White blood cell count: an independent predictor of coronary heart disease risk in middle-aged and elderly population with hyperuricemia

Abstract

Previous studies have shown that hyperuricemia is an independent risk factor for cardiovascular disease. The aim of the study was to examine the association between white blood cell (WBC) count and coronary heart disease (CHD) risk in middle-aged and elderly population with hyperuricemia.

Data included in this analysis were from a population-based cross-sectional study, that is, the Xiangya Hospital Health Management Center Study. Hyperuricemia was defined as uric acid ≥416 μmol/L in male population and ≥360 μmol/L in female population. The WBC count was classified into 3 categories based on the tertile distribution of the study population. Framingham risk scores calculated by the Adult Treatment Panel III charts were used to estimate 10-year CHD risk for each participant. The relationship between WBC count and CHD risk in patients with hyperuricemia was examined using the multivariable logistic analysis.

A total of 1148 hyperuricemia patients (855 males and 293 females) aged from 40 to 85 years were included and 418 (36.4%) of them were defined with relatively high 10-year CHD risk. Compared with the lowest tertile, the crude odds ratios (ORs) of high 10-year CHD risk were 1.43 (95% confidence interval [CI] 1.06–1.92) and 1.56 (95% CI 1.16–2.11) in the 2nd and 3rd tertiles of WBC count (P for trend = .004), and the multivariable adjusted ORs of high 10-year CHD risk were 1.39 (95% CI 1.03–1.89) and 1.47 (95% CI 1.08–2.00) in the 2nd and 3rd tertiles of WBC count (P for trend = .015).

This study indicated that WBC count was associated with CHD risk in patients with hyperuricemia, suggesting that WBC count, an easily accessible biomarker, could probably predict CHD risk in middle-aged and elderly population with hyperuricemia.

1. Introduction

Hyperuricemia is a commonly seen condition characterized with abnormality in the serum uric acid level.^[1] Nowadays, hyperuricemia has been regarded as a major health problem with its prevalence rising all over the world in the recent decades.^[2,3] Several earlier studies have demonstrated that an elevated level of serum uric acid was related to a variety of cardiovascular diseases including the congestive heart failure, coronary heart disease (CHD), stroke, and hypertension.^[4–7] In addition, it was also suggested that hyperuricemia was an independent factor of cardiovascular risk,^[8] and many relevant works reported that hyperuricemia played a direct role in the mechanism of CHD.^[6,9,10] More recently, a systematic review and meta-analysis involving 29 prospective cohort studies revealed an association between hyperuricemia and the increased risk of CHD morbidity and mortality.^[11] Thus, hyperuricemia patients are deemed as a high risk group of CHD.

As a commonly used and low-cost test, the white blood cell (WBC) count has been regarded as an effective marker of inflammation in clinical practice.^[12] Illustrated by earlier studies, inflammation has direct effect on the development of atherosclerosis, which is the fundamental pathogenesis of CHD.^[12,13] Meanwhile, several studies have also demonstrated that there is an association between the elevated WBC count and common risk factors of CHD, including hypertension, obesity, and high fasting glucose level.^[14,15] Since 1970s, many studies have been carried out focusing on the association between WBC count and CHD from both the epidemiologic and clinical perspectives. However, the results were controversial.^[16–21] Some of them reported a significant association between WBC count and the incidence of CHD,^[17–19] while others reached opposite findings.^[20,21] Furthermore, to the best of our knowledge, no study examines the association between WBC count and CHD risk in patients with hyperuricemia, a high-risk population in the development of cardiovascular diseases. Relevant studies would not only have important implications in understanding the etiology of CHD in hyperuricemia patients, but also contribute to the development of a simple and inexpensive method to predict the future CHD risk of hyperuricemia patients.

To fill this knowledge gap, we conducted a cross-sectional study to investigate the independent association between WBC count and the 10-year estimated CHD risk, measured by the Framingham risk score (FRS),^[22] in a middle-aged and elderly population with hyperuricemia.

2. Materials and methods

2.1. Study population

The present cross-sectional study was performed in the Department of Health Examination Center Xiangya Hospital, Central South University in Changsha, Hunan Province of China, after the protocol had been reviewed and approved by the local Ethics and Research Committee. The study design has been described in our previously published works.^[23–28] Participants were recruited based on the following inclusion criteria: ≥40 years old; patients diagnosed with hyperuricemia (uric acid ≥ 416 μmol/L in the male population and ≥360 μmol/L in the female) who were undertaking serum uric acid and other basic biochemical measurements; and availability of basic particulars including age, gender, and body mass index (BMI); availability of information on health-related habits, including the smoking, alcohol drinking, physical activity, and medication status. After the 1st round of screening, a total of 13,562 subjects who were aged ≥40 years and undergoing routine checkups from October 2013 to November 2014 were included. About 13343 of them could provide valid information of basic health particulars, such as blood pressure and BMI, and 6347 of them could also submit the information of health-related habits. Then, among these 6347 subjects, 1148 were diagnosed with hyperuricemia and were eventually included in the present study.

2.2. Blood biochemistry

The automated hematology analyzer Beckman Coulter LH750 (Beckman Coulter Inc, Brea, CA) was used to evaluate the results of blood routine examinations (including WBC count), and the Beckman Coulter AU 5800 (Beckman Coulter Inc) was used to perform blood biochemistry tests. Then, the intra- and interassay coefficients of variation were tested at both low concentrations (2.5 mmol/L for glucose and 118 μmol/L for uric acid) and high concentrations (6.7 mmol/L for glucose and 472 μmol/L for uric acid) on the basis of standard human samples. The results were as follows: intra-assay coefficients of variation were 0.98% (2.5 mmol/L) and 1.72% (6.7 mmol/L) for glucose, 1.39% (118 μmol/L) and 0.41% (472 μmol/L) for uric acid; inter-assay coefficients of variation were 2.45% (2.5 mmol/L) and 1.46% (6.7 mmol/L) for glucose, 1.40% (118 μmol/L) and 1.23% (472 μmol/L) for uric acid. Lastly, diabetes mellitus was diagnosed based on 2 conditions: fasting glucose ≥7.0 mmol/L or patients who were currently undergoing drug treatment for blood glucose control.

2.3. Assessment of other exposures

The BMI of each subject was calculated using the measurement of weight and height, and the blood pressure was detected using an electronic sphygmomanometer. Then, participants were requested to describe their status of physical activity, including average frequency (never, 1–2 times per week, 3–4 times per week, 5 times and above per week) and average duration (les than half an hour, half an hour to 1 hour, 1–2 hours, >2 hours). Lastly, the smoking, alcohol drinking and medication status were collected through a face-to-face interview.

2.4. Assessment of 10-year CHD risk

The Adult Treatment Panel III (ATP III) charts were applied to calculate the FRS of each subject,^[29] based on the following set of risk factors: age, gender, smoking status, systolic blood pressure, status of antihypertensive medication, total cholesterol, and high-density lipoprotein (HDL) cholesterol. Then, according to the Framingham chart, the estimated 10-year CHD risk for each subject was generated in 2 steps. First, the number of points for each risk factor was calculated; second, the total risk scores were calculated by summing up the points of each risk factor. A score of 10% or above represents a relatively high 10-year CHD risk.

2.5. Statistical analysis

The continuous data and category data were expressed as mean (standard deviation) and in percentage, respectively. The 1-way analysis of variance (normally distributed data) or Kruskal–Wallis H test (nonnormally distributed data) was used to evaluate the differences in continuous data, and the Chi-squared test was used to evaluate the differences in category data. Then, the WBC count was classified into 3 categories in terms of the tertile distribution of the study sample: ≤5.8 × 10⁹/L, 5.9–7.1 × 10⁹/L, and ≥7.2 × 10⁹/L. For the association between WBC count and the elevated CHD risk, the odds ratio (OR) with 95% confidence interval (CI) were calculated for each tertile of WBC count, with the lowest tertile being considered as the reference category. Subsequently, the multivariable-adjusted model was established by including the following variables: BMI, education background, occupation, alcohol drinking status, physical activity status, serum creatinine, and diabetes. Then, the logistic regression with a median variable of WBC count in each category was used to perform tests for linear trends. All the data were analyzed using SPSS 21.0 (SPSS Inc, Chicago, IL), with P < .05 being regarded as statistically significant. All the tests were 2-tailed.

3. Results

A total of 1148 hyperuricemia patients (855 males and 293 females) aged from 40 to 85 years were included in the present study. There were 418 (36.4%) patients defined with relatively high 10-year CHD risk. The basic characteristics of study population based on the tertiles of WBC count are showed in Table 1. Significant differences across all tertiles of WBC count were observed in terms of age, sex, BMI, relatively high CHD risk, HDL cholesterol, systolic blood pressure, diastolic blood pressure, activity level, smoking, and serum creatinine.

Table 1.

Basic characteristics of study population based on the tertiels of WBC count (n = 1148).

The results of the associations between WBC count and relatively high 10-year CHD risk (≥10%) are shown in Table 2. According to the crude OR values, the WBC count was positively associated with relatively high 10-year CHD risk in the 2nd (OR = 1.43, 95% CI 1.06–1.92, P = .020) and 3rd tertiles (OR = 1.56, 95% CI 1.16–2.11, P = .003) of WBC count when comparing with the reference (P for trend was 0.004). Multivariable adjusted OR value also suggested a significant higher prevalence of relatively high CHD risk in the in the 2nd (OR = 1.39, 95% CI 1.03–1.89, P = .033) and 3rd tertiles (OR = 1.47, 95% CI 1.08–2.00, P = .013) of WBC count when comparing with the lowest tertile (P for trend was .015).

Table 2.

Associations between WBC count and relatively high 10-year CHD risk (≥10%) in hyperuricemia population (n = 1148).

4. Discussion

In this study, we found a positive association between elevated WBC count and an increased level of CHD risk in the middle-aged and elderly population with hyperuricemia. Our findings were independent of the effect of the major confounders, including BMI, education background, occupation, alcohol drinking status, physical activity status, serum creatinine, and diabetes. This study suggests that WBC count, an easily accessible biomarker, could probably predict CHD risk in middle-aged and elderly population with hyperuricemia.

In fact, a number of earlier studies have examined the association between WBC count and CHD, but the conclusions were inconsistent. Some scholars reported a positive association between elevated WBC count and CHD independent of conventional cardiovascular risk factors.^[19,30,31] For example, a national cohort suggested that the elevation of WBC count was an effective predictor of CHD mortality.^[32] Similarly, another cohort study conducted by Weijenberg et al also reported that WBC count could predict CHD and all-cause mortality among elderly male subjects in a 5-year follow-up.^[31] Facchini et al revealed that WBC count was significantly associated with changes in carbohydrate and lipoprotein metabolism as well as blood pressure, leading to increased risk of CHD.^[32] On the contrary, some other studies claimed that, with adjustment of coronary risk factors, no significant association was observed between the elevated WBC count and the increased CHD risk.^[20,21] For example, the NHANES I Epidemiologic Follow-up Study reported that the elevated WBC count was not significantly correlated with the increased level of CHD risk in white men with no smoking history, although such an association existed in white women.^[33] According to a cohort study based on the prospective population, it was shown that the odds of CHD in the male subjects whose WBC count was in the top 3rd of distribution were not significantly different from those in the bottom 3rd of distribution.^[34] Such findings contradict with the results of the present study. One possible explanation may be that the association between WBC count and CHD risk was examined in a hyperuricemia population in the present study, which belongs to a high risk group of CHD. Thus, it is of great significance to subdivide this high-risk group or further screen the high risk factors. In view of this, the present work provides evidence of the clinical utility of WBC count, a relatively low-cost and commonly used biomarker, to screen the CHD risk in the hyperuricemia population.

A number of clinical studies aiming at the correlation between the serum uric acid level and the cardiovascular diseases demonstrated that uric acid could intensify oxidative stress and inflammation and in turn promote atherosclerosis in the patients diagnosed with gout or asymptomatic hyperuricemia.^[35,36] This finding was also supported by some in vitro studies, which reported that soluble uric acid could intensify inflammation, generate intermediate reactive oxidative species and result in endothelial dysfunction and proliferation.^[37] Therefore, elevated serum uric acid may be the underlying reason why the hyperuricemia population should be classified as a high risk group of CHD.

It is well-recognized that the WBC count rises in the patients with inflammatory illnesses. Earlier studies have shown that inflammation is implicated in the process of atherosclerosis, which plays a significant role in the pathogenesis of CHD development.^[35–37] A population-based study reported that the subgroups of hypertensive patients with a relatively higher WBC count involved a higher level of risk for atherosclerosis.^[38] Meanwhile, recent studies reported that the WBC, including monocytes, lymphocytes, and neutrophil, was instrumental at the various stages of the atherosclerotic process.^[12,39] The effects of WBC may be exerted through a variety of mechanisms including microvascular plugging, microvasculature obstruction and platelet recruitment.^[40] These mechanisms can accelerate platelet-leukocyte aggregate forming and generate tissue factors, which facilitate the development of thrombosis and acute coronary diseases.^[41] Therefore, the findings of the present study may contribute to the research on the mechanism of WBC in the pathophysiology of CHD.

With respect to the strengths of the present work, this is the 1st study, to date, conducted in a relatively large sample of hyperuricemia population, with the purpose to examine the association between WBC count and CHD risk. In addition, to improve the reliability of the findings, a considerable number of potentially confounding factors of the multivariable model were adjusted, including BMI, serum creatinine and diabetes. On the contrary, the limitations of this study should also be highlighted. First, no causal relationships can be established due to the nature of cross-sectional study. However, the primary objective of this study was not to prove that WBC count was associated with the incidence of CHD but just to examination association between WBC count and CHD risk. If WBC count was correlated with CHD risk score, we could use it to reflect this complicated index in clinical practice. Then, further more complicated index like Framingham risk score could be used to examine the CHD risk. That is to say, we can use WBC count as a very easily accessible screening method. Second, some participants may have chronic diseases out of the adjusted confounding factors of this work. For example, some studies have shown that the prevalence and incidence of cardiovascular disease were increased in individuals with nonalcoholic fatty liver disease.^[42] However, due to the limited data of the present study, the possible effects of these diseases and the related medications on the present findings could not be eliminated.

5. Conclusion

This study indicated that WBC count was associated with CHD risk in patients with hyperuricemia, suggesting that WBC count, an easily accessible biomarker, could probably predict CHD risk in middle-aged and elderly population with hyperuricemia.

Acknowledgments

The authors appreciate the support of the Joint Surgery Engineering Research Center of Hunan Province, the Clinical Technology and Research Center for Joint Surgery of Hunan Province and the National Clinical Research Center for Geriatric Disorders.

Author contributions

Conceptualization: Hu Chen, Yilun Wang, Dongxing Xie.

Data curation: Xiang Ding, Jiatian Li, Ziying Wu, Yuqing Wang, Hongyi He.

Formal analysis: Zidan Yang, Jing Wu.

Methodology: Hu Chen, Xiang Ding, Zidan Yang, Jing Wu, Yilun Wang, Dongxing Xie.

Writing – original draft: Hu Chen, Xiang Ding.

Writing – review & editing: Yilun Wang, Dongxing Xie.