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Prognostic significance of circulating leukocyte subtype counts in patients with coronary artery disease
Atherosclerosis xxx (2016) 1e7
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Atherosclerosis journal homepage: www.elsevier.com/locate/atherosclerosis
Prognostic significance of circulating leukocyte subtype counts in patients with coronary artery disease Eiichiro Yamamoto a, *, Seigo Sugiyama b, Yoshihiro Hirata a, Takanori Tokitsu a, Noriaki Tabata a, Koichiro Fujisue a, Koichi Sugamura a, Kenji Sakamoto a, Kenichi Tsujita a, Takeshi Matsumura c, Koichi Kaikita a, Seiji Hokimoto a a b c
Department of Cardiovascular Medicine, Faculty of Life Sciences, Graduate School of Medical Science, Kumamoto University, Kumamoto, Japan Cardiovascular Division Diabetes Care Center, Jinnouchi Hospital, Kumamoto, Japan Department of Metabolic Medicine, Faculty of Life Sciences, Graduate School of Medical Science, Kumamoto University, Kumamoto, Japan
a r t i c l e i n f o
a b s t r a c t
Article history: Received 5 April 2016 Received in revised form 16 May 2016 Accepted 23 August 2016 Available online xxx
Background and aims: This study investigated the association of leukocyte subtype counts with vascular endothelial dysfunction and future cardiovascular events in patients with coronary artery disease (CAD). Methods: The study included 389 consecutive CAD patients (259 male, 130 female; mean age, 70.1 ± 9.9 years). The patients underwent coronary angiography, and measurement of blood parameters, including leukocyte subtype counts. Results: There were 84 cardiovascular events during a mean follow-up of 586 ± 378 days. KaplaneMeier analysis showed a higher probability of cardiovascular events in the high-monocyte group (360/mm3) compared with the low-monocyte group (<360/mm3) (log-rank test, p ¼ 0.047). Multivariate Cox hazard analysis identified a high monocyte count as an independent predictor of cardiovascular events (hazard ratio: 1.63, 95% confidence interval:1.05e2.51, p ¼ 0.028). Peripheral endothelial function in 355 of the CAD patients was assessed by reactive hyperemia peripheral arterial tonometry index (RHI) to examine the association of ln-RHI with leukocyte subtype counts. Total leukocyte, monocyte and neutrophil counts were significantly higher in CAD patients with low ln-RHI (<0.57: the mean ln-RHI value) compared with those with high ln-RHI (0.57). Univariate analyses revealed that ln-RHI in CAD patients was positively correlated with ln-total leukocyte (r ¼ 0.187, p < 0.001), ln-monocyte (r ¼ 0.316, p < 0.001), and neutrophil (r ¼ 0.175, p ¼ 0.001) counts. Multiple regression analysis showed that the monocyte count was a significant and independent factor associated with ln-RHI (adjusted R2 ¼ 0.126, p < 0.001). Conclusions: A high monocyte count was an independent and incremental predictor of cardiovascular events in CAD patients. The monocyte count was also significantly correlated with peripheral endothelial dysfunction in CAD patients. © 2016 Elsevier Ireland Ltd. All rights reserved.
Keywords: Biological marker Coronary artery disease Inflammation Monocytes Prognosis Vascular endothelial cells
1. Introduction Coronary artery disease (CAD) is now the leading cause of death worldwide, and its prevalence is associated with aging of the population, and with the prevalence of obesity, type 2 diabetes mellitus (DM), and metabolic syndrome [1]. Because cardiovascular
* Corresponding author. Department of Cardiovascular Medicine, Faculty of Life Sciences, Graduate School of Medical Science, Kumamoto University, 1-1-1 Honjo, Chuo-ku, Kumamoto 860-8556, Japan. E-mail address: [email protected] (E. Yamamoto).
events are the main cause of death in CAD patients, risk stratification for future cardiovascular events in these patients can provide valuable information in the clinical setting. Vascular endothelial function plays a key role in the pathophysiology and prognosis of cardiovascular diseases, including atherosclerosis, ischemic heart disease, and heart failure [2,3]. In addition, vascular endothelial dysfunction in high risk patients is found from the early phase of arteriosclerosis to advanced atheroma, resulting in obstructive CAD [4] and cardiovascular events [5,6]. Previous reports showed that vascular endothelial dysfunction, as assessed by forearm flowmediated vasodilation is closely associated with various cardiovascular diseases [7,8]. Using fingertip reactive hyperemia
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E. Yamamoto et al. / Atherosclerosis xxx (2016) 1e7
Abbreviations list CAD DM RH-PAT RHI
coronary artery disease diabetes mellitus reactive hyperemia peripheral arterial tonometry reactive hyperemia peripheral arterial tonometry index CAG coronary angiography SVD single-vessel disease MVD multiple-vessel disease eGFR estimated glomerular filtration rate UMIN University Hospital Medical Information Network HDL cholesterol high-density lipoprotein cholesterol LDL cholesterol low-density lipoprotein cholesterol TG triglycerides
BNP B-type natriuretic peptide hs-troponin T high-sensitivity troponin T hs-CRP high-sensitivity C-reactive protein HR hazard ratio CI confidence interval E/e0 ratio of early transmitral flow velocity to tissue doppler early diastolic mitral annular velocity BMI body mass index LVEF left ventricular ejection fraction ACEI angiotensin-converting enzyme inhibitor ARB angiotensin II receptor blocker CCB calcium channel blockers HMG-CoA RI hydroxymethylglutaryl coenzyme-A reductase inhibitors
peripheral arterial tonometry (RH-PAT), we previously reported that the RH-PAT index (RHI) correlated inversely with various cardiovascular risk factors [9e12], indicating the practical usefulness of the RH-PAT test. Inflammation, characterized by early leukocyte recruitment, is known to be closely associated with vascular endothelial dysfunction and atherosclerosis [4]. Previous epidemiologic studies have reported that an increased leukocyte count is a strong and independent risk factor for progression of atherosclerosis [13], and also for cardiovascular events [13e16]. However, the association between leukocyte subtype counts and vascular endothelial function in patients with CAD has not been fully elucidated. Therefore, the aim of this study was to investigate the associations between leukocyte subtype counts and vascular endothelial function, and the prognostic usefulness of leukocyte subtype counts in patients with CAD.
informed consent was obtained from all patients. This study is registered at the University Hospital Medical Information Network (UMIN) Clinical Trials Registry (UMIN000018886).
2. Materials and methods
2.3. Measurement of blood parameters
2.1. Study subjects and protocol
Blood samples were taken early in the morning in the fasting state before any medications were administered and stored at 80 C until analysis. The levels of plasma B-type natriuretic peptide (BNP), high-sensitivity troponin T (hs-troponin T), serum high-sensitivity C-reactive protein (hs-CRP), and other relevant biochemical markers were measured.
Consecutive stable patients with suspected CAD who were referred for hospitalization and scheduled for coronary angiography (CAG) at Kumamoto University Hospital between January 2008 and August 2013 were registered. Based on the results of CAG, patients with atherosclerotic organic coronary artery stenosis (75%) were diagnosed as having CAD (diameter of stenosis in vessels 1.5 mm). On the basis of the CAG results, CAD patients were classified into single-vessel disease (SVD) or multiple-vessel disease (MVD) groups according to the number of diseased vessels to evaluate the severity of CAD. Patients were excluded for the following reasons: heart failure, history of a coronary artery bypass graft, active infective disease, history of malignancy, and end stage of renal disease (estimated glomerular filtration rate [eGFR] <15 mL/min/1.73 m2). Finally, a total of 389 patients were enrolled in the study, and followed prospectively until February 2014 or until the occurrence of a cardiovascular event. The RHI was used to assess peripheral endothelial function and was measured in 350 study participants before CAG using fingertip RH-PAT by EndoPAT2000 (Itamar Medical Ltd., Caesarea, Israel) to assess the relationship between vascular endothelial dysfunction and leukocyte subtype counts in CAD (Supplemental Fig. 1). The study protocol conformed to the principles of the Declaration of Helsinki and the study has been approved by an institutional review committee at Kumamoto University Hospital. Written
2.2. Definition of coronary risk factors DM was defined as the presence of symptoms of diabetes and a resting plasma glucose concentration 200 mg/dL, a fasting plasma glucose concentration 126 mg/dL, a 2-h plasma glucose concentration 200 mg/dL in a 75 g oral glucose tolerance test, or taking medication for DM. Hypertension was defined as >140/90 mmHg or taking antihypertensive medication. Current smoking was defined as smoking at the time of admission. Dyslipidemia was defined as high-density lipoprotein (HDL) cholesterol <40 mg/dL or lowdensity lipoprotein (LDL) cholesterol 140 mg/dL, triglycerides (TG) > 150 mg/dL, or taking medication for dyslipidemia.
2.4. Follow-up and cardiovascular events Patients were followed up until February 2014 or until the occurrence of a cardiovascular event, such as cardiovascular death, nonfatal myocardial infarction, unstable angina pectoris, nonfatal ischemic stroke, hospitalization for heart failure decompensation, or coronary revascularization. Cardiovascular death was defined as death as a result of myocardial infarction (within 28 days of onset), heart failure, or documented sudden death in the absence of noncardiovascular causes. Myocardial infarction was diagnosed by the rise or fall of cardiac biomarkers (plasma creatine kinase-MB and cardiac troponin-T) above the 99th percentile of the upper limit of the normal range, with evidence of myocardial ischemia, as indicated by at least one of the following: electrocardiogram changes (new ST-T changes, left bundle branch block, pathological Q wave) or imaging evidence of new loss of viable myocardium or new abnormalities in regional wall motion. Unstable angina pectoris was diagnosed by new or accelerating symptoms of myocardial ischemia accompanied by new ischemic ST-T changes. Ischemic
Please cite this article in press as: E. Yamamoto, et al., Prognostic significance of circulating leukocyte subtype counts in patients with coronary artery disease, Atherosclerosis (2016), http://dx.doi.org/10.1016/j.atherosclerosis.2016.08.033
E. Yamamoto et al. / Atherosclerosis xxx (2016) 1e7
stroke was diagnosed by focal neurological deficits with radiological evidence of brain infarction, excluding intracranial hemorrhage. Hospitalization for heart failure decompensation was diagnosed if the patient was admitted with symptoms typical of heart failure and had objective signs of worsening heart failure requiring intravenous drug administration. Coronary revascularization was diagnosed if the patient underwent percutaneous coronary intervention or coronary artery bypass grafting with evidence of myocardial ischemia. Cardiovascular events were ascertained from a review of medical records and confirmed by direct dialogue with the patients, their families, and physicians. 2.5. Reactive hyperemia peripheral arterial tonometry RH-PAT has been described previously [17]. RH-PAT was conducted in the morning after subjects had fasted, but before medication intake and CAG. Noninvasive RH-PAT was performed with a blood pressure cuff placed on an upper arm (study arm), while the contralateral arm served as a control (control arm). The PAT probe was placed on a finger of each hand. After a 5-min equilibration period, the blood pressure cuff was inflated on the study arm to 60 mmHg above the systolic pressure or 200 mmHg for 5 min, and then the cuff was deflated to induce reactive hyperemia. RH-PAT data were digitally analyzed online (Endo-PAT2000 software, version 3.0.4 and 3.4.4, Itamar Medical Ltd., Caesarea, Israel). RHI was calculated as the ratio of the mean amplitude of the PAT signal over 1 min starting 1.5 min after cuff deflation (control arm, A; occluded arm, C) divided by the average amplitude of the PAT signal of a 2.5-min period before cuff inflation (baseline) (control arm, B; occluded arm, D). RHI values were automatically calculated by the online computer based on the ratio of (C/D)/(A/B). Because RHI values are not normally distributed, the natural logarithmic transformed RHI values (ln-RHI) were calculated for use in regression analyses, as reported previously [9,12]. The reproducibility of RHPAT technology has been confirmed in previous studies [9,12,18].
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Table 1 Baseline characteristics of coronary artery disease patients. All CAD (n ¼ 389) Age (years) Sex (male, %) BMI (kg/m2) Hypertension (yes, %) DM (yes, %) Current smoking (yes, %) Dyslipidemia (yes, %) BNP (pg/mL) eGFR (mL/min/1.73 m2) hs-CRP (mg/L) TC (mg/dL) TG (mg/dL) HDL-C (mg/dL) LDL-C (mg/dL) Total leukocyte count (/mm3) Monocyte count (/mm3) Neutrophil count (/mm3) Lymphocyte count (/mm3) Eosinophil count (/mm3) Basophil count (/mm3) LVEF (%) E/e0 Aspirin (%) b-blocker (%) ACE-I or ARB (%) CCB (%) HMG-CoA RI (%) Loop diuretics (%)
70.1 (9.9) 66.6 24.2 (3.4) 88.4 50.6 12.3 91.0 37.0 (16.9e71.9) 63.8 (16.8) 0.7 (0.3e1.3) 159.8 (35.2) 116 (87e156) 48.8 (12.5) 91.6 (29.8) 5600 (4600e6800) 328.6 (258.4e407) 3283.2 (2566.2e4151) 1679.6 (1324.8e2109.4) 158.1 (98.6e244.2) 22 (17.1e33.2) 62.8 (6.3) 13.6 (4.8) 97.7 75.1 74.0 65.0 96.1 7.5
Data are mean (standard deviation), median (interquartile range), or numbers (percentages). CAD indicates coronary artery disease; SVD, single vessel disease; MVD, multiple vessel disease; BMI, body mass index; DM, diabetes mellitus; BNP, Btype natriuretic peptide; eGFR, estimated glomerular filtration rate; Hs-CRP, highsensitivity C-reactive protein; TC, total cholesterol; TG, triglyceride; HDL-C, highdensity lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; LVEF, left ventricular ejection fraction; E/e0 , the ratio of early transmitral flow velocity to tissue Doppler early diastolic mitral annular velocity; ACE-I, angiotensin-converting enzyme inhibitors; ARB, angiotensin II receptor blockers; CCB, calcium channel blockers; HMG-CoA RI, hydroxymethylglutaryl coenzyme-A reductase inhibitors.
2.6. Statistical analyses
3. Results
patients, respectively. The total leukocyte, monocyte, neutrophil, lymphocyte, eosinophil, and basophil counts were 5600 [4600e6800]/mm3, 328.6 [258.4e407]/mm3, 3283.2 3 [2566.2e4151]/mm , 1679.6 [1316.1e2092.3]/mm3, 158.1 [98.6e244.2]/mm3 and 22 [17.1e33.2]/mm3, respectively. To examine the differences in clinical characteristics according to the severity of CAD, the patients were classified into CAD with SVD (n ¼ 149) or CAD with MVD (n ¼ 240). Total leukocyte and neutrophil counts tended to be higher in CAD patients with MVD compared with those with SVD, but the differences were not statistically significant (5500 [4400e6400] vs. 5700 [4700e6900], p ¼ 0.06 and 3256.2 [2553.6e4012.8] vs. 3337.7 [2627.2e4253.4], p ¼ 0.06, respectively, data not shown). Monocyte, lymphocyte, eosinophil, and basophil counts were not significantly different between CAD patients with SVD and those with MVD. The prevalence of DM and dyslipidemia were significantly higher (p ¼ 0.009 and p ¼ 0.02, respectively), and the use of aspirin, b-blockers, and angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers was also significantly higher in CAD patients with MVD than in those with SVD (p ¼ 0.01, p ¼ 0.004, and p ¼ 0.03, respectively, data not shown).
3.1. Baseline characteristics of CAD patients
3.2. Follow-up of cardiovascular events in CAD patients
The baseline characteristics of 389 consecutive CAD patients are shown in Table 1. Mean age was 70.1 ± 9.9 years, and 66.6% of the subjects were male. Hypertension, DM, current smoking, and dyslipidemia were present in 88.4%, 50.6%, 12.3%, and 91.0% of CAD
During a mean follow-up of 586 ± 378 days, 84 cardiovascular events were recorded in the total cohort of CAD patients. Those who had a cardiovascular event were more likely to be elderly and female (both p ¼ 0.02), have a higher prevalence of DM (p ¼ 0.01),
Non-normally distributed data are expressed as median (interquartile range). Continuous variables with normal distribution are expressed as mean ± standard deviation. The KolmogoroveSmirnov test was used to assess normal distribution of continuous data. Categorical data are presented by frequencies and percentages. Differences between two groups were tested with Fisher's exact test for categorical variables. Differences in continuous variables were analyzed by the unpaired t-test, or MannWhitney U test, as appropriate. KaplaneMeier analysis was performed in CAD patients and comparisons of the incidence of cardiovascular events was performed using the log-rank test. The Cox proportional hazard model was used to estimate the cardiovascular event hazard ratio (HR) and its 95% confidence interval (CI) in CAD patients by simple and multivariate analysis with stepwise backward models, including various clinical parameters other than total leukocyte count. A p-value <0.05 was considered statistically significant. Statistical analyses were performed using SPSS version 22 (IBM Japan Ltd., Tokyo, Japan).
Please cite this article in press as: E. Yamamoto, et al., Prognostic significance of circulating leukocyte subtype counts in patients with coronary artery disease, Atherosclerosis (2016), http://dx.doi.org/10.1016/j.atherosclerosis.2016.08.033
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E. Yamamoto et al. / Atherosclerosis xxx (2016) 1e7
and higher BNP, HDL cholesterol, and E/e0 (ratio of early transmitral flow velocity to tissue doppler early diastolic mitral annular velocity) (p < 0.001, p < 0.001, and p ¼ 0.001, respectively). They also had lower TG levels (p ¼ 0.01) compared with those without a cardiovascular event (n ¼ 305) (Supplemantal Table 1). Monocyte counts tended to be higher in CAD patients with a cardiovascular event than in those without an event (323.3 [253e393.6]/mm3 vs. 354.2 [265.4e436.5]/mm3, p ¼ 0.07, Supplemental Table 1). Total leukocyte, neutrophil, lymphocyte, eosinophil, and basophil counts were not significantly different between CAD patients with and without a cardiovascular event (Supplemental Table 1). Receiver operating characteristics curves were constructed to determine the optimum cutoff value for monocyte count in CAD patients for the occurrence of a cardiovascular event. The monocyte count correlated significantly with the occurrence of cardiovascular events (area under the curve: 0.56, 95% CI: 0.49e0.63, data not shown), and showed that the cutoff threshold of monocyte count was 360/mm [3]. Using this threshold, the sensitivity, specificity, positive predictive value, and negative predictive value of monocyte count for the occurrence of a future cardiovascular event were 50.0%, 63.9%, 27.6%, and 82.3%, respectively. The cutoff value was used to stratify CAD patients into low-monocyte (n ¼ 242) and high-monocyte (n ¼ 147) groups. KaplaneMeier analysis then showed that the high-monocyte group had a higher risk for a future cardiovascular event than the low-monocyte group (p ¼ 0.047 by log-rank test, Fig. 1). Crude Cox hazard analysis identified seven variables as significant predictors of a cardiovascular event: age, sex, the prevalence of DM, ln-hs-CRP, BNP 100 pg/mL, high monocyte count (360/ mm3), and high E/e0 (Table 2). Multivariate Cox proportional hazard analysis, performed by a stepwise backward regression model, identified that a high monocyte count was a significant and independent predictor for a future cardiovascular event in CAD patients (HR: 1.63, 95% CI: 1.05e2.51, p ¼ 0.028, Table 2). 3.3. Association of ln-RHI with leukocyte subset counts in CAD patients The association between peripheral vascular endothelial dysfunction and leukocyte subtype counts was examined in 355 CAD patients who underwent RH-PAT. The patients were stratified into low-ln-RHI (n ¼ 176) and high-ln-RHI (n ¼ 179) groups
Fig. 1. KaplaneMeier analysis for the probability of cardiovascular events in CAD patients with low- or high-monocyte count (n ¼ 242 and n ¼ 147, respectively). CAD patients were divided into two groups using the cut-off value of monocyte count (360/mm3).
according to the mean ln-RHI value (ln-RHI: 0.57). BNP was significantly higher in low-ln-RHI patients than in high-ln-RHI patients (37.4 [18.0e85.3] pg/mL vs. 35.3 [13.3e63.8] pg/mL, p ¼ 0.007, Table 3). Total leukocyte, monocyte, and neutrophil counts were significantly higher in CAD patients with low-ln-RHI compared with those with high-ln-RHI (5950 [4800e6925] vs. 5400 [4350e6400], p ¼ 0.007, 341.7 [274.8e435.8] vs. 308.7 [238.5e383.5], p < 0.001 and 3373.5 [2775.6e4418.4] vs. 3129.3 [2417.3e3936.2], p ¼ 0.009, respectively, Table 3). In contrast, lymphocyte, eosinophil, and basophil counts were not significantly different between CAD patients with low-ln-RHI and those with high-ln-RHI (Table 3). The results of univariate analysis of the associations between lnRHI and clinical characteristics are shown in Supplemental Table 2. Ln-RHI was negatively correlated with ln-BNP, ln-TG, and E/e0 (Supplemental Table 2). Furthermore, ln-RHI was negatively correlated with ln-total leukocyte (r ¼ 0.187, p < 0.001), lnmonocyte (r ¼ 0.316, p < 0.001), and ln-neutrophil (r ¼ 0.175, p ¼ 0.001) counts (Supplemental Table 2). Univariate analysis also found that total leukocyte count was positively correlated with body mass index (BMI), current smoking, ln-hs-CRP, and ln-TG, but negatively correlated with age, ln-RHI, and ln-HDL cholesterol (Supplemental Table 3). The ln-monocyte count was positively correlated with male sex, BMI, current smoking, and ln-hs-CRP, and negatively correlated with ln-RHI and HDL cholesterol (Supplemental Table 3). The ln-neutrophil count was positively correlated with BMI, current smoking, and ln-hs-CRP, and negatively correlated with ln-RHI, eGFR, and HDL cholesterol (Supplemental Table 3). A stepwise multiple regression analysis was performed to identify the independent factors associated with ln-RHI. As there is an innate correlation between ln-total leukocyte and ln-neutrophil counts, significant clinical parameters associated with ln-RHI other than ln-total leukocyte in Pearson's correlation analysis were entered into the stepwise multiple regression analysis. Finally, lnmonocyte count and ln-BNP were found to be significant and independent factors associated with ln-RHI (adjusted R2 ¼ 0.126, p < 0.001, Table 4). Also, ln-TG was independently associated with ln-RHI (p ¼ 0.026, Table 4). 4. Discussion This study established the following associations in CAD patients: the risk of a cardiovascular event was significantly higher in patients with a high monocyte count (360/mm3); a high monocyte count was a significant and independent predictor of a cardiovascular event; monocyte counts were significantly higher in patients with low-ln-RHI than in those with high-ln-RHI; ln-RHI values were significantly and negatively correlated with monocyte, total leukocyte and neutrophil counts; and ln-monocyte count and ln-BNP were significant and independent factors associated with ln-RHI. The presence of CAD is associated with increased risk of death, and patients with severe CAD have a poor prognosis. However, the relationships between biomarkers of leukocyte subtype counts and the prognosis of patients with CAD remain unclear. In the present study, the occurrence of a cardiovascular event was significantly higher in CAD patients with a high rather than a low monocyte count, suggesting that a high monocyte count may contribute to the state of atherosclerosis and cardiovascular events in CAD. In addition, the present study showed that the baseline monocyte count tended to be higher in patients who had a cardiovascular event, and that a high monocyte count was a significant and independent predictor of cardiovascular events in CAD patients. A previous report showed that a high monocyte 500/mm3 in healthy and
Please cite this article in press as: E. Yamamoto, et al., Prognostic significance of circulating leukocyte subtype counts in patients with coronary artery disease, Atherosclerosis (2016), http://dx.doi.org/10.1016/j.atherosclerosis.2016.08.033
E. Yamamoto et al. / Atherosclerosis xxx (2016) 1e7
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Table 2 Cox proportional hazards analysis of risk of a cardiovascular event in CAD patients. Variable
Age Sex (male) BMI Hypertension (yes) DM (yes) Current smoking (yes) Dyslipidemia (yes) BNP (100 pg/mL) EGFR Ln-Hs-CRP Hemoglobin Ln-total leukocyte count High-monocyte (yes) Ln-neutrophil count Ln-lymphocyte count Ln-eosinophil count Ln-basophil count LVEF E/e0
Simple regression
Multiple regression stepwise backward
HR
95% CI
p-value
1.03 0.60 0.98 1.18 1.842 0.90 0.84 2.49 1.00 1.25 1.01 1.30 1.54 1.28 0.81 0.95 1.11 1.00 1.06
1.00e1.05 0.39e0.92 0.92e1.04 0.59e2.36 1.18e2.87 0.45e1.80 0.43e1.63 1.58e3.91 0.98e1.01 1.03e1.51 0.98e1.03 0.61e2.79 1.00e2.36 0.71e2.29 0.45e1.44 0.74e1.23 0.79e1.54 0.97e1.04 1.01e1.10
0.03 0.02 0.51 0.64 0.007 0.77 0.61 <0.001 0.49 0.02 0.62 0.50 0.049 0.41 0.46 0.71 0.55 1.00 0.009
HR 0.67
1.81
2.56
1.63
95% CI not selected 0.43e1.03 not selected not selected 1.15e2.83 not selected not selected 1.61e4.07 not selected not selected not selected not selected 1.05e2.51 not selected not selected not selected not selected not selected not selected
p-value 0.07
0.01
<0.001
0.028
HR, hazard ratio; 95% CI, 95% confidence interval.
Table 3 Baseline characteristics of CAD patients with rhi measurement.
Age (years) Sex (male, %) BMI (kg/m2) MVD (yes, %) Gensini score Hypertension (yes, %) DM (yes, %) Current smoking (yes, %) Dyslipidemia (yes, %) BNP (pg/mL) eGFR (mL/min/1.73 m2) Hs-CRP (mg/L) TC (mg/dL) TG (mg/dL) HDL-C (mg/dL) LDL-C (mg/dL) Total leukocyte count (/mm3) Monocyte count (/mm3) Neutrophil count (/mm3) Lymphocyte count (/mm3) Eosinophil count (/mm3) Basophil count (/mm3) LVEF (%) E/e0 Aspirin (%) b-blocker (%) ACE-I or ARB (%) CCB (%) HMG-CoA RI (%) Loop diuretics (%)
All CAD patients (n ¼ 355)
CAD þ Low-RHI (n ¼ 176)
CAD þ High-RHI (n ¼ 179)
p-value*
69.9 (9.9) 66.8 24.2 (3.4) 61.7 35.7 (30.1) 87.9 51.8 11.8 90.1 36.6 (16.4e72.3) 63.8 (16.8) 0.7 (0.3e1.3) 160.1 (35.3) 115 (87.5e155) 48.9 (12.5) 91.8 (29.9) 5600 (4600e6800) 329 (252.9e405.4) 3264 (2568.9e4075.6) 1682.1 (1334.2e2111) 151.8 (98.1e244.2) 22 (15.6e33) 63.0 (6.2) 13.6 (4.9) 97.7 74.4 74.4 65.1 96.3 7.3
69.5 (10.0) 70.5 24.4 (3.4) 62.5 34.4 (30.8) 87.5 50.6 14.2 90.3 37.4 (18.0e85.3) 63.3 (17.9) 0.7 (0.3e1.4) 161.7 (38.7) 124.5 (89e161) 48.3 (12.7) 92.5 (32.7) 5950 (4800e6925) 341.7 (274.8e435.8) 3373.5 (2775.6e4418.4) 1679.6 (1380.2e2109.2) 151 (102e228) 22 (12.4e33.7) 62.9 (6.2) 14.1 (5.2) 98.3 71.6 76.1 64.2 95.5 7.4
70.3 (9.7) 63.1 24.1 (3.4) 60.8 37.0 (29.4) 88.3 53.1 9.5 89.9 35.3 (13.3e63.8) 64.3 (15.7) 0.6 (0.3e1.1) 158.5 (31.6) 107 (84.5e140) 49.4 (12.4) 91.0 (27.0) 5400 (4350e6400) 308.7 (238.5e383.5) 3129.3 (2417.3e3936.2) 1694 (1286.3e2111) 159 (89.1e264.6) 22 (18.2e32.5) 63.1 (6.2) 13.2 (4.7) 97.2 77.1 72.6 65.9 97.2 7.3
0.45 0.14 0.35 0.76 0.4 0.82 0.64 0.17 0.9 0.007 0.56 0.3 0.39 0.05 0.42 0.64 0.007 <0.001 0.009 0.2 0.78 0.51 0.63 0.1 0.49 0.24 0.45 0.73 0.38 0.96
Data are mean (standard deviation), median (interquartile range), or numbers (percentages). *Comparison between 176 low-RHI group and 179 high-RHI group.
middle-aged subjects was predictive of a coronary event [19], while the present study demonstrated that a high monocyte 360/mm3 in CAD patients predicted a cardiovascular event, including a coronary event. These studies suggest that the cutoff values of monocyte counts for predicting a cardiovascular event may vary according to the clinical characteristics of the patient. One reason for this difference in monocyte count cutoff value from previous reports could be related to differences in the study populations, and CAD patients in the current study had a higher risk of a
cardiovascular event than the general population. Another consideration is that all patients in this study were Japanese, which may limit comparisons with other studies with different cutoff values of monocyte counts in other countries. A previous report by Nozawa et al. [20] demonstrated that the cutoff value of monocyte count for plaque progression in patients during the acute phase of acute myocardial infarction was 800/mm3, suggesting that the cutoff value of monocyte counts for predicting cardiovascular outcome may vary according to the severity of atherosclerosis.
Please cite this article in press as: E. Yamamoto, et al., Prognostic significance of circulating leukocyte subtype counts in patients with coronary artery disease, Atherosclerosis (2016), http://dx.doi.org/10.1016/j.atherosclerosis.2016.08.033
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Table 4 Stepwise multivariable regression analysis for ln-RHI. Variable
Ln-neutrophil count Ln-monocyte count Ln-BNP Ln-TG
Unstandardized coefficient
Standardized coefficient
95% CI for B
p-value
B
SEM
b
Lower bound
Upper bound
0.003 0.197 0.018 0.057
0.036 0.035 0.007 0.025
0.005 0.322 0.132 0.110
0.068 0.266 0.032 0.106
0.074 0.127 0.005 0.007
0.938 <0.001 0.007 0.026
SEM, standard error of the mean.
Inflammation is believed to have a pivotal role in the pathogenesis of various cardiovascular diseases, and Ridker et al. previously reported that plasma concentration of CRP, a representative biomarker of inflammation, predicts the risk of future myocardial infarction in apparently healthy men [21] and women [22]. Thus, atherosclerosis is now regarded as a chronic inflammatory disease, with monocytes and monocyte-derived macrophages playing pivotal roles in its initiation and progression [23e25]. The recruitment of monocytes into the arterial wall and their development into macrophages are the earliest events in atherosclerosis, indicating the importance of inflammation in vascular endothelial dysfunction and initiation of atherosclerosis. Several studies have reported that vascular endothelial dysfunction is a useful marker for cardiovascular events in subjects with CAD [2,3,5]. Hence, we hypothesized that a high monocyte count would predict a future cardiovascular event in CAD patients at least partially via vascular endothelial dysfunction. This study clearly revealed that total leukocyte count and its components (i.e., monocyte and neutrophil counts) were correlated with ln-RHI, reflecting peripheral vascular endothelial function. For the first time, as far as we are aware, it was established that the monocyte count in CAD patients was strongly and significantly correlated with peripheral endothelial dysfunction. The monocyte count has also been reported to be an independent predictor of common carotid atherosclerosis in healthy subjects [26,27]. In addition, Matsumura et al. recently reported that monocyte counts were positively correlated with both mean and maximum intima-media thickness of the common carotid artery in subjects with type 2 DM [28]. Taken together, these studies suggest that, of the leukocyte fractions, the monocyte count is the most useful marker for the evaluation of atherosclerosis, and is involved at all stages of the progression of atherosclerosis. Monocytes, as representatives of the innate immune system, may play a major role not only in vascular endothelial dysfunction, but also in atherosclerotic plaque development. Monocyte-endothelial interactions have been implicated in the initiation of endothelial dysfunction in many vascular diseases [29]. Furthermore, these dysfunctions have been partially attributed to impaired activity of endothelial-derived nitric oxide, and overproduction of reactive oxygen species. For instance, excessive production of reactive oxygen species increases lectin-like oxidized low-density lipoprotein receptor-1 expression, and accelerates vascular endothelial dysfunction and atherosclerosis [30]. The current study indicates that the RHI value in CAD patients is correlated with the severity of coronary atherosclerosis, and may constitute a significant predictor for the occurrence of a coronary event. Indeed, Bonetti et al. previously reported that an attenuated digital hyperemic response, as measured by RH-PAT, was closely associated with impaired coronary endothelial function, measured by the increase in coronary blood flow in response to acetylcholine [17], and we previously demonstrated the usefulness of RHI as a predictor of coronary revascularization in CAD patients complicated by chronic kidney disease [10]. Recently, Li et al. reported that a high leukocyte count was independently associated with vascular
dysfunction assessed by RH-PAT in patients with low cardiovascular risk [31]. In the present study, leukocyte and monocyte counts in CAD patients were closely associated with peripheral endothelial dysfunction, indicated by decreased RHI. Therefore, the monocyte count, reflecting vascular inflammation, may predict vascular endothelial dysfunction, leading to a cardiovascular event. There are several limitations in this study. First, this was a onecenter study with a relatively small patient population. However, even in this small population, the monocyte count was found to be closely associated with vascular endothelial dysfunction and prognosis of CAD. Further large multicenter studies involving larger numbers of patients will be required to determine the importance of leukocyte subtype counts in CAD. Second, this study was observational and did not include an intervention such as anti-inflammatory drugs. The benefits of anti-inflammatory therapy for cardiovascular diseases still remain unclear. Therefore, prospective interventional studies in CAD patients in a large-scale population are necessary. Third, in this study, as we measured hs-CRP, but not proinflammatory mediators, such as monocyte chemotactic protein-1 and tumor necrosis factor-a, we could not examine the relationship between monocyte count and other inflammatory biomarkers and their involvement in peripheral vascular endothelial dysfunction. However, despite these limitations, the prognostic significance of monocyte count in CAD patients was clearly demonstrated. To the best of our knowledge, the study provides the first evidence for the significant association between monocyte count and peripheral endothelial dysfunction in CAD patients. Monocyte counts may be a useful predictor of vascular endothelial dysfunction and cardiovascular events in CAD patients. Conflict of interest The authors declared they do not have anything to disclose regarding conflict of interest with respect to this manuscript. Financial support This work was supported in part by Grants-in Aid for Scientific Research (grant number: B24790770 to E. Yamamoto) from the Japanese Ministry of Education, Culture, Sports, Science and Technology, the SENSHIN Medical Research Foundation (to E. Yamamoto), and the Japan Cardiovascular Research Foundation (to H. Ogawa). Clinical trial registration URL: http://www.umin.ac.jp/ctr/. UMIN000018886.
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Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.atherosclerosis.2016.08.033.
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Atherosclerosis journal homepage: www.elsevier.com/locate/atherosclerosis
Prognostic significance of circulating leukocyte subtype counts in patients with coronary artery disease Eiichiro Yamamoto a, *, Seigo Sugiyama b, Yoshihiro Hirata a, Takanori Tokitsu a, Noriaki Tabata a, Koichiro Fujisue a, Koichi Sugamura a, Kenji Sakamoto a, Kenichi Tsujita a, Takeshi Matsumura c, Koichi Kaikita a, Seiji Hokimoto a a b c
Department of Cardiovascular Medicine, Faculty of Life Sciences, Graduate School of Medical Science, Kumamoto University, Kumamoto, Japan Cardiovascular Division Diabetes Care Center, Jinnouchi Hospital, Kumamoto, Japan Department of Metabolic Medicine, Faculty of Life Sciences, Graduate School of Medical Science, Kumamoto University, Kumamoto, Japan
a r t i c l e i n f o
a b s t r a c t
Article history: Received 5 April 2016 Received in revised form 16 May 2016 Accepted 23 August 2016 Available online xxx
Background and aims: This study investigated the association of leukocyte subtype counts with vascular endothelial dysfunction and future cardiovascular events in patients with coronary artery disease (CAD). Methods: The study included 389 consecutive CAD patients (259 male, 130 female; mean age, 70.1 ± 9.9 years). The patients underwent coronary angiography, and measurement of blood parameters, including leukocyte subtype counts. Results: There were 84 cardiovascular events during a mean follow-up of 586 ± 378 days. KaplaneMeier analysis showed a higher probability of cardiovascular events in the high-monocyte group (360/mm3) compared with the low-monocyte group (<360/mm3) (log-rank test, p ¼ 0.047). Multivariate Cox hazard analysis identified a high monocyte count as an independent predictor of cardiovascular events (hazard ratio: 1.63, 95% confidence interval:1.05e2.51, p ¼ 0.028). Peripheral endothelial function in 355 of the CAD patients was assessed by reactive hyperemia peripheral arterial tonometry index (RHI) to examine the association of ln-RHI with leukocyte subtype counts. Total leukocyte, monocyte and neutrophil counts were significantly higher in CAD patients with low ln-RHI (<0.57: the mean ln-RHI value) compared with those with high ln-RHI (0.57). Univariate analyses revealed that ln-RHI in CAD patients was positively correlated with ln-total leukocyte (r ¼ 0.187, p < 0.001), ln-monocyte (r ¼ 0.316, p < 0.001), and neutrophil (r ¼ 0.175, p ¼ 0.001) counts. Multiple regression analysis showed that the monocyte count was a significant and independent factor associated with ln-RHI (adjusted R2 ¼ 0.126, p < 0.001). Conclusions: A high monocyte count was an independent and incremental predictor of cardiovascular events in CAD patients. The monocyte count was also significantly correlated with peripheral endothelial dysfunction in CAD patients. © 2016 Elsevier Ireland Ltd. All rights reserved.
Keywords: Biological marker Coronary artery disease Inflammation Monocytes Prognosis Vascular endothelial cells
1. Introduction Coronary artery disease (CAD) is now the leading cause of death worldwide, and its prevalence is associated with aging of the population, and with the prevalence of obesity, type 2 diabetes mellitus (DM), and metabolic syndrome [1]. Because cardiovascular
* Corresponding author. Department of Cardiovascular Medicine, Faculty of Life Sciences, Graduate School of Medical Science, Kumamoto University, 1-1-1 Honjo, Chuo-ku, Kumamoto 860-8556, Japan. E-mail address: [email protected] (E. Yamamoto).
events are the main cause of death in CAD patients, risk stratification for future cardiovascular events in these patients can provide valuable information in the clinical setting. Vascular endothelial function plays a key role in the pathophysiology and prognosis of cardiovascular diseases, including atherosclerosis, ischemic heart disease, and heart failure [2,3]. In addition, vascular endothelial dysfunction in high risk patients is found from the early phase of arteriosclerosis to advanced atheroma, resulting in obstructive CAD [4] and cardiovascular events [5,6]. Previous reports showed that vascular endothelial dysfunction, as assessed by forearm flowmediated vasodilation is closely associated with various cardiovascular diseases [7,8]. Using fingertip reactive hyperemia
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Abbreviations list CAD DM RH-PAT RHI
coronary artery disease diabetes mellitus reactive hyperemia peripheral arterial tonometry reactive hyperemia peripheral arterial tonometry index CAG coronary angiography SVD single-vessel disease MVD multiple-vessel disease eGFR estimated glomerular filtration rate UMIN University Hospital Medical Information Network HDL cholesterol high-density lipoprotein cholesterol LDL cholesterol low-density lipoprotein cholesterol TG triglycerides
BNP B-type natriuretic peptide hs-troponin T high-sensitivity troponin T hs-CRP high-sensitivity C-reactive protein HR hazard ratio CI confidence interval E/e0 ratio of early transmitral flow velocity to tissue doppler early diastolic mitral annular velocity BMI body mass index LVEF left ventricular ejection fraction ACEI angiotensin-converting enzyme inhibitor ARB angiotensin II receptor blocker CCB calcium channel blockers HMG-CoA RI hydroxymethylglutaryl coenzyme-A reductase inhibitors
peripheral arterial tonometry (RH-PAT), we previously reported that the RH-PAT index (RHI) correlated inversely with various cardiovascular risk factors [9e12], indicating the practical usefulness of the RH-PAT test. Inflammation, characterized by early leukocyte recruitment, is known to be closely associated with vascular endothelial dysfunction and atherosclerosis [4]. Previous epidemiologic studies have reported that an increased leukocyte count is a strong and independent risk factor for progression of atherosclerosis [13], and also for cardiovascular events [13e16]. However, the association between leukocyte subtype counts and vascular endothelial function in patients with CAD has not been fully elucidated. Therefore, the aim of this study was to investigate the associations between leukocyte subtype counts and vascular endothelial function, and the prognostic usefulness of leukocyte subtype counts in patients with CAD.
informed consent was obtained from all patients. This study is registered at the University Hospital Medical Information Network (UMIN) Clinical Trials Registry (UMIN000018886).
2. Materials and methods
2.3. Measurement of blood parameters
2.1. Study subjects and protocol
Blood samples were taken early in the morning in the fasting state before any medications were administered and stored at 80 C until analysis. The levels of plasma B-type natriuretic peptide (BNP), high-sensitivity troponin T (hs-troponin T), serum high-sensitivity C-reactive protein (hs-CRP), and other relevant biochemical markers were measured.
Consecutive stable patients with suspected CAD who were referred for hospitalization and scheduled for coronary angiography (CAG) at Kumamoto University Hospital between January 2008 and August 2013 were registered. Based on the results of CAG, patients with atherosclerotic organic coronary artery stenosis (75%) were diagnosed as having CAD (diameter of stenosis in vessels 1.5 mm). On the basis of the CAG results, CAD patients were classified into single-vessel disease (SVD) or multiple-vessel disease (MVD) groups according to the number of diseased vessels to evaluate the severity of CAD. Patients were excluded for the following reasons: heart failure, history of a coronary artery bypass graft, active infective disease, history of malignancy, and end stage of renal disease (estimated glomerular filtration rate [eGFR] <15 mL/min/1.73 m2). Finally, a total of 389 patients were enrolled in the study, and followed prospectively until February 2014 or until the occurrence of a cardiovascular event. The RHI was used to assess peripheral endothelial function and was measured in 350 study participants before CAG using fingertip RH-PAT by EndoPAT2000 (Itamar Medical Ltd., Caesarea, Israel) to assess the relationship between vascular endothelial dysfunction and leukocyte subtype counts in CAD (Supplemental Fig. 1). The study protocol conformed to the principles of the Declaration of Helsinki and the study has been approved by an institutional review committee at Kumamoto University Hospital. Written
2.2. Definition of coronary risk factors DM was defined as the presence of symptoms of diabetes and a resting plasma glucose concentration 200 mg/dL, a fasting plasma glucose concentration 126 mg/dL, a 2-h plasma glucose concentration 200 mg/dL in a 75 g oral glucose tolerance test, or taking medication for DM. Hypertension was defined as >140/90 mmHg or taking antihypertensive medication. Current smoking was defined as smoking at the time of admission. Dyslipidemia was defined as high-density lipoprotein (HDL) cholesterol <40 mg/dL or lowdensity lipoprotein (LDL) cholesterol 140 mg/dL, triglycerides (TG) > 150 mg/dL, or taking medication for dyslipidemia.
2.4. Follow-up and cardiovascular events Patients were followed up until February 2014 or until the occurrence of a cardiovascular event, such as cardiovascular death, nonfatal myocardial infarction, unstable angina pectoris, nonfatal ischemic stroke, hospitalization for heart failure decompensation, or coronary revascularization. Cardiovascular death was defined as death as a result of myocardial infarction (within 28 days of onset), heart failure, or documented sudden death in the absence of noncardiovascular causes. Myocardial infarction was diagnosed by the rise or fall of cardiac biomarkers (plasma creatine kinase-MB and cardiac troponin-T) above the 99th percentile of the upper limit of the normal range, with evidence of myocardial ischemia, as indicated by at least one of the following: electrocardiogram changes (new ST-T changes, left bundle branch block, pathological Q wave) or imaging evidence of new loss of viable myocardium or new abnormalities in regional wall motion. Unstable angina pectoris was diagnosed by new or accelerating symptoms of myocardial ischemia accompanied by new ischemic ST-T changes. Ischemic
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stroke was diagnosed by focal neurological deficits with radiological evidence of brain infarction, excluding intracranial hemorrhage. Hospitalization for heart failure decompensation was diagnosed if the patient was admitted with symptoms typical of heart failure and had objective signs of worsening heart failure requiring intravenous drug administration. Coronary revascularization was diagnosed if the patient underwent percutaneous coronary intervention or coronary artery bypass grafting with evidence of myocardial ischemia. Cardiovascular events were ascertained from a review of medical records and confirmed by direct dialogue with the patients, their families, and physicians. 2.5. Reactive hyperemia peripheral arterial tonometry RH-PAT has been described previously [17]. RH-PAT was conducted in the morning after subjects had fasted, but before medication intake and CAG. Noninvasive RH-PAT was performed with a blood pressure cuff placed on an upper arm (study arm), while the contralateral arm served as a control (control arm). The PAT probe was placed on a finger of each hand. After a 5-min equilibration period, the blood pressure cuff was inflated on the study arm to 60 mmHg above the systolic pressure or 200 mmHg for 5 min, and then the cuff was deflated to induce reactive hyperemia. RH-PAT data were digitally analyzed online (Endo-PAT2000 software, version 3.0.4 and 3.4.4, Itamar Medical Ltd., Caesarea, Israel). RHI was calculated as the ratio of the mean amplitude of the PAT signal over 1 min starting 1.5 min after cuff deflation (control arm, A; occluded arm, C) divided by the average amplitude of the PAT signal of a 2.5-min period before cuff inflation (baseline) (control arm, B; occluded arm, D). RHI values were automatically calculated by the online computer based on the ratio of (C/D)/(A/B). Because RHI values are not normally distributed, the natural logarithmic transformed RHI values (ln-RHI) were calculated for use in regression analyses, as reported previously [9,12]. The reproducibility of RHPAT technology has been confirmed in previous studies [9,12,18].
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Table 1 Baseline characteristics of coronary artery disease patients. All CAD (n ¼ 389) Age (years) Sex (male, %) BMI (kg/m2) Hypertension (yes, %) DM (yes, %) Current smoking (yes, %) Dyslipidemia (yes, %) BNP (pg/mL) eGFR (mL/min/1.73 m2) hs-CRP (mg/L) TC (mg/dL) TG (mg/dL) HDL-C (mg/dL) LDL-C (mg/dL) Total leukocyte count (/mm3) Monocyte count (/mm3) Neutrophil count (/mm3) Lymphocyte count (/mm3) Eosinophil count (/mm3) Basophil count (/mm3) LVEF (%) E/e0 Aspirin (%) b-blocker (%) ACE-I or ARB (%) CCB (%) HMG-CoA RI (%) Loop diuretics (%)
70.1 (9.9) 66.6 24.2 (3.4) 88.4 50.6 12.3 91.0 37.0 (16.9e71.9) 63.8 (16.8) 0.7 (0.3e1.3) 159.8 (35.2) 116 (87e156) 48.8 (12.5) 91.6 (29.8) 5600 (4600e6800) 328.6 (258.4e407) 3283.2 (2566.2e4151) 1679.6 (1324.8e2109.4) 158.1 (98.6e244.2) 22 (17.1e33.2) 62.8 (6.3) 13.6 (4.8) 97.7 75.1 74.0 65.0 96.1 7.5
Data are mean (standard deviation), median (interquartile range), or numbers (percentages). CAD indicates coronary artery disease; SVD, single vessel disease; MVD, multiple vessel disease; BMI, body mass index; DM, diabetes mellitus; BNP, Btype natriuretic peptide; eGFR, estimated glomerular filtration rate; Hs-CRP, highsensitivity C-reactive protein; TC, total cholesterol; TG, triglyceride; HDL-C, highdensity lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; LVEF, left ventricular ejection fraction; E/e0 , the ratio of early transmitral flow velocity to tissue Doppler early diastolic mitral annular velocity; ACE-I, angiotensin-converting enzyme inhibitors; ARB, angiotensin II receptor blockers; CCB, calcium channel blockers; HMG-CoA RI, hydroxymethylglutaryl coenzyme-A reductase inhibitors.
2.6. Statistical analyses
3. Results
patients, respectively. The total leukocyte, monocyte, neutrophil, lymphocyte, eosinophil, and basophil counts were 5600 [4600e6800]/mm3, 328.6 [258.4e407]/mm3, 3283.2 3 [2566.2e4151]/mm , 1679.6 [1316.1e2092.3]/mm3, 158.1 [98.6e244.2]/mm3 and 22 [17.1e33.2]/mm3, respectively. To examine the differences in clinical characteristics according to the severity of CAD, the patients were classified into CAD with SVD (n ¼ 149) or CAD with MVD (n ¼ 240). Total leukocyte and neutrophil counts tended to be higher in CAD patients with MVD compared with those with SVD, but the differences were not statistically significant (5500 [4400e6400] vs. 5700 [4700e6900], p ¼ 0.06 and 3256.2 [2553.6e4012.8] vs. 3337.7 [2627.2e4253.4], p ¼ 0.06, respectively, data not shown). Monocyte, lymphocyte, eosinophil, and basophil counts were not significantly different between CAD patients with SVD and those with MVD. The prevalence of DM and dyslipidemia were significantly higher (p ¼ 0.009 and p ¼ 0.02, respectively), and the use of aspirin, b-blockers, and angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers was also significantly higher in CAD patients with MVD than in those with SVD (p ¼ 0.01, p ¼ 0.004, and p ¼ 0.03, respectively, data not shown).
3.1. Baseline characteristics of CAD patients
3.2. Follow-up of cardiovascular events in CAD patients
The baseline characteristics of 389 consecutive CAD patients are shown in Table 1. Mean age was 70.1 ± 9.9 years, and 66.6% of the subjects were male. Hypertension, DM, current smoking, and dyslipidemia were present in 88.4%, 50.6%, 12.3%, and 91.0% of CAD
During a mean follow-up of 586 ± 378 days, 84 cardiovascular events were recorded in the total cohort of CAD patients. Those who had a cardiovascular event were more likely to be elderly and female (both p ¼ 0.02), have a higher prevalence of DM (p ¼ 0.01),
Non-normally distributed data are expressed as median (interquartile range). Continuous variables with normal distribution are expressed as mean ± standard deviation. The KolmogoroveSmirnov test was used to assess normal distribution of continuous data. Categorical data are presented by frequencies and percentages. Differences between two groups were tested with Fisher's exact test for categorical variables. Differences in continuous variables were analyzed by the unpaired t-test, or MannWhitney U test, as appropriate. KaplaneMeier analysis was performed in CAD patients and comparisons of the incidence of cardiovascular events was performed using the log-rank test. The Cox proportional hazard model was used to estimate the cardiovascular event hazard ratio (HR) and its 95% confidence interval (CI) in CAD patients by simple and multivariate analysis with stepwise backward models, including various clinical parameters other than total leukocyte count. A p-value <0.05 was considered statistically significant. Statistical analyses were performed using SPSS version 22 (IBM Japan Ltd., Tokyo, Japan).
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and higher BNP, HDL cholesterol, and E/e0 (ratio of early transmitral flow velocity to tissue doppler early diastolic mitral annular velocity) (p < 0.001, p < 0.001, and p ¼ 0.001, respectively). They also had lower TG levels (p ¼ 0.01) compared with those without a cardiovascular event (n ¼ 305) (Supplemantal Table 1). Monocyte counts tended to be higher in CAD patients with a cardiovascular event than in those without an event (323.3 [253e393.6]/mm3 vs. 354.2 [265.4e436.5]/mm3, p ¼ 0.07, Supplemental Table 1). Total leukocyte, neutrophil, lymphocyte, eosinophil, and basophil counts were not significantly different between CAD patients with and without a cardiovascular event (Supplemental Table 1). Receiver operating characteristics curves were constructed to determine the optimum cutoff value for monocyte count in CAD patients for the occurrence of a cardiovascular event. The monocyte count correlated significantly with the occurrence of cardiovascular events (area under the curve: 0.56, 95% CI: 0.49e0.63, data not shown), and showed that the cutoff threshold of monocyte count was 360/mm [3]. Using this threshold, the sensitivity, specificity, positive predictive value, and negative predictive value of monocyte count for the occurrence of a future cardiovascular event were 50.0%, 63.9%, 27.6%, and 82.3%, respectively. The cutoff value was used to stratify CAD patients into low-monocyte (n ¼ 242) and high-monocyte (n ¼ 147) groups. KaplaneMeier analysis then showed that the high-monocyte group had a higher risk for a future cardiovascular event than the low-monocyte group (p ¼ 0.047 by log-rank test, Fig. 1). Crude Cox hazard analysis identified seven variables as significant predictors of a cardiovascular event: age, sex, the prevalence of DM, ln-hs-CRP, BNP 100 pg/mL, high monocyte count (360/ mm3), and high E/e0 (Table 2). Multivariate Cox proportional hazard analysis, performed by a stepwise backward regression model, identified that a high monocyte count was a significant and independent predictor for a future cardiovascular event in CAD patients (HR: 1.63, 95% CI: 1.05e2.51, p ¼ 0.028, Table 2). 3.3. Association of ln-RHI with leukocyte subset counts in CAD patients The association between peripheral vascular endothelial dysfunction and leukocyte subtype counts was examined in 355 CAD patients who underwent RH-PAT. The patients were stratified into low-ln-RHI (n ¼ 176) and high-ln-RHI (n ¼ 179) groups
Fig. 1. KaplaneMeier analysis for the probability of cardiovascular events in CAD patients with low- or high-monocyte count (n ¼ 242 and n ¼ 147, respectively). CAD patients were divided into two groups using the cut-off value of monocyte count (360/mm3).
according to the mean ln-RHI value (ln-RHI: 0.57). BNP was significantly higher in low-ln-RHI patients than in high-ln-RHI patients (37.4 [18.0e85.3] pg/mL vs. 35.3 [13.3e63.8] pg/mL, p ¼ 0.007, Table 3). Total leukocyte, monocyte, and neutrophil counts were significantly higher in CAD patients with low-ln-RHI compared with those with high-ln-RHI (5950 [4800e6925] vs. 5400 [4350e6400], p ¼ 0.007, 341.7 [274.8e435.8] vs. 308.7 [238.5e383.5], p < 0.001 and 3373.5 [2775.6e4418.4] vs. 3129.3 [2417.3e3936.2], p ¼ 0.009, respectively, Table 3). In contrast, lymphocyte, eosinophil, and basophil counts were not significantly different between CAD patients with low-ln-RHI and those with high-ln-RHI (Table 3). The results of univariate analysis of the associations between lnRHI and clinical characteristics are shown in Supplemental Table 2. Ln-RHI was negatively correlated with ln-BNP, ln-TG, and E/e0 (Supplemental Table 2). Furthermore, ln-RHI was negatively correlated with ln-total leukocyte (r ¼ 0.187, p < 0.001), lnmonocyte (r ¼ 0.316, p < 0.001), and ln-neutrophil (r ¼ 0.175, p ¼ 0.001) counts (Supplemental Table 2). Univariate analysis also found that total leukocyte count was positively correlated with body mass index (BMI), current smoking, ln-hs-CRP, and ln-TG, but negatively correlated with age, ln-RHI, and ln-HDL cholesterol (Supplemental Table 3). The ln-monocyte count was positively correlated with male sex, BMI, current smoking, and ln-hs-CRP, and negatively correlated with ln-RHI and HDL cholesterol (Supplemental Table 3). The ln-neutrophil count was positively correlated with BMI, current smoking, and ln-hs-CRP, and negatively correlated with ln-RHI, eGFR, and HDL cholesterol (Supplemental Table 3). A stepwise multiple regression analysis was performed to identify the independent factors associated with ln-RHI. As there is an innate correlation between ln-total leukocyte and ln-neutrophil counts, significant clinical parameters associated with ln-RHI other than ln-total leukocyte in Pearson's correlation analysis were entered into the stepwise multiple regression analysis. Finally, lnmonocyte count and ln-BNP were found to be significant and independent factors associated with ln-RHI (adjusted R2 ¼ 0.126, p < 0.001, Table 4). Also, ln-TG was independently associated with ln-RHI (p ¼ 0.026, Table 4). 4. Discussion This study established the following associations in CAD patients: the risk of a cardiovascular event was significantly higher in patients with a high monocyte count (360/mm3); a high monocyte count was a significant and independent predictor of a cardiovascular event; monocyte counts were significantly higher in patients with low-ln-RHI than in those with high-ln-RHI; ln-RHI values were significantly and negatively correlated with monocyte, total leukocyte and neutrophil counts; and ln-monocyte count and ln-BNP were significant and independent factors associated with ln-RHI. The presence of CAD is associated with increased risk of death, and patients with severe CAD have a poor prognosis. However, the relationships between biomarkers of leukocyte subtype counts and the prognosis of patients with CAD remain unclear. In the present study, the occurrence of a cardiovascular event was significantly higher in CAD patients with a high rather than a low monocyte count, suggesting that a high monocyte count may contribute to the state of atherosclerosis and cardiovascular events in CAD. In addition, the present study showed that the baseline monocyte count tended to be higher in patients who had a cardiovascular event, and that a high monocyte count was a significant and independent predictor of cardiovascular events in CAD patients. A previous report showed that a high monocyte 500/mm3 in healthy and
Please cite this article in press as: E. Yamamoto, et al., Prognostic significance of circulating leukocyte subtype counts in patients with coronary artery disease, Atherosclerosis (2016), http://dx.doi.org/10.1016/j.atherosclerosis.2016.08.033
E. Yamamoto et al. / Atherosclerosis xxx (2016) 1e7
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Table 2 Cox proportional hazards analysis of risk of a cardiovascular event in CAD patients. Variable
Age Sex (male) BMI Hypertension (yes) DM (yes) Current smoking (yes) Dyslipidemia (yes) BNP (100 pg/mL) EGFR Ln-Hs-CRP Hemoglobin Ln-total leukocyte count High-monocyte (yes) Ln-neutrophil count Ln-lymphocyte count Ln-eosinophil count Ln-basophil count LVEF E/e0
Simple regression
Multiple regression stepwise backward
HR
95% CI
p-value
1.03 0.60 0.98 1.18 1.842 0.90 0.84 2.49 1.00 1.25 1.01 1.30 1.54 1.28 0.81 0.95 1.11 1.00 1.06
1.00e1.05 0.39e0.92 0.92e1.04 0.59e2.36 1.18e2.87 0.45e1.80 0.43e1.63 1.58e3.91 0.98e1.01 1.03e1.51 0.98e1.03 0.61e2.79 1.00e2.36 0.71e2.29 0.45e1.44 0.74e1.23 0.79e1.54 0.97e1.04 1.01e1.10
0.03 0.02 0.51 0.64 0.007 0.77 0.61 <0.001 0.49 0.02 0.62 0.50 0.049 0.41 0.46 0.71 0.55 1.00 0.009
HR 0.67
1.81
2.56
1.63
95% CI not selected 0.43e1.03 not selected not selected 1.15e2.83 not selected not selected 1.61e4.07 not selected not selected not selected not selected 1.05e2.51 not selected not selected not selected not selected not selected not selected
p-value 0.07
0.01
<0.001
0.028
HR, hazard ratio; 95% CI, 95% confidence interval.
Table 3 Baseline characteristics of CAD patients with rhi measurement.
Age (years) Sex (male, %) BMI (kg/m2) MVD (yes, %) Gensini score Hypertension (yes, %) DM (yes, %) Current smoking (yes, %) Dyslipidemia (yes, %) BNP (pg/mL) eGFR (mL/min/1.73 m2) Hs-CRP (mg/L) TC (mg/dL) TG (mg/dL) HDL-C (mg/dL) LDL-C (mg/dL) Total leukocyte count (/mm3) Monocyte count (/mm3) Neutrophil count (/mm3) Lymphocyte count (/mm3) Eosinophil count (/mm3) Basophil count (/mm3) LVEF (%) E/e0 Aspirin (%) b-blocker (%) ACE-I or ARB (%) CCB (%) HMG-CoA RI (%) Loop diuretics (%)
All CAD patients (n ¼ 355)
CAD þ Low-RHI (n ¼ 176)
CAD þ High-RHI (n ¼ 179)
p-value*
69.9 (9.9) 66.8 24.2 (3.4) 61.7 35.7 (30.1) 87.9 51.8 11.8 90.1 36.6 (16.4e72.3) 63.8 (16.8) 0.7 (0.3e1.3) 160.1 (35.3) 115 (87.5e155) 48.9 (12.5) 91.8 (29.9) 5600 (4600e6800) 329 (252.9e405.4) 3264 (2568.9e4075.6) 1682.1 (1334.2e2111) 151.8 (98.1e244.2) 22 (15.6e33) 63.0 (6.2) 13.6 (4.9) 97.7 74.4 74.4 65.1 96.3 7.3
69.5 (10.0) 70.5 24.4 (3.4) 62.5 34.4 (30.8) 87.5 50.6 14.2 90.3 37.4 (18.0e85.3) 63.3 (17.9) 0.7 (0.3e1.4) 161.7 (38.7) 124.5 (89e161) 48.3 (12.7) 92.5 (32.7) 5950 (4800e6925) 341.7 (274.8e435.8) 3373.5 (2775.6e4418.4) 1679.6 (1380.2e2109.2) 151 (102e228) 22 (12.4e33.7) 62.9 (6.2) 14.1 (5.2) 98.3 71.6 76.1 64.2 95.5 7.4
70.3 (9.7) 63.1 24.1 (3.4) 60.8 37.0 (29.4) 88.3 53.1 9.5 89.9 35.3 (13.3e63.8) 64.3 (15.7) 0.6 (0.3e1.1) 158.5 (31.6) 107 (84.5e140) 49.4 (12.4) 91.0 (27.0) 5400 (4350e6400) 308.7 (238.5e383.5) 3129.3 (2417.3e3936.2) 1694 (1286.3e2111) 159 (89.1e264.6) 22 (18.2e32.5) 63.1 (6.2) 13.2 (4.7) 97.2 77.1 72.6 65.9 97.2 7.3
0.45 0.14 0.35 0.76 0.4 0.82 0.64 0.17 0.9 0.007 0.56 0.3 0.39 0.05 0.42 0.64 0.007 <0.001 0.009 0.2 0.78 0.51 0.63 0.1 0.49 0.24 0.45 0.73 0.38 0.96
Data are mean (standard deviation), median (interquartile range), or numbers (percentages). *Comparison between 176 low-RHI group and 179 high-RHI group.
middle-aged subjects was predictive of a coronary event [19], while the present study demonstrated that a high monocyte 360/mm3 in CAD patients predicted a cardiovascular event, including a coronary event. These studies suggest that the cutoff values of monocyte counts for predicting a cardiovascular event may vary according to the clinical characteristics of the patient. One reason for this difference in monocyte count cutoff value from previous reports could be related to differences in the study populations, and CAD patients in the current study had a higher risk of a
cardiovascular event than the general population. Another consideration is that all patients in this study were Japanese, which may limit comparisons with other studies with different cutoff values of monocyte counts in other countries. A previous report by Nozawa et al. [20] demonstrated that the cutoff value of monocyte count for plaque progression in patients during the acute phase of acute myocardial infarction was 800/mm3, suggesting that the cutoff value of monocyte counts for predicting cardiovascular outcome may vary according to the severity of atherosclerosis.
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E. Yamamoto et al. / Atherosclerosis xxx (2016) 1e7
Table 4 Stepwise multivariable regression analysis for ln-RHI. Variable
Ln-neutrophil count Ln-monocyte count Ln-BNP Ln-TG
Unstandardized coefficient
Standardized coefficient
95% CI for B
p-value
B
SEM
b
Lower bound
Upper bound
0.003 0.197 0.018 0.057
0.036 0.035 0.007 0.025
0.005 0.322 0.132 0.110
0.068 0.266 0.032 0.106
0.074 0.127 0.005 0.007
0.938 <0.001 0.007 0.026
SEM, standard error of the mean.
Inflammation is believed to have a pivotal role in the pathogenesis of various cardiovascular diseases, and Ridker et al. previously reported that plasma concentration of CRP, a representative biomarker of inflammation, predicts the risk of future myocardial infarction in apparently healthy men [21] and women [22]. Thus, atherosclerosis is now regarded as a chronic inflammatory disease, with monocytes and monocyte-derived macrophages playing pivotal roles in its initiation and progression [23e25]. The recruitment of monocytes into the arterial wall and their development into macrophages are the earliest events in atherosclerosis, indicating the importance of inflammation in vascular endothelial dysfunction and initiation of atherosclerosis. Several studies have reported that vascular endothelial dysfunction is a useful marker for cardiovascular events in subjects with CAD [2,3,5]. Hence, we hypothesized that a high monocyte count would predict a future cardiovascular event in CAD patients at least partially via vascular endothelial dysfunction. This study clearly revealed that total leukocyte count and its components (i.e., monocyte and neutrophil counts) were correlated with ln-RHI, reflecting peripheral vascular endothelial function. For the first time, as far as we are aware, it was established that the monocyte count in CAD patients was strongly and significantly correlated with peripheral endothelial dysfunction. The monocyte count has also been reported to be an independent predictor of common carotid atherosclerosis in healthy subjects [26,27]. In addition, Matsumura et al. recently reported that monocyte counts were positively correlated with both mean and maximum intima-media thickness of the common carotid artery in subjects with type 2 DM [28]. Taken together, these studies suggest that, of the leukocyte fractions, the monocyte count is the most useful marker for the evaluation of atherosclerosis, and is involved at all stages of the progression of atherosclerosis. Monocytes, as representatives of the innate immune system, may play a major role not only in vascular endothelial dysfunction, but also in atherosclerotic plaque development. Monocyte-endothelial interactions have been implicated in the initiation of endothelial dysfunction in many vascular diseases [29]. Furthermore, these dysfunctions have been partially attributed to impaired activity of endothelial-derived nitric oxide, and overproduction of reactive oxygen species. For instance, excessive production of reactive oxygen species increases lectin-like oxidized low-density lipoprotein receptor-1 expression, and accelerates vascular endothelial dysfunction and atherosclerosis [30]. The current study indicates that the RHI value in CAD patients is correlated with the severity of coronary atherosclerosis, and may constitute a significant predictor for the occurrence of a coronary event. Indeed, Bonetti et al. previously reported that an attenuated digital hyperemic response, as measured by RH-PAT, was closely associated with impaired coronary endothelial function, measured by the increase in coronary blood flow in response to acetylcholine [17], and we previously demonstrated the usefulness of RHI as a predictor of coronary revascularization in CAD patients complicated by chronic kidney disease [10]. Recently, Li et al. reported that a high leukocyte count was independently associated with vascular
dysfunction assessed by RH-PAT in patients with low cardiovascular risk [31]. In the present study, leukocyte and monocyte counts in CAD patients were closely associated with peripheral endothelial dysfunction, indicated by decreased RHI. Therefore, the monocyte count, reflecting vascular inflammation, may predict vascular endothelial dysfunction, leading to a cardiovascular event. There are several limitations in this study. First, this was a onecenter study with a relatively small patient population. However, even in this small population, the monocyte count was found to be closely associated with vascular endothelial dysfunction and prognosis of CAD. Further large multicenter studies involving larger numbers of patients will be required to determine the importance of leukocyte subtype counts in CAD. Second, this study was observational and did not include an intervention such as anti-inflammatory drugs. The benefits of anti-inflammatory therapy for cardiovascular diseases still remain unclear. Therefore, prospective interventional studies in CAD patients in a large-scale population are necessary. Third, in this study, as we measured hs-CRP, but not proinflammatory mediators, such as monocyte chemotactic protein-1 and tumor necrosis factor-a, we could not examine the relationship between monocyte count and other inflammatory biomarkers and their involvement in peripheral vascular endothelial dysfunction. However, despite these limitations, the prognostic significance of monocyte count in CAD patients was clearly demonstrated. To the best of our knowledge, the study provides the first evidence for the significant association between monocyte count and peripheral endothelial dysfunction in CAD patients. Monocyte counts may be a useful predictor of vascular endothelial dysfunction and cardiovascular events in CAD patients. Conflict of interest The authors declared they do not have anything to disclose regarding conflict of interest with respect to this manuscript. Financial support This work was supported in part by Grants-in Aid for Scientific Research (grant number: B24790770 to E. Yamamoto) from the Japanese Ministry of Education, Culture, Sports, Science and Technology, the SENSHIN Medical Research Foundation (to E. Yamamoto), and the Japan Cardiovascular Research Foundation (to H. Ogawa). Clinical trial registration URL: http://www.umin.ac.jp/ctr/. UMIN000018886.
Unique
identifier:
Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.atherosclerosis.2016.08.033.
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