Circulation Journal
Online ISSN : 1347-4820
Print ISSN : 1346-9843
ISSN-L : 1346-9843
Arrhythmia/Electrophysiology
Uric Acid Level and Prevalence of Atrial Fibrillation in a Japanese General Population of 285,882
Shin KawasoeTakuro KubozonoShiro YoshifukuSatoko OjimaNaoya OketaniMasaaki MiyataHironori MiyaharaShigeho MaenoharaMitsuru Ohishi
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2016 Volume 80 Issue 12 Pages 2453-2459

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Abstract

Background: The association between serum uric acid (UA) levels and atrial fibrillation (AF) in the general population in Japan is not well known.

Methods and Results: In total, 285,882 consecutive subjects (men, 130,897; women, 154,985; age, 58±15 years) not receiving treatment for hyperuricemia who underwent health checkups were enrolled. Subjects were stratified into deciles according to age, body mass index, estimated glomerular filtration rate, systolic blood pressure, and UA level. AF prevalence was calculated for each decile. The odds ratio that defined the decile with the lowest AF prevalence as reference was calculated in each sex. In men, the mean UA was 6.0±1.4 mg/dl; AF prevalence was 1.8% and was lowest in the decile with UA 4.4–4.9 mg/dl. Deciles with both high and low UA (5.4–5.6 mg/dl to >7.8 mg/dl and <4.3 mg/dl) were associated with significantly higher AF prevalence. In women, the mean UA was 4.5±1.1 mg/dl; AF prevalence was 0.7% and was lowest in the decile with UA 3.6–3.8 mg/dl. Deciles with highest UA (5.0–5.2 mg/dl to >5.9 mg/dl) were associated with significantly higher AF prevalence. The analysis adjusted for other clinical covariates demonstrated an independent association between UA and AF in both sexes.

Conclusions: In a representative Japanese general population, UA level was significantly associated with AF, independently of other cardiovascular risk factors. (Circ J 2016; 80: 2453–2459)

Atrial fibrillation (AF) is the most common type of arrhythmia and a worldwide health problem. The AF prevalence in the Japanese general population is between 1.35%1 and 1.6%;2 it is increasing and is expected to rise further as life expectancy increases globally. AF is associated with decreased quality of life and increased frequency of prolonged hospitalization because of its clinical consequences such as heart failure and stroke.3 Despite recent advances in therapy, including the use of anticoagulant agents, rate control, and techniques to maintain sinus rhythm, the mortality and morbidity of patients with AF remains unacceptably high. Thus, we need to identify patients at high risk of AF to devise prevention strategies.

Many epidemiological studies have reported risk factors for AF, with aging being one of the key risk factors. Age-related fibrosis or accumulation of accompanying disorders that occur with increasing frequency in older individuals may explain this association.4 Another important and well-established risk factor is heart failure,5 including with reduced or preserved ejection fraction6 and with coronary artery disease.7 Other reported risk factors include male sex,5,7 hypertension,8 chronic kidney disease,9 sleep apnea syndrome,10 and metabolic factors such as obesity11 and diabetes mellitus.12

Many studies have reported associations between hyperuricemia and cardiovascular diseases, including ischemic heart disease,13 heart failure,14 stroke,15 and other atherosclerotic disorders.16,17 Conversely, several studies have reported an association between high serum uric acid (UA) levels and the onset of AF. However, those studies were performed in small populations or in patients at high risk of cardiovascular diseases. Therefore, the correlation between UA and AF needs to be clarified in large, general populations.

Here we aimed to investigate the association between serum UA levels and AF prevalence, including sex specificity, in the general Japanese population.

Methods

Study Population

In total, 325,771 consecutive subjects who underwent routine health checkups at the JA Kagoshima Kouseiren Medical Health Care Center from January, 1979 to December, 2013 were enrolled in this cross-sectional study. Subjects who were receiving medical treatment for hyperuricemia or those with missing serum UA measurement data were excluded, leaving 285,882 included in the final analysis.

This study conformed to the Declaration of Helsinki and was approved by the Institutional Ethics Committee of the Graduate School of Medical and Dental Sciences, Kagoshima University and JA Kagoshima Kouseiren Hospital.

Data Collection

Data regarding medical history, including history of hypertension, diabetes mellitus, dyslipidemia, and cardiovascular diseases, and medication history was obtained through self-administered questionnaires. Body mass index (BMI, kg/m2) was calculated for each subject. Blood pressure was measured using a mercury sphygmomanometer after subjects sat quietly for 5 min. A 12-lead surface ECG was performed. Blood samples were obtained in the overnight non-fasting state.

Serum UA, triglyceride, low-density lipoprotein-cholesterol, high-density lipoprotein-cholesterol, and creatinine levels were measured using standard laboratory procedures. The estimated glomerular filtration rate (eGFR) was determined according to the new Japanese coefficient for the modified isotope dilution mass spectrometry-traceable Modification of Diet in Renal Disease study equation:

eGFR=194×SCr−1.094×age−0.287

For women, eGFR was multiplied by a correction factor of 0.739;18 the cardiovascular risk factors were defined as follows: hypertension: current use of antihypertensive medications, systolic blood pressure (SBP) ≥140 mmHg, and/or diastolic blood pressure (DBP) ≥90 mmHg; diabetes mellitus: active treatment with oral hypoglycemic agents or insulin, or glycosylated hemoglobin ≥6.5%; dyslipidemia: use of lipid-lowering agents, serum triglycerides ≥150 mg/dl, serum low-density lipoprotein-cholesterol ≥140 mg/dl, or serum high-density lipoprotein-cholesterol <40 mg/dl.

Definition of AF

AF was diagnosed using 12-lead surface ECG; subjects with a history of AF were assigned to the AF group. Although we could recognize the existence of cardiac disease in the medical questionnaire used in the health checkups, we could not study the details of the diseases. The evaluation of cardiac function by echocardiography was not included in the present health check-up, and the subjects of this study did not undergo routine echocardiographic examination. Therefore, we could not determine the number of subjects with existing valvular heart disease.

Statistical Analysis

As serum UA levels differ substantially between the sexes, results were analyzed separately for men and women. Continuous variables, including age, BMI, BP, eGFR, and serum UA concentration, are expressed as mean±standard deviation. Categorical variables, including presence of cardiovascular disease or cardiovascular risk factors, are expressed as number of subjects and proportions (percentages). Differences between men and women for continuous and categorical variables were analyzed using Student’s unpaired t-test and the χ2 test, respectively. Subjects were stratified into deciles by each continuous variable, including age, BMI, eGFR, SBP, and UA level, and AF prevalence was calculated for each decile. Furthermore, using logistic regression analysis, the odds ratio (OR) that defined the decile with the lowest AF prevalence as reference was calculated for each sex. Regarding serum UA levels, the results of logistic regression analysis were adjusted for other clinical variables. Univariate and multivariate logistic regression analyses, using clinical variables as continuous parameters, were performed to identify factors associated with AF.

All statistical analyses were performed using JMP Pro version 11 (SAS Institute Inc, Cary, NC, USA) for Windows. P<0.05 was considered significant.

Results

Characteristics of the Study Population

The clinical characteristics of subjects are summarized in Table 1. There were 130,897 men (46%; mean age, 57±16 years) and 154,985 women (54%; mean age, 58±16 years). The average serum UA level was higher in men than in women (men, 6.0±1.4 mg/dl; women, 4.5±1.1 mg/dl; P<0.0001). Furthermore, AF prevalence was higher in men (1.8%) than in women (0.7%; P<0.0001).

Table 1. Characteristics of Health Study Subjects
Variable Men
(n=130,897)
Women
(n=154,985)
P value
Age (years) 56.7±15.8 57.7±15.9 <0.0001
BMI (kg/m2) 23.4±3.3 22.8±3.5 <0.0001
Hypertension, n (%) 49,609 (36.4) 52,938 (32.6) <0.0001
Diabetes mellitus, n (%) 7,178 (10.4) 4,748 (6.6) <0.0001
Dyslipidemia, n (%) 60,626 (45.9) 67,115 (42.7) <0.0001
Cardiovascular disease, n (%)
 AF 2,395 (1.8) 1,035 (0.7) <0.0001
 Chronic heart failure 355 (0.3) 248 (0.2) <0.0001
 Ischemic heart disease 1,731 (1.3) 1,204 (0.7) <0.0001
 Stroke 1,912 (1.4) 1,258 (0.8) <0.0001
eGFR (ml/min/1.73 m2) 77.4±17.2 78.3±18.0 <0.0001
UA (mg/dl) 6.0±1.4 4.5±1.1 <0.0001

AF, atrial fibrillation; BMI, body mass index; eGFR, estimated glomerular filtration rate; UA, uric acid.

Association Between AF Prevalence and Other Parameters

Associations between AF prevalence and other parameters categorized into deciles are shown in Table 2.

Table 2. Association Between AF Prevalence and Other Parameters Categorized Into Deciles
Men
 Age (years) <37 38–44 45–50 51–55 56–60 61–64 65–67 68–71 72–76 ≥77
  AF (%) 0.1 0.2 0.5 0.8 1.3 2.0 2.2 3.2 3.6 5.0
  OR Ref. 2.74 7.10 12.73 21.28 31.01 34.97 51.43 58.86 81.86
  95% CI   1.31–
6.22
3.71–
15.33
6.81–
27.12
11.58–
44.81
16.94–
65.11
19.06–
73.59
28.27–
107.66
32.4–
123.10
45.11–
171.09
  P value   0.0063 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
 BMI (kg/m2) <19.4 19.5–20.6 20.7–21.6 21.7–22.4 22.5–23.1 23.2–23.9 24.0–24.8 24.9–25.8 25.9–27.4 ≥27.5
  AF (%) 1.6 1.7 1.6 1.8 1.8 1.7 2.0 1.9 1.9 2.3
  OR Ref. 1.06 1.02 1.10 1.12 1.09 1.23 1.21 1.19 1.45
  95% CI   0.87–1.29 0.84–1.25 0.94–1.30 0.89–1.33 0.89–1.32 1.02–1.48 1.03–1.52 0.97–1.42 1.19–1.72
  P value   0.5595 0.8064 0.3367 0.2299 0.3597 0.0247 0.0431 0.0658 <0.0001
 eGFR
(ml/min/1.73 m2)
<57.6 57.7–64.0 64.1–68.7 68.8–72.7 72.8–76.6 76.7–80.5 80.6–84.9 85.0–90.3 90.4–98.4 ≥98.5
  AF (%) 5.1 3.2 2.6 1.9 1.5 1.2 1.2 0.8 0.5 0.5
  OR 11.55 7.19 5.75 4.24 3.22 2.61 2.50 1.66 Ref. 1.05
  95% CI 9.10–15.62 5.70–9.91 4.51–7.90 3.31–5.89 2.43–4.40 1.91–3.54 1.90–3.51 1.22–2.35   0.75–1.54
  P value <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 0.0017   0.7771
 SBP (mmHg) <104 105–110 111–115 116–120 121–123 124–128 129–132 133–138 139–148 ≥149
  AF (%) 1.0 1.0 1.0 1.1 0.8 1.0 1.2 1.2 1.4 1.3
  OR 1.20 1.20 1.13 1.28 Ref. 1.15 1.47 1.37 1.71 1.58
  95% CI 0.73–2.01 0.73–2.02 0.67–1.92 0.80–2.11   0.70–1.92 0.90–2.46 0.84–2.30 1.06–2.81 0.98–2.63
  P value 0.4708 0.4632 0.6452 0.3039   0.5771 0.1192 0.2032 0.0250 0.0601
 UA (mg/dl) <4.3 4.4–4.9 5.0–5.3 5.4–5.6 5.7–6.0 6.1–6.3 6.4–6.6 6.7–7.1 7.2–7.7 ≥7.8
  AF (%) 1.5 1.2 1.3 1.5 1.7 1.9 1.7 2.1 2.5 3.0
  OR 1.25 Ref. 1.09 1.25 1.39 1.57 1.42 1.72 2.10 2.49
  95% CI 1.01–1.53   0.88–1.35 1.01–1.54 1.14–1.68 1.28–1.91 1.15–1.74 1.42–2.08 1.73–2.54 2.07–2.99
  P value 0.0332   0.3999 0.0362 0.0007 <0.0001 0.0011 <0.0001 <0.0001 <0.0001
Women
 Age (years) <37 38–45 46–52 53–57 58–61 62–65 66–69 70–72 73–76 ≥77
  AF (%) 0.04 0.05 0.1 0.2 0.4 0.4 0.8 1.1 1.6 2.2
  OR Ref. 1.13 2.61 4.42 9.12 9.07 19.02 25.04 35.64 51.12
  95% CI   0.40–
3.24
1.14–
6.68
2.04–
10.97
4.46–
21.94
4.47–
21.73
9.62–
44.87
12.64–
59.13
18.15–
83.71
26.16–
119.71
  P value   0.8045 0.0214 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
 BMI (kg/m2) <18.6 18.7–19.8 19.9–20.7 20.8–21.6 21.7–22.4 22.5–23.3 23.4–24.2 24.3–25.4 25.5–27.3 ≥27.4
  AF (%) 0.5 0.6 0.6 0.6 0.6 0.7 0.7 0.7 0.8 0.9
  OR Ref. 1.28 1.22 1.10 1.28 1.39 1.40 1.31 1.61 1.82
  95% CI   0.93–1.72 0.89–1.67 0.77–1.47 0.90–1.69 1.03–1.89 1.02–1.89 0.97–1.78 1.16–2.08 1.30–2.30
  P value   0.0957 0.1923 0.5272 0.0958 0.0261 0.0220 0.0706 0.0008 <0.0001
 eGFR
(ml/min/1.73 m2)
<57.5 57.6–64.0 64.1–68.7 68.8–72.8 72.9–76.9 77.0–81.1 81.2–85.9 86.0–91.9 92.0–101.0 ≥101.1
  AF (%) 2.6 1.2 0.7 0.6 0.4 0.3 0.3 0.3 0.2 0.2
  OR 16.4 7.19 4.27 3.83 2.29 1.87 2.00 1.60 Ref. 1.20
  95% CI 11.12–
25.09
4.76–
11.05
2.67–
6.47
2.34–
5.73
1.43–
3.69
1.21–
3.21
1.24–
3.27
0.96–
2.64
  0.70–
2.04
  P value <0.0001 <0.0001 <0.0001 <0.0001 0.0003 0.0093 0.0034 0.0593   0.4940
 SBP (mmHg) <98 99–105 106–110 111–115 116–120 121–124 125–130 131–136 137–144 ≥145
  AF (%) 0.2 0.1 0.2 0.2 0.2 0.3 0.4 0.3 0.4 0.3
  OR 2.46 Ref. 2.62 2.55 2.08 3.89 4.37 4.06 5.06 3.70
  95% CI 0.80–9.10   0.87–9.55 0.80–9.58 0.67–7.71 1.33–14.07 1.65–15.03 1.43–14.44 1.85–17.69 1.31–13.16
  P value 0.1169   0.0862 0.1124 0.2032 0.0122 0.0020 0.0071 0.0010 0.0123
 UA (mg/dl) <3.1 3.2–3.5 3.6–3.8 3.9–4.1 4.2–4.3 4.4–4.6 4.7–4.9 5.0–5.2 5.3–5.8 ≥5.9
  AF (%) 0.4 0.4 0.3 0.4 0.4 0.4 0.4 0.8 1.1 2.0
  OR 1.19 1.14 Ref. 1.11 1.18 1.37 1.40 2.44 3.37 6.59
  95% CI 0.80–1.77 0.76–1.69   0.76–1.63 0.78–1.77 0.95–1.97 0.97–2.03 1.74–3.48 2.48–4.69 4.92–9.04
  P value 0.3811 0.5088   0.5697 0.4170 0.0834 0.0691 <0.0001 <0.0001 <0.0001

CI, confidence interval; OR, odds ratio; SBP, systolic blood pressure. Other abbreviations as in Table 1.

In men, AF prevalence was lowest in the age decile under 37 years (0.1%), and it increased significantly with increasing age. In the decile above 77 years, AF prevalence was 5.0%, and OR was 81.86 (P<0.0001) compared with the decile under 37 years. Regarding BMI, AF prevalence was lowest in the decile with BMI <19.4 kg/m2 (1.6%); the prevalence increased with increasing BMI; particularly in the decile >27.5 kg/m2, it significantly increased to 2.3% compared with that of the decile under 19.4 kg/m2 (OR=1.45, P<0.0001). AF prevalence was lowest in the decile with eGFR 90.4–98.4 ml/min/1.73 m2 (0.5%) and significantly high in those with lower eGFR. No clear association was found between SBP and AF prevalence.

Deciles with higher UA levels (5.4–5.6 mg/dl to >7.8 mg/dl) showed significantly higher AF prevalence than those with UA levels 4.4–4.9 mg/dl, with the latter having the lowest AF prevalence. In addition, AF prevalence in the decile with lowest UA levels (UA <4.3 mg/dl) was significantly higher than that in the decile with levels 4.4–4.9 mg/dl (OR=1.25, P=0.0332).

In women, the relationships of AF prevalence with age, BMI, and eGFR were similar to those observed in men. However, in deciles with higher SBP of 121–124 mmHg, AF prevalence was significantly higher than in the reference SBP decile (SBP, 99–105 mmHg). Furthermore, deciles with higher UA levels (5.0–5.2 mg/dl to >5.9 mg/dl) had a significantly higher AF prevalence than those with UA levels 3.6–3.8 mg/dl (OR=2.44 to 6.59, P<0.0001 for all), with the latter having the lowest prevalence. As observed in men, there was a trend towards higher AF prevalence in deciles with lower UA levels (<3.1 mg/dl and 3.2–3.5 mg/dl) than in the decile with UA levels 3.6–3.8 mg/dl; however, this trend did not reach significance.

Independent Association Between UA Level and AF Prevalence

The Figure shows the OR obtained from the adjusted logistic regression analysis for each UA decile compared with the lowest AF prevalence decile as the reference. ORs were adjusted for clinical covariates, including age, eGFR, BMI, and coexisting diseases, such as hypertension, diabetes mellitus, dyslipidemia, heart failure, ischemic heart disease, and stroke.

Figure.

Adjusted odds ratios (ORs) for the prevalence of atrial fibrillation (AF) according to serum uric acid (UA) decile in men (A) and women (B). ORs were adjusted for clinical covariates, including age; eGFR; BMI; and coexisting disease such as hypertension, diabetes mellitus, dyslipidemia, heart failure, ischemic heart disease, and stroke. *P<0.05; **P<0.001.

In men, deciles with higher UA levels (5.4–5.6 mg/dl to >7.8 mg/dl) had a significantly higher AF prevalence than those with UA levels 4.4–4.9 mg/dl. Furthermore, the decile with the lowest UA levels (<4.3 mg/dl) had a higher AF prevalence than that with UA levels 4.4–4.9 mg/dl (OR=1.42, P=0.0171).

In women, deciles with higher UA levels (5.0–5.2 mg/dl to >5.9 mg/dl) had a significantly higher AF prevalence than those with UA levels 3.6–3.8 mg/dl. Furthermore, deciles with lower UA levels (<3.1 mg/dl and 3.2–3.5 mg/dl) had a higher AF prevalence than that with UA levels 3.6–3.8 mg/dl; however, these differences did not reach significance (decile with UA levels <3.1 mg/dl, OR=1.84, P=0.0702; decile with UA levels 3.2–3.5 mg/dl, OR=1.82, P=0.0737).

Multivariate Analyses of Factors Associated With AF

Table 3 shows the results of logistic regression analysis for factors associated with AF. In men, the univariate analysis revealed that all variables were significantly associated with AF; the multivariate analysis revealed that age, BMI, eGFR, UA, and the presence of diabetes mellitus, dyslipidemia, chronic heart failure, ischemic heart disease, and stroke were significantly associated with AF, but not with hypertension. In women, univariate analysis revealed that all variables, except dyslipidemia, were significantly associated with AF; multivariate analysis revealed that all variables, except BMI and the presence of hypertension or ischemic heart disease, were significantly associated with AF.

Table 3. Factors Associated With AF
  Univariate Multivariate
OR 95% CI P value OR 95% CI P value
Men
 Age 1.07 1.06–1.07 <0.0001 1.06 1.05–1.06 <0.0001
 BMI 1.02 1.01–1.04 <0.0001 1.08 1.06–1.09 <0.0001
 Hypertension 1.67 1.54–1.81 <0.0001 0.99 0.89–1.10 0.8882
 Diabetes mellitus 1.34 1.15–1.56 0.0002 1.40 1.19–1.63 <0.0001
 Dyslipidemia 0.66 0.61–0.72 <0.0001 0.69 0.61–0.77 <0.0001
 Chronic heart failure 9.11 6.66–12.20 <0.0001 6.27 4.42–8.69 <0.0001
 Ischemic heart disease 3.27 2.63–4.01 <0.0001 1.70 1.34–2.12 <0.0001
 Stroke 3.98 3.29–4.77 <0.0001 2.10 1.71–2.55 <0.0001
 eGFR 0.95 0.95–0.96 <0.0001 0.98 0.98–0.98 <0.0001
 UA 1.20 1.17–1.23 <0.0001 1.19 1.14–1.24 <0.0001
Women
 Age 1.09 1.08–1.10 <0.0001 1.07 1.06–1.08 <0.0001
 BMI 1.03 1.01–1.05 <0.0001 1.00 0.97–1.03 0.7225
 Hypertension 2.27 2.01–2.56 <0.0001 1.17 0.97–1.41 0.0858
 Diabetes mellitus 2.14 1.63–2.77 <0.0001 1.80 1.36–2.35 <0.0001
 Dyslipidemia 0.92 0.81–1.04 0.2043 0.68 0.56–0.82 <0.0001
 Chronic heart failure 17.37 11.16–25.86 <0.0001 9.91 6.10–15.48 <0.0001
 Ischemic heart disease 2.58 1.58–3.88 0.0003 1.31 0.80–2.03 0.2577
 Stroke 3.89 2.65–5.48 <0.0001 2.10 1.40–3.02 0.0005
 eGFR 0.94 0.94–0.95 <0.0001 0.98 0.97–0.98 <0.0001
 UA 1.72 1.65–1.80 <0.0001 1.44 1.34–1.55 <0.0001

Abbreviations as in Tables 1,2.

Discussion

In this cross-sectional study of a large sample, we found an interesting association between serum UA levels and AF prevalence. In men, AF prevalence increased in both deciles with high and low UA levels. Although a similar trend was observed in women, high serum UA levels had a stronger association with AF prevalence in women than in men.

Hyperuricemia and AF

The association between UA level and cardiovascular diseases, such as cardiovascular events, heart failure, and carotid atherosclerosis, has been reported,19 and a few studies have reported the association between hyperuricemia and AF. Tamariz et al reported a significant association between hyperuricemia and AF in their prospective study of 15,382 ethnically-diverse subjects.20 Suzuki et al demonstrated a similar significant association in a cross-sectional study of approximately 7,155 cardiovascular outpatients with high cardiovascular risk.21 On the other hand, the evidence of an independent association between serum UA levels and cardiovascular diseases is weak and less consistent in healthy populations. We demonstrated an independent association between serum UA levels and AF prevalence in 285,882 subjects from a Japanese general population with a mean age of 57 years (range, 19–99 years).

Serum UA is the final product of purine metabolism catalyzed by xanthine oxidase. Xanthine oxidase has been reported to be correlated with oxidative stress22 and elevation of systemic inflammatory markers. Thus, serum UA levels are considered a marker of tissue oxidative stress and inflammation.23 Electrical and structural remodeling of the left atrium is an important process in the pathogenesis of AF.2426 Onset and persistence of AF is posited to be associated with oxidative stress27 and inflammation.28,29 A previous study reported that serum UA levels significantly correlated with the left atrial diameter and hyperuricemia, and that UA was an important risk factor for new-onset AF.30 Recently, a further explanation of the association between high UA levels and AF has emerged. Intracellular accumulation of UA via activation of urate transporters (UATs) is posited to cause cell injury through several signaling pathways.31 UATs are expressed not only in renal tubular cells but also vascular smooth muscle cells and endothelial cells.32,33 Intracellular UA uptake by UATs reportedly enhances Kv1.5 protein expression, which may be attributable to shortening of the action potential duration (APD), resulting in the initiation or sustainment of AF.34

Hyperuricemia is caused by accelerated generation of UA and/or impaired excretion in the kidney and is classified into 3 types: overproduction, underexcretion, and mixed types. We lacked data on urinary excretion of UA, and therefore we could not determine the type of hyperuricemia in the present subjects. There are no reports that show AF prevalence related to the type of hyperuricemia, and further study is needed to clarify this point, including the underlying mechanisms.

Hypouricemia and AF

The association between serum UA levels and the risk of cardiovascular events or death reportedly follows a J-shaped curve. A previous study reported that serum UA levels <4.5 mg/dl in men and <3.2 mg/dl in women were associated with increased risk cardiovascular diseases.35 Another study showed that subjects with serum UA levels <4.9 mg/dl were at increased risk of death from cardiovascular diseases.36

In this study, we first demonstrated that extremely low UA levels were associated with an increased risk of AF in the general population. The AF prevalence increased at serum UA levels <4.3 mg/dl in men and <3.5 mg/dl in women. UA is a powerful antioxidant and scavenger of singlet oxygen and radicals;37 it has been shown to contribute as much as 60% of free radical scavenging in human serum.38 Previous study reported that elevated reactive oxygen species resulted in shortening of the atrial APD by increasing the transient outward current (Ito)39 and producing delayed afterdepolarizations by increasing sarcoplasmic reticulum Ca2+ release via enhanced ryanodine receptor activity.40 The relationship between renal hypouricemia related to SLC22A12 (URAT1) or SLC2A9 (GLUT9) gene mutations and exercise-induced acute renal failure has been reported in several studies.41,42 Murakami et al proposed that increased oxidative stress because of renal hypouricemia induced renal arterial spasms after exercise, resulting in loss of kidney function.43 Although extremely low UA levels may increase oxidative stress in the left atrium, increasing the risk of AF, further studies are warranted to elucidate the currently poorly-understood association between hypouricemia and AF.

In the present study, there were 1,214 subjects (men, 296 and women, 918) whose UA values were <2.0 mg/dl, and 2 male subjects (0.7%) and 5 female subjects (0.5%) had AF. In women, the AF prevalence in those with UA <2.0 mg/dl was slightly higher than that in women with a UA value in the 1st decile (UA <3.1 mg/dl, 0.4%) or in women with a value in the reference range (UA=3.6–3.8 mg/dl, 0.3%), but the result did not reach statistical significance. In men, the AF prevalence in subjects with UA <2.0 mg/dl was not higher than that in men with a UA value in the 1st decile (UA <4.3 mg/dl, 1.5%) or in those with a value in the reference range (UA=4.4–4.9 mg/dl, 1.2%). Consequently, we could not demonstrate higher AF prevalence in subjects with UA <2.0 mg/dl. The reason for this may be that the subjects with UA <2.0 mg/dl were younger in the female group and had lower BMI and higher eGFR in both sexes compared with the other groups. Further studies are needed to clarify the association between extremely low levels of UA and AF.

Sex Differences in the Association Between UA and AF

Several studies have demonstrated that hyperuricemia in women is more strongly associated with cardiovascular events44 and death45 than in men. Increased UA levels are reportedly associated with a greater risk of AF among women.20 Corroborating those studies, we demonstrated that high UA levels were more strongly associated with AF prevalence in women compared with men. Although the mechanism underlying this sex difference remains unknown, it may be attributable to differences in the sex hormones. Menopause is associated with increased serum UA levels because of the uricosuric effect of estrogen that induces UA excretion from kidney’s proximal tubules. Further studies are warranted to elucidate the underlying mechanism of sex-related differences in the association between serum UA levels and AF prevalence.

Beneficial Effects of UA-Lowering Therapy

We demonstrated an independent relationship between increased serum UA levels and AF prevalence. UA-lowering therapy has been shown to be beneficial in patients with coronary artery disease46 and heart failure,47 and early intervention is expected to reduce the possibility of AF. However, the efficacy of such therapy in lowering the AF risk and for cardiovascular mortality prevention remains unknown.

The AF prevalence increased at serum UA levels of 5.3 mg/dl in men and 5.0 mg/dl in women. Despite the differences in the distribution of serum UA levels between men and women, limited dissociation between serum UA levels increasing AF prevalence was observed in each sex. Hyperuricemia was generally defined as serum UA level ≥7.0 mg/dl based on the limit of serum-solubility in both sexes. Even in patients with gout, the recommended serum UA level for recurrence prevention and tophi resolution is <6.0 mg/dl.48 Even after assuming the efficacy of aggressive UA-lowering therapy, treatment goals need to be determined. Further studies are warranted to elucidate the association between hyperuricemia and AF prevalence.

Study Limitations

First, we were unable to clarify the causal relationship between serum UA levels and AF prevalence and determine the predictive value of UA on incident AF because of the cross-sectional design. Therefore, a longitudinal study should be performed. Second, the subjects were limited to participants in health checkups at a single facility in Japan. Third, we might have underestimated AF prevalence by failing to notice paroxysmal or persistent AF without symptoms, as the diagnosis of AF was made on the basis of 12-lead ECG or self-reported medical history. Finally, we did not include data regarding medications, such as diuretics or renin-angiotensin system inhibitors, that may affect serum UA levels and AF prevalence, or regarding menopause, which may influence serum UA levels in women. We also lacked data about lifestyle factors, including drinking, smoking and exercise, which are reported to affect serum UA levels and AF prevalence. Therefore, further research that includes these factors should be performed.

Conclusions

In a large Japanese population of health check-up subjects, serum UA levels were significantly associated with AF prevalence in both men and women, an association that was independent of other cardiovascular risk factors.

References
 
© 2016 THE JAPANESE CIRCULATION SOCIETY
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