Objective. The predominant mechanism driving hyperuricemia in gout is renal uric acid underexcretion; however, the standard urate-lowering therapy (ULT) recommendation is first-line xanthine oxidase inhibitor (XOI), irrespective of the cause of hyperuricemia. This comparative effectiveness clinical trial was undertaken to compare first-line nontitrated low-dose benzbromarone (LDBen) uricosuric therapy to XOI ULT with low-dose febuxostat (LDFeb) in gout patients with renal uric acid underexcretion.Methods. We conducted a prospective, randomized, single-center, open-label trial in men with gout and renal uric acid underexcretion (defined as fractional excretion of urate <5.5% and uric acid excretion ≤600 mg/day/1.73 m 2 ). A total of 196 participants were randomly assigned to receive LDBen 25 mg daily or LDFeb 20 mg daily for 12 weeks. All participants received daily urine alkalization with oral sodium bicarbonate. The primary end point was the rate of achieving the serum urate target of <6 mg/dl.Results. More participants in the LDBen group achieved the serum urate target than those in the LDFeb group (61% compared to 32%, P < 0.001). Rates of adverse events, including gout flares and urolithiasis, did not differ between groups, with the exception of greater transaminase elevation in the LDFeb group (4% for LDBen compared to 15% for LDFeb, P = 0.008).Conclusion. Compared to LDFeb, LDBen has superior urate-lowering efficacy and similar safety in treating relatively young and healthy patients with renal uric acid underexcretion-type gout.
ObjectivesTo discover differential metabolites and pathways underlying infrequent gout flares (InGF) and frequent gout flares (FrGF) using metabolomics and establish a predictive model by machine learning (ML) algorithms.MethodsSerum samples from a discovery cohort with 163 InGF and 239 FrGF patients were analyzed by mass spectrometry‐based untargeted metabolomics to profile differential metabolites and explore dysregulated metabolic pathways using pathway enrichment analysis and network propagation‐based algorithms. ML algorithms were performed to establish a predictive model based on selected metabolites, which was further optimized by a quantitative targeted metabolomics method and validated in an independent validation cohort with 97 participants with InGF and 139 participants with FrGF.Results439 differential metabolites between InGF and FrGF groups were identified. Top dysregulated pathways included carbohydrates, amino acids, bile acids, and nucleotide metabolism. Subnetworks with maximum disturbances in the global metabolic networks featured cross‐talk between purine metabolism and caffeine metabolism, as well as interactions among pathways involving primary bile acid biosynthesis, taurine and hypotaurine metabolism, alanine, aspartate and glutamate metabolism, suggesting epigenetic modifications and gut microbiome in metabolic alterations underlying InGF and FrGF. Potential metabolite biomarkers were identified using ML‐based multivariable selection and further validated by targeted metabolomics. Area under receiver operating characteristics curve for differentiating InGF and FrGF achieved 0.88 and 0.67 for the discovery and validation cohorts, respectively.ConclusionsSystematic metabolic alterations underlie InGF and FrGF, and distinct profiles are associated with differences in gout flare frequencies. Predictive modeling based on selected metabolites from metabolomics can differentiate InGF and FrGF.
BackgroundGout is a polygenetic inflammatory disease. Although hundreds of genetic variants associated with gout and serum urate levels have been identified in studies of adults, the pathogenesis of adolescent–onset gout remains unclear. To better characterize the genetic landscape of adolescent–onset gout, a whole genome sequencing study was done in a large Chinese adolescent–onset gout cohort.MethodsWe conducted whole genome sequencing in a discovery adolescent–onset gout cohort of 905 individuals (gout onset 12–19 years) to discover common SNVs, uncommon SNVs, and indels associated with gout. Candidate common SNVs were replicated in an early–onset gout cohort of 2834 individuals (gout onset ≤ 30 years old). Loci associated with early–onset gout (P < 5.0 × 10-8) were identified after meta–analysis with the discovery and replication cohorts. Transcriptome and epigenomic analyses, RT–qPCR and RNA–seq in human peripheral blood leukocytes, and knock–down experiments in human THP–1 macrophage cells investigated regulation and functions of candidate gene RCOR1.FindingsIn addition to ABCG2, a urate transporter previously linked to pediatric–onset and early–onset gout, we identified four novel loci:VPRBP(rs868933181, Pmeta= 6.27 × 10-9; ORmeta= 1.66),NKILA–MIR4532(rs72626599, Pmeta= 6.48 × 10-9; ORmeta= 1.58),RCOR1(rs12887440, Pmeta= 3.37 × 10-8; ORmeta= 1.48), andFSTL5–MIR4454(rs35213808, Pmeta= 4.02 × 10-8; ORmeta= 1.49). Additionally, we found association atABCG2andSLC22A12that was driven by low frequency SNVs. Furthermore, eight uncommon SNVs and three indels in the exome were predicted to be harmful. SNVs inRCOR1were linked to heightened blood leukocyte mRNA levels. THP–1 macrophage culture studies revealed the potential of decreased RCOR1 to suppress gouty inflammation.InterpretationPerforming the first comprehensive characterization of adolescent–onset gout genomes identified risk loci of early–onset gout. Loci mediate inflammatory responsiveness to crystals that could mediate gouty arthritis. This study will contribute to risk prediction and therapeutic interventions to prevent adolescent–onset gout.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.