Diluk R. W. Kannangara

Understanding the dose–response relationship of allopurinol: predicting the optimal dosage

AIMS The aim of the study was to identify and quantify factors that control the plasma concentrations of urate during allopurinol treatment and to predict optimal doses of allopurinol. METHODS Plasma concentrations of urate and creatinine (112 samples, 46 patients) before and during treatment with various doses of allopurinol (50-600 mg daily) were monitored. Non-linear and multiple linear regression equations were used to examine the relationships between allopurinol dose (D), creatinine clearance (CLcr) and plasma concentrations of urate before (UP) and during treatment with allopurinol (UT). RESULTS Plasma concentrations of urate achieved during allopurinol therapy were dependent on the daily dose of allopurinol and the plasma concentration of urate pre-treatment. The non-linear equation: UT = (1 - D/(ID50 + D)) × (UP - UR) + UR , fitted the data well (r(2) = 0.74, P < 0.0001). The parameters and their best fit values were: daily dose of allopurinol reducing the inhibitable plasma urate by 50% (ID50 = 226 mg, 95% CI 167, 303 mg), apparent resistant plasma urate (UR = 0.20 mmol l(-1), 95 % CI 0.14, 0.25 mmol l(-1)). Incorporation of CLcr did not significantly improve the fit (P = 0.09). CONCLUSIONS A high baseline plasma urate concentration requires a high dose of allopurinol to reduce plasma urate below recommended concentrations. This dose is dependent on only the pre-treatment plasma urate concentration and is not influenced by CLcr .

Multiplicative interaction of functional inflammasome genetic variants in determining the risk of gout.

IntroductionThe acute gout flare results from a localised self-limiting innate immune response to monosodium urate (MSU) crystals deposited in joints in hyperuricaemic individuals. Activation of the caspase recruitment domain-containing protein 8 (CARD8) NOD-like receptor pyrin-containing 3 (NLRP3) inflammasome by MSU crystals and production of mature interleukin-1β (IL-1β) is central to acute gouty arthritis. However very little is known about genetic control of the innate immune response involved in acute gouty arthritis. Therefore our aim was to test functional single nucleotide polymorphism (SNP) variants in the toll-like receptor (TLR)-inflammasome-IL-1β axis for association with gout.Methods1,494 gout cases of European and 863 gout cases of New Zealand (NZ) Polynesian (Māori and Pacific Island) ancestry were included. Gout was diagnosed by the 1977 ARA gout classification criteria. There were 1,030 Polynesian controls and 10,942 European controls including from the publicly-available Atherosclerosis Risk in Communities (ARIC) and Framingham Heart (FHS) studies. The ten SNPs were either genotyped by Sequenom MassArray or by Affymetrix SNP array or imputed in the ARIC and FHS datasets. Allelic association was done by logistic regression adjusting by age and sex with European and Polynesian data combined by meta-analysis. Sample sets were pooled for multiplicative interaction analysis, which was also adjusted by sample set.ResultsEleven SNPs were tested in the TLR2, CD14, IL1B, CARD8, NLRP3, MYD88, P2RX7, DAPK1 and TNXIP genes. Nominally significant (P < 0.05) associations with gout were detected at CARD8 rs2043211 (OR = 1.12, P = 0.007), IL1B rs1143623 (OR = 1.10, P = 0.020) and CD14 rs2569190 (OR = 1.08; P = 0.036). There was significant multiplicative interaction between CARD8 and IL1B (P = 0.005), with the IL1B risk genotype amplifying the risk effect of CARD8.ConclusionThere is evidence for association of gout with functional variants in CARD8, IL1B and CD14. The gout-associated allele of IL1B increases expression of IL-1β – the multiplicative interaction with CARD8 would be consistent with a synergy of greater inflammasome activity (resulting from reduced CARD8) combined with higher levels of pre-IL-1β expression leading to increased production of mature IL-1β in gout.

Fractional clearance of urate: validation of measurement in spot-urine samples in healthy subjects and gouty patients

IntroductionHyperuricemia is the greatest risk factor for gout and is caused by an overproduction and/or inefficient renal clearance of urate. The fractional renal clearance of urate (FCU, renal clearance of urate/renal clearance of creatinine) has been proposed as a tool to identify subjects who manifest inefficient clearance of urate. The aim of the present studies was to validate the measurement of FCU by using spot-urine samples as a reliable indicator of the efficiency of the kidney to remove urate and to explore its distribution in healthy subjects and gouty patients.MethodsTimed (spot, 2-hour, 4-hour, 6-hour, 12-hour, and 24-hour) urine collections were used to derive FCU in 12 healthy subjects. FCUs from spot-urine samples were then determined in 13 healthy subjects twice a day, repeated on 3 nonconsecutive days. The effect of allopurinol, probenecid, and the combination on FCU was explored in 11 healthy subjects. FCU was determined in 36 patients with gout being treated with allopurinol. The distribution of FCU was examined in 118 healthy subjects and compared with that from the 36 patients with gout.ResultsNo substantive or statistically significant differences were observed between the FCUs derived from spot and 24-hour urine collections. Coefficients of variation (CVs) were both 28%. No significant variation in the spot FCU was obtained either within or between days, with mean intrasubject CV of 16.4%. FCU increased with probenecid (P < 0.05), whereas allopurinol did not change the FCU in healthy or gouty subjects. FCUs of patients with gout were lower than the FCUs of healthy subjects (4.8% versus 6.9%; P < 0.0001).ConclusionsThe present studies indicate that the spot-FCU is a convenient, valid, and reliable indicator of the efficiency of the kidney in removing urate from the blood and thus from tissues. Spot-FCU determinations may provide useful correlates in studies investigating molecular mechanisms underpinning the observed range of efficiencies of the kidneys in clearing urate from the blood.Trial RegistrationACTRN12611000743965

The toll-like receptor 4 (TLR4) variant rs2149356 and risk of gout in European and polynesian sample sets

Deposition of crystallized monosodium urate (MSU) in joints as a result of hyperuricemia is a central risk factor for gout. However other factors must exist that control the progression from hyperuricaemia to gout. A previous genetic association study has implicated the toll-like receptor 4 (TLR4) which activates the NLRP3 inflammasome via the nuclear factor-κB signaling pathway upon stimulation by MSU crystals. The T-allele of single nucleotide polymorphism rs2149356 in TLR4 is a risk factor associated with gout in a Chinese study. Our aim was to replicate this observation in participants of European and New Zealand Polynesian (Māori and Pacific) ancestry. A total of 2250 clinically-ascertained prevalent gout cases and 13925 controls were used. Non-clinically-ascertained incident gout cases and controls from the Health Professional Follow-up (HPFS) and Nurses Health Studies (NHS) were also used. Genotypes were derived from genome-wide genotype data or directly obtained using Taqman. Logistic regression analysis was done including age, sex, diuretic exposure and ancestry as covariates as appropriate. The T-allele increased the risk of gout in the clinically-ascertained European samples (OR = 1.12, P = 0.012) and decreased the risk of gout in Polynesians (OR = 0.80, P = 0.011). There was no evidence for association in the HPFS or NHS sample sets. In conclusion TLR4 SNP rs2143956 associates with gout risk in prevalent clinically-ascertained gout in Europeans, in a direction consistent with previously published results in Han Chinese. However, with an opposite direction of association in Polynesians and no evidence for association in a non-clinically-ascertained incident gout cohort this variant should be analysed in other international gout genetic data sets to determine if there is genuine evidence for association.

Hyperuricaemia: contributions of urate transporter ABCG2 and the fractional renal clearance of urate

Objective To investigate the contributions towards hyperuricaemia of known risk factors, focusing on fractional (renal) clearance of urate (FCU) and variation in the ATP-binding cassette transporter, sub-family G 2 (ABCG2) gene. Methods The contributions of age, sex, ancestry, Q141K genotype for ABCG2, FCU, sugar-sweetened beverage and alcohol consumption, metabolic syndrome disorders and measures of renal function to the risk of hyperuricaemia were evaluated by comparing hyperuricaemic (serum urate≥0.42 mmol/L, n=448) with normouricaemic (serum urate<0.42 mmol/L, n=344) participants using stepwise logistic regression. Model performance was evaluated using the area under the receiver operator characteristic curve (AUROC). Results ABCG2 genotype, FCU, male sex, body mass index, serum triglyceride concentrations, estimated glomerular filtration rate and consumption of alcohol were the best predictors of hyperuricaemia (AUROC 0.90, 81% accuracy). Homozygosity in the 141K variant for ABCG2 conferred an adjusted OR of 10.5 for hyperuricaemia (95% CI 2.4 to 46.2). For each 1% decrease of FCU, the adjusted OR increased by 51% (OR 1.51, 95% CI 1.37 to 1.66). There was no association between ABCG2 genotype and FCU (r=0.02, p=0.83). Conclusions The ABCG2 141K variant and the FCU contribute strongly but independently to hyperuricaemia. These findings provide further evidence for a significant contribution of ABCG2 to extra-renal (gut) clearance of urate.

Effect of xanthine oxidase inhibitors on the renal clearance of uric acid and creatinine

To the Editor: We read with interest the paper by Ma et al. [1] on uratelowering therapies and specifically, their effects on the renal clearance of uric acid (CUA). Ma et al. reported that xanthine-oxidase inhibition (XOI), as achieved by allopurinol and febuxostat, promotes CUA and, in parallel, increases the renal clearance of creatinine (CCR). There are several aspects of the results of Ma et al. which we would like to comment on. Firstly, it should be noted that the mean changes in CCR and CUA observed by Ma et al. are small (CCR, 89.1 to 92.3 mL/min/1.73 m and CUA, 2.87 to 3.09 mL/min/ 1.73 m). The influence of allopurinol on renal function is inconsistent in the literature. A systematic review and meta-analysis by Bose et al. [2] found no significant effect of allopurinol on GFR (mean difference from placebo, 3.1 mL/min/1.73 m2, 95 % CI: −0.9–7.1, p= 0.13), although the effect size found in the meta-analysis is similar to that found in the study by Ma et al. [1, 2]. However, Bose et al. considered that allopurinol may slow the progression of chronic renal impairment [2]. Secondly, a confounding aspect of Ma et al.’s study is that all subjects in this study were given sodium bicarbonate (600 mg/day) to alkalize the urine. Alkalization of urine has been reported to increase the renal clearance of uric acid [3, 4]. Whether sodium bicarbonate was administered before the therapy with XOIs commenced must be answered in order to demonstrate any effect of ULT on the renal clearance of uric acid. Thirdly, Ma et al. observed a non-significant decrease in the fractional clearance of urate (FCU, CUA/CCR) in patients taking XOIs. The FCU is a much more reliable indicator of the efficiency of the kidney to clear uric acid [5] than CUA alone. However, Ma et al. found the FCU was maintained in patients who reached the treatment target serum UA of <6 mg/dL (0.36 mmol/L) but decreased in patients who did not achieve the target. Our research indicates that the patients who do not reach target are more likely to have a higher baseline UA [6]. Consistent with our findings, the target-failure patients in Ma et al. had higher baseline UA concentrations than those who reached target (baseline mean UA 10.3 vs 9.4 mg/dL, p< 0.05). It would have been of interest to relate the contrasts in CUA, CCR, and FCU values directly to the baseline serum UA. Finally, experimental methods are not ideal. Ma et al. used a 24-hour urine collection to quantify various indices of the renal handling of UA. The 24-hour urine collection, while generally deemed the Bgold-standard^ for renal function analysis, is highly prone to error [7]. This is because it is difficult for ambulatory patients to time the collection accurately and to remember to collect all voids of urine. To determine the effect of XOI inhibition on renal handling of UA, we agree that further study is needed. It would be important to take account of urine pH and baseline plasma urate and to match the groups on and off XOI for these variables.

Oxypurinol, allopurinol and allopurinol-1-riboside in plasma following an acute overdose of allopurinol in a patient with advanced chronic kidney disease

Allopurinol is used to prevent gout. It is metabolized by xanthine oxidoreductase to oxypurinol, itself a xanthine oxidoreductase inhibitor, thereby reducing urate formation. It may also be metabolized by aldehyde oxidase to oxypurinol [1]. Another metabolite of allopurinol is allopurinol-1-riboside, formed directly by the enzyme purine nucleoside phosphorylase or indirectly through the dephosphorylation of allopurinol-1-ribotide [2]. An acute overdose of allopurinol can have contrasting outcomes. Severe reactions were reported in two cases [3], [4], while no reaction was reported in one case [5]. Allopurinol and oxypurinol are renally excreted, so renal impairment would reduce its clearance and possibly potentiate acute toxicity. However, the effect of renal impairment on clinical outcomes following an acute overdose has not been described. We report a case of allopurinol overdose in a patient with advanced chronic kidney disease. The case is of interest because accumulation of oxypurinol during routine dosing in renal failure has been considered a risk factor for severe allopurinol toxicity, including Stevens–Johnson syndrome and toxic epidermal necrolysis [6], which have mortalities of 30–50%. A 36-year-old transgender woman presented to hospital 30 min after ingesting 10 g allopurinol. The patient selected allopurinol because Internet information indicated low toxicity in overdose. There were no abnormal clinical signs on presentation and no adverse sequelae. She was discharged within 24 h. The medical history included an overdose of allopurinol 2 years earlier (oxypurinol concentration 44 mg l−1; time after allopurinol ingestion unknown), from which she also suffered no adverse effects. Her medical history also included gout (20 years), hypertension, hypercholesterolaemia and advanced chronic kidney disease [creatinine 493 µm; estimated glomerular filtration rate of 10–12 ml min−1 (1.73 m)−2] due to focal segmental glomerulosclerosis. The patient was reportedly taking allopurinol 100 mg day−1 prior to the overdose. Other medications included perindopril and rosuvastatin, as well as synthetic oestrogens. Urine screening was positive for opiates, benzodiazepines and amphetamines. She consented to return over the next week for additional blood tests. Allopurinol, oxypurinol and allopurinol-1-riboside concentrations were determined by high-performance liquid chromatography. The assay is validated for oxypurinol [7], and standard curves for all analytes were linear (r2 > 0.999). The identity and purity of each analyte was confirmed by comparison of retention times against standards and by scanning UV spectrophotometry of the peaks. Apparent elimination half-lives (t1/2) were estimated by nonlinear regression, assuming a one-compartment model. The t1/2 of oxypurinol was 65 h, considerably longer than found in healthy subjects (approximately 24 h) [1]. The longer t1/2 is attributed to the impaired renal function of this patient, as oxypurinol is renally excreted [1]. The peak plasma concentration (Cmax) of oxypurinol in this patient was 106 mg l−1. The apparent elimination t1/2 of allopurinol was 4.4 h. Again, this is longer than the t1/2 (1.2 ± 0.3 h) in healthy subjects [1], possibly due to saturation of xanthine oxidoreductase. The patients poor renal function may also have contributed to slower elimination, although renal clearance usually accounts for only approximately 10% of an oral dose of allopurinol [1]. The Cmax of allopurinol following a therapeutic dose of allopurinol (300 mg) is about 3 mg l−1,[1]. By contrast, the Cmax in this patient was much higher, at 29 mg l−1 (Figure 1). Figure 1 Time courses of allopurinol, oxypurinol and allopurinol-1-riboside after an overdose of allopurinol (10 g). Oxypurinol (); Allopurinol (); Allopurinol-1-riboside () Approximately 10% of allopurinol is excreted as allopurinol-1-riboside [1]. The t1/2 of the allopurinol-1- riboside is approximately 3 h following dosage of the riboside itself [8]. We found substantial concentrations of the riboside (up to 19 mg l−1). Given its high aqueous solubility, its renal excretion may be delayed in chronic kidney disease. One of the three previously reported cases of acute allopurinol overdose died from hepatic centrilobular necrosis. The dose of allopurinol was unknown, but the plasma concentration was recorded as 231 mg l−1, which is much greater than the value for our patient (29 mg l−1). The assay details were, however, not presented, and it is unclear whether oxypurinol or allopurinol was measured. Other causes of the hepatotoxicity may have been concurrent use of indomethacin and captopril [3]. Another patient who ingested 20 g allopurinol developed a variety of toxic effects, including hepatitis, leukopaenia, fever and diarrhoea but recovered with supportive care [4]. By contrast, in a third case, no adverse effects following the ingestion of approximately 20 g allopurinol were reported. The oxypurinol concentration for this latter subject was approximately 43 mg l−1 at approximately 12 h and the elimination half-life was 26 h [5]. By comparison, in our patient who purportedly took 10 g allopurinol, the estimated plasma concentration of oxypurinol at 12 h was approximately 100 mg l−1 (Figure 1). It is not known why there was no clinical toxicity. In the two cases where toxicity was reported, involvement of other drugs may have been contributory. The relationship between plasma concentrations of oxypurinol and adverse reactions is still unclear. Further investigation is required to clarify these observations. In summary, it is unclear whether or not adverse effects from acute overdoses of allopurinol are expected. Despite high concentrations of allopurinol and metabolites, our patient was largely unaffected by the overdose. Renal impairment appears to have contributed to the delayed elimination of allopurinol and its metabolites.

Understanding and improving the use of allopurinol in a teaching hospital

An emphasis on renal function in deciding maintenance doses of allopurinol to prevent allopurinol hypersensitivity has resulted in ineffective prevention of attacks of gout. New therapeutic guidelines for gout have shifted the focus back to titrating maintenance doses to reach a serum uric acid (SUA) concentration target of ≤0.36 mmol/L.

THU0493 Association of the Toll-Like Receptor 4 (TLR4) Gene with Gout

Background Gout results from innate immune response to monosodium urate (MSU) crystals that form when serum urate is elevated. Identification of genetic risk factors for hyperuricemia and the MSU immune response is therefore important for insight into the etiology of gout. Whilst genome-wide association studies have provided significant insights into the causes of hyperuricemia there are no confirmed loci for non-serum urate pathways in gout. Recently association of the rs2149356 variant in the TLR4 locus with gout was reported in a Chinese sample set (odds ratio TT genotype =1.88, P=8x10–5)1. TLR4 triggers innate immune response to endogenous ligands, including MSU crystals2. Objectives To test rs2149356 for association in European and New Zealand (NZ) Polynesian gout case-control sample sets. Methods All gout cases were clinically ascertained according to the American Rheumatism Association criteria. European cases (n=1606) were recruited from New Zealand (n=599), by the Eurogout consortium within the European Crystal Network (n=784) and by the Arthritis Genomics Recruitment Initiative in Australasia (AGRIA; n=223). European non-gouty controls (n=8066) were recruited from NZ (n=875) and sourced from the Atherosclerosis Risk in Communities (n=4144) and Framingham Heart (n=3047) studies. There were 872 New Zealand Maori and Pacific Island (Polynesian) cases and 1088 controls. Genotyping was done by Taqman and statistical analysis by STATA. Results Using unstratified controls the T allele, but not the TT genotype, was associated with gout in Europeans (ORTallele=1.09, P=0.05; ORTTgenotype=1.15, P=0.13). There was no evidence for association in Polynesians (ORTallele=0.90, P=0.12; ORTTgenotype=0.88, P=0.31). However, comparison of cases to hyperuricemic controls strengthened evidence for association with gout in Europeans (ORTallele=1.18, P=0.004; ORTTgenotype=1.38, P=0.017), but made no difference in Polynesians (ORTallele=, P=0.30; ORTTgenotype=0.87, P=0.47). Conclusions The previous report of association of TLR4 with gout in Chinese was replicated in Europeans but not Polynesians. Strengthening of association using hyperuricemic controls is consistent with a role for this locus in gouty inflammation in the presence of hyperuricemia. Subject to further replication, TLR4 represents the first non-serum urate genetic risk locus identified in gout, and provides support for a role of TLR4 in etiology. References Qing et al. PLoS One 2013;5:e64845. Liu-Bryan et al. Arthritis Rheum 2005;52:2936 Disclosure of Interest : None declared DOI 10.1136/annrheumdis-2014-eular.4781

An audit of a therapeutic drug monitoring service for allopurinol therapy.

Background: Oxypurinol, the active metabolite of allopurinol, is the major determinant of the hypouricemic effect of allopurinol. Monitoring oxypurinol concentrations is undertaken to determine adherence to therapy, to investigate reasons for continuing attacks of acute gout and/or insufficiently low plasma urate concentrations despite allopurinol treatment, and to assess the risk of allopurinol hypersensitivity, an adverse effect that has been putatively associated with elevated plasma oxypurinol concentrations. Methods: An audit of request forms requesting plasma oxypurinol concentration measurements received by the pathology service (SydPath) at St Vincents Hospital, Darlinghurst, Sydney was undertaken for the 7-year period January 2005–December 2011. Patient demographics, biochemical data, including plasma creatinine and uric acid concentrations, comorbidities, and concomitant medications were recorded. Results: There were 412 requests for determination of an oxypurinol concentration. On 48% of occasions, the time of allopurinol dosing was recorded, while just 79 (19%) blood samples were collected 6–9 hours postdosing, the time window used to establish the therapeutic range for oxypurinol. For these optimally interpretable concentrations, 32 (8%) were within the putative therapeutic range (5–15 mg/L), while 5 (1%) were below and 41 (10%) above this range. The daily dose of allopurinol was documented on only one-third of the request forms. Individually, plasma urate and creatinine concentrations were requested concomitantly with plasma oxypurinol concentrations in 66% and 58% of the cases, respectively; while plasma oxypurinol, urate, and creatinine concentrations were requested concomitantly in 49% of the cases. Conclusions: Requesting clinicians and blood specimen collectors often fail to provide relevant information (dose, times of last dose, and blood sample collection) to allow the most useful interpretation of oxypurinol concentrations. Concomitant plasma urate and creatinine concentrations should be requested to allow more complete interpretation of the data.