The particular interactions of the traditional cardiovascular risk factors with different circulating specific leukocyte subtype counts in blood: an observational study.

Abstract

The pathogenesis of atherosclerosis is multifactorial, however the impact of inflammatory cells in this process is well known. Different traditional cardiovascular risk factors (CVRFs) may have specifically different effects on leukocyte subtype. Thus, these special interactions may induce different vascular involvement forms due to the altered endothelial damage and vascular repair mechanisms. The aim of the present study was to investigate whether there is any specific relationship between the leukocyte subtypes and the traditional CVRFs and to evaluate the independency of possible relationships.
The study had a cross-sectional observational design. The study population consisted of the patients who underwent coronary angiography with a suspicion of coronary artery disease (CAD) at our institution in an outpatient manner. We enrolled 677 consecutive eligible patients with CAD or normal coronary arteries (NCA) and investigated the associations of traditional CVRFs, demographic properties and biochemical parameters including fasting plasma glucose (FPG), creatinine, serum uric acid level (SUA) and lipids with total circulating inflammatory cell (WBC, leukocytes) and subtype counts including neutrophils (N), lymphocytes (L) and monocytes (M). As a dependent variable, total leukocyte count and subtypes, and neutrophil/lymphocyte ratio (N/L ratio) which has been found to being related with increased vascular risk and events were investigated in the groups determined by the presence or absence of CVRFs and CAD by the univariate analyses and then multiple linear regression analyses.
When we performed multiple linear regression analyses to determine the independent associations of inflammatory cell subtypes, we have found that FPG had an independent incremental association with WBC (β±SE:4.2±1.4, p=0.004) and N (β±SE:4.2±1.2, p=0.001). Current smoking had an independent incremental association with WBC and all cell subtypes (for WBC, N, L, and M: β±SE: 748±161, p<0.001; β±SE: 556±136, p<0.001; β±SE: 185±69, p=0.007; β±SE: 38±20, p=0.061, respectively) and SUA had an independent incremental association with WBC (β±SE: 115±43, p=0.008), N (β±SE: 107±38, p=0.005) and M (β±SE: 26±6, p<0.001). Hypertension had an independent incremental association with WBC (β±SE: 431±140, p=0.002) and N (β±SE: 315±118, p=0.008). Male gender had an independent incremental association with only M (β±SE: 52±20, p=0.010). Family history of CAD had an independent decremental association with WBC (β±SE: -327±139, p=0.019) and N (β±SE: -326±121, p=0.007). Finally, age had an independent decremental association with WBC (β±SE: -32±7, p<0.001) and L (β±SE: -16±3, p<0.001). The N/L ratio was independently related with increased age (p<0.001), FPG (p=0.003) and SUA (p=0.012).
Our study results demonstrate that leukocyte subtypes have different specific associations with traditional CVRFs. We found that FPG affects specifically N while SUA affects specifically N and M, and current smoking affects nonspecifically on all cell subtypes. While hypertension with N and male gender with M were specifically related, age and family history of CAD were only related to L. These different interactions may lead to different endothelial damage and vascular repair mechanisms.

Full text

Page 1

The particular interactions of the traditional cardiovascular risk
factors with different circulating specific leukocyte subtypes counts in
blood: an observational study
Geleneksel kardiyovasküler risk faktörlerinin dolaşımdaki farklı özgül lökosit alt tip sayımları
ile belirli etkileşimleri: Gözlemsel bir çalışma
Original Investigation Özgün Araşt›rma
Address for Correspondence/Yaz›şma Adresi: Dr. Sinan Altan Kocaman, Gazi Üniversitesi Tıp Fakültesi, Kardiyoloji Anabilim Dalı,
Beşevler, 06500, Ankara-Turkey Phone: +90 312 202 56 29 Fax: +90 312 212 90 12 E-mail: sinanaltan@gmail.com
The work partly presented at the 25. National Congress of the Turkish Society of Cardiology as a poster presentation, 22-25 October, 2009, İstanbul, Turkey.
Türk Kardiyol Dern Arş 2009; 37:109-241[P-189].
Accepted Date/Kabul Tarihi: 07.06.2011 Available Online Date/Çevrimiçi Yayın Tarihi: XXXXXX
©Telif Hakk› 2011 AVES Yay›nc›l›k Ltd. Şti. - Makale metnine www.anakarder.com web sayfas›ndan ulaş›labilir.
©Copyright 2011 by AVES Yay›nc›l›k Ltd. - Available on-line at www.anakarder.com
doi:10.5152/akd.2011.158
Sinan Altan Kocaman, Asife Şahinarslan, Tolga Kunak, Serhat Balcıoğlu, Mustafa Çetin1, Mustafa Cemri,
Timur Timurkaynak, Bülent Boyacı, Atiye Çengel
Department of Cardiology, Faculty of Medicine, Gazi University, Ankara
1Clinic of Cardiology, Rize Education and Research Hospital, Rize-Turkey
ABSTRACT
Objective: The pathogenesis of atherosclerosis is multifactorial, however the impact of inflammatory cells in this process is well known.
Different traditional cardiovascular risk factors (CVRFs) may have specifically different effects on leukocyte subtype. Thus, these special inter-
actions may induce different vascular involvement forms due to the altered endothelial damage and vascular repair mechanisms. The aim of
the present study was to investigate whether there is any specific relationship between the leukocyte subtypes and the traditional CVRFs and
to evaluate the independency of possible relationships.
Methods: The study had a cross-sectional observational design. The study population consisted of the patients who underwent coronary
angiography with a suspicion of coronary artery disease (CAD) at our institution in an outpatient manner. We enrolled 677 consecutive eligible
patients with CAD or normal coronary arteries (NCA) and investigated the associations of traditional CVRFs, demographic properties and bio-
chemical parameters including fasting plasma glucose (FPG), creatinine, serum uric acid level (SUA) and lipids with total circulating inflamma-
tory cell (WBC, leukocytes) and subtype counts including neutrophils (N), lymphocytes (L) and monocytes (M). As a dependent variable, total
leukocyte count and subtypes, and neutrophil/lymphocyte ratio (N/L ratio) which has been found to being related with increased vascular risk
and events were investigated in the groups determined by the presence or absence of CVRFs and CAD by the univariate analyses and then
multiple linear regression analyses.
Results: When we performed multiple linear regression analyses to determine the independent associations of inflammatory cell subtypes, we
have found that FPG had an independent incremental association with WBC (β±SE:4.2±1.4, p=0.004) and N (β±SE:4.2±1.2, p=0.001). Current
smoking had an independent incremental association with WBC and all cell subtypes (for WBC, N, L, and M: β±SE: 748±161, p<0.001; β±SE:
556±136, p<0.001; β±SE: 185±69, p=0.007; β±SE: 38±20, p=0.061, respectively) and SUA had an independent incremental association with WBC
(β±SE: 115±43, p=0.008), N (β±SE: 107±38, p=0.005) and M (β±SE: 26±6, p<0.001). Hypertension had an independent incremental association with
WBC (β±SE: 431±140, p=0.002) and N (β±SE: 315±118, p=0.008). Male gender had an independent incremental association with only M (β±SE:
52±20, p=0.010). Family history of CAD had an independent decremental association with WBC (β±SE: -327±139, p=0.019) and N (β±SE: -326±121,
p=0.007). Finally, age had an independent decremental association with WBC (β±SE: -32±7, p<0.001) and L (β±SE: -16±3, p<0.001). The N/L ratio
was independently related with increased age (p<0.001), FPG (p=0.003) and SUA (p=0.012).
Conclusion: Our study results demonstrate that leukocyte subtypes have different specific associations with traditional CVRFs. We found that
FPG affects specifically N while SUA affects specifically N and M, and current smoking affects nonspecifically on all cell subtypes. While
hypertension with N and male gender with M were specifically related, age and family history of CAD were only related to L. These different
interactions may lead to different endothelial damage and vascular repair mechanisms. (Anadolu Kardiyol Derg 2011 Nov 1; 11(7): 000-000)
Key words: Coronary artery disease, inflammatory cells, neutrophil, monocyte, lymphocyte, cardiovascular risk factors, neutrophil-to-lympho-
cyte ratio, regression analysis
Article in Press

Page 2

Introduction
In recent years, it has been recognized that atherosclerosis
is an active, chronic inflammatory process. Inflammation is a
critical feature of atherosclerosis and its clinical manifestations.
The pathogenesis of atherosclerosis is multifactorial; however,
the effector roles of inflammatory cells in this process are well
known (1).
Although leukocyte subtypes play a crucial role in athero-
sclerosis (2-4), little attention has been paid to the different
relationships of leukocyte subtypes with traditional cardiovas-
cular risk factors (CVRFs), demographic properties and bio-
chemical parameters. Different CVRFs may have specifically
different peripheral effects on leukocyte subtype, through which
these particular interactions may induce different vascular
involvement forms due to the altered endothelial damage and
vascular repair mechanisms. These effects may be a prerequi-
site for initiation and progression of the coronary artery disease
(CAD) and may determine the type of vascular lesion with a dif-
ferent inflammatory milieu.
For a long time it has been believed that in vascular system,
the damaged endothelial cells can only be repaired or replaced
by the proliferation and migration of neighboring endothelial
cells (5). However, this concept has changed together with
determination of endothelial progenitor cells (EPC) having both
of stem cell and endothelial cell markers and being able to trans-
form into the endothelial phenotype (6-9). After first time defined
by Asaraha et al. (10), we have more knowledge about their
source, roles, levels and functionality. The peripheral effects of
CVRFs on progenitors were provided by many studies (11-13).
The relationship between leukocytes and increased cardio-
vascular risk is well known. Horne et al. (14) have aimed to deter-
mine the predictive ability of total white blood cell (WBC) count
and its subtypes for risk of death or myocardial infarction (MI) and
found that high neutrophil (N), monocyte (M) and low lymphocyte
(L) counts as well as high N/L ratio are independently related to
increased cardiovascular events. These findings were supported
by other studies (15-17). However, there are no studies on spe-
cific relationships between the inflammatory cells of atheroscle-
rosis and traditional CVRFs focusing particularly on N, L and M as
well as total circulating inflammatory cell count (WBC, white
blood cell count, leukocyte).
The aim of the present study was to investigate whether
there is any specific relationship between the leukocyte subtype
counts and the traditional CVRF, biochemical parameters and to
evaluate the independency of possible relationships.
Methods
Study design and patients
This study has a cross-sectional and observational design.
The Local Ethics review board approved the study protocol. All
the patients had given informed consent before the study. The
study population consisted of the patients who underwent coro-
nary angiography with a suspicion of CAD at Gazi University
School of Medicine in an outpatient manner between October
2005 and June 2006. The study population consisted of 677 eli-
gible consecutive patients. Five hundred and eight (75%) of 677
patients had CAD (men 76%, mean age: 60±10 years). One hun-
dred sixty nine patients (25%) had normal coronary arteries
Kocaman et al.
Circulating specific leukocyte subtypes
Anadolu Kardiyol Derg 2011 Kasım 1; 11(7): 000-000
doi:10.5152/akd.2011.158
ÖZET
Amaç: Aterosklerozun patogenezi çok faktörlüdür, bununla birlikte enflamasyon hücrelerinin bu süreçteki etkin rolleri iyi bilinmektedir. Farklı gele-
neksel kardiyovasküler risk faktörleri (KVRF) lökosit alt tipleri üzerine özgül olarak farklı etkilere sahip olabilirler ve bu özel etkileşimler değişen
endotel hasarı ve vasküler onarım mekanizmalarıyla farklı vasküler tutulum şekillerine sebep olabilir. Bu çalışmanın amacı lökosit alt tipleri ve gele-
neksel KVRF arasında özgül bir ilişkinin var olup olmadığını incelemek ve olası ilişkilerin bağımsızlığını değerlendirmekti.
Yöntemler: Çalışma gözlemsel ve enine-kesitli olarak planlandı. Çalışma popülasyonu hastanemize ayaktan başvuran ve koroner arter hastalığı
(KAH) şüphesi ile koroner anjiyografileri yapılmış hastalardan oluşturuldu. Koroner arter hastalığı ya da normal koroner arterleri (NKA) olan 677
ardışık, çalışma kriterlerine uygun hasta dâhil edildi. Geleneksel KVRF’leri, demografik özellikler ve açlık kan şekeri (AKŞ), kreatinin, serum ürik asit
(SUA) düzeyi ve lipit düzeylerinin periferik kan toplam enflamasyon hücre sayısı (WBC, lökositler) ve nötrofil (N), lenfosit (L) ve monositleri (M)
içeren alt tiplerinin sayıları ile olan ilişkileri araştırıldı. Bağımlı değişken olarak total lökosit sayısı, alt tipleri ve artmış vasküler risk ve olaylar ile
ilişkili olduğu ortaya konmuş olan nötrofil/lenfosit oranı (N/L oranı), KVRF’lerinin ve KAH’nın varlığı ya da yokluğu ile belirlenen gruplarda tek değiş-
kenli ve daha sonra çok değişkenli analizler ile araştırıldı.
Bulgular: Lökosit alt tiplerinin bağımsız öngörücülerini belirlemek için çoklu regresyon analizleri gerçekleştirdiğimizde, AKŞ’nin WBC (β±SE:4.2±1.4,
p=0.004) ve N (β±SE:4.2±1.2, p=0.001) ile bağımsız arttırıcı bir ilişkiye sahip olduğunu bulduk. Aktif sigara içimi WBC ve tüm hücre alt tipleri ile bağım-
sız bir arttırıcı ilişkiye sahipti (WBC, N, L ve M için: 748±161, p<0.001; β±SE: 556±136, p<0.001; β±SE: 185±69, p=0.007 ve β±SE: 38±20, p=0.061, sırasıyla)
ve SUA düzeyi WBC (β±SE: 115±43, p=0.008), N (β±SE: 107±38, p=0.005) ve M (β±SE: 26±6, p<0.001) ile bağımsız artırıcı bir ilişkiye sahipti.
Hipertansiyon WBC (β±SE: 431±140, p=0.002) ve N (β±SE: 315±118, p=0.008) ile artışımsal bir ilişkiye sahipti. Erkek cinsiyet yalnız monosit sayısı ile
artışımsal bir ilişkiye sahipti β±SE: 52±20, p=0.010). Koroner arter hastalığı için aile öyküsü WBC (β±SE: -327±139, p=0.019) ve N (β±SE: -326±121,
p=0.007) sayısı ile ters ilişkiye sahipti. Son olarak, yaş WBC (β±SE: -32±7, p<0.001) ve L (β±SE: -16±3, p<0.001) ile bağımsız azaltıcı bir ilişkiye sahip-
ti. Artmış yaş, AKŞ ve ürik asit bağımsız olarak N/L oranı ile ilişkiliydi (p<0.001; p=0.003; p=0.012, sırasıyla).
Sonuç: Bizim çalışma sonuçlarımız lökosit alt tiplerinin geleneksel KVRF’leri ile farklı özgül ilişkilere sahip olduğunu ortaya koymaktadır. Biz SUA’nın
özgül olarak N ve M’leri etkilediği ve aktif sigara içiminin özgül olmayan bir şekilde tüm hücre alt tiplerini etkilerken, AKŞ’nin özgül olarak N’leri
etkilediğini bulduk. Hipertansiyon N ile ve erkek cinsiyet M ile özgül olarak ilişkiliyken, yaş ve KAH için aile öyküsü varlığı sadece L ile ilişkiliydi. Bu
farklı ilişkiler farklı endotel hasarı ve vasküler onarım mekanizmalarına yol açabilir. (Anadolu Kardiyol Derg 2011 Kas 1; 11(7): 000-000)
Anahtar kelimeler: Koroner arter hastalığı, enflamasyon hücreleri, nötrofil, monosit, lenfosit, kardiyovasküler risk faktörleri, nötrofil-lenfosit
oranı, regresyon analizi

Page 3

(NCA) without any stenotic lesion with visual assessment (men
53%, mean age: 53±11 years).
As a dependent variable, total leukocyte count and subtypes,
and neutrophil/lymphocyte were investigated in the groups
determined by the presence or absence of CVRFs and CAD.
Total and differential leukocyte counts and biochemical
markers, which were obtained at most one week before coro-
nary angiography, were used for analyses. Patients with symp-
tomatic peripheral vascular disease (transient ischemic attack,
stroke, intermittent claudication, peripheral revascularization, or
amputation), evidence of ongoing infection or inflammation,
recent acute coronary syndrome either with or without
ST-segment elevation (one month before enrollment), hemato-
logical disorders, known malignancy and drug history included
anti-gout agent were excluded from the study.
Clinical variables and cardiovascular risk factors
Baseline characteristics were recorded during the direct
interview with the patient. Hypertension was defined as the
active use of antihypertensive drugs or documentation of blood
pressure more than 140/90 mmHg. Diabetes mellitus was defined
as fasting plasma glucose (FPG) levels over 126 mg/dl or glucose
level over 200 mg/dl at any measurement or active use antidia-
betic treatment. Smoking was defined as current smoking. The
family history for CAD was defined as a history of CAD or sudden
death in a first-degree relative before the age of 55 years for men
and 65 years for women.
Traditional CVRFs were defined as presence of hyperten-
sion, diabetes mellitus, smoking status, and family history for
CAD. Demographic properties included age and gender, and bio-
chemical parameters included fasting plasma glucose (FPG),
creatinine, serum uric acid level (SUA) and lipids. Baseline char-
acteristics, predictor variables - presence of CAD and CVRFs,
outcome variables - leukocyte count and subtypes were includ-
ed the analyses.
Laboratory analyses
Fasting blood glucose, serum creatinine, total cholesterol,
HDL- cholesterol, LDL- cholesterol, and triglyceride levels were
recorded. Blood samples were drawn by venipuncture to per-
form routine blood chemistry. Serum uric acid (SUA) levels were
determined with enzymatic colorimetric method by clinical
chemistry auto-analyzer (Aeroset, Abbott Laboratory, Abbott
Park, IL, USA). Total and differential leukocyte counts were mea-
sured by an automated hematology analyzer (Coulter Gen-S,
COULTER Corp, Miami, USA). Absolute cell counts were used in
the analyses.
Statistical analysis
The SPSS statistical software (SPSS 15.0 for windows, Inc.,
Chicago, IL, USA) was used for all statistical calculations.
Continuous variables are given as mean±SD; categorical vari-
ables are defined as percentage. Data were tested for normal
distribution using the Kolmogorov-Smirnov test. The Student’s
t-test was used for the univariate analysis of the continuous
variables and the Chi-square test for the categorical variables.
Firstly, the inflammatory status of study population was assessed
by Student’s t-test as an univariate analysis between NCA and
CAD groups. After then, to compare the effect of each risk factor
on each leukocyte subtype, we performed univariate analyses
including Student’s t-test and ANOVA, in which different groups
were determined by FPG and the quartiles for SUA levels (for
categories of FPG: <100mg/dl, 100-126mg/dl and >126mg/dl and
for quartiles of SUA: Q1, 1.5-4.1 mg/dl; Q2, 4.2-5.0 mg/dl; Q3, 5.1-
6.2 mg/dl; Q4, 6.3-12.9 mg/dl). Lastly, we performed multiple lin-
ear regression models to assess multivariate relations between
total and differential leukocyte counts and the CVRFs in all
patients and also separately in NCA and CAD groups.
All tests of significance were two-tailed. Statistical signifi-
cance was defined as p<0.05.
Results
Inflammatory cells and presence of CAD (Table 1)
When the inflammatory status of study population was
assessed according to circulating inflammatory cells, WBC
(p<0.001), N (p<0.001) and M (p<0.001) were higher in patients
with CAD than those with NCA. Lymphocytes were not signifi-
cantly different between two groups.
The univariate relationships of leukocyte subtypes
with CVRFs (Table 2)
When the effects of each risk factor on each leukocyte sub-
type were compared in univariate analyses the following rela-
tionships were observed: age with L (p=0.001) negatively, male
gender with M (p<0.001) positively, hypertension with N (p=0.021)
positively, current smoking with N, L and M positively (p<0.001;
p<0.001; p=0.005, respectively), family history of CAD with N
(p=0.017) negatively, the categories for fasting plasma glucose
with N positively (<100mg/dl, 100-126mg/dl and >126mg/dl,
p=0.003), and the quartiles for SUA with M positively (Q1 to Q4,
p<0.001). While diabetes mellitus was positively related with N,
(p=0.019) and especially in patients with NCA was negatively
related with M. This reverse relation, which was confined to
NCA group was also verified by multivariate analysis. Lipids,
creatinine and other biochemical parameters except SUA and
FPG were not significantly related to leukocyte subtypes.
The multivariate relationships of leukocyte subtypes with
CVRFs (Tables 3-7)
When we performed multiple linear regression analyses to
determine the independent associations of inflammatory cell
subtypes, we have found that FPG had an independent incre-
mental association with WBC (β±SE:4.2±1.4, p=0.004) and N
(β±SE:4.2±1.2, p=0.001). Current smoking had an independent
Kocaman et al.
Circulating specific leukocyte subtypes
Anadolu Kardiyol Derg 2011 Kasım 1; 11(7): 000-000
doi:10.5152/akd.2011.158

Page 4

incremental association with WBC and all cell subtypes (for
WBC, N, L, and M: β±SE: 748±161, p<0.001; β±SE: 556±136,
p<0.001; β±SE: 185±69, p=0.007; β±SE: 38±20, p=0.061, respec-
tively). SUA had an independent incremental association with
WBC (β±SE: 115±43, p=0.008), N (β±SE: 107±38, p=0.005) and M
(β±SE: 26±6, p<0.001). Hypertension had an independent incre-
mental association with WBC (β±SE: 431±140, p=0.002) and N
(β±SE: 315±118, p=0.008). Male gender had an independent incre-
mental association with only M (β±SE: 52±20, p=0.010). Family
history of CAD had an independent decremental association with
WBC (β±SE: -327±139, p=0.019) and N (β±SE: -326±121, p=0.007).
Finally, age had an independent decremental association with
WBC (β±SE: -32±7, p<0.001) and L (β±SE: -16±3, p<0.001). Similar
results were also obtained separately in both NCA and CAD sub-
groups. The N/L ratio was independently related with increased
age (p<0.001), FPG (p=0.003) and SUA (p=0.012).
Discussion
Our study results demonstrate that leukocyte subtypes have
different specific associations with traditional CVRFs.
We found that FPG affects specifically N while SUA affects
specifically N and M, and current smoking affects nonspecifi-
cally on all cell subtypes. While hypertension with N and male
gender with M were specifically related, age and family history
of CAD were only related to L. Furthermore, these relationships
were independent of all confounding factors and CAD.
In an additional analysis, we also as a dependent variable
searched the N/L ratio which has been found to being related with
increased vascular risk and events in previous studies (14-17) and
found that it was independently related with increased age, FPG
and SUA.
Atherosclerosis is a multifactorial disease, with hypertension,
dyslipidemia, dysglycemia, smoking and other CVRFs. These fac-
tors cause endothelial injury and contribute to pathogenesis.
Atherosclerosis develops as a process occurring in vessel
wall, which begins with an active cellular and passive infiltrative
response to endothelial injury. Endothelial dysfunction is char-
acterized with dysfunction and loss of monolayer cells covering
the inside of the vessels, which is endothelium. Endothelial dys-
function is the first stage in atherosclerosis. The regenerative
capacity of endothelium provides protection against atheroscle-
rosis. Failure of the endothelial repair initiates atherosclerotic
inflammation and lesion formation, so-called plaque, especially
in non-laminar flow stress points in vascular bed (18).
In recent years, it has been recognized that atherogenesis
represents an active, inflammatory process rather than simply
passive injury with infiltration of lipids and other substances in
blood (19-22). Inflammation plays a critical key role in CAD and
other manifestations of atherosclerosis, in which immune mecha-
nisms interact with metabolic risk factors and hemodynamics to
initiate, propagate, and activate lesions in the arterial tree (23).
Leukocytes play a major role in these inflammatory processes
(24), which may be reparative or pathogenic in nature. The micro-
environments produced by CVRFs may determine these roles.
Inflammatory cells dominate in early atherosclerotic lesions. Their
functional molecules accelerate progression of the lesions, and
can elicit acute coronary syndromes. Monocytes (macrophages
in tissue) and T-lymphocytes are prevalent and pathogenic within
unstable plaques. The pathogenesis of atherosclerosis is multifac-
torial; however, the effector roles of inflammatory cells for plaque
formation is clear (1).
Blood-borne inflammatory and immune cells constitute an
important part of an atheroma. Chapman et al. (25) found that an
inflammatory cell subtype count, monocyte count, in blood was
a better cross-sectional marker for the presence of atheroscle-
rotic plaque than interleukine-6 (IL-6), high-sensitive C-reactive
Kocaman et al.
Circulating specific leukocyte subtypes
Anadolu Kardiyol Derg 2011 Kasım 1; 11(7): 000-000
doi:10.5152/akd.2011.158
Variables

Age, years
Gender, male, %
Hypertension, %
Diabetes mellitus, %
Family history, %
Smoking, current, %
Total cholesterol, mg/dl
LDL, mg/dl
HDL, mg/dl
Triglycerides, mg/dl
Fasting plasma glucose, mg/dl
Serum creatinine, mg/dl
Serum uric acid, mg/dl
Hemoglobin, mg/dl
Platelets, 103/mm-3
Leukocytes, mm-3
Neutrophils, mm-3
Lymphocytes, mm-3
Monocytes, mm-3
Medications
Aspirin, %
ACEi/ARB, %
Calcium channel blockers, %
β-blockers, %
Statin, %
NCA
(n=169)
53±11
53
53
17
28
46
202±40
123±32
46±12
164±89
103±25
1.0±0.5
4.69±1.35
14.0±1.7
243±72
6959±1669
4084±1327
2170±683
506±150

60
44
30
38
30
CAD
(n=508)
60±10
76
59
29
32
57
188±41
116±35
43±10
147±76
127±56
1.2±1.1
5.59±1.66
13.9±1.8
247±77
8117±2530
5100±2331
2178±795
594±234

70
52
40
36
36
p*
<0.001
<0.001
0.08
<0.001
NS
0.002
<0.001
0.001
<0.001
0.002
<0.001
<0.001
<0.001
NS
NS
<0.001
<0.001
NS
<0.001
NS
NS
NS
NS
NS
Continuous variables are given as mean ± SD and categorical variables are presented
as percentage values
*unpaired Student’s t-test and Chi-square test
ACEi - angiotensin-converting enzyme inhibitors, ARB - angiotensin II receptor blockers,
CAD - coronary artery disease, HDL - high density lipoprotein, LDL - low density lipopro-
tein, NCA - normal coronary arteries
Table 1. Characteristics of the study population

Page 5

protein (hsCRP), fibrinogen, and white blood cells. Furthermore,
Johnsen et al. (26) showed that monocyte count was an inde-
pendent predictor of future atherosclerotic plaque formation.
Except the patients with chronic kidney disease, cross-sectional
studies reported increased numbers of circulating monocytes in
individuals with prevalent atherosclerotic disease (27, 28).
Additionally, prospective studies suggested that monocyte count
can predict cardiovascular events independently (29, 30).
Recent research has focused on the use of inflammatory
biomarkers and cells (31) in the prediction of cardiovascular
risk. However, information is scant regarding the association
between particularly these inflammatory cells and CVRFs. To our
knowledge, our study is the first report focusing on the specific
relationships between CVRFs and leukocyte subtypes.
A recent research has shown that WBC count has signifi-
cant correlation with fasting (32) and postprandial glucose (33).
In another study, SUA was significantly and independently asso-
ciated with neutrophil count (34). In a recently published study,
hyperlipidemia-triggered neutrophilia was shown to promote
early atherosclerosis (35).
Kocaman et al.
Circulating specific leukocyte subtypes
Anadolu Kardiyol Derg 2011 Kasım 1; 11(7): 000-000
doi:10.5152/akd.2011.158
Risk factors
Age
<45 years
≥45 years
Gender
Female
Male
Hypertension
Absent
Present
Diabetes Mellitus Overall 7244±1665 7534±1520 0.053
Absent NCA 6963±1630 6577±1222 0.261
Present CAD 7383±1592 7695±1483 0.060
Smoking, current Overall 7100±1551 8019±1490 <0.001 4260±1357 4813±1282 <0.001 2070±694
Absent NCA 6545±1440 8039±1391 <0.001 3820±1229 4731±1137 <0.001 2050±646
Present CAD 7308±1529 8011±1536 <0.001 4418±1341 4846±1340 0.005
Family history Overall 7398±1566 7145±1629 0.068
of CAD
Absent NCA 6976±1631 6733±1446 0.335
Present CAD 7566±1494 7294±1669 0.090
Fasting plasma Overall 7185± 7341± 7646±
glucose 1620 1562 1548
T1 (<100 mg/dl) NCA 7018± 6785± 6873±
T2 (100-126 mg/dl) 1738 1385 1417
T3 (>126 mg/dl) CAD 7275± 7521± 7715±
1549 1578 1486
Serum uric acid Overall 7025± 7254± 7505± 7450± 0.037 4247± 4293± 4471± 4573± 0.145 2094± 2151± 2249± 2007± 0.029 479± 554± 569± 607± <0.001
Q1 (1.5-4.1 mg/dl) 1673 1431 1589 1526 F=2.9 1498 1187 1347 1396 F=1.8 733
Q2 (4.2-5.0 mg/dl) NCA 6780± 6721± 7454± 7289± 0.143 4031± 3977± 4265± 4150± 0.800 2117± 2015± 2418± 2305± 0.051 443± 494± 556± 616± <0.001
Q3 (5.1-6.2 mg/dl) 1742 1585 1398 1272 F=1.8 1567 1145 1041 1175 F=0.3 663
Q4 (6.3-12.9 mg/dl) CAD 7212± 7455± 7519± 7471± 0.535 4411± 4413± 4529± 4628± 0.558 2076± 2202± 2203± 2968± 0.033 507± 553± 597± 605± 0.003
1604 1322 1644 1559 F=0.7 1431 1187 1420 1417 F=0.6 786
Continuous variables are given as mean±SD (in mm-3)
*unpaired Student’s t-test and ANOVA test
CAD - coronary artery disease, NCA - normal coronary arteries, WBC - white blood cell (leukocyte) counts, Q1 to Q4 are quartiles for serum uric acid and T1 to T3 are tertiles for fasting plasma glucose
WBC, mm-3 p/F* Neutrophils, mm-3
4217±1397 4436±1376 0.164
4138±1446 4011±1243 0.554
4371±1308 4535±1372 0.525
4431±1453 4397±1348 0.765
4024±1423 4071±1189 0.807
4740±1405 4462±1351 0.052
4242±1259 4499±1426 0.021
3918±1189 4140±1341 0.255
4399±1265 4605±1406 0.124
4315±1355 4616±1387 0.019
4071±1323 3811±895 0.345
4436±1356 4736±1355 0.038
p/F* Lymphocytes, mm-3
2367±673
2219±603
2653±717
2093±721
2114±705
2078±736
2196±666
2138±587
2224±701
2146±706
2169±701
2135±709
p/F*
0.001
0.366
Monocytes, mm-3
538±161 553±193 0.492
500±141 503±147 0.885
p/F*
Overall 7316±1686 7336±1577 0.916
NCA 7029±1753 6847±1538 0.477
CAD 7872±1416 7454±1557 0.152
Overall 7215±1614 7381±1578 0.206
NCA 6788±1670 7007±1539 0.356
CAD 7537±1498 7460±1568 0.633
Overall 7211±1563 7395±1610 0.162
NCA 6758±1576 7038±1575 0.249
CAD 7429±1514 7507±1594 0.617
2099±700
2122±702
2096±699 <0.001 613±175 565±203 0.213
2149±693 0.335 497±163 574±196 <0.001
2188±637 0.451 459±134 544±141 <0.001
2143±704 0.379 526±176 581±207 0.010
2102±743 0.114 542±189 551±193 0.572
2185±750 0.648 510±141 501±147 0.675
2078±737 0.043 558±207 569±205 0.618
2124±733 0.744 548±189 543±198 0.771
2140±522 0.844 519±145 424±104 0.002
2132±763 0.971 563±207 566±205 0.901
2375±720 <0.001 535±191 587±186 0.005
2504±641 <0.001 488±142 557±135 0.006
2321±747 0.004 553±204 599±207 0.051
2130±674 0.758 544±187 552±200 0.653
2081±710
2149±730 4480±1373 4198±1318 0.017
4130±1340 3809±1074 0.129
4612±1334 4338±1372 0.048
0.015 4259± 4402± 4734± 0.003 2164± 2115± 2125± 0.721 542± 559± 554±
F=4.2 1393 1305 1408 F=6.0 695
0.698 4111± 3981± 4030± 0.844 2209± 2077± 2163± 0.533 498± 519± 418±
F=0.4 1454 1079 948 F=0.2 718
0.038 4339± 4539± 4784± 0.016 2140± 2127± 2132± 0.986 566± 572± 562±
F=3.3 1357 1346 1378 F=4.2 683
2136±683
2160±747
2224±655
2095±680
0.435
0.391
512±143 488±143 0.318
558±202 575±212 0.421
0.596
F=0.5
0.561
F=0.6
0.922
F=0.08
696 772 F=0.3 189 178 213
637 524 F=0.6 143 145 134
715 792 F=0.01 207 186 220
695 741 623 F=3.0 163 176 195 222 F=11.4
630 671 662 F=2.7 127 124 129 147 F=10.5
713 755 609 F=3.0 183 188 209 230 F=4.7
Table 2. The changes in leukocyte subtypes according to traditional cardiovascular risk factors

Page 6

In another recent study, Tian et al. (36) searched the asso-
ciation between circulating specific leukocyte types and blood
pressure and found that blood pressure is specifically related to
N and L. Kawada et al. (37) showed an independent relationship
between N and hypertension. In the study by Yen et al., the
investigators searched the relation between hsCRP , standard
CVRFs and WBC, neutrophils and monocytes. Although SUA and
L were not included analyses, several overlapping results were
obtained in multivariate analyses. While hsCRP was related to
nonspecifically all CVRFs, glucose was only related with N.
Smoking was, in a manner consistent with our findings, related
with WBC, N and M nonspecifically. Other than these, diastolic
blood pressure, body mass index, lipids were related WBC, N
and M (38). In our opinion, SUA could change the specificity of
these relationships and this is a limitation for their multivariate
analyses. Lavi et al. (39) searched the effect of smoking status
on leukocyte subtypes and found that smoking was related with
WBC, N, L and M. Although, in these studies, the investigators
had not focused specifically on the relationship between leuko-
cyte subtypes and CVRFs, their findings were consentient with
our results.
The specific detrimental peripheral effects of CVRFs on circulat-
ing leukocyte subtypes and also on vascular progenitors (11, 12) are
important to be recognized in the pathogenesis of atherosclerosis.
Since these different effects may lead to different kinds of defects in
endothelial function and vascular repair mechanisms, solutions that
Kocaman et al.
Circulating specific leukocyte subtypes
Anadolu Kardiyol Derg 2011 Kasım 1; 11(7): 000-000
doi:10.5152/akd.2011.158
Variables


Age, years
Hypertension, +
Current smoking, +
Family history of CAD, +
Fasting plasma glucose, mg/dl
SUA, mg/dl
CAD, +
Constant
R2
Overall (n=677)
Standardized
coefficients
-0.214
0.136
0.202
-0.097
0.125
0.114
0.164
-
0.145
CAD (n=541)
Standardized
coefficients
-0.199
0.102
0.151
-0.095
0.159
0.098
-
-
0.106
NCA (n=136)
Standardized
coefficients
-0.194
0.244
0.311
-0.135
-0.109
0.180
-
-
0.231
β±SE

-32±7
431±140
748±161
-327±139
4.2±1.4
115±43
574±162
7260±455
p*

β±SE

-31±8
321±168
554±192
-311±164
4.7±1.5
94±49
-
7985±607
p*

β±SE

-29±13
763±254
1122±292
-463±272
-8.7±6
234±100
-
7675±962
p*
<0.001
0.002
<0.001
0.019
0.004
0.008
<0.001
<0.001
<0.001
0.056
0.004
0.058
0.002
0.054
-
<0.001
0.022
0.003
<0.001
0.091
NS
0.021
-
<0.001
*Linear regression with stepwise method: dependent variable - leukocyte count, independent variables- age, gender, HT, DM, current smoking, family history of CAD, total cholesterol,
LDL, HDL, triglyceride, fasting plasma glucose, creatinine, SUA and presence of CAD
After exclusion of gender, DM, total cholesterol, LDL, HDL, triglyceride and creatinine variables from model, linear regression with enter method was performed
β±SE- Beta±standard error, CAD - coronary artery disease, DM - diabetes mellitus, HDL - high density lipoprotein, HT - hypertension, LDL - low density lipoprotein, NCA - normal coro-
nary arteries, SUA - serum uric acid level
Table 3. Effects of demographical and traditional cardiovascular risk factors, and laboratory parameters on leukocyte (white blood cell) count in blood
Variables


Hypertension, +
Current smoking, +
Family history of CAD, +
Fasting plasma glucose, mg/dl
SUA, mg/dl
CAD, +
Constant
R2
Overall (n=677)
Standardized
coefficients
0.116
0.176
-0.114
0.153
0.124
0.089
-
0.107
CAD (n=541)
Standardized
coefficients
0.101
0.137
-0.113
0.190
0.129
-
-
0.081
NCA (n=136)
Standardized
coefficients
0.176
0.271
-0.159
-0.091
0.110
-
-
0.127
β±SE

315±118
556±136
-326±121
4.2±1.2
107±38
268±134
2905±256
p*

0.008
<0.001
0.007
0.001
0.005
0.047
<0.001
β±SE

277±143
438±164
-323±144
4.7±1.3
109±43
-
3152±318
p*

0.054
0.008
0.026
<0.001
0.012
-
<0.001
β±SE

447±221
797±243
-441±230
-5.9±5
115±86
-
3799±669
p*
0.036
0.001
0.058
NS
NS
-
<0.001
*Linear regression with stepwise method: dependent variable - neutrophil count, independent variables- age, gender, HT, DM, total cholesterol, LDL, HDL, triglyceride, fasting plasma
glucose, creatinine, SUA and presence of CAD
After exclusion of age, gender, DM, total cholesterol, LDL, HDL, triglyceride and creatinine variables from model, linear regression with enter method was performed
β±SE- Beta±standard error, CAD - coronary artery disease, DM - diabetes mellitus, HDL - high density lipoprotein, HT - hypertension, LDL - low density lipoprotein, NCA - normal coro-
nary arteries, SUA - serum uric acid level
Table 4. Effects of demographical and traditional cardiovascular risk factors, and laboratory parameters on neutrophil count in blood

Page 7

Kocaman et al.
Circulating specific leukocyte subtypes
Anadolu Kardiyol Derg 2011 Kasım 1; 11(7): 000-000
doi:10.5152/akd.2011.158
Variables


Gender, male
Diabetes mellitus, +
Current smoking, +
SUA, mg/dl
CAD, +
Constant
R2
Overall (n=677)
Standardized
coefficients
0.121
0.033
0.082
0.209
0.068
-
0.097
CAD (n=541)
Standardized
coefficients
0.102
0.081
0.074
0.185
-
-
0.057
NCA (n=136)
Standardized
coefficients
0.175
-0.198
0.104
0.305
-
-
0.264
β±SE

52±20
15±19
38±20
26±6
29±20
340±31
p*

0.010
NS
0.061
<0.001
NS
<0.001
β±SE

52±28
37±24
37±26
24±7
-
373±44
p*

0.061
NS
NS
<0.001
-
<0.001
β±SE

50±23
-77±29
34±25
34±9
-
322±40
p*
0.032
0.008
NS
<0.001
-
<0.001
*Linear regression with stepwise method: dependent variable - monocyte count, independent variables - age, gender, HT, DM, current smoking, family history of CAD, total cholesterol,
LDL, HDL, triglyceride, fasting plasma glucose, creatinine, SUA and presence of CAD
After exclusion of age, HT, family history of CAD, total cholesterol, LDL, HDL, triglyceride, fasting plasma glucose, and creatinine variables from model, linear regression with enter
method was performed
β±SE- Beta±standard error, CAD - coronary artery disease, DM - diabetes mellitus, HDL - high density lipoprotein, HT - hypertension, LDL - low density lipoprotein, NCA - normal coro-
nary arteries, SUA - serum uric acid level
Table 6. Effects of demographical and traditional cardiovascular risk factors, and laboratory parameters on monocyte count in blood
Variables


Age, years
Family history of CAD, +
Fasting plasma glucose, mg/dl 0.01±0.001
SUA, mg/dl
Constant
R2
Overall (n=677)
Standardized
coefficients
0.156
-0.088
0.129
0.109
-
0.068
CAD (n=541)
Standardized
coefficients
0.163
-0.088
0.169
0.159
-
0.081
NCA (n=136)
Standardized
coefficients
0.121
-0.134
-0.041
-0.044
-
0.036
β±SE

0.2±0.006
-0.3±0.1
p*

β±SE

0.02±0.01
-0.3±0.2
0.01±0.001
0.1±0.04
-0.2±0.5
p*

0.001
NS
0.001
0.002
NS
β±SE

0.02±0.01
-0.4±0.3
-0.003±0.01
-0.05±0.1
1.9±1.0
p*
<0.001
0.041
0.003
0.012
<0.001
NS
NS
NS
NS
0.048
0.1±0.04
0.3±0.4
*Linear regression with stepwise method: dependent variable - neutrophil / lymphocyte ratio, independent variables - age, gender, HT, DM, current smoking, family history of CAD, total
cholesterol, LDL, HDL, triglyceride, fasting plasma glucose, creatinine, SUA and presence of CAD
After exclusion of gender, HT, DM, family history of CAD, presence of CAD, total cholesterol, LDL, HDL, triglyceride, and creatinine variables from model, linear regression with enter
method was performed
β±SE - Beta±standard error, CAD - coronary artery disease, DM - diabetes mellitus, HDL - high density lipoprotein, HT - hypertension, LDL - low density lipoprotein, NCA - normal coro-
nary arteries, SUA - serum uric acid level
Table 7. Effects of demographical and traditional cardiovascular risk factors, and laboratory parameters on neutrophil / lymphocyte ratio in blood
Variables


Age, years
Current smoking, +
CAD, +
Constant
R2
Overall (n=677)
Standardized
coefficients
-0.251
0.112
0.072
-
0.084
CAD (n=541)
Standardized
coefficients
-0.274
0.063
-
-
0.089
NCA (n=136)
Standardized
coefficients
-0.132
0.247
-
-
0.100
β±SE

-16±3
185±69
114±67
2970±164
p*

β±SE

-20±4
108±83
-
3313±223
p*

β±SE

-8.3±5
384±122
-
2497±270
p*
<0.001
0.007
0.089
<0.001
<0.001
NS
-
<0.001
0.093
0.002
-
<0.001
*Linear regression with stepwise method: dependent variable -lymphocyte count, independent variables- age, gender, HT, DM, current smoking, family history of CAD, total cholesterol,
LDL, HDL, triglyceride, fasting plasma glucose, creatinine, SUA and presence of CAD
After exclusion of gender, DM, HT, family history of CAD, total cholesterol, LDL, HDL, triglyceride, fasting plasma glucose, creatinine and SUA variables from model, linear regression
with enter method was performed
β±SE- Beta±standard error, CAD - coronary artery disease, DM - diabetes mellitus, HDL - high density lipoprotein, HT - hypertension, LDL - low density lipoprotein, NCA - normal coro-
nary arteries, SUA - serum uric acid level
Table 5. Effects of demographical and traditional cardiovascular risk factors, and laboratory parameters on lymphocyte count in blood

Page 8

are more specific may be provided by understanding these relation-
ships to protect against the peripheral effects of CVRFs.
The CVRFs have detrimental effects on circulating progeni-
tors, which partially may be related to their peripheral effect on
inflammatory cells and the inflammatory pathological microenvi-
ronment as well as direct detrimental effects on progenitor cells
and blocking effects on the mobilization of progenitors from
bone marrow.
In our opinion, increase in circulating inflammatory cells,
which is induced by some uncontrolled CVRFs may lead to more
complicated diffuse and severe vascular involvement due to the
accelerated progression of atherosclerotic process. The plaque
stabilization providing a specific decrease in leukocyte subtypes
may be achieved by the controlling blood sugar, lowering uric
acid levels and cessation of smoking. In long term, these meth-
ods may provide a decrease in acute and chronic manifesta-
tions of atherosclerosis, such as, triggering of acute coronary
syndromes and recurrent adverse events.
In a recent intracoronary ultrasound study, atherosclerotic
plaque regression and simultaneous inflammatory cell count
suppression were achieved with statin therapy. In this study,
authors concluded that especially monocyte count may serve as
a simple marker of plaque regression with statins. Since athero-
sclerosis is characterized by recruitment of monocytes to the
arterial wall, monocyte count may be a more specific measure-
ment of inflammatory activity in the arterial wall than total leu-
kocyte count (40). In addition, these relationships between risk
factors and inflammatory cell subtypes may also provide a sim-
ple and risk factor-specific biomarker for follow up in clinical
settings. Therefore, the easily measurable neutrophil, monocyte
counts by automatic counter can be used to determine the
effectiveness of risk factor modification and anti-atherogenic
treatment in clinical practice. In our opinion, if we know which
risk factor is associated with which specific cell subtype, we
can trace a specific cell subtype for related risk factor in indi-
vidual course of patient.
Study limitations
Our study had some limitations. The main limitation of our
study may be the absence of the other inflammatory markers in
the analyses. But, we focused more specifically on the relation-
ship between the circulating inflammatory cell subtypes and the
traditional CVRFs rather than the relationship between leuko-
cyte subtypes and coronary artery disease, therefore hsCRP is
not necessary to search the main goal in current study.
We assessed leukocyte and subtypes by an automatic cell
counter and more specific cell determinations could be per-
formed by a flow cytometer with cluster of differentiation (CDs)
antigens. Another limitation in current study, it is to have not
been done a work for in vitro cell functions, which may be in
reparative or pathological nature for physiologic and pathologi-
cal micro-circumstances. This kind of analysis would probably
provide additional information on atherosclerosis.
Lastly, in our study, the patients included in the control group
were not completely normal. Although they have angiographi-
cally normal coronary arteries, they still have cardiac risk fac-
tors or may have cardiac syndrome-X. Therefore, the statistical
differences would be difficult to determine between normal and
pathologic group. Otherwise, our study population proved many
significant relations among study groups.
Conclusion
Our findings show special influences of age, FPG, SUA levels
and male gender, current smoking and presence of hypertension
on specific subtypes of circulating inflammatory cells. Further
studies with larger study populations would be warranted to dem-
onstrate whether the risk factor modification and anti-atherogen-
ic treatment could provide simultaneous decrease in specific cell
subtype count and number of adverse clinical events.
Conflict of interest: None declared.
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Circulating specific leukocyte subtypes
Anadolu Kardiyol Derg 2011 Kasım 1; 11(7): 000-000
doi:10.5152/akd.2011.158