# Characteristics of the gut microbiome of asymptomatic hyperuricemia

## TL;DR

This study explores how gut bacteria differ in people with asymptomatic hyperuricemia compared to healthy individuals, suggesting potential biomarkers for early diagnosis.

## Contribution

The study identifies gut microbiota differences and potential biomarkers in asymptomatic hyperuricemia patients.

## Key findings

- AH patients had lower gut microbiota richness and diversity compared to healthy controls.
- Uric acid levels correlated with specific gut microbes like Granulicatella.
- AH patients showed higher BMI, triglycerides, and other metabolic risk factors.

## Abstract

Asymptomatic hyperuricemia(AH) is characterized by elevated blood uric acid levels without symptoms,posing risks like gout, kidney stones, and cardiovascular diseases. This study aims to investigate the role of the gut microbiota in uric acid metabolism in AH.

Clinical data from 30 AH patients and 30 healthy controls were collected. Fecal microbiota genomic DNA was extracted, PCR amplified, library constructed, and sequenced. Bioinformatics and statistical analyses were conducted to study the gut microbiota of the two groups.

The AH group exhibited significantly elevated levels of body mass index (BMI), Triglycerides (TG), Total Cholesterol (TC), as along with a history of smoking, hypertension, and fatty liver disease compared to the healthy group (P < 0.05). The overall richness and ecological diversity of gut microbiota in the AH group decreased, with differences in the distribution at the phylum and genus levels compared to the healthy group. Uric acid demonstrated significant correlations with various gut microbiota (e.g., Granulicatella), suggesting their potential as biomarkers for AH. Despite limitations such as a small sample size and lack of long-term follow-up, our findings provide new insights for the early diagnosis and personalized treatment of AH. Looking ahead, these discoveries may advance the clinical management of AH and the exploration of associated biomarkers.