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


Introduction
Gout is characterized by acute arthritis ares that typically are excruciatingly painful and incapacitating 1,2 .Exogenous factors, including joint trauma, certain dietary excesses, and alcohol consumption, can trigger ares [3][4][5] .Gout ares require treatment with nonsteroidal anti-in ammatory drugs, corticosteroids, and colchicine, which are nonselective, frequently toxic, and interact frequently with other medications 1,6,7 .Undertreated, gout commonly progresses to more frequent ares, chronic arthritis, and permanent joint damage 1 .Gout also is linked to prevalent comorbidities mediated by lowgrade in ammation (eg, obesity, type 2 diabetes, atherosclerosis, chronic kidney disease) 1,8 .Pharmacologic treatment of hyperuricemia, most commonly prescribed using XOI drugs (principally allopurinol or febuxostat), is central to gout management 6,7 .However, effective XOI urate-lowering treatment (ULT) to target also paradoxically induces an elevated gout are burden early in treatment 6,7,9 .Remodeling of articular monosodium urate (MSU) crystal deposits and consequent release of free crystals are held partly responsible [10][11][12] .Notably, changes in a subset of CD14 positive monocytes, overactivation of CD8 + T cells, and upregulate arachidonate metabolism also have been implicated perpetuating systemic gouty in ammation after ULT initiation 13 .
MSU crystals stimulate gouty in ammation in large part by activating monocytes and macrophages, promoting NLRP3 in ammasome-mediated IL-1b release, and neutrophil in ux and activation that amplify the in ammatory cascade 1,14 .C5 cleavage on the MSU crystal surface, and consequent C5b-9 complement membrane attack complex (MAC) assembly and membrane pore-forming activity play a major role in the model gouty arthritis in ammatory process 15,16 .
Recent clinical trials have demonstrated that effective XOI urate-lowering treatment (ULT) to target eventually reduces gout are burden and synovitis between 1-2 years therapy [17][18][19] .Importantly, ares decrease in this time frame.despite total resolution of urate crystal deposits being far slower and particularly di cult to achieve 10 , and despite continuing systemic in ammation even in the periods between ares and in clinical remission 13 .In clinical practice, this situation is associated with lack of clarity on how long anti-in ammatory gout are prophylaxis, typically using low dose colchicine, is necessary after initiating ULT and achieving the serum urate target 9 .
Signi cantly, XOI drugs exert anti-in ammatory effects in monocytes and some other cells, including by antioxidant and urate-lowering effects [20][21][22][23][24] .For example, XOI drugs inhibit NLRP3 in ammasome activation, IL-1b release, and chemokine expression in cultured monocyte/macrophage lineage cells 20,21 .In vivo, XOI drugs limit mouse models of atherosclerosis, nonalcoholic steatohepatosis, and certain other diseases involving low-grade chronic in ammation and oxidative stress processes [20][21][22][23][24] .Hence, we conducted a seminal study to test the hypothesis that sustained, effective ULT remodels in ammatory networks in gout by 48 weeks therapy, that XOI could contribute to this effect, and that this could be detectable using unbiased proteomics.
The data revealed the ability of proteomics to detect anti-in ammatory changes in cultured XOI-treated macrophages, and in response to sustained, effective XOI-based ULT in gout patient sera and PBMCs.Our results provide unbiased evidence that sustained treat to target ULT in gout affects complement activation and other in ammatory pathways, and that XOI inhibition may contribute to remodeling of pathways that regulate gouty in ammation.

Subjects
As previously reported in detail 25 , Cohort 1 and Cohort 2 human subjects were studied under informed consent, and with local IRB approval (at the Jennifer Moreno San Diego Veterans Affairs Medical Center, and at the University of Nebraska Medical Center, respectively).All experiments were performed in accordance with relevant guidelines and regulations.Human subjects samples and clinical and clinical laboratory data were collected speci cally in prospective study ancillary to the national, multi-site comparative effectiveness ULT trial VA CSP594 STOP GOUT, whose protocol and CONSORT statement were previously published. 19In that trial, gout patients were randomized to a treat to urate target ULT regimen using allopurinol or the more selective XOI febuxostat.Unless contraindicated, colchicine was prescribed as the primary anti-in ammatory gout are prophylaxis, with colchicine routinely stopped at 6 months ULT.Twenty consecutive patients meeting the 2015 ACR/EULAR gout classi cation criteria 26 , and with current hyperuricemia, were recruited from the Rheumatology Outpatient Clinic at the San Diego site 25 .Once again 25 , the gout validation cohort (Cohort 2, n = 30)) was from the University of Nebraska Medical Center, in Omaha, NE research site, under informed consent and with local IRB approval.Subjects with active are, or CRP elevated over 2 mg/L at study onset and endpoints were not excluded from analyses.We previously characterized Cohort 1 gout patient metabolomic pro les at time zero and 12 and 24 weeks of treat to target ULT, done in a blinded way for the XOI used, and following the trial protocol 25 .

Proteomics:
Sera were obtained from both cohorts, with peripheral blood mononuclear cells (PBMCs) also prepared from Cohort 1 samples.All subjects were clinically assessed by study physicians for palpable tophaceous disease and presence of active are or quiescent arthritis, with co-morbidities and current medications also recorded.
For serum collection, research personnel collected non-fasting blood samples into 10 ml BD Vacutainer Blood Collection Tubes containing spray-coated silica and a polymer gel to facilitate serum separation.
Following 30 min incubation at room temperature, tubes were centrifuged for 10 min at 2000×g and sera were transferred into 1.7ml tubes and immediately frozen and stored at − 80°C until analyses were performed.
For PBMC preparation, non-fasting blood samples collected into 10 ml BD Vacutainer K2 EDTA Plus Blood Collection Tubes were transferred to a conical tube containing equal volume of PBS (~ total 20 ml).The samples were then layered over Sigma Histopaque®-1077 (20 mL) in 50 mL conical tubes at room temperature, followed by centrifugation at 400×g in a swinging bucket centrifuge for 30 minutes at room temperature with no brake.The white cellular layer containing PBMCs at the interface between the plasma and density gradient was collected and washed in PBS by dilution and centrifugation for 10 minutes at 250×g.PBMC pellets were immediately frozen and stored at − 80°C until analyzed.

Mass Spectrometry Proteomics:
Sample preparation for proteomic analyses of BMDMs and patient sera was done as we previously described in extensive detail 27 , with slight modi cation to the sample digestion protocol, which used 10µg trypsin in 50mM TEAB at 47˚C for 3 hours.After protein extraction and trypsin digest, 50ug aliquots of samples were reserved for TMT pro-labeling 27 .Bridge channels for downstream data analysis of serum samples, were prepped by combining 5µg of all samples; 50µg aliquots of our bridge sample were then prepared for each TMT-plex (5 total).

Mass spectrometry data acquisition
Serum and BMDM proteomic data were acquired as described in detail 27 .In brief, serum and BMDM proteomic data were acquired through an Thermo Orbitrap Fusion equipped with a Thermoeasy nLC 1000.For Mass spectrometry data search, raw mass spectrometry les were searched using Proteome Discoverer 2.5.0.400.The SEQUEST algorithm was used for spectral matches of raw data with in silico generated protein databases.Serum samples were searched against the UniProt Homo sapiens proteome (05-06-2023) and BMDM samples were searched against the Mus musculus proteome (05-06-23).

Mass Spectrometry Metabolomics
Sample preparation of patient sera for metabolomics were essentially as previously described 27 .In brief, for data Analysis, metabolite features were rst normalized to the intensity of value of the internal standard, sulfamethazine, in each sample and then multiplied by 1E6.Missing values (with peak intensities of 0) in metabolite features were set to NA.Then, features with more than 20% missing values per group (timepoint) were removed from analysis.Missing values in remaining features were imputed using K-Nearest Neighbor (KNN) imputation using the R package (1.68.0).Intensity values were then log2 transformed.
Principal coordinate analysis (PcoA) was conducted with metabolite features, using Bray-Curtis distance calculation in the R package.PERMANOVA analysis was conducted using categorical metadata and metabolite features using Bray-Curtis distance calculation in the ADONIS R package.Binary comparisons between timepoints were done through the R package using Students T-test.Volcano plots were created in GraphPad Prism.All other plots were made using package in R. MetaboAnalyst (5.0) was used for metabolite functional enrichment analysis using MS peaks ranked by Student's T test p-values.A p-value cutoff of 0.05 was used for the mummichog algorithm.

Murine Bone Marrow Derived Macrophage (BMDM) preparation
Mouse macrophage studies were done using a protocol approved by the Jennifer Moreno San Diego Veterans Affairs Medical Center Institutional Animal Care and Use Committee (IACUC).All experiments were performed in accordance with ARRIVE guidelines and other relevant ethics and veterinary practice guidelines and regulations.No experiments were performed on live mice.To prepare mouse BMDMs for in vitro studies, 12-week-old C57BL/6 male mice (from The Jackson Lab, Bar Harbor, ME) were euthanized using the carbon dioxide (CO 2 ) inhalation method, according to the 2020 American Veterinary Medical Association (AVMA) Guidelines for the Euthanasia of Animals.Bone marrow cells were then ushed from femur and tibia bones of these mice and were cultured in vitro in RPMI containing 10% FBS, penicillin (100 U/ml), streptomycin (100µg/ml), and, for the source of Macrophage-Colony Stimulating Factor, 20% L929 conditioned media for 7 days.BMDMs generated from 3 individual mice (n = 3 biological replicates) were used for the in vitro experiments.

Statistical analyses:
Paired statistical analyses of gout patient serum and PBMC samples across two timepoints (UCSD cohort), and for three timepoints for sera (Nebraska cohort), were conducted to identify signi cantly altered proteins.Unpaired statistical analyses were conducted for the cultured mouse BMDM samples.Signi cantly altered proteins were calculated using a Wilcoxon matched pairs signed rank test using Graphpad Prism, with p-value adjusted values using Benjamini and Hochberg false discovery rate found in Supplementary Table 1.
For multivariate Analysis, Principal Component Analysis (PCA) was conducted using the R package using all normalized protein features.Principal Coordinate Analysis (PCoA) was conducted using the R package using the Euclidean Distance Matrix (EDM) of normalized protein features.PERMANOVA analysis was used to calculate data in uence by metadata categories.
Gene Ontology enrichment analysis was conducted through input of signi cantly altered proteins in both diseases to their respective controls into Cytoscape.Protein interactome analysis was conducted through input of signi cantly altered proteins in both diseases to their respective controls into String-DB with an interaction con dence of 0.700 (high-con dence).

Effects of Febuxostat on BMDMs i n vitro
We incubated BMDMs with IL-1β to model the gout pro-in ammatory state (4,14)(Fig.1A) 4,14 .Cells were treated with and without the selective XOI febuxostat, since allopurinol non-selectively inhibits both purine and pyrimidine metabolism 28 .We rst identi ed signi cantly altered proteins between untreated and IL-1β-treated macrophages (mock gouty in ammation group) in vitro, with 32 proteins found to be stats stats signi cantly altered in response to IL-1b (Fig. 1B, left).Next, we compared IL-1β-treated macrophages with febuxostat co-treated macrophages, which demonstrated suppression of multiple pro-in ammatory proteome changes triggered by IL-1β.Speci cally, we found 184 signi cantly altered (p < 0.05) proteins (Fig. 1B, right), of which 71 proteins were found to interact via STRING-DB analysis (con dence = 0.700) (Fig. 1C, right).

Effects of XOI-based ULT to target in gout patients
Validation of XOI treatment effects on purine metabolism and the serum metabolome We previously validated XOI treatment effects on purine metabolism in Cohort 1 25 .Here, we conducted untargeted metabolomics on sera of gout patients on effective serum treat to target ULT in Cohort 2 subjects treated with either febuxostat or allopurinol for 48 weeks.We annotated metabolite features using the Global Natural Products Social Molecular Networking (GNPS) platform.Since timepoint signi cantly in uenced our paired proteomic data set, we conducted paired binary comparisons between timepoints.Comparison of baseline (BL) and proteomics endpoint 48wks of ULT revealed several signi cantly altered metabolites, with some signi cantly changed by 24wks ULT (Supplemental Fig. 2A).Functional enrichment analysis of all identi ed metabolite features, using MS1 peak information, validated serum metabolome changes in purine and pyrimidine metabolism in Cohort 2 in this study.These ndings were associated with signi cant changes in multiple other pathways, including arachidonic acid metabolism, and most pronounced for linoleate metabolism at 24 and 48wks ULT (Supplemental Fig. 1B).The new ndings for Cohort 2 reinforced previously published effects of XOI treatment on the serum metabolome in gout patients of Cohort.

Effects of XOI treatment to urate target on the serum proteome
We performed quantitative proteomic analysis on patient serum samples to understand global serum proteome changes before and at 48wks XOI-based ULT.Experimental approach, patient demographics and changes in serum urate are summarized (Fig. 2A, Supplemental Fig. 1).Brie y, patient racial and ethnic backgrounds varied with cohort 1 patients identi ed as largely White and Black, and cohort 2 identi ed as predominantly White (Supplemental Fig. 1D and 1H).Additionally, we observed overall decrease in serum urate (sUA) levels after 48wks ULT and patient reported ares, but relatively stable Creactive protein (CRP) levels after ULT in both cohorts (Supplemental Fig. 1A-C & 1E-G).
Examining each cohort independently from Baseline (BL) to serum proteomics Endpoint (48 wks of ULT;EP), we found 21 and 49 signi cantly altered proteins (p < 0.05, Wilcoxon signed-ranks test) for Cohort 1 and 2, respectively.Interactome analysis through STRING-db, was accompanied by "pindropping" known gouty-in ammation markers, known to be below the mass spectrometry detection limits 29 , along with the signi cantly altered proteins from both cohorts.We identi ed 23 high con dence interacting proteins (Fig. 2B), which Gene Ontology enrichment analyses revealed to belong to 4 major categories: Innate immune response, humoral immune response, protein/peptide secretion, and posttranslation modi cation of proteins (Fig. 2C, Table 1).

Table 1
Interactome Proteins Proteins, denoted by their respective gene names, that are present in our protein interactome describing interactions between altered proteins at proteomics endpoint 48wks ULT (Fig. 2B).Gene names are annotated by cohort they were differentially abundant in, along with their known function and potential roles in gouty in ammation.* Denotes features whose statistical p-value was found to be < 0.10, all other features had a p-value < 0.05.We next sought to understand overlapping changes between our two independently sampled patient cohorts.To accomplish this, we rst identi ed all proteins identi ed in both cohorts and then subsequently strati ed these proteins to include only those proteins that changed similarly over the course of ULT treatment (baseline to proteomics endpoint).We found 277 overlapping protein identi cations between both independent cohorts.We subjected these proteins to interactome analysis, and observed 135 high con dence interacting proteins (Supplemental Table 1 & Fig. 2D).Moreover, we identi ed 70 proteins that were similarly altered at 48wks ULT (Supplemental Table 1 & Fig. 2D) in both cohorts.Enrichment analysis of the 70 similarly changed protein showed enrichment in innate or humoral gene ontology enrichment categories (Fig. 2E).Results showed rewiring of networked key in ammation mediators not detectable by conventional serum biomarker pro ling, including C8 cleavage products, VIM, PPBP/CXCL7, KRT16, TGFB1, IGF-I, and sCD44.These novel biomarkers of XOI ULT effects were clustered with central gout mediators including IL-1B, CXCL8, IL6, and C5, in a tight protein interactome.Results revealed a novel functionally important network of physically interacting serum proteins in gouty in ammation that was altered in response to ULT to target, here performed using XOI drugs.

XOI treatment to serum urate target effects on the PBMC Proteome
Last, to further characterize in vivo response to XOI-based ULT in gout, we isolated PBMCs from Cohort 1 patients.We identi ed 197 signi cantly altered proteins at 48wks ULT (p < 0.05, Fig. 3A), with 42 highcon dence (> 0.700) interacting proteins (Fig. 3B).Gene enrichment analysis found these proteins belonging largely to secretion, leukocyte, and neutrophil activation gene ontology pathways (Fig. 3C).
Moreover, the KRT protein ndings for serum proteins were further validated in the PBMC proteomics studies, as shown by their presence as signi cantly altered proteins in our PBMC proteomics.
We next sought to understand how patient metadata associated to the PBMC proteome.To accomplish this, we rst performed a metadata association analysis (Supplemental Fig. 2A) followed by correlation analysis between patient samples.Metadata association analysis through PERMANOVA analysis identi ed no signi cant in uences from sample metadata categories, such as suA or CRP levels, or cytokine levels from IL1B,IL6, and IL8 (Supplemental Fig. 2A).Spearman rank correlation analysis of patient PBMC proteome samples identi ed two distinct proteome groups (Supplemental Fig. 2A-B).To begin to understand proteomics features that drove this patient separation, we performed PERMANOVA and statistical analysis between both proteome groups 1(n = 5) and 2 (n = 14).We analyzed samples separated by timepoint and identi ed the top scored proteins at Baseline and 48wks of ULT (Fig. 3D).We identi ed overlapping protein drivers of separation at both timepoints, and interactome analysis of identi ed driver proteins at both timepoints along with "pin-dropped" gout proteins (Fig. 3E) found strong and high con dence (> 0.700) interactions between known gout mediators and top identi ed proteins, particularly MMP9 and other proteins identi ed at 48wks ULT.Hence, PBMC proteome analysis further teased apart XOI-based ULT effects in gout patients while highlighting anti-in ammatory effects.

Discussion
Gout requires a unique approach to arthritis targets and biomarkers of the response to XOI-based ULT, due to variable phenotypes, and weaving of urate homeostasis, comorbidities, and in ammatory arthritis [1][2][3][4][5]8 . Incontrast to the genetics of urate biology, genome-wide association studies have identi ed few genetic coding variants potentially involved in gouty arthritis 30,31 .Therefore, this biomarker study pro led the serum proteome of gout patient sera at 48wks sustained ULT to urate target, here using XOI, and with achievement of reduced are burden and serum urate in two independent cohorts.Speci c serum proteomics ndings at 48wks XOI-based treat to target ULT, in both cohorts studied, included decreased C8A and C8G chains, which play a major role in complement C5b-9 MAC assembly and activity that, along with C5a generation, contribute substantially to the in ammatory process in model gouty arthritis 15,16,32 .Paradoxically, we detected increase in serum of the NLRP3 in ammasome scaffolder and activation promoter VIM (vimentin) 33 , of interest because early increase in gout ares is seen in XOI-based ULT 9 , Increased serum sCD44 was noteworthy, since sCD44 inhibits macrophage phagocytosis of urate crystals and consequent NLRP3 in ammasome activation, by blocking crystal binding to transmembrane CD44 34 .
We also observed increase in serum of TGFB1, which promotes model gout are resolution by suppressing macrophage activation by crystals 35 .Conversely, IGF-I, which cross-talks with and can synergize with TGF-beta, was decreased in serum at 48wks ULT 36 .We detected decrease in serum of the phagocyte-recruiting chemokine PPBP/CXCL7 37 , and decreased lactoferrin, a neutrophil-released coactivator of the lubricin-degrading serine protease Cathepsin G 38 .That nding was of note, since Cathepsin G is a major degrader of lubricin, which functions as a substantial constitutive suppressor of gouty in ammation and urate production by synovial resident macrophages 39 .We also observed an increase in monocyte/macrophage-expressed keratin-related proteins (KRT9,14,16), further validated by Cohort 1 gout patient PBMC proteomics.KRT16 is implicated in monocyte to macrophage differentiation, and MMP-1 and innate immune responses to tissue damage in epithelia 40 .
Last, STRING-db analyses of signi cantly altered proteins from both cohorts revealed that the tight serum protein interactome network altered by XOI-based ULT encompassed a core group of central mediators of gouty in ammation (including IL-1B, CXCL8, IL6, C5) 4 .
Robustness of our ndings on effects of effective ULT on the serum protein interactome discovered here was buttressed by a group of parallel studies.First, in this context, previously published evidence in gout Cohort 1 that the ULT regimen altered the serum metabolome, and the serum lipidome in gout Cohorts 1 and 2, and effects of febuxostat on lipolysis in cultured adipocytes 25 .Moreover, the current study demonstrated that the serum metabolome was signi cantly altered for purine and pyrimidine metabolism in Cohort 2, associated with signi cant changes in multiple other pathways, most pronounced for linoleate metabolism at both 24wks and 48wks ULT.Second, analyses of the Cohort 1 proteome of gout patient PBMCs identi ed 42 high-con dence interacting proteins belonging largely to secretion, leukocyte, and neutrophil activation gene ontology pathways.The KRT ndings for serum proteins were validated in the PBMC proteome.In addition, we found strong and high con dence (> 0.700) interactions between known gout mediators and EFS identi ed proteins, particularly in the proteins identi ed at 48wks of ULT, including MMP9.Whereas no signi cant difference in MMP9 abundance levels was identi ed between BL and 48wks of ULT, further study would be needed to validate signi cance of differences between PBMC proteome groups 1 and 2. The collective results of PBMC proteome analysis further teased apart the effects of XOI-based ULT in gout, and highlighted antiin ammatory effects of XOI-based ULT on these leukocytes as a whole.
We employed in vitro studies that characterized effects of the selective XOI febuxostat on the proteome of cultured murine BMDMs stimulated by the major gouty in ammation driver IL-1b.Febuxostat suppressed multiple pro-in ammatory IL-1b-induced changes in the macrophage proteome.Analyses of gene ontology enrichment of proteins found in the macrophage protein interactome revealed that in vitro XOI treatment of activated BMDMs broadly reversed many pro-in ammatory responses.Notably, the most pronounced pathway changes were seen in classical and alternative pathway complement activation, which reinforced the impact of the ndings for XOI-treatment effects on C8A and C8G in the gout patient serum proteome.Febuxostat also altered lymphocyte-mediated immunity, brinolysis, and cytolysis gene ontology pathways in cultured macrophages in response to IL-1b.Our ndings in cultured macrophages and gout patient PBMCs were novel partly because previous studies have suggested that both hyperuricemia and urate crystals program elevated monocyte in ammatory responses in vitro and that hyperuricemia primes model gout in ammation in mice in vivo model gout [41][42][43] .
A pro-in ammatory serum proteome signature was recently characterized in asymptomatic hyperuricemia (AH) by targeted proteomics 44 .The approach used the Olink Target 96 In ammation Panel™ 44 , distinct from the unbiased mass spectrometry-based approach utilized in the current study.
The methodology employed dual recognition by oligonucleotide-labelled antibody probe pairs and DNAcoupled quantitative PCR, designed to detect speci c immunoregulatory proteins below mass spectrometry detection limits 44 .Upregulated serum immunoregulatory proteins in AH group included the mTOR effector 4E-BP1, IL-18R1, multiple growth factors, chemokines, and members of the IL-6 cytokine and TNF superfamily 44 .A Th17 cell signature, and increases in in ammation-dampening IL-10 and FGF21 also were identi ed 44 .Using the same targeted serum proteomics approach, a small sub-study of 13 subjects before and 3 months into successful XOI-based treat to target ULT revealed signi cant downregulation of LIF-R.CDCP1, IL-18, NT-3, IL10RB, CCL28, CCL11, and SLAMF1 44 .A second, recent study of the serum proteome in gout are, using the same targeted proteomics approach in two independent cohorts, identi ed four markers elevated during gout are compared to the treat to target phase and in-between are (intercritical) phase.These in ammation-mediating proteins were tumor necrosis factor superfamily 14 (TNFSF14), IL-6, colony-stimulating factor 1 and vascular endothelial growth factor A 45 .
The differentially detected proteins in both these referenced targeted proteomics studies 45 were predominantly cytokines and growth factors below the detection limits of our unbiased mass spectrometry serum proteomics approach.Therefore, the design, approach, and sample size of the current study were unique and provided distinct information on the molecular signature of XOI effects on hyperuricemia in gout.
Hyperuricemia increases blood monocyte population expansion in vivo in humans 42 , however, monocytes, and other mononuclear leukocytes, are heterogeneous, and can be recruited into diseased or challenged tissues, and one limitation in this study is that monocytes are normally only a small fraction (ie, ≤ 10%) of PBMCs 46 .PBMCs remain a source of highly informative biomarkers for acute and chronic in ammatory diseases, but also are highly heterogeneous 47 , buttressing the limitation of this study that PBMCs only were obtained at the Cohort 1 site.This trial did not have a placebo, and the clinical trial did not include a uricosuric treatment arm, with the infrequently employed and frequently contraindicated USA-approved drug probenecid, to isolate effects due to serum urate-lowering without XOI.We did not exclude subjects with are at onset of study enrollment and rst and nal blood sampling, or CRP higher than 2 mg/L, but it is noted that such CRP elevation was present at blood sampling in less than a handful of subjects.Also, we did not study gout patient controls from the same clinical trial that failed to achieve serum urate target.However, the proportion of such subjects overall in the VA STOP GOUT trial was low (ie, ~ 20%) 19 , and all those subjects were considered at least partially treated since they received XOIbased ULT.
In conclusion, a novel, functionally important network of physically interacting proteins in gouty in ammation emerged in association with response to sustained XOI-based ULT that effectively reduced gout are burden.Potential clinical signi cance of the results, especially for data from the clinical trial, included that the treat to target ULT regimen is associated with early increase in are activity before gout ares eventually decrease 9 .Moreover, the current study provides further support for the use of serum proteomics, including biomarker approaches highlighting the complement pathway and the in ammatory secretome, to help identify responsiveness of gouty in ammation to ULT pharmacotherapy, and for characterization and prognosis of different clinical phenotypes in gout 39,44,48 .C. Gene ontology enrichment analysis of signi cantly altered proteins from both proteomic cohorts.

Abbreviations
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 Figures