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Arthritis Rheum. Author manuscript; available in PMC Jul 15, 2010.
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PMCID: PMC2714267
NIHMSID: NIHMS117715

Hyperuricemia and Risk of Stroke: A Systematic Review and Meta-analysis

Seo Young Kim, MD,1,2 James P Guevara, MD, MPH,2,3 Kyoung Mi Kim, MD,4 Hyon K Choi, MD, DrPH,5 Daniel F. Heitjan, PhD,2,6 and Daniel A Albert, MD7

Abstract

BACKGROUND

Hyperuricemia is hypothesized to be a risk factor for stroke and other cardiovascular disease, but to date results from observational studies are conflicting.

METHODS

We conducted a systematic review and meta-analysis to assess the association between hyperuricemia and risk of stroke incidence and mortality. Studies were identified by searching major electronic databases using the Medical Subject Headings and keywords without restriction in languages. Only prospective cohort studies were included if they had data on stroke incidences or mortalities related to serum uric acid levels in adults. Pooled risk ratios (RRs) for the association of stroke incidence and mortality with serum uric acid levels were calculated.

RESULTS

A total of 16 studies including 238,449 adults were eligible and abstracted. Hyperuricemia was associated with a significantly higher risk of both stroke incidence [N=6 studies, RR 1.41, 95% confidence interval (CI): 1.05–1.76] and mortality [N=6 studies, RR 1.36, 95% CI: 1.03–1.69] in our meta-analyses of unadjusted study estimates. Subgroup analyses of studies adjusting for known risk factors such as age, hypertension, diabetes, and cholesterol still showed that hyperuricemia was significantly associated with both stroke incidence [N=4 studies, RR 1.47, 95% CI: 1.19–1.76] and mortality [N=6 studies, RR 1.26, 95% CI: 1.12–1.39]. The pooled estimate of multivariate RRs did not differ much by gender.

CONCLUSION

Our study suggests that hyperuricemia may modestly increase the risks of both stroke incidence and mortality. Future research is needed to determine whether lowering uric acid level has any beneficial effects on stroke.

Keywords: hyperuricemia, stroke, systematic review, meta-analysis

INTRODUCTION

Uric acid is the end-product of purine metabolism in humans. There is no universally accepted definition for hyperuricemia, but it is usually defined as serum urate concentration in excess of 6.8 mg/dL, which is the limit of urate solubility in serum 1, 2. Currently, no urate-lowering therapy is indicated in asymptomatic hyperuricemia 3. High serum uric acid level with or without gout is associated with cardiovascular diseases such as hypertension, coronary heart disease, peripheral vascular disease, and stroke 410. However, the role of high serum uric acid level as an independent risk factor for cardiovascular disease including stroke has been controversial 1116. Several patho-physiological mechanisms through endothelial dysfunction, oxidative metabolism, platelet adhesiveness and aggregation, related to hyperuricemia in cardiovascular disease have been suggested 1719. According to a recent report 20, about 780,000 Americans experience a new or recurrent stroke each year, on average, one stroke every 40 seconds. Preliminary data from 2005 indicate that stroke accounted for about 1 of every 17 deaths in the United States 20. If asymptomatic hyperuricemia has a deleterious effect on serious morbidity and mortality related to stroke, hyperuricemia may become a new target for more comprehensive risk factor management in the primary prevention of stroke. Accordingly, we conducted a meta-analysis of prospective cohort studies to determine the association between hyperuricemia and the risk of stroke.

METHODS

Data Sources

We searched three major electronic databases — MEDLINE (1950-July 2008), EMBASE (1980-July 2008), and the Cochrane library — for studies of the association between serum uric acid levels and stroke incidence and/or mortality. We also searched bibliographies of identified reports and review articles for additional references. Our search strategy is described in Figure 1.

Figure 1
Search strategy

Study Eligibility

To be eligible for inclusion, we only considered (1) prospective cohort studies of adult patients, (2) longer than one year of follow-up, (3) with sample size of at least fifty subjects, and (4) inception cohort free of stroke. We imposed no geographic or language restrictions. Studies reporting interventional and secondary prevention trials were excluded.

Selection of Studies

Two authors (S. Kim and K. Kim) independently screened each of the potential titles, abstracts, and/or full-texts to determine inclusion. Areas of disagreement or uncertainty were resolved by consensus. When multiple articles were published from a single study, we selected the report that contained the most complete and relevant data on the association between hyperuricemia and stroke. The electronic search retrieved 566 potentially relevant studies. Non-electronic search identified 3 additional studies. On initial screening, 504 were excluded based on title. Of the 65 screened abstracts, 22 studies were retrieved for detailed evaluation. Of those, two studies were based on the same patient population, so they were considered as one study in the meta-analysis 21, 22. One study was excluded because it reported insufficient data on stroke outcome 23. Four studies that reported data on carotid intima-media thickness only were excluded 2427. Eventually 16 studies were included in this meta-analysis (Figure 2).

Figure 2
Selection of studies included in the analysis.

Data Abstraction and Quality Assessment

All data were independently abstracted in duplicate by two authors (S. Kim and K. Kim) using a data abstraction form. Discrepancies were resolved by consensus. When necessary, the original authors were contacted for additional information. Data on the study characteristics such as author name, year of publication, language, sample size, mean age, uric acid level and number of outcome were collected. The Newcastle–Ottawa Scale was used to assess the quality of studies 28 (Table 1). A quality score was calculated on the basis of three major components: selection of the study groups (0–4 points), quality of the adjustment for confounding (0–2 points) and ascertainment of the outcome of interest in the cohorts (0–3 points). A higher score represents better methodological quality. Adjustment for known stroke risk factors, duration of follow-up of at least 5 years, and adequate follow-up rate were criteria of higher quality.

Table 1
Quality assessment of included studies based on Newcastle-Ottawa Scale

Statistical Analysis

Some studies included in our meta-analysis used the International system (SI) of units (µmol per liter) to report levels of serum uric acid. We therefore converted those to the conventional units (milligram per deciliter), using a conversion rate of 16.81 (1 mg/dL = 59.48 µmol/L) 29. Pooled estimates of risk ratios (RRs) were calculated using the DerSimonian and Laird random effects model 30, 31 for stroke incidence and mortality. This statistical technique weighs individual studies by sample size and variance (both within- and between-study variance) and yields a pooled point estimate and a 95% confidence interval. The DerSimonian and Laird technique was considered an appropriate pooling technique because of the relative heterogeneity of the source population in each study. We also evaluated the presence of heterogeneity across trials by using the I2 statistic, which quantifies the percentage of variability that can be attributed to between-study differences 32. To assess the potential for publication bias, we performed the Begg’s test and the Egger’s test and constructed funnel plots to visualize a possible asymmetry 33. All the statistical analyses were done in Stata 10 (Stata Corp, College Station, TX). We followed the Meta-analyses of Observational Studies in Epidemiology (MOOSE) guidelines 34 in the report of this meta-analysis.

RESULTS

Study Characteristics

Sixteen prospective cohort studies representing data from 238,449 participants were included in the meta-analysis. The characteristics of the studies and of their participants are presented in Table 2. Of the 16 trials, 2 were conducted primarily in the United States although the study by Kagan et al 35 was based on a Hawaiian Japanese cohort. Eight studies were done in Asian countries and six studies were from European countries. The number of participants ranged from 153 in a study by Tofuku et al 36 to 83,683 in the Vorarlberg Health Monitoring and Promotion Program cohort study by Strasak et al 37. Nine studies 14, 15, 21, 22, 36, 3842 included both men and women. Four studies used a lower cut-off value to define hyperuricemia for women compared to men 39, 40, 42, 43. Six studies 35, 37, 4447 included only men, and one study 43 only women. Seven studies 35, 37, 39, 41, 4345 reported gender-specific outcome for ischemic stroke. Six studies 15, 35, 37, 39, 41, 43 provided only adjusted risk estimates.

Table 2
Characteristics of included cohort studies.

Hyperuricemia and Stroke Incidence

The pooled estimate of unadjusted RRs for stroke based on six studies 14, 36, 3840, 46 was 1.41 (95% CI: 1.05–1.76) among subjects with hyperuricemia, compared with those with normouricemia. The heterogeneity test was not significant (I2 =23.8%, p=0.25). The pooled multivariate RR based on four studies14, 3941 fully adjusting for known risk factors of stroke was 1.47 (95% CI: 1.19–1.76). The heterogeneity test for this analysis was not significant (I2=0.0%, p=0.96).

The pooled estimate of unadjusted RRs among men based on two studies 40, 46 was 1.82, (95% CI: 0.84–2.80), whereas only one study reported unadjusted RR of 2.55 among women (95% CI: 0.84–4.27)40. The pooled estimate of multivariate RRs based on three studies3941 was 1.42 (95% CI: 1.03–1.80) among women and 1.42 among men (95% CI: 0.94–1.90). The forest plot of multivariate RRs and 95% CIs for stroke incidence and hyperuricemia are shown in Figure 3 (top).

Figure 3
Random effects analysis of fully adjusted studies for the association between hyperuricemia and stroke

Hyperuricemia and Stroke Mortality

The pooled estimate of unadjusted RR based on 6 studies 21, 22, 36, 42, 44, 45, 47 was 1.36 (95% CI: 1.03–1.69) for patients with hyperuricemia, compared with those with normouricemia. There was no statistically significant heterogeneity among the studies (I2= 0.0%, p=0.62). The pooled multivariate RR based on six studies 15, 37, 4244 fully adjusting for known risk factors of stroke was 1.26 (95% CI: 1.12–1.39) with a non-significant heterogeneity test (I2= 0.0%, p=0.50).

The pooled estimate of unadjusted RRs among men based on 5 studies 21, 42, 44, 45, 47 was 1.34 (95% CI: 1.01–1.67). The pooled unadjusted RR among women based on only two studies 21, 42 was 4.75, but it was not statistically significant (95% CI: 0.53–8.98).

The pooled multivariate RRs were significantly higher for both men [N=4 studies 37, 42, 44, 45, RR 1.20, 95% CI: 1.05–1.35] and women [N=2 studies 42, 43, RR 1.35, 95% CI: 1.04–1.66], compared to those with normouricemia. The forest plot of multivariate RRs and 95% CIs for stroke mortality and hyperuricemia are shown in Figure 3 (bottom).

Publication Bias Assessment

The funnel plots for both stroke incidence and mortality were visually examined (Figure 4). There was no statistical evidence of publication bias among studies for stroke incidence or mortality by using Egger’s (p=0.80; 0.25 respectively) and Begg’s (p=0.70; 0.48 respectively) tests.

Figure 4
Begg’s funnel plot for publication bias in studies for stroke incidence and mortality

Sensitivity Analyses

Meta-regression was performed to further investigate the effect of three study-level characteristics (year of publication, race, and gender) on the risk of stroke. None of the regression coefficients was statistically significant (Appendix 1). A linear regression model (Appendix 2) showed that studies that adjusted for more confounding variables had lower risk estimates than studies that adjusted for fewer or no potentially confounding variables. For both stroke outcomes, the risk estimates remained above 1 even after adjusting for more than ten potential risk factors although the confidence intervals crossed 1.

DISCUSSION

Our systematic review and meta-analysis of 16 prospective cohort studies finds that the elevated serum uric acid level in adults is associated with a modest but statistically significant increased risk of stroke incidence and mortality.

There has been considerable debate whether uric acid is neuro-protective as an antioxidant or neuro-toxic as a pro-oxidant 12, 48, 49. A pathogenetic role for uric acid in cardiovascular disease also remains to be elucidated, although recent experimental studies have shown that hyperuricemia is associated with endothelial dysfunction, local oxidant generation, elevated circulating levels of systemic inflammatory mediators such as monocyte chemoattractant protein-1, NF-κB, interleukin-1β, interleukin-6, and tumor necrosis factor-α, and vascular smooth muscle proliferation 18, 19, 5053. Hypertension, one of the most common causes of stroke, is closely related to hyperuricemia 19. Several experimental animal models showed the development of systemic hypertension in hyperuricemic rats 5457. In a recent randomized, placebo-controlled, crossover trial 58 involving 30 hyperuricemic adolescents with newly diagnosed hypertension, allopurinol treatment was associated with significant reductions in casual and 24-hour ambulatory blood pressure compared to placebo. More clinical trials with longer follow-up periods are needed to determine the safety and the generalizability of urate-lowering therapy such as allopurinol in hypertension.

Interestingly, many previous studies that investigated the role of the uric acid level on either cardiovascular disease or all-cause mortality observed a J-curve relationship 11, 16, 5961. Similar results were noted in some of the studies included in our analysis 14, 15, 35, 42, 44. It has been postulated that a low uric acid level is associated with a higher mortality because uric acid may play an antioxidant role 19.

The limitations of this meta-analysis fall into two categories: those attributable to the data available for analysis and those attributable to the techniques generally used to perform the meta-analysis. Our analysis is based on observational studies which are subject to confounding and other biases and cannot prove causality. Randomized clinical trials were, however, neither generally useful to evaluate etiological hypotheses over a long period of follow-up 31, nor available in the literature to examine our study questions. We selected only large prospective studies with inception cohort free of disease, which helped increase precision of estimates while minimizing heterogeneity. There were different definitions of hyperuricemia across the studies; therefore, we chose the category nearest to 6.8 mg/dl in each study for the hyperuricemia group. Although studies differed by geographic location, age, race, sex distribution and size, meta-regression analysis did not reveal any significant association with these factors. Nonetheless, we cannot rule out other potential sources for heterogeneity such as clinical features.

All meta-analyses are inherently vulnerable to publication bias. We attempted to minimize this bias by searching three major electronic databases with no language restriction. Three different statistical tests to examine the issue of publication bias were performed revealing no statistical evidence for significant publication bias. Lastly, because we did not have access to the raw data on adjustments in each study, we utilized the best adjusted RRs per individual study. The use of medications such as diuretics was adjusted for in only a few studies 14, 39, 41, 42. For the stroke outcome data, there is a possibility of misclassification bias because most of the papers we included used death certificates or diagnostic codes to define their outcomes.

Our study has several important strengths. This meta-analysis is based on large prospective cohort studies over a long follow-up period in many different countries. To our knowledge, this is the first systematic review and meta-analysis on hyperuricemia and the risk of stroke. We assessed the quality of individual studies using the Newcastle–Ottawa Scale 28. The majority of the included studies had adequate sizes, follow-up lengths, and adjustments for other risk factors. We furthermore performed subgroup analyses of the studies with full adjustments for known stroke risk factors as the degree of adjustments for potential confounders was still different in each study.

In conclusion, our meta-analysis of published prospective studies suggests that high serum uric acid levels may modestly increase the risk of stroke incidence and mortality. Future research should focus on confirming the pathogenetic mechanisms of hyperuricemia as well as examining the role of urate-lowering therapy in stroke.

ACKNOWLEDGMENTS

Seo Young Kim is funded, in part, by a National Institutes of Health T32 training grant for training program in rheumatic disease.

Appendix 1

Effect of study variables by meta-regression

StrokeIncidenceStrokeMortality
Coefficient95 % CICoefficient95 % CI
Gender−0.09−0.33-0.140.21−0.11-0.53
Year0.003−0.02-0.03−0.06−0.12-0.01
Race0.25−0.14-0.650.27−0.14-0.69

CI; confidence interval

Appendix 2

Linear regression plot for the relative risks (RR) of stroke against the number of adjusted risk factors in each study

An external file that holds a picture, illustration, etc.
Object name is nihms117715f5.jpg

CI: confidence interval

Footnotes

Financial supports or conflicts disclosure

S Kim - NIH T32 (AR07442) Training Program in Rheumatic Disease

HK Choi - Holds the Mary Pack Arthritis Society of Canada Chair in Rheumatology, served on the advisory board for TAP and Savient Pharmaceuticals

JP Guevara and DA Albert – None

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