Association Between Serum Uric Acid Levels and Progression of Coronary Artery Calcification in Asian Population

DOI: https://doi.org/10.21203/rs.3.rs-139520/v1

Abstract

Background: Coronary artery calcium (CAC) is associated coronary heart disease risk. In addition, CAC progression is associated with worsening coronary atherosclerosis and predicts future cardiac events. We aimed to investigate risk factors for the progression of CAC in an asymptomatic Japanese population using low dose computed tomography (CT) lung cancer screening performed during routine health checkup.

Methods: The risk factors for CAC progression were analyzed in 771 asymptomatic subjects who underwent repeated CAC measurement.

Results: Of the 771 subjects, 632 (82.0%) were males with a mean age of 56 years old, 208 (27.0%) had a history of hypertension, 299 (38.8%) had dyslipidemia, 81 (10.5%) had diabetes mellitus, and 180 (23.3%) had hyperuricemia. During observation, 103 (13.4%) subjects had CAC progression, while 515 subjects (66.8%) showed no calcification. On multivariate analysis, increasing uric acid level was significantly associated with the progression of CAC (odds ratio 1.203, 95% confidence interval 1.045-1.387, P = 0.010).

Conclusions: The results of this study show that hyperuricemia is associated with CAC progression in asymptomatic Japanese subjects.

Background

Arteriosclerosis is a cause of ischemic heart disease in many patients. It is important, therefore, to identify factors associated with the progression of arteriosclerosis to prevent ischemic heart disease. Coronary artery calcium (CAC) measured by computed tomography (CT) correlates with the amount of coronary atherosclerotic plaque, is a noninvasive technique to evaluate the severity of coronary atherosclerosis, and has been used to predict future coronary events.[1–5] Furthermore, progression of coronary atherosclerosis has been studied using CAC progression in longitudinal studies.[6–8]

A previous study showed age, sex, diabetes, and dyslipidemia to be risk factors for atherosclerotic diseases, in addition to the CAC score.[5] However, it is still unknown whether these risk factors assessed in cross-sectional studies have the same influence on progression of coronary atherosclerosis as factors assessed in longitudinal studies. Thus, we aimed to investigate risk factors of coronary atherosclerosis progression, measured as CAC progression, in an asymptomatic Japanese population using low dose CT lung cancer screening performed during a routine health checkup.

Methods

Study population

The study included 2124 asymptomatic subjects who voluntarily underwent CT scan for lung cancer screening at a general health checkup in Toranomon Hospital Health Management Center between April 2010 and December 2012 at baseline. Of these subjects, 836 had at least two visits at our institution. Of these 836 subjects, 65 were excluded from the study for the following reasons: 56 subjects had a history of coronary artery disease, 7 had a pacemaker or valve implantation that could cause artifacts, and 2 had no records of a calcium score. A total of 771 subjects were included in the final analysis. The average time between CT scans was 3.1 ± 0.9 years. Medical histories and current medications were derived from medical questionnaires. Hypertension was defined as systolic blood pressure (SBP) ≥ 140 mmHg or diastolic blood pressure (DBP) ≥ 90 mmHg without medication in the outpatient clinic on at least two separate measurements or antihypertensive medication use. Diabetes mellitus was defined as fasting blood glucose ≥ 126 mg/dL, HbA1c ≥ 6.5%, or use of medication for diabetes. Dyslipidemia was defined as total cholesterol ≥ 240 mg/dL, low-density lipoprotein (LDL) cholesterol ≥ 140 mg/dL, triglyceride (TG) ≥ 150 mg/dL, high-density lipoprotein (HDL) cholesterol < 40 mg/dL, or previous use of lipid-lowering medication. Hyperuricemia was defined as uric acid ≥ 7.1 mg/dL. Obesity was defined as a body mass index (BMI) ≥ 25 kg/m2, according to the criteria in the World Health Organization (WHO) Asia-Pacific guidelines.[9] Metabolic syndrome was classified using the NCEP/ATP-III recommendations.[10] Smoking habits (never, former, and current) were obtained from a self-completed questionnaire. The institutional review boards (IRB) at our hospital (Toranomon Hospital IRB [IRB 1175]) approved the study, informed consent was obtained from all subjects, and the study was performed in accordance with the declaration of Helsinki.

Cac Scoring Assessment And Definition Of Progression Of Cac

All subjects underwent lung cancer screening with a multidetector CT system (Acquilion 64; Toshiba Medical Systems, Tochigi, Japan). CT scans were acquired during one deep inspiratory breath hold, without use of contrast medium or ECG-gating. Low dose lung CT scan was performed using a tube voltage of 120 kV, a tube current of 60–70 mA and 30–35 mAs based on the body size of the subject, and a 300–400 mm field of view. The technical parameters for lung cancer screening CT and reconstruction of images for CAC scoring have been documented previously.[11] In brief, the image was reconstructed using non-overlapping 3.0 mm slices with a 260-mm field of view, which is the standard method used in clinical practice based on electron beam CT.[12] Use of slice thickness and overlapping reconstruction have a major influence on CAC scoring;[13] thus we used the same reconstruction protocol as that used for cardiac CT for CAC scoring. CAC scores were calculated quantitatively according to the methods by Agatston et al. [14]

We defined the progression of CAC into three groups. No calcification observed during follow up was defined as 0 calcification (group A). Using the percentage methods, CAC progression was defined as an annual percentage change ≥ 15% at follow up in some studies.[15, 16] Considering of definite CAC progression, we defined annual percentage change ≥ 20% at follow up as severe progression (group C), and < 20% change at follow up was defined as no or mild progression (group B).

Statistical analysis

Data are expressed as mean ± standard deviation for continuous variables, and as frequencies and percentages for categorical variables. The significance of differences in quantitative data was determined by the Mann-Whitney U-test and Kruskal Wallis test. Ordered logistic regression analysis was applied to determine which factors were associated with the progression of CAC (0 CAC, no or mild CAC progression, and severe CAC progression). Statistical analyses were performed using SPSS for Windows, ver. 13.0 (Chicago, IL, USA), with P < 0.05 considered significant.

Results

Clinical characteristics of the subjects

The characteristics of subjects are shown in Table 1. (Please insert Table 1 here.) Of the 771subjects, 632 (82.0%) were males with a mean age of 56 years old, 208 (27.0%) had a history of hypertension, 299 (38.8%) had dyslipidemia, 81 (10.5%) had diabetes mellitus, and 180 (23.3%) had hyperuricemia. There were 515 subjects (66.8%) in group A, 153 (19.8%) in group B, and 103 (13.4%) in group C. Compared to group A, subjects in group C were older and more likely to be male. Risk factors including renal function disorder (creatinine, estimate glomerular filtration rate (eGFR)) and uric acid level were significantly higher in group C than groups A and B. Total cholesterol, LDL cholesterol, HDL cholesterol, smoking habit, and alcohol intake were not significantly different among the three groups.

Table 1

Characteristics of the study participants
 

Group A

(n = 515)

Group B

(n = 153)

Group C

(n = 103)

P value

Age (years)

53.2 ± 9.4

61.4 ± 9.5

61.9 ± 9.1

< 0.001

Sex (male, %)

404 (78.4)

134 (87.6)

94 (91.3)

0.001

Body mass index (kg/m2)

23.4 ± 3.1

23.6 ± 2.9

24.3 ± 3.0

0.013

Abdominal circumference (cm)

83.7 ± 9.0

85.2 ± 8.2

87.0 ± 8.6

0.001

Systolic blood pressure (mmHg)

120.1 ± 13.3

123.5 ± 14.2

124.7 ± 12.2

< 0.001

Diastolic blood pressure (mmHg)

77.1 ± 9.0

78.4 ± 8.9

79.2 ± 8.6

0.067

Fasting blood glucose (mg/dL)

102.3 ± 15.3

103.7 ± 13.6

112.1 ± 32.1

< 0.001

HbA1c (%)

5.4 ± 0.5

5.5 ± 0.6

5.6 ± 0.8

< 0.001

Total cholesterol (mg/dL)

204.8 ± 32.2

210.7 ± 33.2

206.2 ± 33.9

0.158

LDL cholesterol (mg/dL)

118.7 ± 29.1

121.2 ± 28.5

117.9 ± 32.8

0.458

HDL cholesterol (mg/dL)

56.6 ± 14.9

54.2 ± 14.9

54.2 ± 13.7

0.103

Triglycerides (mg/dL)

116.6 ± 69.1

135.7 ± 95.3

133.1 ± 85.5

0.046

L/H ratio

2.24 ± 0.80

2.36 ± 0.70

2.30 ± 0.80

0.096

Creatinine (mg/dL)

0.79 ± 0.19

0.80 ± 0.15

0.93 ± 1.06

0.045

eGFR (ml/min/1.73 m2)

78.8 ± 14.3

76.0 ± 12.5

73.4 ± 15.3

< 0.001

Uric acid (mg/dL)

5.85 ± 1.32

6.04 ± 1.34

6.21 ± 1.24

0.007

Hypertension (n, %)

115 (22.3)

46 (30.1)

47 (45.6)

< 0.001

Diabetes (n, %)

45 (8.7)

14 (9.2)

22 (21.4)

< 0.001

Dyslipidemia (n, %)

175 (34.0)

73 (47.7)

51 (49.5)

< 0.001

Smoking history (n, %)

        

current

179 (35.1)

45 (30.2)

38 (37.3)

0.441

including former

363 (70.5)

112 (73.2)

81 (76.6)

0.229

CKD (eGFR < 60 ml/min/1.73 m2) (n, %)

31 (6.0)

12 (7.8)

16 (15.5)

0.004

Hyperuricemia (n, %)

102 (19.8)

40 (26.1)

38 (36.9)

< 0.001

Metabolic syndrome

86 (16.7)

33 (21.6)

27 (26.2)

0.052

Alcohol intake (≥ 20 g/day) (n, %)

157 (30.5)

40 (26.1)

38 (36.9)

0.308

Mean number of constituent factors for metabolic syndrome (n, %)

1.1 ± 1.2

1.5 ± 1.3

1.8 ± 1.2

< 0.001
Data are shown as the mean and (SD) or percentages. HbA1c, glycated hemoglobin; LDL, low-density lipoprotein; HDL, high-density lipoprotein; L/H ratio, LDL/HDL ratio; LDL, eGFR, estimated glomerular filtration rate; CKD, chronic kidney disease; SD, standard deviation

Risk Factors Associated With Severe Progression Of Cac

Univariate regression analyses were performed to determine factors affecting progression of CAC. (Please insert Table 2 here.) The progression of CAC was associated with conventional risk factors with the exception of total cholesterol, LDL cholesterol, smoking habit, and alcohol intake.

Table 2

Results of the univariate analysis of risk factors for CAC progression

Variable

Risk ratio

95%

CI

P value
   

lower limit

upper limit

  

Age (/1 year)

1.090

1.452

3.552

< 0.001

Sex (male/female)

2.262

1.452

1.109

< 0.001

Body mass index (/1 kg/m2)

1.051

1.002

1.102

0.040

Abdominal circumference (/1 cm)

1.032

1.015

1.050

< 0.001

Systolic blood pressure (/1 mmHg)

1.021

1.010

1.033

< 0.001

Diastolic blood pressure (/1 mmHg)

1.020

1.003

1.037

0.018

Fasting blood glucose (/1 mg/dL)

1.018

1.009

1.027

< 0.001

HbA1c (/1%)

1.864

1.436

2.421

< 0.001

Total cholesterol (/1 mg/dL)

1.003

0.999

1.008

0.159

LDL cholesterol (/1 mg/dL)

1.001

0.996

1.006

0.730

HDL cholesterol (/1 mg/dL)

0.989

0.979

0.999

0.037

Triglyceride (/1 mg/dL)

1.003

1.001

1.004

0.006

eGFR (ml/min/1.73 m2)

0.979

0.969

0.990

< 0.001

Uric acid (/1 mg/dL)

1.167

1.042

1.306

0.007

Hypertension (y/n)*

2.116

1.540

2.907

< 0.001

Diabetes mellitus (y/n)*

1.970

1.263

3.070

0.003

Dyslipidemia (y/n)*

1.794

1.331

2.418

< 0.001

Hyperuricemia (y/n)*

1.856

1.332

2.586

< 0.001

CKD (≥ 60/<60 ml/min/1.73 m2)

2.125

1.281

3.526

0.004

Metabolic syndrome (ATP III) (y/n)

1.551

1.083

2.221

0.017

The number of risk factors for METS(/1)

1.346

1.119

1.512

< 0.001

Smoking history (current, ex / no)

1.311

0.936

1.837

0.115

Alcohol (≥ 20/<20 g/day)

0.480

0.206

1.121

0.090
*CI, confidence interval; CAC, coronary artery calcium; HbA1C, glycated hemoglobin; LDL, low-density lipoprotein; HDL, high-density lipoprotein; eGFR, estimate glomerular filtration rate; CKD, chronic kidney disease; ATP III, Adult Treatment Panel III; METS, metabolic syndrome

The results of multivariate analysis of clinical parameters associated with progression of CAC score are shown in Table 3. The multivariate model was adjusted for age, sex, abdominal circumference, systolic blood pressure, triglyceride level, hemoglobin A1c level, eGFR, and uric acid level. On multivariate analysis, high uric acid level was significantly associated with progression of CAC (odds ratio 1.203, 95% confidence interval 1.045–1.387, P = 0.010). (Please insert Table 3 here.)

Table 3

Results of the ordered logistic regression analysis of risk factors for CAC progression

Variable

Risk ratio

95%

CI

P value
   

lower limit

upper limit

  

Age (/1 year)

1.111

1.088

1.134

< 0.001

Sex (male/female)

2.719

1.618

4.570

< 0.001

Uric acid (/1 mg/dL)

1.203

1.045

1.387

0.010

Triglyceride (/1 mg/dL)

1.002

1.000

1.004

0.030
*CI, confidence interval; CAC, coronary artery calcium

Discussion

This is the first study showing that hyperuricemia is a risk factor for CAC progression in asymptomatic Japanese subjects. There are some published studies evaluating the risk factors for CAC progression. From the MESA study, standard coronary risk factors including age, sex, race, smoking, BMI, blood pressure, and diabetes mellitus correlated with both high CAC score and progression.[8] Another studies showed that fatty liver [17] and metabolic syndrome [18] were associated with CAC progression. And recent study from China showed the association between uric acid and CAC progression in young adults with originally zero CAC [19]. Considering about the relationship between uric acid and coronary artery disease, Sun et al studied about the relationship between uric acid and coronary atherosclerosis [20], and Lv et al showed it among young adults less than 35 years of age [21]. But there are still limited number of studies which are evaluated the relationship between uric acid and CAC. Mostly many studies had not been analyzed the association with uric acid and CAC. In this study, we investigated risk factors including not only traditional coronary risk factors but also uric acid level. We found hyperuricemia to be associated with CAC progression.

Although it has been hypothesized that uric acid provides an antioxidant defense in humans, previous clinical and epidemiological studies suggested that elevated uric acid levels are associated with cardiovascular diseases. Several publications demonstrated the association between serum uric acid levels and cardiovascular disorders, including hypertension, [22–24] coronary artery disease, [25–27] and carotid artery atherosclerosis.[28] The potential mechanisms of the association between hyperuricemia and cardiovascular diseases are related to xanthine oxidase and urate transporters. Higher concentration of uric acid may reflect high levels of xanthine oxidase activity and oxidative stress. The action of xanthine oxidase leads to generation of superoxide anions and is one of the principle sources of reactive oxygen species (ROS) in the human vasculature. [29, 30] Allopurinol is rapidly metabolized to ozypurinol, an analogue of xanthine that preferentially binds to xanthine oxidase, thereby inhibiting its activity.[31] A recent study revealed that urate transporters, which have a major role in renal regulation of urate excretion, are expressed in smooth muscle cells. In case of hyperuricemia, urate transporters may allow uric acid to enter human vascular smooth muscle cells. [32, 33] As a result, the renin angiotensin system pathway is activated and NO synthesis is inhibited, causing endothelial dysfunction and cardiovascular diseases.

This study has several limitations. First, the study was retrospective and subjects were self-referred, which may have caused a selection bias compared to population-based participants. In addition, subjects were enrolled based on repeated participation in health screening examinations, and subjects who did not undergo a second CT scan were excluded. Second, use of lung cancer screening CT may also be a limitation, because the CAC score using this method tends to be lower than that that using ECG-gated CT. [11, 34, 35] The main reason for the lower score may be the radiation dose used in lung cancer screening CT, which is lower than that that used in ECG-gated CT. However, a recent meta-analysis by Xie et al. [34] showed that CAC score categories correlated well between ECG-gated CT and lung cancer screening CT, although the values were still slightly lower than in ECG gated CT. Third, the follow up duration may not be sufficient to evaluate CAC progression. More long-term follow up studies are warranted.

Conclusions

Our study showed that CAC progressed in one-third of subjects and hyperuricemia was a risk factor for CAC progression in this asymptomatic Japanese population.

Abbreviations

BMI

body mass index; CAC:coronary artery calcium; CT:computed tomography; DBP:diastolic blood pressure; ECG:electrocardiogram; eGFR:estimated glomerular filtration rate; HbA1c:glycated hemoglobin; HDL:high-density lipoprotein; IRB:institutional review board; LDL:low-density lipoprotein; MESA Multi-Ethnic Study of Atherosclerosis; NCEP/ATP-III:National Cholesterol Education Program Adult Treatment Panel III; NO:nitric oxide; ROS:reactive oxygen species; SBP:systolic blood pressure; TG:triglyceride; WHO:World Health Organization

Declarations

Ethics approval and consent to participate

The institutional review boards (IRB) at our hospital (Toranomon Hospital IRB [IRB 1175]) approved the study, and informed consent was obtained from all subjects.

Consent for publication

Not applicable.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

This research received no grant from any funding agency in the public, commercial, or

not-for-profit sectors.

Authors' contributions

YOS conceived of the study, set the study design, collected data, analyzed and interpreted the data, and was a major contributor in writing the manuscript. MI, KA and YO collected data, analyzed and interpreted the data.

YA oversaw the study assessments. All authors oversaw, contributed and approved the final manuscripts.

Acknowledgement

We would like to thank all study participants.

Authors' information (optional)

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