Xanthine oxidase inhibitor urate-lowering therapy titration to target decreases serum free fatty acids in gout and suppresses lipolysis by adipocytes

Causal impact of human blood metabolites and metabolic pathways on serum uric acid and gout: a mendelian randomization study

Objective

Hyperuricaemia and gout are common metabolic disorders. However, the causal relationships between blood metabolites and serum urate levels, as well as gout, remain unclear. A systematic evaluation of the causal connections between blood metabolites, hyperuricemia, and gout could enhance early screening and prevention of hyperuricemia and gout in clinical settings, providing novel insights and approaches for clinical treatment.

Methods

In this study, we employed a bidirectional two-sample Mendelian randomization analysis utilizing data from a genome-wide association study involving 7,286 participants, encompassing 486 blood metabolites. Serum urate and gout data were sourced from the Chronic Kidney Disease Genetics consortium, including 288,649 participants for serum urate and 9,819 African American and 753,994 European individuals for gout. Initially, LDSC methodology was applied to identify blood metabolites with a genetic relationship to serum urate and gout. Subsequently, inverse-variance weighting was employed as the primary analysis method, with a series of sensitivity and pleiotropy analyses conducted to assess the robustness of the results.

Results

Following LDSC, 133 blood metabolites exhibited a potential genetic relationship with serum urate and gout. In the primary Mendelian randomization analysis using inverse-variance weighting, 19 blood metabolites were recognized as potentially influencing serum urate levels and gout. Subsequently, the IVW p-values of potential metabolites were corrected using the false discovery rate method. We find leucine (IVW P FDR = 0.00004), N-acetylornithine (IVW P FDR = 0.0295), N1-methyl-3-pyridone-4-carboxamide (IVW P FDR = 0.0295), and succinyl carnitine (IVW P FDR = 0.00004) were identified as significant risk factors for elevated serum urate levels. Additionally, 1-oleoylglycerol (IVW P FDR = 0.0007) may lead to a substantial increase in the risk of gout. Succinyl carnitine exhibited acceptable weak heterogeneity, and the results for other blood metabolites remained robust after sensitivity, heterogeneity, and pleiotropy testing. We conducted an enrichment analysis on potential blood metabolites, followed by a metabolic pathway analysis revealing four pathways associated with serum urate levels.

Conclusion

The identified causal relationships between these metabolites and serum urate and gout offer a novel perspective, providing new mechanistic insights into serum urate levels and gout.

Effective xanthine oxidase inhibitor urate lowering therapy in gout is linked to an emergent serum protein interactome of complement activation and inflammation modulators

Background

Urate-lowering treatment (ULT) to target with xanthine oxidase inhibitors (XOIs) paradoxically causes early increase in gouty arthritis flares. Because delayed reduction in flare burden is mechanistically unclear, we tested for ULT inflammation responsiveness markers.

Methods

Unbiased proteomics analyzed blood samples (baseline, 48 weeks ULT) in two, independent ULT out trial cohorts (n = 19, n = 30). STRING-db and multivariate analyses supplemented determinations of altered proteins via Wilcoxon matched pairs signed rank testing in XOI ULT responders. Mechanistic studies characterized proteomes of cultured XOI-treated murine bone marrow macrophages (BMDMs).

Results

At 48 weeks ULT, serum urate normalized in all gout patients, and flares declined, with significantly altered proteins (p < 0.05) in clustering and proteome networks in sera and peripheral blood mononuclear cells. Serum proteome changes included decreased complement C8 heterotrimer C8A and C8G chains and chemokine PPBP/CXCL7, and increased urate crystal phagocytosis inhibitor sCD44. In both cohorts, a treatment-emergent serum interactome included key gouty inflammation mediators (C5, IL-1B, CXCL8, IL6). Last, febuxostat inhibited complement activation pathway proteins in cultured BMDMs.

Conclusions

Reduced gout flares are kinked with a XOI-treatment emergent complement- and inflammation-regulatory serum protein interactome. Serum and leukocyte proteomes could help identify onset of anti-inflammatory responsiveness to ULT in gout.

Trial registration

ClinicalTrials.gov Identifier: NCT02579096, posted October 19, 2015.

Predictors of Inadequate Serum Urate Response to Low-Dose Febuxostat in Male Patients with Gout

Objective

This study aimed to understand predictors of inadequate response (IR) to low-dose febuxostat treatment based on clinical variables.

Methods

We pooled data from 340 patients of an observational cohort and two clinical trials who received febuxostat 20 mg/day for at least 3 months. IR was defined as failure to reach the target serum urate level (sUA<6 mg/dL) at any time point during 3 months treatment. The potential predictors associated with short- or mid-term febuxostat IR after pooling the three cohorts were explored using mixed-effect logistic analysis. Machine learning models were performed to evaluate the predictors for IR using the pooled data as the discovery set and validated in an external test set.

Results

Of the 340 patients, 68.9% and 51.8% were non-responders to low-dose febuxostat during short- and mid-term follow-up, respectively. Serum urate and triglyceride (TG) levels were significantly associated with febuxostat IR, but were also selected as significant features by LASSO analysis combined with age, BMI, and C-reactive protein (CRP). These five features in combination, using the best-performing stochastic gradient descent classifier, achieved an area under the receiver operating characteristic curve of 0.873 (95% CI [0.763, 0.942]) and 0.706 (95% CI [0.636, 0.727]) in the internal and external test sets, respectively, to predict febuxostat IR.

Conclusion

Response to low-dose febuxostat is associated with early sUA improvement in individual patients, as well as patient age, BMI, and levels of TG and CRP.

Sustained xanthine oxidase inhibitor treat to target urate lowering therapy rewires a tight inflammation serum protein interactome

Background

Effective xanthine oxidoreductase inhibition (XOI) urate-lowering treatment (ULT) to target significantly reduces gout flare burden and synovitis between 1-2 years therapy, without clearing all monosodium urate crystal deposits. Paradoxically, treat to target ULT is associated with increased flare activity for at least 1 year in duration on average, before gout flare burden decreases. Since XOI has anti-inflammatory effects, we tested for biomarkers of sustained, effective ULT that alters gouty inflammation.

Methods

We characterized the proteome of febuxostat-treated murine bone marrow macrophages. Blood samples (baseline and 48 weeks ULT) were analyzed by unbiased proteomics in febuxostat and allopurinol ULT responders from two, independent, racially and ethnically distinct comparative effectiveness trial cohorts (n=19, n=30). STRING-db and multivariate analyses supplemented determinations of significantly altered proteins via Wilcoxon matched pairs signed rank testing.

Results

The proteome of cultured IL-1b-stimulated macrophages revealed febuxostat-induced anti-inflammatory changes, including for classical and alternative pathway complement activation pathways. At 48 weeks ULT, with altered purine metabolism confirmed by serum metabolomics, serum urate dropped >30%, to normal (<6.8 mg/dL) in all the studied patients. Overall, flares declined from baseline. Treated gout patient sera and peripheral blood mononuclear cells (PBMCs) showed significantly altered proteins (p<0.05) in clustering and proteome networks. CRP was not a useful therapy response biomarker. By comparison, significant serum proteome changes included decreased complement C8 heterotrimer C8A and C8G chains essential for C5b-9 membrane attack complex assembly and function; increase in the NLRP3 inflammasome activation promoter vimentin; increased urate crystal phagocytosis inhibitor sCD44; increased gouty inflammation pro-resolving mediator TGFB1; decreased phagocyte-recruiting chemokine PPBP/CXCL7, and increased monocyte/macrophage-expressed keratin-related proteins (KRT9,14,16) further validated by PBMC proteomics. STRING-db analyses of significantly altered serum proteins from both cohorts revealed a tight interactome network including central mediators of gouty inflammation (eg, IL-1B, CXCL8, IL6, C5).

Conclusions

Rewiring of inflammation mediators in a tight serum protein interactome was a biomarker of sustained XOI-based ULT that effectively reduced serum urate and gout flares. Monitoring of the serum and PBMC proteome, including for changes in the complement pathway could help determine onset and targets of anti-inflammatory changes in response to effective, sustained XOI-based ULT.Trial Registration: ClinicalTrials.gov Identifier: NCT02579096.

Metabolomics and Machine Learning Identify Metabolic Differences and Potential Biomarkers for Frequent Versus Infrequent Gout Flares

OBJECTIVE

The objective of this study was to discover differential metabolites and pathways underlying infrequent gout flares (InGF) and frequent gout flares (FrGF) using metabolomics and to establish a predictive model by machine learning (ML) algorithms.

METHODS

Serum samples from a discovery cohort of 163 patients with InGF and 239 patients with FrGF 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.

RESULTS

A total of 439 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.

CONCLUSION

Systematic 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.

Gas Chromatography-Mass Spectrometry Reveals Stage-Specific Metabolic Signatures of Ankylosing Spondylitis

Ankylosing spondylitis (AS) is a type of chronic rheumatic immune disease, and the crucial point of AS treatment is identifying the correct stage of the disease. However, there is a lack of effective diagnostic methods for AS staging. The primary objective of this study was to perform an untargeted metabolomic approach in AS patients in an effort to reveal metabolic differences between patients in remission and acute stages. Serum samples from 40 controls and 57 AS patients were analyzed via gas chromatography-mass spectrometry (GC-MS). Twenty-four kinds of differential metabolites were identified between the healthy controls and AS patients, mainly involving valine/leucine/isoleucine biosynthesis and degradation, phenylalanine/tyrosine/tryptophan biosynthesis, glutathione metabolism, etc. Furthermore, the levels of fatty acids (linoleate, dodecanoate, hexadecanoate, and octadecanoate), amino acids (serine and pyroglutamate), 2-hydroxybutanoate, glucose, etc., were lower in patients in the acute stage than those in the remission stage, which may be associated with the aggravated inflammatory response and elevated oxidative stress in the acute stage. Multiple stage-specific metabolites were significantly correlated with inflammatory indicators (CRP and ESR). In addition, the combination of serum 2-hydroxybutanoate and hexadecanoate plays a significant role in the diagnosis of AS stages. These metabolomics-based findings provide new perspectives for AS staging, treatment, and pathogenesis studies.