Gut's role in gout: New study unravels microbiome's influence on uric acid levels

By Pooja Toshniwal PahariaReviewed by Susha Cheriyedath, M.Sc.Oct 9 2023

In a recent study published in the journal Nutrients, researchers investigated the causal association between gut microbiome (GM) composition, gout, and serological urate (SUA) values using Mendelian randomization (MR).

Gout, a prevalent inflammatory disease characterized by high SUA levels, has been linked to other metabolic disorders. GM may impact uric acid metabolism by influencing the metabolism of short-chain fatty acids and purines. However, the link between GM dysbiosis and gout development remains unknown. GM may be a therapeutic target for reducing hyperuricemia processes, implying a possible relationship between the gut microbiome and serological urate levels. However, insufficient data shows a causal link between the two.

Study: Causal Relationship between Gut Microbiota and Gout: A Two-Sample Mendelian Randomization Study. Image Credit: staras / Shutterstock

About the study

In the present study, researchers evaluated the impact of the gut microbiome on gout development.

MR was performed using genetic variants as instrumental variables (IVs) to evaluate the causal relationship between the gut microbiota and serological urate levels. In addition, a reverse Mendelian randomization analysis was performed with serological urate-associated SNPs and gout-associated single-nucleotide polymorphisms (SNPs) as instrumental variables, SUA levels and gout as the study exposures, and the gut microbiome as the study outcome, to evaluate the potential causal influence of gout and SUA levels on GM.

The researchers utilized the MiBioGen collaboration’s GM genome-wide association study (GWAS) data, including 16s ribosomal ribonucleic acid (RNA) sequencing and genotyping information for 18,340 people. The study comprised 211 microbial taxa, divided into 131, 35, 20, 16, and nine genera, families, orders, classes, and phyla, respectively. GWAS data for serological urate levels were obtained from a publicly available meta-analysis, which included data provided by 457,690 people who participated in 74 studies.

A meta-analysis of 763,813 people and 13,179 cases of gout yielded GWAS data on gout. SNPs linked with gut microbial taxa met the genome-wide significance cut-off (p-value less than 5 x 10^-8) to assure data robustness and the correctness of the findings. In addition, in line with prior research, SNPs related to the gut microbial taxa at a relatively broad threshold (p-value less than 1.0 x 10^-5) were selected as potential IVs. The researchers also performed linkage disequilibrium (LD) assessment on the clumped SNPs using the European 1,000 Genomes Project data for reference to determine the LD.

SNPs that were duplicated, palindromic, or ambiguous were eliminated from the analysis. IV strength was used to calculate F-statistic values. For microbial taxa with a single single-nucleotide polymorphism as an instrumental variable, Wald ratios were used for the MR estimations. Other approaches, such as inverse-variance-weighting (IVW), the weighted mode, and the weighted median (WM), were used for taxa with multiple IVs. Multiple-testing corrections were accomplished using the Bonferroni procedure. Sensitivity studies were performed, including leave-one evaluation and MR-Egger-type regression.

Results

After eliminating 15 unknown gut microbial taxa from MiBioGen data, 196 gut microbial taxa from five levels were available for analysis. In total, 2,410 and 2,412 IVs were associated with the 196 gut microbial taxa for serological urate levels and gout, respectively. For the instrumental variables, the F-statistic values varied from 11 to 207, confirming the lack of mild instrument bias.

After SNPs were harmonized and clumped, 28 single-nucleotide polymorphisms for gout were related to 20 taxa, while 29 SNPs for SUA were connected to 21 taxa. Twelve SNPs related to the complete GM were chosen as IVs from among the 196 GM taxa. With F-statistic values of more than 10, each SNP proved acceptable validity. There were five taxa related to SUA levels and ten to gout.

The reverse Mendelian randomization analysis showed six single-nucleotide polymorphisms linked to gout for five taxa of gut microbes and 35 single-nucleotide polymorphisms related to serological urate levels for 31 microbial taxa, indicating that gout affected the composition of five GM taxa while SUA levels influenced the composition of 30 GM taxa. SUA levels showed negative correlations with Lachnospiraceae FCS020 and NC2004 strains. Combining prior research, the researchers proposed a potential negative feedback loop between the Actinobacteria phylum and SUA levels.

Contrastingly, Escherichia was positively associated with serological urate levels. In addition, gout was positively correlated with melainabacteria and betaproteobacteria, with odds ratio (OR) values of 1.1 and 1.2, respectively. Further, the analysis indicated that microbes such as Actinomycetales, Gastranaerophilales, Burkholderiales, Actinomycetaceae, and Porphyromonadaceae increased gout risks, with OR values of 1,2, 1.1, 1.3, 1.2, and 1.2, respectively.

In addition, positive associations were observed between Ruminococcaceae UCG011 (OR, 1.1) and gout. On the contrary, Anaerotruncus species (OR, 0.8) showed negative associations with gout. Wald ratio analyses for gout also showed negative correlations with the Oxalobacteraceae family (OR, 0.6), Romboutsia genus (OR, 0.7), Ruminococcus genus (OR, 0.7), and Tyzzerella genus (OR, 0.8).

The team proposed two new relationships connecting GM taxa (Prevotella genus and Faecalibacterium genus), SUA levels, and gout. While Prevotella was positively associated with serological urate levels and gout, a negative correlation was observed for Faecalibacterium. The sensitivity analyses showed no horizontal pleiotropy, heterogeneity, or potential outliers. The Bonferroni corrections showed significant findings only for Betaproteobacteria and Burkholderiales relative to gout.

Overall, the study findings showed that the abundance of genetically predicted GM taxa has a key influence on SUA levels and the development of gout. Furthermore, GM composition is influenced by gout and SUA levels. The findings provide important information for gout therapy. More extensive study, however, is necessary to establish specific causal linkages. Exploring the molecular processes behind the reciprocal interactions between GM and gout or SUA levels necessitates additional animal experiments and population investigations.