Exploring the mechanism underlying hyperuricemia using comprehensive research on multi-omics

Abstract

Abstract Hyperuricemia involves multiple complex metabolisms, but no study has conducted a comprehensive analysis using human blood and urine metabolomics for hyperuricemia. Serum and urine samples from 10 patients with hyperuricemia and 5 controls were collected and analyzed by the UHPLC-MS/MS. Differential metabolites were identified and used in the enrichment analysis where we collected hyperuricemia target genes. Hyperuricemia kidney differential expressed genes (DEGs) were identified using RNA-sequencing data from the hyperuricemia mouse model induced by the potassium oxonate. A Mendelian randomization analysis of the association between caffeine-containing drinks and gout risk was conducted. An intersection analysis between hyperuricemia target genes and hyperuricemia kidney DEGs was conducted and the resulting genes were used for network analysis using the STRING. 227 differential metabolites were identified as differential metabolites and were enriched in 7 KEGG pathways, among which “Caffeine metabolism” was the top. The Mendelian randomization analysis revealed a significant association between tea or coffee intake and gout risk. There were 2173 genes that were identified as hyperuricemia kidney DEGs from mouse data. The intersection analysis identified 51 genes for the hyperuricemia regulation network. A hyperuricemia regulation protein network in the kidney was constructed. This study suggested a potential association between caffeine and hyperuricemia and constructed a hyperuricemia regulation network for future reference.