The lack of association between the burden of monosodium urate crystals assessed with dual-energy computed tomography or ultrasonography with cardiovascular risk in the commonly high-risk gout patient

The lack of association between the burden of monosodium urate crystals assessed with dual-energy... Background: Gout is associated with higher cardiovascular risk that increases with disease severity. The objective of this study was to explore the relationship between the extent of monosodium urate (MSU) crystal deposition, assessed with ultrasonography (US) and dual-energy computed tomography (DECT), and cardiovascular risk. Methods: Gout patients were included in this cross-sectional study to undergo DECT scans for the assessment of total MSU volume deposition in the knees and feet, and US to evaluate the number of joints with the double contour (DC) sign. Participants were screened for traditional cardiovascular risk factors, and levels of the American College of Cardiology (ACC)/American Heart Association (AHA) 10-year risk for heart disease or stroke were calculated. The primary endpoint was the Spearman correlation coefficient ρ between DECT MSU volume and cardiovascular risk. Results: A total of 42 patients were included; they were predominantly male (40/42) and aged 63.0 ± 13.2 years. Overall, 28/42 patients presented with the metabolic syndrome and the average 10-year coronary event or stroke risk according to the ACC/AHA (n = 33) was 21 ± 15%. Correlations between DECT volumes of MSU deposits in the knees, feet, and knees + feet and cardiovascular risk according to the ACC/AHA were very poor, with ρ = 0.18, −0.01, and 0.13, respectively. The was no correlation between the number of joints with the DC sign and cardiovascular risk (ρ = −0.07). DECT MSU deposit volume was similar in patients with and without metabolic syndrome (p = 0.29). Conclusions: The extent of MSU burden does not increase the estimated risk of cardiovascular events in gout patients. Keywords: Dual-energy computed tomography, Ultrasonography, Gout, Cardiovascular risk, Triglycerides * Correspondence: tristan.pascart@hotmail.fr Department of Rheumatology, Lille Catholic Hospitals, University of Lille, F-59160 Lomme, France EA 4490, PMOI, Physiopathologie des Maladies Osseuses Inflammatoires, University of Lille, F-59000 Lille, France Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Pascart et al. Arthritis Research & Therapy (2018) 20:97 Page 2 of 7 Background and physical examination (including measures of body Gout is the result of an inflammatory response to mono- mass index (BMI) and arterial blood pressure (BP)). La- sodium urate (MSU) crystal deposition following pro- boratory testing of SU levels, lipid levels, blood glucose, longed hyperuricemia [1]. The association of gout with and the estimated glomerular filtration rate (eGFR) increased cardiovascular risk is now fully recognized, but measured by CKD-EPI or MDRD was to be performed mechanisms linking the two remain unclear [2–4]. Car- within the 2 weeks of US and DECT examinations. diovascular risk in gout seems to increase with disease severity, the presence of clinical tophi, and serum urate Cardiovascular risk assessment and the metabolic (SU) levels [5]. It has been hypothesized that a greater syndrome urate load could explain this increased cardiovascular Traditional cardiovascular risk factors were systematic- mortality [5]. Systematic evaluation of the cardiovascular ally assessed: BP, BMI, blood glucose, total cholesterol, risk of gout patients at the time of the diagnosis revealed high-density lipoprotein (HDL) cholesterol, calculated that a majority of patients are classified as having a high low-density lipoprotein (LDL) cholesterol, triglycerides, cardiovascular risk [6]. In non-gout patients, SU levels and smoking status. Cardiovascular risk was then calcu- may be associated with higher cardiovascular risk scores lated using the American College of Cardiology (ACC)/ but causality of hyperuricemia on cardiovascular comor- American Heart Association (AHA) guidelines [13], the bidities and events, and the metabolic syndrome, re- Framingham general 10-year cardiovascular risk factors mains uncertain [3, 7]. Furthermore, the association [14], and the Framingham 10-year risk of coronary dis- between MSU crystal burden and traditional cardiovas- ease [15]. These scores could not be calculated for pa- cular risk factors needs to be studied. Were they to be tients whoseage wasoutside therespectiverange of correlated, quantifying MSU deposition could help iden- applicability and for participants with a prior history of tify gout patients at high cardiovascular risk. coronary heart disease, peripheral arterial disease, and Ultrasonography (US) and dual-energy computed tom- stroke. The metabolic syndrome was defined by the ography (DECT) are two imaging techniques that can presence of three out of five items among the following: visualize and provide a quantification of the MSU bur- obesity (BMI > 30 kg/m in the absence of available waist den [8]. DECT uses two x-ray beams with two different circumference measurements), elevated BP (systolic energies allowing us to distinguish between urate and BP ≥ 130 mmHg or diastolic BP ≥ 85 mmHg or on- calcium in soft tissues surrounding bone when the vol- going antihypertensive therapy), elevated triglycerides ume of deposits exceeds 0.01 cm [9, 10]. US, on the (≥ 15 mg/dL or on-going treatment), low HDL choles- other hand, can identify intra-articular cartilage MSU terol (≤ 40 mg/dL in men and ≤ 50 mg/dL in women deposition appearing as a double contour (DC) sign or on-going treatment), and hyperglycemia (≥ 100 mg/dL which disappears during urate depletion [11]. Both tech- or drug treatment for elevated blood glucose) [16]. niques can quantify tophi volume but do not provide the same measurements [8]. US examination The main objective of this study was to explore the re- Examinations were performed by one of four trained lationship between the extent of MSU deposition, musculoskeletal radiologists (JFB, NN, BC, or JL) on an assessed with US and DECT, and cardiovascular risk Applio 400 US machine (Toshiba Medical Systems, assessment. Tochigi, Japan). High-frequency probes were used: a 12-Mhz probe for knee examination and an 18-MHz Methods probe for ankle and foot examination. US examination Patients for the DC sign was performed on the femoro-patellar Consecutive patients with a diagnosis of gout accord- joints, talo-crural joints, and first metatarsophalangeal ing to the American College of Rheumatology (ACR)/ joints [17]. European League Against Rheumatism (EULAR) 2015 criteria [12] were prospectively recruited to undergo a CT data acquisition and image reconstruction quantification of urate deposition in the knees and feet All scans were performed using a single-source CT using US and DECT [8], and an assessment of their (Somatom Definition Edge; Siemens, Erlangen, Germany). cardiovascular risk. The study was approved by the in- The patients were positioned feet first in a supine position. stitutional review board of the Lille Catholic Hospitals Knees and feet were scanned axially in two separate acqui- and all participants provided informed consent before sitions performed consecutively on the same day. All scans inclusion into the study. were performed with the same image protocol, acquisition At the initial clinical visit, the following were recorded: at 128 × 0.6 mm, and pitch of 0.7. For each body part, two demographic details, comorbid disorders (particularly prior scans were acquired with tube potentials of 80 kV and major cardiovascular events), gout history, medications, 140 kV. Depending on the scanned body region, quality Pascart et al. Arthritis Research & Therapy (2018) 20:97 Page 3 of 7 reference tube currents ranged between 62 and 260 mAs. Table 1 Population characteristics Automated attenuation-based tube current modulation Characteristic was used in all examinations. Demographics Axial images with soft (B30f) and bone (B70f) convo- Male (n (%)) 40 (95.2%) lution kernels were reconstructed with a 1-mm slice Age (years) 63 ± 13.2 thickness and an increment of 1 mm. DECT postproces- Gout duration (years) 7.9 ± 9.6 sing was performed by the radiologists with dedicated Familial gout (n (%)) 7 (16.7%) software (syngo.via VB10B, syngo Dual Energy Gout; Siemens), following the parameters described else- Number of flares per year 4.1 ± 6.6 where [18]: UH threshold, 150; iodine ratio, 1.4; mater- Alcohol consumption (g/day) 15 ± 20.7 ial definition ratio, 1.25; resolution, 4; air distance, 5; Creatinine clearance (ml/min) 80.0 ± 31.1 bone distance, 10. Two kinds of images were recon- Cardiovascular risk factors structed for each body part. First, volume-rendered Body mass index (kg/m ) 30.2 ± 5.7 three-dimensional (3D) images in which urate crystal Total cholesterol (mg/dL) 177 ± 63 deposits coded in green were reconstructed with a bone tissue convolution kernel (B70f). These images HDL cholesterol (mg/dL) 44 ± 13 allowed a straightforward overview of MSU deposits. LDL cholesterol (mg/dL) 97 ± 43 Second, multiplanar reformations associating images Triglycerides (mg/dL) 207 ± 393 reconstructed with a soft tissue kernel (B30f) and col- Systolic blood pressure (mmHg) 132.8 ± 13.7 ored images were reconstructed. The aspect of the Diastolic blood pressure (mmHg) 77 ± 9.9 final fusion images could be changed by modulating Smoker (n (%)) 6 (14.3%) the relative percentages of the morphological and col- ored images from 0 to 100% with a slider. Metabolic syndrome (n (%)) 28 (66.7%) Cardiovascular comorbidities Statistical analysis Coronary heart disease (n (%)) 6 (14.3%) Statistical analysis was performed using the R software Peripheral arterial disease (n (%)) 3 (7.1%) (version 3.4.2). Quantitative variables are expressed as Stroke (n (%)) 3 (7.1%) mean and standard deviation, and qualitative variables Diabetes mellitus (n (%)) 15 (35.7%) as number and percentage. Two-by-two correlations of quantitative variables were Cardiovascular risk assessment assessed by the Spearman correlation coefficient given ACC/AHA 10-year risk (%) 21 ± 14 the absence of normal distribution of values. Tests for Framingham 10-year general cardiovascular risk (%) 22 ± 14 nullity of coefficients were performed. Framingham 10-year coronary risk (%) 15 ± 11 DECT volumes of urate deposition, the number of Urate burden joints with the DC, and SU levels were compared Serum urate (mg/dL) 8.1 ± 2.3 between the groups of patients presenting with and without the metabolic syndrome using the Mann- Subcutaneous (clinical) tophi (n (%)) 12 (28.6%) Whitney-Wilcoxon test as data were not normal. Ultrasound tophus (n (%)) 29 (69%) The significance level was set at 5%. 3 Ultrasound tophus volume (cm ) 1.1 ± 1.4 The primary endpoint was the Spearman correlation At least one joint with the double contour sign 41 (97.6%) coefficient ρ between DECT MSU volume deposited on (n (%)) the feet and cardiovascular risk. DECT MSU volume knees (cm )(n = 39) 1.9 ± 4.6 DECT MSU volume feet (cm )(n = 41) 2.7 ± 6.7 Results DECT MSU volume knees + feet (cm )(n = 38) 4.7 ± 10.8 0f the 50 patients included, eight were excluded since Ongoing drugs lipid and glucose levels were not collected. The remaining 42 patients included were predominantly Diuretics (n (%)) 11 (26.2%) male (40/42) and aged 63.0 ± 13.2 years. Patient charac- Antidiabetic treatment (n (%)) 15 (35.7%) teristics are described in Table 1. Of these 42 patients, Hypolipidemic treatment (n (%)) 16 (38.1%) 33 had no prior coronary heart disease, peripheral Treatment for high blood pressure (n (%)) 25 (59.5%) arterial disease, or stroke, and therefore could have their ACC/AHA American College of Cardiology/American Heart Association, cardiovascular risk scores calculated. DECT dual-energy computed tomography, HDL high-density lipoprotein, Overall, 29/42 had at least one US tophus of 1.1 ± LDL low-density lipoprotein, MSU monosodium urate 1.4 cm . Patients presented with 2.2 ± 1.0 joints Pascart et al. Arthritis Research & Therapy (2018) 20:97 Page 4 of 7 Fig. 1 Imaging of monosodium urate crystal deposition. a Double contour sign of intra-articular cartilage deposition of the femoro-patellar joint 3 3 (arrows), (b) large (volume 5.39 cm ) and (c) small (volume 0.02 cm ) soft tissue volumes of deposits on the feet visualized with dual-energy computed tomography with the DC sign out of 6 (median 2, interquartile Discussion range (IQR) 2–3). The volume of MSU deposits with This study found no, or only very weak, correlation be- 3 3 DECT was 2.7 ± 6.7 cm for the feet (median 0.7 cm , tween levels of overall cardiovascular risk and the extent IQR 0.1–2.2) and 1.9 ± 4.6 cm for the knees of urate burden in the knees and feet measured using (median 0.2 cm ,range 0–1.2) (Fig. 1). Correlations DECT and US. Urate burden was not associated with the between SU levels and DECT volumes of MSU deposits of prevalence of the metabolic syndrome. Some weak cor- the knees, feet, and knees + feet were weak (ρ = 0.28, 0.20, relations were established between individual compo- and 0.23, respectively). Overall, 28/42 patients presented nents of cardiovascular risk, notably serum triglyceride with the metabolic syndrome and the average 10-year levels. coronary event or stroke risk according to the ACC/AHA Correlations between urate burden and cardiovascular (n = 33) was high (21 ± 15%). risk were particularly weak when considering measure- Correlations between DECT volumes of MSU de- ments of the feet only. These results are in direct con- posits in the knees, feet, and knees + feet and cardio- trast with the conclusions recently made by Lee et al. vascular risk according to the ACC/AHA were very from their retrospective study [19], considering that poor, with ρ =0.18, −0.01, and 0.13, respectively (Fig. 2), there was a correlation between total DECT urate vol- and did not differ significantly from zero (p >0.05). The ume of the feet and both the 10-year Framingham risk was no correlation between the number of joints with the for cardiovascular disease and prevalence of the meta- DC sign and cardiovascular risk (ρ = −0.07) and the cor- bolic syndrome [19]. Explanations for these discrepan- relation was very poor with SU levels (ρ = 0.15). DECT cies include biases inherent to retrospective studies that MSU deposit volume was similar in patients with and may have affected the study from Lee et al., both the fact without metabolic syndrome (p = 0.29) (Table 2). Correla- that no mention was made on the exclusion of patients tions between the urate burden assessed by SU levels, the with prior major cardiovascular factors for whom cardio- number of joints with the DC sign, and DECT volumes of vascular risk scores are not applicable, and also potential MSU deposition and individual cardiovascular risk factors differences between gout and cardiovascular comorbidi- are weak to null, and are shown in Fig. 3. ties across populations [20, 21], in this case of European Fig. 2 Correlation between the dual-energy computed tomography (DECT) volumes of monosodium urate deposition and the assessment of the risk of coronary heart disease or stroke according to the American College of Cardiology/American Heart Association (ACC/AHA), and the assessment of the Framingham coronary heart disease and general cardiovascular disease risks Pascart et al. Arthritis Research & Therapy (2018) 20:97 Page 5 of 7 Table 2 Comparison of dual-energy computed tomography (DECT) volumes of monosodium urate deposition, number of joints presenting with the double contour (DC) sign, and serum urate levels depending on whether the metabolic syndrome is present or not Total population No metabolic syndrome Metabolic syndrome p value (n = 42) (n = 14) (n = 28) Number of joints with DC sign 2 (2–3) 2 (1–3) 2 (2–3) 0.65 DECT volume knees (mm ) 0.2 (0–1) 0.4 (0–0.6) 0.1 (0–1.2) 0.91 DECT volume feet (mm ) 0.5 (0.1–1.8) 0.8 (0.3–1.9) 0.4 (0–1.3) 0.46 DECT volume knees + feet (mm ) 0.8 (0.2–2.8) 1.2 (0.6–2.2) 0.4 (0.1–2.3) 0.29 Serum urate level (mg/dL) 7.6 (6.8–9.4) 7.6 (7.2–8.8) 7.5 (6.0–9.4) 0.63 As the Mann-Whitney-Wilcoxon test was used (no normality), data are expressed as median (interquartile range) and Asian origin. Furthermore, when looking directly at weakly correlated to the BMI. A technical explanation the numbers, the Spearman correlation coefficient for could be that it is known that visceral fat increases noise volumes of urate deposition of the feet and the 10-year in the 80 kV images [24]; this remains to be shown for Framingham risk score for general cardiovascular disease peripheral joints. A weak negative correlation of the was −0.07 (very weakly negatively correlated to no cor- prevalence of the DC sign with the BMI was also found, relation) in our study but only 0.22 (weak correlation) in which could also be explained by the difficulty of observ- the study by Lee et al. [19]. ing joints with US with greater surrounding adipose tis- Despite a known higher prevalence of the metabolic sue. However, so far, no study has reported difficulties in syndrome in the population of gout patients, it does not the search for the DC sign in peripheral joints of obese seem to be related to the extent of urate burden [22]. patients. This result is consistent with previous results from the Cholesterol abnormalities (increased LDL and de- study by Lee et al. in which the metabolic syndrome was creased HDL cholesterol) are weakly associated with not associated with the volume of urate deposition in joint MSU deposition. Our study found a weak associ- multivariate analysis [19]. Surprisingly, despite a known ation of HDL levels with intra-articular MSU deposition trend of increasing SU levels with BMI [23], all volumes assessed with the US DC sign, urate burden of the knees of MSU deposits measured with DECT were negatively with DECT, and SU levels, and a weak association Fig. 3 Correlation between the urate burden and individual cardiovascular risk factors. BMI, body mass index; BP, blood pressure; DC, double contour; DECT, dual-energy computed tomography; HDL, high-density lipoprotein; LDL, low-density lipoprotein Pascart et al. Arthritis Research & Therapy (2018) 20:97 Page 6 of 7 between LDL levels and the DC sign only. These weak risk factors. The extent of MSU burden does not increase or very weak correlations are consistent with the results the estimated risk of cardiovascular events and, thus, from the third NHANES which showed an increased quantifying the MSU burden is not a surrogate marker for prevalence of low HDL in gout patients, but to a far traditional cardiovascular risk assessment of gout patients lesser extent than the high prevalence of hypertriglyc- naive of urate lowering therapy. eridemia [22]. It is unclear whether these correlations Abbreviations are only due to the same correlations between LDL and ACC: American College of Cardiology; ACR: American College of HDL levels with SU that are similar. Rheumatology; AHA: American Heart Association; BMI: Body mass index; BP: Blood pressure; DC: Double contour; DECT: Dual-energy computed An increase in triglyceride levels in gout is weakly as- tomography; eGFR: Estimated glomerular filtration rate; EULAR: European sociated with an increased MSU soft tissue deposition League Against Rheumatism; HDL: High-density lipoprotein; LDL: Low-density measured with DECT. Genetic associations showed that lipoprotein; MSU: Monosodium urate; SU : Serum urate; US : Ultrasonography mutations in the apolipoprotein gene cluster play a Availability of data and materials causal role in gout, even after adjustment for lipid and The datasets used and/or analyzed during the current study are available SU levels [21]. Apolipoprotein plays a central role in from the corresponding author on reasonable request. lipid metabolism and, notably, in the transport of triglyc- Authors’ contributions erides. A study using Mendelian randomization has pre- TP designed the study, participated in clinical data collection, analyzed data, viously shown the causal role of triglycerides in raising and participated in the writing of the manuscript. AG participated in clinical SU levels in men, but the reverse was not true [25]. Ele- data collection and in the writing of the manuscript. LN performed the statistical analyses. VD, MM, HL, MV, CG, and EH contributed to patient vations of very low-density lipoprotein (VLDL)-triglycer- recruitment and a critical review of the manuscript. NN, JL, and BC performed ides may be implicated in the transition between US examinations and read DECT scans. JFB designed the study, performed US asymptomatic hyperuricemia and gout [20]. One of the examinations, read DECT scans, and participated in the writing of the manuscript. All authors read and approved the manuscript. explanations for the association between lipid modifica- tions and gout would be that lipids are of importance in Ethics approval and consent to participate the coating of MSU crystals and that modifications of Ethical approval for the study was received from the Institutional Medical Ethics Review Board of the Lille Catholic Hospitals (reference number 2016–04-06). All this coating has implications on the inflammatory patients provided informed consent. response to the presence of these crystals [26]. The correlation between triglyceride levels and MSU burden Competing interests The authors declare that they have no competing interests. found in our study suggests that not only do triglycer- ides increase circulating urate but are also possibly Publisher’sNote involved in MSU deposition itself. Springer Nature remains neutral with regard to jurisdictional claims in We acknowledge that this study presents with some published maps and institutional affiliations. limitations. The first one is sample size, which limited Author details our ability to establish the precise level of the correla- Department of Rheumatology, Lille Catholic Hospitals, University of Lille, tions studied. Second, the fact that most gout patients F-59160 Lomme, France. Department of Radiology, Lille Catholic Hospitals, had significant cardiovascular risk as shown in other University of Lille, F-59160 Lomme, France. Department of Medical Research, Biostatistics, Lille Catholic Hospitals, University of Lille, F-59160 Lomme, studies made identifying factors able to discriminate France. EA 4490, PMOI, Physiopathologie des Maladies Osseuses between levels of risk difficult [6]. Nonetheless, given Inflammatoires, University of Lille, F-59000 Lille, France. Saint-Philibert the fact that all correlations found were null to weak, Hospital, Rue du Grand But, 59160 Lomme, France. it seems improbable that a strong correlation has Received: 14 March 2018 Accepted: 20 April 2018 been missed using our methodology. The third limita- tion is inherent to the cross-sectional nature of the study itself as it cannot establish a correlation be- References 1. Dalbeth N, Merriman TR, Stamp LK. Gout. Lancet. 2016;388:2039–52. tween urate burden and prevalence of cardiovascular 2. Richette P, Perez-Ruiz F, Doherty M, Jansen TL, Nuki G, Pascual E, Punzi L, events. The present study can only establish whether So AK, Bardin T. Improving cardiovascular and renal outcomes in gout: what there is a link between MSU burden and cardiovascular should we target? Nat Rev Rheumatol. 2014;10:654–61. 3. Bardin T, Richette P. Impact of comorbidities on gout and hyperuricaemia: risk factors. A longitudinal study is necessary to an update on prevalence and treatment options. BMC Med. 2017;15:123. explore if the MSU burden is an independent risk for 4. Singh JA, Ramachandaran R, Yu S, Yang S, Xie F, Yun H, Zhang J, Curtis JR. cardiovascular events. Is gout a risk equivalent to diabetes for stroke and myocardial infarction? A retrospective claims database study. Arthritis Res Ther. 2017;19:228. 5. Perez-Ruiz F, Martinez-Indart L, Carmona L, Herrero-Beites AM, Pijoan JI, Krishnan Conclusions E. Tophaceous gout and high level of hyperuricaemia are both associated with The present study demonstrates that, while the quantity increased risk of mortality in patients with gout. Ann Rheum Dis. 2014;73:177–82. 6. Andres M, Bernal JA, Sivera F, Quilis N, Carmona L, Vela P, Pascual E. of urate burden is involved in the association of gout with Cardiovascular risk of patients with gout seen at rheumatology clinics increased cardiovascular events, it does not seem to be following a structured assessment. Ann Rheum Dis. 2017; https://doi.org/10. through an overall increase in traditional cardiovascular 1136/annrheumdis-2016-210357. Pascart et al. Arthritis Research & Therapy (2018) 20:97 Page 7 of 7 7. Borghi C, Rodriguez-Artalejo F, De Backer G, Dallongeville J, Medina J, 25. Rasheed H, Hughes K, Flynn TJ, Merriman TR. Mendelian randomization Nuevo J, Guallar E, Perk J, Banegas JR, Tubach F, et al. Serum uric acid levels provides no evidence for a causal role of serum urate in increasing serum are associated with cardiovascular risk score: a post hoc analysis of the triglyceride levels. Circ Cardiovasc Genet. 2014;7:830–7. EURIKA study. Int J Cardiol. 2018;253:167–73. 26. Ortiz-Bravo E, Sieck MS, Schumacher HR Jr. Changes in the proteins coating 8. Pascart T, Grandjean A, Norberciak L, Ducoulombier V, Motte M, Luraschi H, monosodium urate crystals during active and subsiding inflammation. Vandecandelaere M, Godart C, Houvenagel E, Namane N, et al. Immunogold studies of synovial fluid from patients with gout and of fluid Ultrasonography and dual-energy computed tomography provide different obtained using the rat subcutaneous air pouch model. Arthritis Rheum. quantification of urate burden in gout: results from a cross-sectional study. 1993;36:1274–85. Arthritis Res Ther. 2017;19:171. 9. Choi HK, Al-Arfaj AM, Eftekhari A, Munk PL, Shojania K, Reid G, Nicolaou S. Dual energy computed tomography in tophaceous gout. Ann Rheum Dis. 2009;68:1609–12. 10. Bayat S, Aati O, Rech J, Sapsford M, Cavallaro A, Lell M, Araujo E, Petsch C, Stamp LK, Schett G, et al. Development of a dual-energy computed tomography scoring system for measurement of urate deposition in gout. Arthritis Care Res (Hoboken). 2016;68:769–75. 11. Ottaviani S, Gill G, Aubrun A, Palazzo E, Meyer O, Dieude P. Ultrasound in gout: a useful tool for following urate-lowering therapy. Joint Bone Spine. 2015;82:42–4. 12. Neogi T, Jansen TL, Dalbeth N, Fransen J, Schumacher HR, Berendsen D, Brown M, Choi H, Edwards NL, Janssens HJ, et al. Gout classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative. Ann Rheum Dis. 2015;2015(74):1789–98. 13. Goff DC Jr, Lloyd-Jones DM, Bennett G, Coady S, D'Agostino RB, Gibbons R, Greenland P, Lackland DT, Levy D, O'Donnell CJ, et al. ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation. 2013;2014(129):S49–73. 14. D'Agostino RB Sr, Vasan RS, Pencina MJ, Wolf PA, Cobain M, Massaro JM, Kannel WB. General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation. 2008;117:743–53. 15. Wilson PW, D'Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation. 1998;97:1837–47. 16. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, Fruchart JC, James WP, Loria CM, Smith SC Jr, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009;120:1640–5. 17. Gutierrez M, Schmidt WA, Thiele RG, Keen HI, Kaeley GS, Naredo E, Iagnocco A, Bruyn GA, Balint PV, Filippucci E, et al. International consensus for ultrasound lesions in gout: results of Delphi process and web-reliability exercise. Rheumatology (Oxford). 2015;54:1797–805. 18. Finkenstaedt T, Manoliou A, Toniolo M, Higashigaito K, Andreisek G, Guggenberger R, Michel B, Alkadhi H. Gouty arthritis: the diagnostic and therapeutic impact of dual-energy CT. Eur Radiol. 2016;26:3989–99. 19. Lee KA, Ryu SR, Park SJ, Kim HR, Lee SH. Assessment of cardiovascular risk profile based on measurement of tophus volume in patients with gout. Clin Rheumatol. 2017; https://doi.org/10.1007/s10067-017-3963-4. 20. Rasheed H, Hsu A, Dalbeth N, Stamp LK, McCormick S, Merriman TR. The relationship of apolipoprotein B and very low density lipoprotein triglyceride with hyperuricemia and gout. Arthritis Res Ther. 2014;16:495. 21. Rasheed H, Phipps-Green AJ, Topless R, Smith MD, Hill C, Lester S, Rischmueller M, Janssen M, Jansen TL, Joosten LA, et al. Replication of association of the apolipoprotein A1-C3-A4 gene cluster with the risk of gout. Rheumatology (Oxford). 2016;55:1421–30. 22. Choi HK, Ford ES, Li C, Curhan G. Prevalence of the metabolic syndrome in patients with gout: the Third National Health and Nutrition Examination Survey. Arthritis Rheum. 2007;57:109–15. 23. Lyngdoh T, Vuistiner P, Marques-Vidal P, Rousson V, Waeber G, Vollenweider P, Bochud M. Serum uric acid and adiposity: deciphering causality using a bidirectional Mendelian randomization approach. PLoS One. 2012;7:e39321. 24. Karcaaltincaba M, Aktas A. Dual-energy CT revisited with multidetector CT: review of principles and clinical applications. Diagn Interv Radiol. 2011;17: 181–94. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Arthritis Research & Therapy Springer Journals

The lack of association between the burden of monosodium urate crystals assessed with dual-energy computed tomography or ultrasonography with cardiovascular risk in the commonly high-risk gout patient

Free
7 pages

Loading next page...
 
/lp/springer_journal/the-lack-of-association-between-the-burden-of-monosodium-urate-0Hm1x8dSPg
Publisher
BioMed Central
Copyright
Copyright © 2018 by The Author(s).
Subject
Medicine & Public Health; Rheumatology; Orthopedics
eISSN
1478-6362
D.O.I.
10.1186/s13075-018-1602-3
Publisher site
See Article on Publisher Site

Abstract

Background: Gout is associated with higher cardiovascular risk that increases with disease severity. The objective of this study was to explore the relationship between the extent of monosodium urate (MSU) crystal deposition, assessed with ultrasonography (US) and dual-energy computed tomography (DECT), and cardiovascular risk. Methods: Gout patients were included in this cross-sectional study to undergo DECT scans for the assessment of total MSU volume deposition in the knees and feet, and US to evaluate the number of joints with the double contour (DC) sign. Participants were screened for traditional cardiovascular risk factors, and levels of the American College of Cardiology (ACC)/American Heart Association (AHA) 10-year risk for heart disease or stroke were calculated. The primary endpoint was the Spearman correlation coefficient ρ between DECT MSU volume and cardiovascular risk. Results: A total of 42 patients were included; they were predominantly male (40/42) and aged 63.0 ± 13.2 years. Overall, 28/42 patients presented with the metabolic syndrome and the average 10-year coronary event or stroke risk according to the ACC/AHA (n = 33) was 21 ± 15%. Correlations between DECT volumes of MSU deposits in the knees, feet, and knees + feet and cardiovascular risk according to the ACC/AHA were very poor, with ρ = 0.18, −0.01, and 0.13, respectively. The was no correlation between the number of joints with the DC sign and cardiovascular risk (ρ = −0.07). DECT MSU deposit volume was similar in patients with and without metabolic syndrome (p = 0.29). Conclusions: The extent of MSU burden does not increase the estimated risk of cardiovascular events in gout patients. Keywords: Dual-energy computed tomography, Ultrasonography, Gout, Cardiovascular risk, Triglycerides * Correspondence: tristan.pascart@hotmail.fr Department of Rheumatology, Lille Catholic Hospitals, University of Lille, F-59160 Lomme, France EA 4490, PMOI, Physiopathologie des Maladies Osseuses Inflammatoires, University of Lille, F-59000 Lille, France Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Pascart et al. Arthritis Research & Therapy (2018) 20:97 Page 2 of 7 Background and physical examination (including measures of body Gout is the result of an inflammatory response to mono- mass index (BMI) and arterial blood pressure (BP)). La- sodium urate (MSU) crystal deposition following pro- boratory testing of SU levels, lipid levels, blood glucose, longed hyperuricemia [1]. The association of gout with and the estimated glomerular filtration rate (eGFR) increased cardiovascular risk is now fully recognized, but measured by CKD-EPI or MDRD was to be performed mechanisms linking the two remain unclear [2–4]. Car- within the 2 weeks of US and DECT examinations. diovascular risk in gout seems to increase with disease severity, the presence of clinical tophi, and serum urate Cardiovascular risk assessment and the metabolic (SU) levels [5]. It has been hypothesized that a greater syndrome urate load could explain this increased cardiovascular Traditional cardiovascular risk factors were systematic- mortality [5]. Systematic evaluation of the cardiovascular ally assessed: BP, BMI, blood glucose, total cholesterol, risk of gout patients at the time of the diagnosis revealed high-density lipoprotein (HDL) cholesterol, calculated that a majority of patients are classified as having a high low-density lipoprotein (LDL) cholesterol, triglycerides, cardiovascular risk [6]. In non-gout patients, SU levels and smoking status. Cardiovascular risk was then calcu- may be associated with higher cardiovascular risk scores lated using the American College of Cardiology (ACC)/ but causality of hyperuricemia on cardiovascular comor- American Heart Association (AHA) guidelines [13], the bidities and events, and the metabolic syndrome, re- Framingham general 10-year cardiovascular risk factors mains uncertain [3, 7]. Furthermore, the association [14], and the Framingham 10-year risk of coronary dis- between MSU crystal burden and traditional cardiovas- ease [15]. These scores could not be calculated for pa- cular risk factors needs to be studied. Were they to be tients whoseage wasoutside therespectiverange of correlated, quantifying MSU deposition could help iden- applicability and for participants with a prior history of tify gout patients at high cardiovascular risk. coronary heart disease, peripheral arterial disease, and Ultrasonography (US) and dual-energy computed tom- stroke. The metabolic syndrome was defined by the ography (DECT) are two imaging techniques that can presence of three out of five items among the following: visualize and provide a quantification of the MSU bur- obesity (BMI > 30 kg/m in the absence of available waist den [8]. DECT uses two x-ray beams with two different circumference measurements), elevated BP (systolic energies allowing us to distinguish between urate and BP ≥ 130 mmHg or diastolic BP ≥ 85 mmHg or on- calcium in soft tissues surrounding bone when the vol- going antihypertensive therapy), elevated triglycerides ume of deposits exceeds 0.01 cm [9, 10]. US, on the (≥ 15 mg/dL or on-going treatment), low HDL choles- other hand, can identify intra-articular cartilage MSU terol (≤ 40 mg/dL in men and ≤ 50 mg/dL in women deposition appearing as a double contour (DC) sign or on-going treatment), and hyperglycemia (≥ 100 mg/dL which disappears during urate depletion [11]. Both tech- or drug treatment for elevated blood glucose) [16]. niques can quantify tophi volume but do not provide the same measurements [8]. US examination The main objective of this study was to explore the re- Examinations were performed by one of four trained lationship between the extent of MSU deposition, musculoskeletal radiologists (JFB, NN, BC, or JL) on an assessed with US and DECT, and cardiovascular risk Applio 400 US machine (Toshiba Medical Systems, assessment. Tochigi, Japan). High-frequency probes were used: a 12-Mhz probe for knee examination and an 18-MHz Methods probe for ankle and foot examination. US examination Patients for the DC sign was performed on the femoro-patellar Consecutive patients with a diagnosis of gout accord- joints, talo-crural joints, and first metatarsophalangeal ing to the American College of Rheumatology (ACR)/ joints [17]. European League Against Rheumatism (EULAR) 2015 criteria [12] were prospectively recruited to undergo a CT data acquisition and image reconstruction quantification of urate deposition in the knees and feet All scans were performed using a single-source CT using US and DECT [8], and an assessment of their (Somatom Definition Edge; Siemens, Erlangen, Germany). cardiovascular risk. The study was approved by the in- The patients were positioned feet first in a supine position. stitutional review board of the Lille Catholic Hospitals Knees and feet were scanned axially in two separate acqui- and all participants provided informed consent before sitions performed consecutively on the same day. All scans inclusion into the study. were performed with the same image protocol, acquisition At the initial clinical visit, the following were recorded: at 128 × 0.6 mm, and pitch of 0.7. For each body part, two demographic details, comorbid disorders (particularly prior scans were acquired with tube potentials of 80 kV and major cardiovascular events), gout history, medications, 140 kV. Depending on the scanned body region, quality Pascart et al. Arthritis Research & Therapy (2018) 20:97 Page 3 of 7 reference tube currents ranged between 62 and 260 mAs. Table 1 Population characteristics Automated attenuation-based tube current modulation Characteristic was used in all examinations. Demographics Axial images with soft (B30f) and bone (B70f) convo- Male (n (%)) 40 (95.2%) lution kernels were reconstructed with a 1-mm slice Age (years) 63 ± 13.2 thickness and an increment of 1 mm. DECT postproces- Gout duration (years) 7.9 ± 9.6 sing was performed by the radiologists with dedicated Familial gout (n (%)) 7 (16.7%) software (syngo.via VB10B, syngo Dual Energy Gout; Siemens), following the parameters described else- Number of flares per year 4.1 ± 6.6 where [18]: UH threshold, 150; iodine ratio, 1.4; mater- Alcohol consumption (g/day) 15 ± 20.7 ial definition ratio, 1.25; resolution, 4; air distance, 5; Creatinine clearance (ml/min) 80.0 ± 31.1 bone distance, 10. Two kinds of images were recon- Cardiovascular risk factors structed for each body part. First, volume-rendered Body mass index (kg/m ) 30.2 ± 5.7 three-dimensional (3D) images in which urate crystal Total cholesterol (mg/dL) 177 ± 63 deposits coded in green were reconstructed with a bone tissue convolution kernel (B70f). These images HDL cholesterol (mg/dL) 44 ± 13 allowed a straightforward overview of MSU deposits. LDL cholesterol (mg/dL) 97 ± 43 Second, multiplanar reformations associating images Triglycerides (mg/dL) 207 ± 393 reconstructed with a soft tissue kernel (B30f) and col- Systolic blood pressure (mmHg) 132.8 ± 13.7 ored images were reconstructed. The aspect of the Diastolic blood pressure (mmHg) 77 ± 9.9 final fusion images could be changed by modulating Smoker (n (%)) 6 (14.3%) the relative percentages of the morphological and col- ored images from 0 to 100% with a slider. Metabolic syndrome (n (%)) 28 (66.7%) Cardiovascular comorbidities Statistical analysis Coronary heart disease (n (%)) 6 (14.3%) Statistical analysis was performed using the R software Peripheral arterial disease (n (%)) 3 (7.1%) (version 3.4.2). Quantitative variables are expressed as Stroke (n (%)) 3 (7.1%) mean and standard deviation, and qualitative variables Diabetes mellitus (n (%)) 15 (35.7%) as number and percentage. Two-by-two correlations of quantitative variables were Cardiovascular risk assessment assessed by the Spearman correlation coefficient given ACC/AHA 10-year risk (%) 21 ± 14 the absence of normal distribution of values. Tests for Framingham 10-year general cardiovascular risk (%) 22 ± 14 nullity of coefficients were performed. Framingham 10-year coronary risk (%) 15 ± 11 DECT volumes of urate deposition, the number of Urate burden joints with the DC, and SU levels were compared Serum urate (mg/dL) 8.1 ± 2.3 between the groups of patients presenting with and without the metabolic syndrome using the Mann- Subcutaneous (clinical) tophi (n (%)) 12 (28.6%) Whitney-Wilcoxon test as data were not normal. Ultrasound tophus (n (%)) 29 (69%) The significance level was set at 5%. 3 Ultrasound tophus volume (cm ) 1.1 ± 1.4 The primary endpoint was the Spearman correlation At least one joint with the double contour sign 41 (97.6%) coefficient ρ between DECT MSU volume deposited on (n (%)) the feet and cardiovascular risk. DECT MSU volume knees (cm )(n = 39) 1.9 ± 4.6 DECT MSU volume feet (cm )(n = 41) 2.7 ± 6.7 Results DECT MSU volume knees + feet (cm )(n = 38) 4.7 ± 10.8 0f the 50 patients included, eight were excluded since Ongoing drugs lipid and glucose levels were not collected. The remaining 42 patients included were predominantly Diuretics (n (%)) 11 (26.2%) male (40/42) and aged 63.0 ± 13.2 years. Patient charac- Antidiabetic treatment (n (%)) 15 (35.7%) teristics are described in Table 1. Of these 42 patients, Hypolipidemic treatment (n (%)) 16 (38.1%) 33 had no prior coronary heart disease, peripheral Treatment for high blood pressure (n (%)) 25 (59.5%) arterial disease, or stroke, and therefore could have their ACC/AHA American College of Cardiology/American Heart Association, cardiovascular risk scores calculated. DECT dual-energy computed tomography, HDL high-density lipoprotein, Overall, 29/42 had at least one US tophus of 1.1 ± LDL low-density lipoprotein, MSU monosodium urate 1.4 cm . Patients presented with 2.2 ± 1.0 joints Pascart et al. Arthritis Research & Therapy (2018) 20:97 Page 4 of 7 Fig. 1 Imaging of monosodium urate crystal deposition. a Double contour sign of intra-articular cartilage deposition of the femoro-patellar joint 3 3 (arrows), (b) large (volume 5.39 cm ) and (c) small (volume 0.02 cm ) soft tissue volumes of deposits on the feet visualized with dual-energy computed tomography with the DC sign out of 6 (median 2, interquartile Discussion range (IQR) 2–3). The volume of MSU deposits with This study found no, or only very weak, correlation be- 3 3 DECT was 2.7 ± 6.7 cm for the feet (median 0.7 cm , tween levels of overall cardiovascular risk and the extent IQR 0.1–2.2) and 1.9 ± 4.6 cm for the knees of urate burden in the knees and feet measured using (median 0.2 cm ,range 0–1.2) (Fig. 1). Correlations DECT and US. Urate burden was not associated with the between SU levels and DECT volumes of MSU deposits of prevalence of the metabolic syndrome. Some weak cor- the knees, feet, and knees + feet were weak (ρ = 0.28, 0.20, relations were established between individual compo- and 0.23, respectively). Overall, 28/42 patients presented nents of cardiovascular risk, notably serum triglyceride with the metabolic syndrome and the average 10-year levels. coronary event or stroke risk according to the ACC/AHA Correlations between urate burden and cardiovascular (n = 33) was high (21 ± 15%). risk were particularly weak when considering measure- Correlations between DECT volumes of MSU de- ments of the feet only. These results are in direct con- posits in the knees, feet, and knees + feet and cardio- trast with the conclusions recently made by Lee et al. vascular risk according to the ACC/AHA were very from their retrospective study [19], considering that poor, with ρ =0.18, −0.01, and 0.13, respectively (Fig. 2), there was a correlation between total DECT urate vol- and did not differ significantly from zero (p >0.05). The ume of the feet and both the 10-year Framingham risk was no correlation between the number of joints with the for cardiovascular disease and prevalence of the meta- DC sign and cardiovascular risk (ρ = −0.07) and the cor- bolic syndrome [19]. Explanations for these discrepan- relation was very poor with SU levels (ρ = 0.15). DECT cies include biases inherent to retrospective studies that MSU deposit volume was similar in patients with and may have affected the study from Lee et al., both the fact without metabolic syndrome (p = 0.29) (Table 2). Correla- that no mention was made on the exclusion of patients tions between the urate burden assessed by SU levels, the with prior major cardiovascular factors for whom cardio- number of joints with the DC sign, and DECT volumes of vascular risk scores are not applicable, and also potential MSU deposition and individual cardiovascular risk factors differences between gout and cardiovascular comorbidi- are weak to null, and are shown in Fig. 3. ties across populations [20, 21], in this case of European Fig. 2 Correlation between the dual-energy computed tomography (DECT) volumes of monosodium urate deposition and the assessment of the risk of coronary heart disease or stroke according to the American College of Cardiology/American Heart Association (ACC/AHA), and the assessment of the Framingham coronary heart disease and general cardiovascular disease risks Pascart et al. Arthritis Research & Therapy (2018) 20:97 Page 5 of 7 Table 2 Comparison of dual-energy computed tomography (DECT) volumes of monosodium urate deposition, number of joints presenting with the double contour (DC) sign, and serum urate levels depending on whether the metabolic syndrome is present or not Total population No metabolic syndrome Metabolic syndrome p value (n = 42) (n = 14) (n = 28) Number of joints with DC sign 2 (2–3) 2 (1–3) 2 (2–3) 0.65 DECT volume knees (mm ) 0.2 (0–1) 0.4 (0–0.6) 0.1 (0–1.2) 0.91 DECT volume feet (mm ) 0.5 (0.1–1.8) 0.8 (0.3–1.9) 0.4 (0–1.3) 0.46 DECT volume knees + feet (mm ) 0.8 (0.2–2.8) 1.2 (0.6–2.2) 0.4 (0.1–2.3) 0.29 Serum urate level (mg/dL) 7.6 (6.8–9.4) 7.6 (7.2–8.8) 7.5 (6.0–9.4) 0.63 As the Mann-Whitney-Wilcoxon test was used (no normality), data are expressed as median (interquartile range) and Asian origin. Furthermore, when looking directly at weakly correlated to the BMI. A technical explanation the numbers, the Spearman correlation coefficient for could be that it is known that visceral fat increases noise volumes of urate deposition of the feet and the 10-year in the 80 kV images [24]; this remains to be shown for Framingham risk score for general cardiovascular disease peripheral joints. A weak negative correlation of the was −0.07 (very weakly negatively correlated to no cor- prevalence of the DC sign with the BMI was also found, relation) in our study but only 0.22 (weak correlation) in which could also be explained by the difficulty of observ- the study by Lee et al. [19]. ing joints with US with greater surrounding adipose tis- Despite a known higher prevalence of the metabolic sue. However, so far, no study has reported difficulties in syndrome in the population of gout patients, it does not the search for the DC sign in peripheral joints of obese seem to be related to the extent of urate burden [22]. patients. This result is consistent with previous results from the Cholesterol abnormalities (increased LDL and de- study by Lee et al. in which the metabolic syndrome was creased HDL cholesterol) are weakly associated with not associated with the volume of urate deposition in joint MSU deposition. Our study found a weak associ- multivariate analysis [19]. Surprisingly, despite a known ation of HDL levels with intra-articular MSU deposition trend of increasing SU levels with BMI [23], all volumes assessed with the US DC sign, urate burden of the knees of MSU deposits measured with DECT were negatively with DECT, and SU levels, and a weak association Fig. 3 Correlation between the urate burden and individual cardiovascular risk factors. BMI, body mass index; BP, blood pressure; DC, double contour; DECT, dual-energy computed tomography; HDL, high-density lipoprotein; LDL, low-density lipoprotein Pascart et al. Arthritis Research & Therapy (2018) 20:97 Page 6 of 7 between LDL levels and the DC sign only. These weak risk factors. The extent of MSU burden does not increase or very weak correlations are consistent with the results the estimated risk of cardiovascular events and, thus, from the third NHANES which showed an increased quantifying the MSU burden is not a surrogate marker for prevalence of low HDL in gout patients, but to a far traditional cardiovascular risk assessment of gout patients lesser extent than the high prevalence of hypertriglyc- naive of urate lowering therapy. eridemia [22]. It is unclear whether these correlations Abbreviations are only due to the same correlations between LDL and ACC: American College of Cardiology; ACR: American College of HDL levels with SU that are similar. Rheumatology; AHA: American Heart Association; BMI: Body mass index; BP: Blood pressure; DC: Double contour; DECT: Dual-energy computed An increase in triglyceride levels in gout is weakly as- tomography; eGFR: Estimated glomerular filtration rate; EULAR: European sociated with an increased MSU soft tissue deposition League Against Rheumatism; HDL: High-density lipoprotein; LDL: Low-density measured with DECT. Genetic associations showed that lipoprotein; MSU: Monosodium urate; SU : Serum urate; US : Ultrasonography mutations in the apolipoprotein gene cluster play a Availability of data and materials causal role in gout, even after adjustment for lipid and The datasets used and/or analyzed during the current study are available SU levels [21]. Apolipoprotein plays a central role in from the corresponding author on reasonable request. lipid metabolism and, notably, in the transport of triglyc- Authors’ contributions erides. A study using Mendelian randomization has pre- TP designed the study, participated in clinical data collection, analyzed data, viously shown the causal role of triglycerides in raising and participated in the writing of the manuscript. AG participated in clinical SU levels in men, but the reverse was not true [25]. Ele- data collection and in the writing of the manuscript. LN performed the statistical analyses. VD, MM, HL, MV, CG, and EH contributed to patient vations of very low-density lipoprotein (VLDL)-triglycer- recruitment and a critical review of the manuscript. NN, JL, and BC performed ides may be implicated in the transition between US examinations and read DECT scans. JFB designed the study, performed US asymptomatic hyperuricemia and gout [20]. One of the examinations, read DECT scans, and participated in the writing of the manuscript. All authors read and approved the manuscript. explanations for the association between lipid modifica- tions and gout would be that lipids are of importance in Ethics approval and consent to participate the coating of MSU crystals and that modifications of Ethical approval for the study was received from the Institutional Medical Ethics Review Board of the Lille Catholic Hospitals (reference number 2016–04-06). All this coating has implications on the inflammatory patients provided informed consent. response to the presence of these crystals [26]. The correlation between triglyceride levels and MSU burden Competing interests The authors declare that they have no competing interests. found in our study suggests that not only do triglycer- ides increase circulating urate but are also possibly Publisher’sNote involved in MSU deposition itself. Springer Nature remains neutral with regard to jurisdictional claims in We acknowledge that this study presents with some published maps and institutional affiliations. limitations. The first one is sample size, which limited Author details our ability to establish the precise level of the correla- Department of Rheumatology, Lille Catholic Hospitals, University of Lille, tions studied. Second, the fact that most gout patients F-59160 Lomme, France. Department of Radiology, Lille Catholic Hospitals, had significant cardiovascular risk as shown in other University of Lille, F-59160 Lomme, France. Department of Medical Research, Biostatistics, Lille Catholic Hospitals, University of Lille, F-59160 Lomme, studies made identifying factors able to discriminate France. EA 4490, PMOI, Physiopathologie des Maladies Osseuses between levels of risk difficult [6]. Nonetheless, given Inflammatoires, University of Lille, F-59000 Lille, France. Saint-Philibert the fact that all correlations found were null to weak, Hospital, Rue du Grand But, 59160 Lomme, France. it seems improbable that a strong correlation has Received: 14 March 2018 Accepted: 20 April 2018 been missed using our methodology. The third limita- tion is inherent to the cross-sectional nature of the study itself as it cannot establish a correlation be- References 1. Dalbeth N, Merriman TR, Stamp LK. Gout. Lancet. 2016;388:2039–52. tween urate burden and prevalence of cardiovascular 2. Richette P, Perez-Ruiz F, Doherty M, Jansen TL, Nuki G, Pascual E, Punzi L, events. The present study can only establish whether So AK, Bardin T. Improving cardiovascular and renal outcomes in gout: what there is a link between MSU burden and cardiovascular should we target? Nat Rev Rheumatol. 2014;10:654–61. 3. Bardin T, Richette P. Impact of comorbidities on gout and hyperuricaemia: risk factors. A longitudinal study is necessary to an update on prevalence and treatment options. BMC Med. 2017;15:123. explore if the MSU burden is an independent risk for 4. Singh JA, Ramachandaran R, Yu S, Yang S, Xie F, Yun H, Zhang J, Curtis JR. cardiovascular events. Is gout a risk equivalent to diabetes for stroke and myocardial infarction? A retrospective claims database study. Arthritis Res Ther. 2017;19:228. 5. Perez-Ruiz F, Martinez-Indart L, Carmona L, Herrero-Beites AM, Pijoan JI, Krishnan Conclusions E. Tophaceous gout and high level of hyperuricaemia are both associated with The present study demonstrates that, while the quantity increased risk of mortality in patients with gout. Ann Rheum Dis. 2014;73:177–82. 6. Andres M, Bernal JA, Sivera F, Quilis N, Carmona L, Vela P, Pascual E. of urate burden is involved in the association of gout with Cardiovascular risk of patients with gout seen at rheumatology clinics increased cardiovascular events, it does not seem to be following a structured assessment. Ann Rheum Dis. 2017; https://doi.org/10. through an overall increase in traditional cardiovascular 1136/annrheumdis-2016-210357. Pascart et al. Arthritis Research & Therapy (2018) 20:97 Page 7 of 7 7. Borghi C, Rodriguez-Artalejo F, De Backer G, Dallongeville J, Medina J, 25. Rasheed H, Hughes K, Flynn TJ, Merriman TR. Mendelian randomization Nuevo J, Guallar E, Perk J, Banegas JR, Tubach F, et al. Serum uric acid levels provides no evidence for a causal role of serum urate in increasing serum are associated with cardiovascular risk score: a post hoc analysis of the triglyceride levels. Circ Cardiovasc Genet. 2014;7:830–7. EURIKA study. Int J Cardiol. 2018;253:167–73. 26. Ortiz-Bravo E, Sieck MS, Schumacher HR Jr. Changes in the proteins coating 8. Pascart T, Grandjean A, Norberciak L, Ducoulombier V, Motte M, Luraschi H, monosodium urate crystals during active and subsiding inflammation. Vandecandelaere M, Godart C, Houvenagel E, Namane N, et al. Immunogold studies of synovial fluid from patients with gout and of fluid Ultrasonography and dual-energy computed tomography provide different obtained using the rat subcutaneous air pouch model. Arthritis Rheum. quantification of urate burden in gout: results from a cross-sectional study. 1993;36:1274–85. Arthritis Res Ther. 2017;19:171. 9. Choi HK, Al-Arfaj AM, Eftekhari A, Munk PL, Shojania K, Reid G, Nicolaou S. Dual energy computed tomography in tophaceous gout. Ann Rheum Dis. 2009;68:1609–12. 10. Bayat S, Aati O, Rech J, Sapsford M, Cavallaro A, Lell M, Araujo E, Petsch C, Stamp LK, Schett G, et al. Development of a dual-energy computed tomography scoring system for measurement of urate deposition in gout. Arthritis Care Res (Hoboken). 2016;68:769–75. 11. Ottaviani S, Gill G, Aubrun A, Palazzo E, Meyer O, Dieude P. Ultrasound in gout: a useful tool for following urate-lowering therapy. Joint Bone Spine. 2015;82:42–4. 12. Neogi T, Jansen TL, Dalbeth N, Fransen J, Schumacher HR, Berendsen D, Brown M, Choi H, Edwards NL, Janssens HJ, et al. Gout classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative. Ann Rheum Dis. 2015;2015(74):1789–98. 13. Goff DC Jr, Lloyd-Jones DM, Bennett G, Coady S, D'Agostino RB, Gibbons R, Greenland P, Lackland DT, Levy D, O'Donnell CJ, et al. ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation. 2013;2014(129):S49–73. 14. D'Agostino RB Sr, Vasan RS, Pencina MJ, Wolf PA, Cobain M, Massaro JM, Kannel WB. General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation. 2008;117:743–53. 15. Wilson PW, D'Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation. 1998;97:1837–47. 16. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, Fruchart JC, James WP, Loria CM, Smith SC Jr, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009;120:1640–5. 17. Gutierrez M, Schmidt WA, Thiele RG, Keen HI, Kaeley GS, Naredo E, Iagnocco A, Bruyn GA, Balint PV, Filippucci E, et al. International consensus for ultrasound lesions in gout: results of Delphi process and web-reliability exercise. Rheumatology (Oxford). 2015;54:1797–805. 18. Finkenstaedt T, Manoliou A, Toniolo M, Higashigaito K, Andreisek G, Guggenberger R, Michel B, Alkadhi H. Gouty arthritis: the diagnostic and therapeutic impact of dual-energy CT. Eur Radiol. 2016;26:3989–99. 19. Lee KA, Ryu SR, Park SJ, Kim HR, Lee SH. Assessment of cardiovascular risk profile based on measurement of tophus volume in patients with gout. Clin Rheumatol. 2017; https://doi.org/10.1007/s10067-017-3963-4. 20. Rasheed H, Hsu A, Dalbeth N, Stamp LK, McCormick S, Merriman TR. The relationship of apolipoprotein B and very low density lipoprotein triglyceride with hyperuricemia and gout. Arthritis Res Ther. 2014;16:495. 21. Rasheed H, Phipps-Green AJ, Topless R, Smith MD, Hill C, Lester S, Rischmueller M, Janssen M, Jansen TL, Joosten LA, et al. Replication of association of the apolipoprotein A1-C3-A4 gene cluster with the risk of gout. Rheumatology (Oxford). 2016;55:1421–30. 22. Choi HK, Ford ES, Li C, Curhan G. Prevalence of the metabolic syndrome in patients with gout: the Third National Health and Nutrition Examination Survey. Arthritis Rheum. 2007;57:109–15. 23. Lyngdoh T, Vuistiner P, Marques-Vidal P, Rousson V, Waeber G, Vollenweider P, Bochud M. Serum uric acid and adiposity: deciphering causality using a bidirectional Mendelian randomization approach. PLoS One. 2012;7:e39321. 24. Karcaaltincaba M, Aktas A. Dual-energy CT revisited with multidetector CT: review of principles and clinical applications. Diagn Interv Radiol. 2011;17: 181–94.

Journal

Arthritis Research & TherapySpringer Journals

Published: May 29, 2018

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off