to visualize the synergistic or antagonistic effect of their genotypes or alleles on KOA development. CONCLUSIONS: Our preliminary results show that the common gene variants related to UA transport are associated with KOA in the Mexican population. Further studies must be carried out to corroborate it.