Abstract
OBJECTIVE
To examine uric acid (UA) as a possible predictor of the progression of coronary artery calcification (CAC) using data from the prospective Coronary Artery Calcification in Type 1 Diabetes (CACTI) Study.
RESEARCH DESIGN AND METHODS
CAC was measured by electron beam tomography at the baseline and at a follow-up 6.0 ± 0.5 years later. The study population included 443 participants with type 1 diabetes and 526 control subjects who were free of diagnosed coronary artery disease at baseline. The presence of renal disease was defined by the presence of albuminuria and/or low glomerular filtration rate.
RESULTS
In subjects without renal disease, serum UA predicted CAC progression (odds ratio 1.30 [95% CI 1.07–1.58], P = 0.007) independent of conventional cardiovascular risk factors including diabetes and the presence of metabolic syndrome.
CONCLUSIONS
Serum UA levels predict the progression of coronary atherosclerosis and may be useful in identifying who is at risk for vascular disease in the absence of significant chronic kidney disease.
Elevated serum uric acid (UA) is associated with kidney disease, but it has also been linked to endothelial dysfunction and development of hypertension irrespective of renal involvement (1). UA may contribute to the atherosclerotic process through induction of endothelial dysfunction (2) and inflammation (3).
Serum UA levels have been correlated with negative cardiovascular outcomes in the general population (4) and type 2 diabetic subjects (5) and predict the progression of diabetic nephropathy (6) in type 1 diabetic subjects. The objective of this study was to evaluate UA levels as a predictor of subclinical atherosclerosis progression in the Coronary Artery Calcification in Type 1 Diabetes (CACTI) Study.
RESEARCH DESIGN AND METHODS
Of the 1,416 individuals asymptomatic for coronary artery disease (CAD) enrolled at baseline, 1,022 had data on coronary artery calcification (CAC) progression. Subjects with coronary events during follow-up (n = 18) and incomplete information about covariates (n = 35) were excluded, resulting in 969 subjects. Clinical and laboratory evaluations were performed as previously described (7). CAC was measured twice and averaged at the baseline and at follow-up 6.0 ± 0.5 years later. CAC progressors were defined as participants whose square root-transformed CAC volume (CVS) increased by ≥2.5 mm (8). Serum UA levels were measured at baseline on the clinical analyzer utilizing a uricase-based commercial kit. Normoalbuminuria was defined as overnight albumin excretion rate ≤20 μg/min or urinary albumin-to-creatinine ratio ≤30 mg/g. Glomerular filtration rate (GFR) was estimated by the Mayo Clinic quadratic equation (GFRMC) (9). Metabolic syndrome (MetS) was defined by the original Adult Treatment Panel III (ATP III) criteria (10). The study protocol was approved by the Colorado Combined Institutional Review Board, and informed consent was obtained from all participants.
Statistical analysis
Serum UA, creatinine, cystatin C, and albumin-to-creatinine ratio were log-transformed. We defined normal renal status as a GFRMC ≥60 ml/min per 1.73 m2 and normoalbuminuria, and chronic kidney disease (CKD) as GFRMC <60 ml/min per 1.73 m2 and/or albuminuria.
Stepwise multiple regression analysis was performed to select predictors of CAC progression (Model 1). Renal status was added to this model and interactions between renal status and each variable were tested. SAS 9.2 (SAS Institute, Cary, NC) was used for these analyses.
RESULTS
Subjects with significant progression of CAC (n = 338) were older and had higher CAC at baseline than nonprogressors. Serum UA levels were also higher in progressors (5.6 [4.9–6.5 mg/dl]) than in nonprogressors (5.1 [4.4–5.9], P < 0.0001).
Baseline characteristics of participants by renal status are displayed in Table 1. Among subjects with normal renal function, CAC progressed in 263/864 (30%). In subjects with CKD, 75/105 (71.4%) progressed. Age, higher CVS at baseline, and the use of ACE inhibitors or angiotensin receptor blockers were significantly associated with progression. Subjects with CKD had higher UA levels (5.9 [5.1–7.0 mg/dl]) than subjects with normal renal status (5.2 [4.5−6.1], P < 0.0001), and this association was not modified by diabetes status.
Table 1.
Clinical and laboratory characteristics at baseline between progressors and nonprogressors by renal status
| Normal renal status |
Significant CKD |
|||||
|---|---|---|---|---|---|---|
| Progressors n = 263 | Nonprogressors n = 601 | P | Progressors n = 75 | Nonprogressors n = 30 | P | |
| Age (years) | 42 ± 8 | 37 ± 8 | <0.0001 | 41 ± 8 | 35 ± 8 | 0.0005 |
| Male (%) | 64 | 38 | <0.0001 | 62 | 70 | 0.47 |
| Type 1 diabetes (%) | 47 | 40 | 0.03 | 80 | 63 | 0.07 |
| Smoking current (%) | 12 | 7 | 0.03 | 11 | 10 | 0.90 |
| Smoking ever (%) | 22 | 19 | 0.31 | 29 | 20 | 0.31 |
| Hypertension (%) | 24 | 9 | <0.0001 | 47 | 31 | 0.13 |
| Systolic BP (mmHg) | 119 ± 13 | 112 ± 11 | <0.0001 | 122 ± 14 | 121 ± 14 | 0.82 |
| Diastolic BP (mmHg) | 80 ± 9 | 76 ± 7 | <0.0001 | 80 ± 10 | 81 ± 10 | 0.81 |
| Baseline square root CAC volume | 3.5 ± 5.9 | 0.22 ± 1.0 | <0.0001 | 5.5 ± 9.0 | 0.9 ± 2.4 | 0.006 |
| BMI (kg/m2) | 27 ± 4 | 25 ± 4 | <0.0001 | 26 ± 4 | 27 ± 4 | 0.82 |
| Waist circumference (cm) | ||||||
| Male | 96 ± 11 | 88 ± 10 | <0.0001 | 93 ± 10 | 91 ± 11 | 0.56 |
| Female | 84 ± 13 | 78 ± 11 | <0.0001 | 84 ± 14 | 78 ± 12 | 0.42 |
| Waist-to-hip ratio | ||||||
| Male | 0.90 ± 0.06 | 0.86 ± 0.06 | <0.0001 | 0.89 ± 0.05 | 0.88 ± 0.05 | 0.30 |
| Female | 0.78 ± 0.06 | 0.76 ± 0.06 | 0.002 | 0.79 ± 0.07 | 0.79 ± 0.07 | 0.97 |
| Uric acid (mg/dl) | ||||||
| Male | 5.9 (5.2–6.8) | 5.8 (5.2–6.4) | 0.42 | 6.2 (5.4–7.3) | 6.5 (5.6–7.7) | 0.32 |
| Female | 4.8 (4.2–5.4) | 4.5 (4.0–5.1) | 0.01 | 5.3 (4.6–5.8) | 5.0 (4.5–5.9) | 0.52 |
| Total cholesterol (mg/dl) | 183 ± 36 | 183 ± 36 | 0.27 | 184 ± 35 | 179 ± 41 | 0.76 |
| HDL (mg/dl) | 49 ± 14 | 55 ± 16 | <0.0001 | 53 ± 16 | 49 ± 14 | 0.29 |
| LDL (mg/dl) | 111 ± 32 | 106 ± 32 | 0.03 | 107 ± 30 | 107 ± 31 | 0.88 |
| Triglycerides (mg/dl) | 105 (73–149) | 90 (64–121) | <0.0001 | 96 (62–138) | 107 (71–139) | 0.41 |
| A1C (%) | ||||||
| Type 1 diabetes | 7.8 ± 1.1 | 7.7 ± 1.2 | 0.85 | 8.3 ± 1.3 | 7.9 ± 0.9 | 0.20 |
| Control subjects | 5.6 ± 0.4 | 5.4 ± 0.3 | <0.0001 | 5.8 ± 0.5 | 5.4 ± 0.4 | 0.03 |
| Serum creatinine (mg/dl) | 1.1 (1.1–1.3) | 1.1 (1.0–1.3) | 0.009 | 1.3 (1.1–1.5) | 1.4 (1.2–1.8) | 0.18 |
| Cystatin C (mg/l) | 0.78 (0.72–0.84) | 0.76 (0.69–0.82) | 0.007 | 0.95 (0.79–0.96) | 0.92 (0.76–1.03) | 0.84 |
| ACR (mg/g creatinine) | 4.8 (3.2–6.6) | 4.4 (3.2–5.7) | 0.03 | 59.7 (26–179) | 51 (15–276) | 0.69 |
| ACE inhibitors/ARB use (%) | 16 | 8 | 0.001 | 57 | 20 | 0.0005 |
| Thiazide diuretic use (%) | 5 | 2.3 | 0.04 | 18 | 3 | 0.001 |
| Statin use (%) | 17 | 5 | <0.0001 | 25 | 10 | 0.08 |
| Alcohol intake positive (%) | 79 | 77 | 0.86 | 59 | 75 | 0.05 |
| Number of alcohol drinks/month | 21 ± 35 | 15 ± 25 | 0.02 | 11 ± 21 | 11 ± 18 | 0.90 |
| MetS (%) | 18.2 | 8.3 | <0.0001 | 30.6 | 13.3 | 0.06 |
Data are means ± SD, %, or geometric means (interquartile range). Any alcohol intake is defined as 12 or more drinks during their lifetime. Drinks per month are a combination of standard amounts of beer (12 oz.), wine (3.5 oz.), or hard liquor (1.5 oz.). ACR, albumin-to-creatinine ratio; ARB, angiotensin receptor blockers; BP, blood pressure.
In stepwise regression, age, sex, type 1 diabetes, baseline CVS, hypertension, smoking, HDL cholesterol, LDL cholesterol, and serum UA were retained. Higher baseline serum UA predicted CAC progression (odds ratio [OR] 1.30 for each 1 SD change [0.2 mg], [95% CI 1.07–1.58], P = 0.007).
To explore if UA predicted CAC progression independently of CKD, interaction terms between renal status and all covariates were entered. The effects of sex (P = 0.01 for the interaction), baseline CVS (P = 0.003), and UA (P = 0.01) differed significantly by renal status. In subjects with normal renal status, all variables selected from Model 1 were significantly associated with CAC progression, including UA (OR 1.25 [95% CI 1.01–1.54], P = 0.03). In subjects with CKD, UA was not a predictor of CAC (0.98 [0.55–1.74], P = 0.96). The addition of MetS, alcohol intake, thiazides, ACEs, or angiotensin receptor blockers to the model did not substantially change the results about UA and the outcome.
CONCLUSIONS
The novel finding of this study is that UA levels predict CAC progression independently of other established CVD risk factors. In contrast to previous studies associating UA with mortality (3,5), in this report we examined an established marker of coronary plaque burden, allowing for the exploration of early events related to the progression of coronary lesions. Fukui et al. (11) reported an association between higher serum UA and greater intima-media thickness and lower ankle-brachial index in patients with type 2 diabetes. However, this is the first report of an independent association of UA levels on the progression of coronary atherosclerosis.
The only previous study to examine an association between UA and CAD in type 1 diabetes (12) found that hyperuricemia was correlated with the presence of CAD in women but not in men, and that this association was independent of hypertension and nephropathy. Recently published data by our group that show baseline serum UA predicts the development of microalbuminuria after 6 years (13), and Hovind et al. (6) observed that elevated serum UA levels are associated with the development of macroalbuminuria. Rosolowsky et al. (14) reported an association between serum UA and impaired GFR in microalbuminuric and normoalbuminuric type 1 diabetic subjects. Experimental information suggests that UA may mediate the development of both hypertension and renal disease by dysfunction of endothelial and vascular smooth muscle cells resulting in oxidative stress, a reduction in endothelial nitric oxide, and activation of the renin-angiotensin system (15).
We found that UA levels predict CAC progression only in subjects with normal renal function. While UA levels may rise secondary to a fall in GFR, our findings suggest that the temporal relation between the elevation of UA levels and CAC progression is not simply a consequence of declining renal function. As CKD advances, other factors may play a more prominent role in vascular disease such as CKD-associated mineral and bone disorders.
Hyperuricemia is more often seen in people with MetS and has been put forward as one of the criteria of the syndrome (1). Our study demonstrated that UA predicted CAC progression independent of the presence of MetS in subjects without renal disease.
Serum UA level should be considered a marker of increased CAD risk in subjects with and without type 1 diabetes in the absence of significant kidney disease.
Acknowledgments
Support for this study was provided by the National Institutes of Health (NIH); the National Heart, Lung, and Blood Institute grants R01 HL61753, R01 HL68607, and R01 HL079611; and the Diabetes Endocrinology Research Center, Clinical Investigation Core P30 DK57516. The study was performed at the Adult General Clinical Research Center at the University of Colorado Denver Anschutz Medical Center and was supported by the NIH M01 RR000051 at the Barbara Davis Center for Childhood Diabetes in Denver, Colorado, and at the Colorado Heart Imaging Center in Denver, Colorado. T.C.R. was supported by a scholarship from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) of the Brazilian government. D.M.M. was supported by K23 DK075360. J.K.S.-B. was supported by the American Diabetes Association-Takeda Cardiovascular Postdoctoral Fellowship 7-09-CVD-06. R.J.J. has several patent applications related to lowering UA as a means to reduce blood pressure or treat MetS. No other potential conflicts of interest relevant to this article were reported.
T.C.R. wrote and edited the manuscript. D.M.M. reviewed and edited the manuscript. R.J.J. reviewed and edited the manuscript and contributed to the discussion. D.I.J. and C.R. reviewed and edited the manuscript. G.L.K. researched the data. M.R. and J.K.S.-B. reviewed and edited the manuscript and contributed to the discussion.
Parts of this study were presented in abstract form at the 2009 Scientific Sessions of the American Heart Association, Orlando, Florida, 14–18 November 2009.
Footnotes
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
References
- 1. Feig DI, Kang DH, Johnson RJ. Uric acid and cardiovascular risk. N Engl J Med 2008;359:1811–1821 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Sánchez-Lozada LG, Soto V, Tapia E, Avila-Casado C, Sautin YY, Nakagawa T, Franco M, Rodríguez-Iturbe B, Johnson RJ. Role of oxidative stress in the renal abnormalities induced by experimental hyperuricemia. Am J Physiol Renal Physiol 2008;295:1134–1141 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Ruggiero C, Cherubini A, Miller E, 3rd, Maggio M, Najjar SS, Lauretani F, Bandinelli S, Senin U, Ferrucci L. Usefulness of uric acid to predict changes in C-reactive protein and interleukin-6 in 3-year period in Italians aged 21 to 98 years. Am J Cardiol 2007;100:115–121 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Fang J, Alderman MH. Serum uric acid and cardiovascular mortality the NHANES I epidemiologic follow-up study, 1971–1992. National Health and Nutrition Examination Survey. JAMA 2000;283:2404–2410 [DOI] [PubMed] [Google Scholar]
- 5. Zoppini G, Targher G, Negri C, Stoico V, Perrone F, Muggeo M, Bonora E. Elevated serum uric acid concentrations independently predict cardiovascular mortality in type 2 diabetic patients. Diabetes Care 2009;32:1716–1720 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Hovind P, Rossing P, Tarnow L, Johnson RJ, Parving HH. Serum uric acid as a predictor for development of diabetic nephropathy in type 1 diabetes: an inception cohort study. Diabetes Care 2009;58:1668–1671 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Dabelea D, Kinney G, Snell-Bergeon JK, Hokanson JE, Eckel RH, Ehrlich J, Garg S, Hamman RF, Rewers M. Coronary Artery Calcification in Type 1 Diabetes Study. Effect of type 1 diabetes on the gender difference in coronary artery calcification: a role for insulin resistance? The Coronary Artery Calcification in Type 1 Diabetes (CACTI) Study. Diabetes 2003;52:2833–2839 [DOI] [PubMed] [Google Scholar]
- 8. Hokanson JE, MacKenzie T, Kinney G, Snell-Bergeon JK, Dabelea D, Ehrlich J, Eckel RH, Rewers M. Evaluating changes in coronary artery calcium: an analytic method that accounts for interscan variability. AJR AM J Roentgenol 2004;182:1327–1332 [DOI] [PubMed] [Google Scholar]
- 9. Rule AD, Rodeheffer RJ, Larson TS, Burnett JC, Jr, Cosio FG, Turner ST, Jacobsen SJ. Limitations of estimating glomerular filtration rate from serum creatinine in the general population. Mayo Clin Proc 2006;81:1427–1434 [DOI] [PubMed] [Google Scholar]
- 10. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive Summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA 2001;285:2486–2497 [DOI] [PubMed] [Google Scholar]
- 11. Fukui M, Tanaka M, Shiraishi E, Harusato I, Hosoda H, Asano M, Kadono M, Hasegawa G, Yoshikawa T, Nakamura N. Serum uric acid is associated with microalbuminuria and subclinical atherosclerosis in men with type 2 diabetes mellitus. Metabolism 2008;57:625–629 [DOI] [PubMed] [Google Scholar]
- 12. Rathmann W, Hauner H, Dannehl K, Gries FA. Association of elevated serum uric acid with coronary heart disease in diabetes mellitus. Diabete Metab 1993;19:159–166 [PubMed] [Google Scholar]
- 13. Jalal DI, Rivard CJ, Johnson RJ, Maahs DM, McFann K, Rewers M, Snell-Bergeon JK. Serum uric acid levels predict the development of albuminuria over 6 years in patients with type 1 diabetes: findings from the Coronary Artery Calcification in Type 1 Diabetes study. Nephrol Dial Transplant 2010;25:1865–1869 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Rosolowsky ET, Ficociello LH, Maselli NJ, Niewczas MA, Binns AL, Roshan B, Warram JH, Krolewski AS. High-normal serum uric acid is associated with impaired glomerular filtration rate in nonproteinuric patients with type 1 diabetes. J Am Soc Nephrol 2008;3:706–713 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Kang DH, Park SK, Lee IK, Johnson RJ. Uric acid-induced C-reactive protein expression: implication on cell proliferation and nitric oxide production of human vascular cells. J Am Soc Nephrol 2005;16:3553–3562 [DOI] [PubMed] [Google Scholar]