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Diagnostic model for predicting hyperuricemia based on alterations of the gut microbiome in individuals with different serum uric acid levels

Authors :
Meiting Liang
Jingkun Liu
Wujin Chen
Yi He
Mayina Kahaer
Rui Li
Tingting Tian
Yezhou Liu
Bing Bai
Yuena Cui
Shanshan Yang
Wenjuan Xiong
Yan Ma
Bei Zhang
Yuping Sun
Source :
Frontiers in Endocrinology, Vol 13 (2022)
Publication Year :
2022
Publisher :
Frontiers Media S.A., 2022.

Abstract

BackgroundWe aimed to assess the differences in the gut microbiome among participants with different uric acid levels (hyperuricemia [HUA] patients, low serum uric acid [LSU] patients, and controls with normal levels) and to develop a model to predict HUA based on microbial biomarkers.MethodsWe sequenced the V3-V4 variable region of the 16S rDNA gene in 168 fecal samples from HUA patients (n=50), LSU patients (n=61), and controls (n=57). We then analyzed the differences in the gut microbiome between these groups. To identify gut microbial biomarkers, the 107 HUA patients and controls were randomly divided (2:1) into development and validation groups and 10-fold cross-validation of a random forest model was performed. We then established three diagnostic models: a clinical model, microbial biomarker model, and combined model.ResultsThe gut microbial α diversity, in terms of the Shannon and Simpson indices, was decreased in LSU and HUA patients compared to controls, but only the decreases in the HUA group were significant (P=0.0029 and P=0.013, respectively). The phylum Proteobacteria (P

Details

Language :
English
ISSN :
16642392
Volume :
13
Database :
Directory of Open Access Journals
Journal :
Frontiers in Endocrinology
Publication Type :
Academic Journal
Accession number :
edsdoj.64df94b295ae4fdfb6f326309ec23b4e
Document Type :
article
Full Text :
https://doi.org/10.3389/fendo.2022.925119