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[Preprint]. 2024 May 9:rs.3.rs-4278877.
doi: 10.21203/rs.3.rs-4278877/v1.

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

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

Concepcion Sanchez et al. Res Sq. .

Update in

Abstract

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.

Keywords: C8; Complement; TGFbeta; Xanthine oxidase; allopurinol; febuxostat; gout; inflammation; proteomics.

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Conflict of interest statement

Competing interests: DJG: Grant from Janssen Pharmaceuticals RT: Dr. Robert Terkeltaub has recently served, or currently serves, as a consultant for Allena, LG Chem, Fortress, Selecta Biosciences, Horizon Therapeutics, Atom Bioscience, Acquist Therapeutics, Generate Biomedicines, Astra-Zeneca, and Synlogic, and was a previous recipient of a research grant from AstraZeneca. He serves as the non-salaried President of the G-CAN (Gout, Hyperuricemia, and Crystal-Associated Disease Network) research society, which annually receives unrestricted arms-length grant support from pharma donors. The other authors declare that they have no conflict of interest.

Figures

Figures 1
Figures 1
Bone Marrow Derived Macrophage (BMDMs) Proteomics. A. BMDM treatment schematic B. Volcano plots of log2- fold change relative protein abundance versus log10 p-value. Points are colored by condition they are found higher in and sized by p-value significance (p-value<0.05, Wilcoxon signed rank test). C. Venn Diagram displaying overlap of differentially abundant proteins in IL1β and IL1β+Febuxostat treated macrophages. D. Protein interactome from String-DB using significantly altered proteins in respective binary comparison of BMDM treatments. Nodes are shaped based on the direction of relative abundance change after respective treatments and outlined in red if found to be significantly altered (p-value<0.05)
Figure 2
Figure 2
Patient Serum Proteomics. A. Experimental design for proteomics studies in gout patient cohorts. Cohort 1= UCSD Cohort, Cohort 2= Nebraska cohort. B. Protein interactome from String-DB using significantly altered proteins identified in each cohort indecently along with central gout mediators. Nodes are colored by cohort they were found to be significantly altered in and shaped by their direction of change after treatment with ULT. Edges are sized by strength of interaction. C. Gene ontology enrichment analysis of significantly altered proteins from both proteomic cohorts. Enrichment was conducted on Cytoscape with the Human Proteome as background. D. Protein interactome of the detected overlapping proteins from both cohorts. Nodes are colored based on whether their abundance change was the same in both cohorts after 48wks of ULT, and shaped based on their direction of change after ULT. E. Gene ontology enrichment analysis of overlapping proteins from both cohorts. Enrichment was conducted on Cytoscape with the Human Proteome as background.
Figure 3
Figure 3
PBMC proteomics. A. Volcano plots of log2- fold change relative protein abundance versus log10 p-value. Points are colored by condition they are found higher in, and sized by p-value significance (p-value<0.05, Wilcoxon signed rank test). B. Protein interactome from String-DB using significantly altered proteins after ULT treatment of gout patients. Nodes are colored by group they are found to have higher relative abundance. C. Gene ontology enrichment analysis of significantly altered proteins after ULT. Enrichment was conducted on Cytoscape with the Human Proteome as background. D. PBMC patient proteome-associated protein abundances to understand PBMC patient proteome separation conducted at baseline and proteomics endpoint (48wks). Protein interactome from String-DB using top protein drivers of PBMC patient proteome separation along with “pin-dropped” central gout mediators. Nodes are colored by group they are found to have higher relative abundance.

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