Relationship of Monocyte Count and Peripheral
Arterial Disease
Results From the National Health and Nutrition Examination
Survey 1999 –2002
Khurram Nasir, Eliseo Guallar, Ana Navas-Acien, Michael H. Criqui, João A.C. Lima
Downloaded from http://atvb.ahajournals.org/ by guest on June 17, 2017
Background—Although white blood cell (WBC) count has been consistently associated with cardiovascular end points,
little information is available on the independent contribution of specific white blood cell types. The objective of this
study is to assess the independent association of WBC types and other inflammatory markers with the presence of
reduced ankle-brachial blood pressure index (ABI), a marker of subclinical peripheral arterial disease (PAD).
Methods & Results—Cross-sectional study in 3949 individuals ⱖ40 years of age without known cardiovascular disease
who participated in the 1999 to 2002 National Health and Nutrition Examination Survey (NHANES). PAD was defined
as an ABI ⬍0.9 in at least 1 leg. After adjustment for traditional cardiovascular risk factors, the odds ratios of PAD
comparing the highest to the lowest quartiles were 2.24 (95% confidence interval 1.24 to 4.04) for monocytes, 1.74 (0.87
to 3.45) for neutrophils, 2.53 (1.62 to 3.96) for C-reactive protein, and 2.68 (1.03 to 6.94) for fibrinogen. When WBC
types and inflammatory markers were simultaneously included in the full model, the corresponding odds ratios were
1.91 (95% confidence interval 1.06 to 3.42) for monocytes, 1.15 (0.49 to 2.69) for neutrophils, 1.37 (0.75 to 2.49) for
C-reactive protein, and 2.21 (0.88 to 5.57) for fibrinogen.
Conclusions—Monocytes were the only WBC type significantly and independently associated with PAD in a
representative sample of the U.S. population after adjustment for other inflammatory markers. These findings reflect the
potential role of circulating monocyte counts as markers of atherosclerosis. (Arterioscler Thromb Vasc Biol.
2005;25:1966-1971.)
Key Words: NHANES 䡲 subclinical atherosclerosis 䡲 peripheral arterial disease 䡲 white blood cells 䡲 monocyte count
A
therogenesis is a chronic inflammatory process characterized by early leukocyte recruitment that continues
throughout plaque maturation and rupture.1,2 Indeed, white
blood cell (WBC) count elevation has been consistently
associated with cardiovascular events.3,4 However, WBC
count includes several cell types with potentially different
pathogenic roles in atherogenesis. Although monocyte-macrophages play a central role in atherogenesis,5–7 little attention has been paid to the association of monocyte count with
subclinical atherosclerosis. Few studies have assessed the
association of specific WBC types with cardiovascular end
points,8 and these studies have not evaluated the specific
contribution of circulating monocytes with respect to other
WBC types and markers of inflammation, such as C-reactive
protein (CRP) and fibrinogen.9 –11
Peripheral arterial disease (PAD) is strongly associated
with increased levels of inflammatory markers, including
WBC count, CRP, and fibrinogen.12–14 The objective of this
study was to assess the association of circulating blood
monocytes and other WBC types with the presence of
reduced ankle-brachial blood pressure index (ABI), a highly
specific marker of PAD.15–18 We were specifically interested
in the independent contribution of each cell type after
adjustment for CRP, fibrinogen, and traditional cardiovascular risk factors.
Methods
Since the 1960s, the National Center for Health Statistics has
conducted the National Health and Nutrition Examination Surveys
(NHANES), a series of cross-sectional surveys designed to provide
data representative of the noninstitutionalized civilian U.S. population. In this study we used data from NHANES 1999 to 2002, as ABI
measurements were only available in NHANES since 1999. The total
population of NHANES 1999 to 2002 was 21 004. Participants 40
years of age and older were asked to participate in the ABI Section
of the Lower Extremity Disease examination. Overall 6671 individ-
Original received April 13, 2005; final version accepted June 9, 2005.
From the Division of Cardiology (K.N., J.A.C.L.), Department of Medicine, Johns Hopkins University, Baltimore, Md; the Department of
Epidemiology (E.G., A.N.-A.), Johns Hopkins University Bloomberg School of Public Health and Welch Center for Prevention, Epidemiology, and
Clinical Research, Johns Hopkins Medical Institutions, Baltimore, Md; and the Division of Epidemiology (M.H.C.), Department of Family and Preventive
Medicine, and Division of Cardiology, Department of Medicine, UCSD School of Medicine, San Diego, Calif.
Correspondence to João A.C. Lima, MD, Cardiology Division, Blalock, 524, Johns Hopkins Hospital, 600 N. Wolfe Street, Baltimore, MD 21287-0409.
E-mail [email protected]
© 2005 American Heart Association, Inc.
Arterioscler Thromb Vasc Biol. is available at http://www.atvbaha.org
1966
DOI: 10.1161/01.ATV.0000175296.02550.e4
Nasir et al
uals were ⱖ40 years of age in NHANES 1999 to 2002. Persons were
excluded from the examination if they have bilateral amputations or
weigh ⬎400 pounds (because of equipment limitations). In addition
to these exclusion criteria, some individuals who were eligible for
the examination (ⱖ40 years) might not have received the examination due to the following multiple reasons: (1) casts, ulcers, dressings, or other conditions of the participant interfered with testing, (2)
participant could not understand the test instructions, (3) participant
became ill and the test could not be performed, (4) there was an
equipment failure, (5) participant refused, (6) participant came late or
left early from the MEC and the LED examination could not be
performed, or (7) some other reason. As a result, these eligible
persons will have missing data for the ABI variables. Overall 5083
individuals ⱖ40 years of age had a valid ABI measurement.
Individuals with a known history of stroke, myocardial infarction,
angina, and congestive heart failure (n⫽749) were excluded. We also
excluded participants with ABI values ⬎1.4 (n⫽68)19 and those with
missing values in variables of interest (n⫽317), leaving 3949
individuals in the present study.
Ankle Brachial Index
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A specific protocol was used to measure ABI in NHANES 1999 to
2002.20 Systolic blood pressure was measured on the right arm
(brachial artery) or the left arm if only choice, and both ankles
(posterior tibial arteries) with a Doppler device (Parks MiniLaboratory IV, model 3100, Parks Medical Electronics). Systolic
blood pressure was measured twice at each site for participants 40 to
59 years of age and once at each site for participants ⱖ60 years of
age. The left and right ABI measurements were obtained by dividing
the ankle systolic blood pressure for each side respectively by the
systolic brachial blood pressure, or by using the mean pressures for
participants with 2 blood pressure measurements at each site. PAD
was defined as an ABI value ⬍0.9 in at least 1 leg.21
WBC Counts, C-Reactive Protein, and Fibrinogen
WBC count was determined on a Coulter Counter Model S-PLUS JR
(Coulter Electronics). Target coefficients of variation were ⬍3.0%.
High-sensitivity CRP was measured using latex-enhanced nephelometry on a Behring Nephelometer Analyzer System (Behring
Diagnostics, Inc) with NA Latex CRP Kit (Behring Diagnostics,
Inc). The intra-assay coefficient of variation was 3.2%. Fibrinogen
was determined by a comparison of the clotting time from a sample
with that of a standardized fibrinogen preparation obtained on a
Coagamate XC Plus automated coagulation analyzer (Organon
Teknika). The intra-assay coefficients of variation ranged from 1.7 to
3.9%. Details about laboratory procedures and quality control in
NHANES are available elsewhere.22
Other Variables
Age, sex, race/ethnicity, and smoking were assessed by self-report.
Obesity was defined as a body mass index ⱖ30 kg/m2. Hypertension
was defined as mean systolic blood pressure ⱖ140 mm Hg, mean
diastolic blood pressure ⱖ90 mm Hg, or a self-report of a physician
diagnosis or medication use. Mean blood pressure was composed of
up to 4 readings on 2 separate occasions. Hypercholesterolemia was
defined as a total cholesterol ⱖ240 mg/dL, or a self-report of a
physician diagnosis or medication use. Diabetes was defined as a
fasting glucose ⱖ126 mg/dL, or a nonfasting glucose ⱖ200 mg/dL,
or a self report of a physician diagnosis or medication use. Glomerular filtration rate (GFR) was estimated by the Modification of Diet
in Renal Disease (MDRD) Study formula.23 Mild kidney dysfunction
was defined as a GFR of 60 to 90 mL/min/1.73 m2, and low kidney
function was defined as a GFR ⬍60 mL/min/1.73 m2.
Statistical Analysis
All statistical analyses were performed using svy commands in Stata
version 8 to account for the complex sampling design and weights in
NHANES 1999 to 2002.
WBC type counts and CRP were markedly right skewed and were
log-transformed for statistical analysis. They were described as
Monocyte Count and PAD
1967
TABLE 1. Characteristics of Study Population by Presence or
Absence of Peripheral Arterial Disease
PAD (n⫽220)
No PAD (n⫽3729)
P Value
68 (1.1)
54 (0.2)
⬍0.001
Sex, % males
36%
48%
0.02
Race, % Whites
75%
79%
0.23
Smoking, % current
39%
17%
0.001
Hypertension
58%
47%
0.03
Diabetes
15%
9%
0.02
Hypercholesteremia
43%
44%
0.92
34%
30%
0.32
17%
9%
0.04
Age, y
BMIⱖ30 kg/m2
2
GFR⬍60 mL/min/1.73 m
Inflammatory markers*
WBC, ⫻109/L
7.38 (7.01–7.77)
6.69 (6.59–6.79)
0.001
Monocytes, ⫻109/L
0.59 (0.56–0.62)
0.53 (0.53–0.54)
0.002
Neutrophils, ⫻109/L
4.32 (4.07–4.58)
3.88 (3.81–3.95)
0.002
Lymphocytes, ⫻109/L
2.06 (1.90–2.22)
1.90 (1.87–1.94)
0.08
Basophils, ⫻109/L
0.10 (0.10–0.11)
0.10 (0.10–0.10)
0.88
Eosinophils, ⫻109/L
0.12 (0.12–0.12)
0.12 (0.12–0.12)
0.87
CRP, mg/L
3.23 (2.80–3.73)
2.17 (2.05–2.29)
⬍0.001
Fibrinogen, g/L
3.97 (3.80–4.14)
3.62 (3.54–3.70)
0.001
PAD indicates peripheral arterial disease.
All values age- and sex-adjusted, except age and sex.
*Geometric means and 95% confidence intervals, except arithmetic mean
for fibrinogen.
geometric means and 95% confidence intervals. Pearson correlations
between WBC types and inflammatory markers were calculated.
WBC types, CRP, and fibrinogen were divided into quartiles
according to the weighted distribution of the whole sample. Because
of the small number of distinct levels, basophil count was grouped in
2 categories (⬍ 0.1 and ⱖ0.1 109/L, with 58% and 42% of subjects,
respectively), and eosinophil count was grouped in 3 categories (⬍
0.2, 0.2, and ⬎0.2 109/L, with 45%, 31%, and 24% of subjects,
respectively). Logistic regression was used to estimate the odds
ratios for the prevalence of PAD in quartiles 2 to 4 of inflammatory
markers compared with the first quartile. Tests for trend across
increasing quartiles (or prespecified cutoffs for eosinophils and
basophils) were computed by introducing variables with the median
level for each quartile in the regression models.
Three sets of multivariable models were used to examine the
association of WBC types, CRP, and fibrinogen in a hierarchical
fashion. Model 1 adjusted for age, sex, and race. Model 2 further
adjusted for traditional risk factors (smoking status, obesity, hypertension, diabetes, hypercholesteremia, and GFR). Model 3 adjusted
simultaneously for WBC types, CRP, and fibrinogen in addition to
the covariates included in Model 2.
Results
There were 220 PAD cases among 3949 study participants
(weighted prevalence 3.6%; 95% CI 3.1% to 4.1%). WBC
count, CRP, and fibrinogen were higher in PAD cases
compared with non-cases (all Pⱕ0.001; Table 1). Among
WBC subtypes, only monocytes and neutrophils were significantly higher in PAD cases.
CRP and fibrinogen were strongly correlated (r⫽0.54), but
their correlation with WBC subtypes was weaker (rⱕ0.30 for
all WBC subtypes; Table 2). Among WBC types, neutrophils
were the most strongly correlated with CRP and fibrinogen.
1968
Arterioscler Thromb Vasc Biol.
TABLE 2.
Correlation Coefficients Among Inflammatory Markers
WBC
Monocytes
Neutrophils
Lymphocytes
Basophils
Eosinophils
CRP
—
—
—
—
—
—
—
0.58
—
—
—
—
—
—
WBC
Monocyte
September 2005
Neutrophil
0.90
0.45
—
—
—
—
—
Lymphocyte
0.59
0.35
0.23
—
—
—
—
Basophils
0.35
0.22
0.28
0.23
—
—
—
Eosinophils
0.31
0.24
0.18
0.23
0.25
—
—
CRP
0.31
0.20
0.30
0.13
0.11
0.12
—
Fibrinogen
0.25
0.15
0.26
0.06*
0.07
0.10
0.54
WBC indicates White blood cell count; CRP, C-reactive protein.
All variables in log scale except fibrinogen.
All P⬍0.001, except *P⫽0.002.
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The correlation coefficient of monocytes with neutrophils
was 0.45 and similar in males and females.
In age-, sex-, and race-adjusted analyses, monocytes,
neutrophils, CRP, and fibrinogen levels were significantly
associated with the prevalence of PAD (Table 3, Model 1).
These associations persisted, although slightly attenuated,
after adjustment for traditional cardiovascular risk factors
(Table 3, Model 2). In risk factor adjusted models, the odds
ratios comparing the prevalence of PAD in the highest versus
the lowest quartiles were 2.24 (95% confidence interval 1.24
to 4.04) for monocytes, 1.74 (0.87 to 3.45) for neutrophils,
2.53 (1.62 to 3.96) for CRP, and 2.68 (1.03 to 6.94) for
fibrinogen. Basophils or eosinophils were not associated with
PAD in either model (data not shown).
When WBC types, CRP, and fibrinogen were introduced in
the models in addition to traditional cardiovascular risk
factors, monocytes and fibrinogen were still associated with
PAD prevalence (Table 3, Model 3). The odds ratios comparing the prevalence of PAD in the highest versus the lowest
quartiles were now 1.91 (95% confidence interval 1.06 to
3.42) for monocytes, 1.15 (0.49 to 2.69) for neutrophils, 1.37
(0.75 to 2.49) for CRP, and 2.21 (0.88 to 5.57) for fibrinogen.
In subgroup analysis, the association of monocyte count with
PAD was similar irrespective of the presence or absence of
traditional risk factors and other inflammatory markers (not
shown).
Discussion
Multiple lines of evidence indicate that inflammation plays a
pivotal role in atherogenesis, and that inflammatory markers
such as WBC count may aid in the detection of individuals at
higher atherosclerotic risk.24 In this cross-sectional study of
apparently healthy men and women, an elevated monocyte
count was significantly associated with PAD after adjustment
for traditional risk factors. This relationship was not present
for other WBC types, and it was independent of CRP and
fibrinogen.
WBC is a strong independent risk factor for cardiovascular
events,25–28 and for the prevalence and progression of subclinical atherosclerosis.29,30 A recent meta-analysis concluded
that, among WBC types, neutrophils were more strongly
associated with future coronary events than monocytes,31 but
none of the studies described in this meta-analysis simulta-
neously controlled for other WBC types, CRP, or fibrinogen.
In our study, neutrophils were more strongly associated with
CRP and fibrinogen than monocytes, and adjusting for CRP
and fibrinogen virtually eliminated the association of neutrophils with PAD. Inflammation is associated with virtually all
stages of vascular disease including atherogenesis, plaque
rupture, and end-organ damage secondary to ischemia and/or
embolism. It is conceivable that monocyte counts may be
more strongly related to early development and progression
of atherosclerosis,32,33 but once established atherosclerotic
disease is present, they do not strongly influence the risk of
events. Quantification of the predictive ability of monocyte
counts will require fresh evidence from prospective studies
with serial measurements of WBC counts, differentials, and
other inflammatory markers.
There is extensive evidence for the active contribution of
monocytes to atherosclerotic lesion development.34.35 The
infiltration of circulating monocytes into the blood vessel
wall, where they are transformed into lipid-laden foam cells,
is one of the earliest events in the development of atherosclerotic lesions. Monocytes are believed to play a critical role
not only in initiation of atherosclerosis, but also at multiple
stages including promotion of plaque instability and remodeling after a myocardial insult.36
The classical immunophenotypic marker for monocytes is
CD14, the lipopolysaccharide (LPS) receptor.37 However, at
least 2 distinct subpopulations of monocytes can be distinguished from the expression patterns of membrane surface
antigens. About 10% of monocytes coexpress CD16, the
low-affinity Fc-gamma receptor III. CD14⫹/CD16⫹ monocytes are considered “proinflammatory monocytes” as they
efficiently produce tumor necrosis factor-alpha (TNF-␣),38
while producing little antiinflammatory cytokine
interleukin-10 (IL-10) in comparison to CD14⫹/CD16⫺
monocytes.39 Levels of TNF-␣ are known to correlate with
carotid intima–media thickness.40 In addition, CD14⫹/
CD16⫹ monocytes are expanded in hypercholestremic patients,35 negatively correlated to HDL cholesterol levels,35
and associated in a dose-dependent fashion with the expression of the more positively charged apo E4.35
In a small case– control study, Schlitt et al found CD14⫹/
CD16⫹ monocytes to be significantly associated with the
prevalence of coronary artery disease,41 but the retrospective
Nasir et al
TABLE 3.
Monocyte Count and PAD
1969
Odd Ratios of Peripheral Arterial Disease by Inflammatory Markers
Quartile 1
Quartile 2
Quartile 3
Quartile 4
P for Trend
4.9
6.1
7.3
9.1
Model 1
1 (ref.)
1.53 (0.79–2.94)
1.71 (0.92–3.19)
3.29 (1.67–3.19)
⬍0.001
Model 2
1 (ref.)
1.27 (0.63–2.59)
1.25 (0.62–2.53)
2.09 (0.98–4.48)
0.029
Model 3*
1 (ref.)
1.13 (0.56–2.28)
1.01 (0.48–2.09)
1.52 (0.67–3.45)
0.24
WBC, ⫻109/L
Median level
Monocyte, ⫻109/L
Median level
0.4
0.5
0.6
0.8
Model 1
1 (ref.)
2.02 (1.08–3.75)
2.16 (1.21–3.85)
3.00 (1.62–5.56)
0.002
Model 2
1 (ref.)
1.90 (1.01–3.58)
1.94 (1.08–3.45)
2.24 (1.24–4.04)
0.021
Model 3
1 (ref.)
1.92 (1.03–3.59)
1.78 (0.94–3.36)
1.91 (1.06–3.42)
0.075
Neutrophils, ⫻10 /L
9
Median level
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2.6
3.5
4.4
5.7
Model 1
1 (ref.)
1.17 (0.53–2.57)
2.46 (1.34–4.53)
2.60 (1.41–4.77)
⬍0.001
Model 2
1 (ref.)
1.05 (0.45–2.45)
1.95 (1.01–3.75)
1.74 (0.87–3.45)
0.025
Model 3
1 (ref.)
0.91 (0.37–2.22)
1.49 (0.72–3.11)
1.15 (0.49–2.69)
0.52
Lymphocytes, ⫻109/L
Median level
1.3
1.7
2.2
2.9
Model 1
1 (ref.)
0.77 (0.48–1.23)
1.08 (0.59–1.99)
1.47 (0.85–2.51)
0.10
Model 2
1 (ref.)
0.72 (0.46–1.14)
0.85 (0.45–1.63)
1.16 (0.64–2.10)
0.51
Model 3
1 (ref.)
0.68 (0.43–1.09)
0.76 (0.40–1.47)
1.04 (0.58–1.86)
0.72
0.6
1.8
3.6
9.1
Model 1
1 (ref.)
1.32 (0.82–2.12)
1.98 (1.18–3.33)
2.60 (1.72–3.94)
⬍0.001
Model 2
1 (ref.)
1.32 (0.81–2.14)
1.90 (1.04–3.47)
2.53 (1.62–3.96)
⬍0.001
Model 3
1 (ref.)
1.08 (0.62–1.89)
1.34 (0.67–2.67)
1.37 (0.75–2.49)
0.26
C-reactive protein, mg/L
Median level
Fibrinogen, g/L
Median level
2.9
3.4
3.9
4.6
Model 1
1 (ref.)
0.84 (0.37–1.90)
1.84 (0.77–4.40)
3.40 (1.40–8.29)
⬍0.001
Model 2
1 (ref.)
0.74 (0.32–1.73)
1.57 (0.63–3.87)
2.68 (1.03–6.94)
0.005
Model 3
1 (ref.)
0.70 (0.30–1.62)
1.42 (0.60–3.37)
2.21 (0.88–5.57)
0.023
Model 1: Adjusted for age, gender, and race.
Model 2: Further adjusted for smoking status, diabetes, hypertension, high cholesterol, GFR (normal, mild
reduction, moderate reduction), and BMI (normal, overweight, obese).
Model 3: Further adjusted for all other inflammatory markers.
*Adjusted for CVD risk factors, CRP, and fibrinogen (not other WBC types).
design and the small sample size make it difficult to interpret
these findings. Because Schlitt et al measured monocyte
levels in cases after occurrence of clinical events, it is
impossible to determine in this study whether CD14⫹/
CD16⫹ levels contributed to the event or were a consequence
of it. The evaluation of the role of CD14⫹/CD16⫹ monocytes in atherosclerosis progression and cardiovascular outcomes in prospective studies should be a research priority.
In our study, fibrinogen was also independently associated
with the prevalence of PAD after taking into account CVD
risk factors, WBC differentials, and CRP. The finding is
consistent with previous reports demonstrating fibrinogen to
be associated with incident CHD events as well subclinical
atherosclerosis adjusting for other inflammatory markers.42– 45
In the Caerphilly study, controlling for CRP did not diminish
the effect of fibrinogen for incident CHD indicating it to be a
more specific CHD risk factor.43 In a population sample of
adults (n⫽519, median age 55.5 years, 80% men) without
clinically overt atherosclerotic disease, elevated fibrinogen
levels was related to carotid IMT independently of a wide
range of important confounding variables including CRP.44
Baseline fibrinogen levels have also been observed to be
associated with higher carotid intimal thickness (IMT) levels
in a 5-year follow-up in the Edinburgh Artery Study.45 Higher
fibrinogen levels may potentially promote atherosclerosis by
increasing platelet adhesion to the subendothelium as well
affecting endothelial function.46,47 Our and previous findings
support the role of fibrinogen as an independent marker of
generalized atherosclerotic lesions in major arterial beds.
The strengths of our study include the rigorous methodology and extensive quality control of NHANES procedures,
the use of a nationally representative sample, and the use of
a validated and specific measure of PAD. Our findings,
however, must be interpreted in the context of certain
1970
Arterioscler Thromb Vasc Biol.
September 2005
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limitations. Because of the cross-sectional design, we could
not determine whether circulating monocytes are directly
related to the atherosclerotic process or their recruitment is
stimulated by the presence of atherosclerotic lesions. Our
study lacked information on monocyte subtypes as well on
the presence of viral or bacterial infections that may be
implicated in atherogenesis and may affect monocyte count.
Whether an elevated monocyte count has direct vascular or
prothrombotic effects, is merely increased secondarily to
prevalent atherosclerosis, or is simply a marker of an uncertain environmental or infectious stimulus remains to be
determined. Confirmation of these findings in prospective
studies is of critical importance. Finally, in our study WBC
determination was performed once; factors such as infections,
day-to-day variations, as well as variability in WBC determination may have potentially effected our findings by categorizing participants with lower levels as having higher levels
and vice versa.48 It is generally considered that impact of such
dilution bias underestimates the true associations with CVD
risk as much as 50% for monocyte counts.48,49 The association of monocyte count with PAD observed in our study is
potentially likely to be underestimated.
Conclusions
This study demonstrates for the first time an independent
association between monocyte count and peripheral arterial
disease defined as a reduced ankle-brachial blood pressure
index in a large population based study. More detailed
characterization of the association between different monocyte populations and clinical and subclinical atherosclerotic
outcomes is needed to better characterize the role of inflammatory cells in atherosclerosis.
References
1. Ross R. Atherosclerosis–an inflammatory disease. N Engl J Med. 1999;
340:115–126.
2. Carlos TM, Harlan JM. Leukocyte-endothelial adhesion molecules.
Blood. 1994;84:2068 –2101.
3. Danesh J, Collins R, Appleby P, Peto R. Association of fibrinogen,
C-reactive protein, albumin, or leukocyte count with coronary heart
disease: meta-analyses of prospective studies. J Am Med Assoc. 1998;
279:1477–1482.
4. Sabatine MS, Morrow DA, Cannon CP, Murphy SA, Demopoulos LA,
DiBattiste PM, McCabe CH, Braunwald E, Gibson CM. Relationship
between baseline white blood cell count and degree of coronary artery
disease and mortality in patients with acute coronary syndromes: a
TACTICS-TIMI 18 (Treat Angina with Aggrastat and determine Cost of
Therapy with an Invasive or Conservative Strategy-Thrombolysis in
Myocardial Infarction 18 trial) substudy. J Am Coll Cardiol. 2002;40:
1761–1768.
5. Gerrity RG. The role of the monocyte in atherogenesis: I. Transition of
blood-borne monocytes into foam cells in fatty lesions. Am J Pathol.
1981;103:181–190.
6. Gerrity RG. The role of the monocyte in atherogenesis: II. Migration of
foam cells from atherosclerotic lesions. Am J Pathol. 1981;103:191–200.
7. Moreno PR, Falk E, Palacios IF, Newell JB, Fuster V, Fallon JT. Macrophage infiltration in acute coronary syndromes. Implications for plaque
rupture. Circulation. 1994;90:775–778.
8. Sweetnam PM, Thomas HF, Yarnell JW, Baker IA, Elwood PC. Total and
differential leukocyte counts as predictors of ischemic heart disease: the
Caerphilly and Speedwell studies. Am J Epidemiol. 1997;145:416 – 421.
9. Prentice RL, Szatrowski TP, Fujikura T, Kato H, Mason MW, Hamilton
HH. Leukocyte counts and coronary heart disease in a Japanese cohort.
Am J Epidemiol. 1982;116:496 –509.
10. Olivares R, Ducimetiere P, Claude JR. Monocyte count: a risk factor for
coronary heart disease? Am J Epidemiol. 1993;137:49 –53.
11. Lee CD, Folsom AR, Nieto FJ, Chambless LE, Shahar E, Wolfe DA.
White blood cell count and incidence of coronary heart disease and
ischemic stroke and mortality from cardiovascular disease in AfricanAmerican and White men and women: atherosclerosis risk in communities study. Am J Epidemiol. 2001;154:758 –764.
12. Ridker PM, Stampfer MJ, Rifai N. Novel risk factors for systemic atherosclerosis: a comparison of C-reactive protein, fibrinogen, homocysteine, lipoprotein(a), and standard cholesterol screening as predictors
of peripheral arterial disease. J Am Med Assoc. 2001;285:2481–2485.
13. Selvin E, Erlinger TP. Prevalence of and risk factors for peripheral
arterial disease in the United States: results from the National Health and
Nutrition Examination Survey, 1999-2000. Circulation. 2004;110:
738 –743.
14. Sharrett AR, Coady SA, Folsom AR, Couper DJ, Heiss G. Smoking and
diabetes differ in their associations with subclinical atherosclerosis and
coronary heart disease–the ARIC Study. Atherosclerosis. 2004;172:
143–149.
15. Criqui MH, Langer RD, Fronek A, Feigelson HS, Klauber MR, McCann
TJ, Browner D. Mortality over a period of 10 years in patients with
peripheral arterial disease. N Engl J Med. 1992;326:381–386.
16. Newman AB, Shemanski L, Manolio TA, Cushman M, Mittelmark M,
Polak JF, Powe NR, Siscovick D. Ankle-arm index as a predictor of
cardiovascular disease and mortality in the Cardiovascular Health Study.
The Cardiovascular Health Study Group. Arterioscler Thromb Vasc Biol.
1999;19:538 –545.
17. Feigelson HS, Criqui MH, Fronek A, Langer RD, Molgaard CA.
Screening for peripheral arterial disease: the sensitivity, specificity, and
predictive value of noninvasive tests in a defined population. Am J
Epidemiol. 1994;140:526 –534.
18. Lijmer JG, Hunink MG, van den Dungen JJ, Loonstra J, Smit AJ. ROC
analysis of noninvasive tests for peripheral arterial disease. Ultrasound
Med Biol. 1996;22:391–398.
19. Resnick HE, Lindsay RS, McDermott MM, Devereux RB, Jones KL,
Fabsitz RR, Howard BV. Relationship of high and low ankle brachial
index to all-cause and cardiovascular disease mortality: the Strong Heart
Study. Circulation. 2004;109:733–739.
20. National Center for Health Statistics. 1999-2000 National Health and
Nutrition Examination Survey. http://www.cdc.gov/nchs/about/major/
nhanes/NHANES99_00.htm . U.S. Departement of Health and Human
Services. 10-8-2004.
21. Newman AB, Siscovick DS, Manolio TA, Polak J, Fried LP, Borhani NO,
Wolfson SK. Ankle-arm index as a marker of atherosclerosis in the
Cardiovascular Health Study. Cardiovascular Heart Study (CHS) Collaborative Research Group. Circulation. 1993;88:837– 845.
22. National Center for Health Statistics. National Health and Nutrition
Examination Survey, 2001-2002. Laboratory Procedure Manuals. http://
www.cdc.gov/nchs/about/major/nhanes/lab_methods.htm . U.S. Departement of Health and Human Services. 12-3-2004.
23. Levey AS, Coresh J, Balk E, Kausz AT, Levin A, Steffes MW, Hogg RJ,
Perrone RD, Lau J, Eknoyan G. National Kidney Foundation practice
guidelines for chronic kidney disease: evaluation, classification, and stratification. Ann Intern Med. 2003;139:137–147.
24. Carlos TM, Harlan JM. Leukocyte-endothelial adhesion molecules.
Blood. 1994;84:2068 –2101.
25. Friedman GD, Klatsky AL, Siegelaub AB. The leukocyte count as a
predictor of myocardial infarction. N Engl J Med. 1974;290:1275–1278.
26. Zalokar JB, Richard JL, Claude JR. Leukocyte count, smoking, and
myocardial infarction. N Engl J Med. 1981;304:465– 468.
27. Brown DW, Giles WH, Croft JB. White blood cell count: an independent
predictor of coronary heart disease mortality among a national cohort.
J Clin Epidemiol. 2001;54:316 –322.
28. Brown DW, Ford ES, Giles WH, Croft JB, Balluz LS, Mokdad AH.
Associations between white blood cell count and risk for cerebrovascular
disease mortality: NHANES II Mortality Study, 1976-1992. Ann Epidemiol. 2004;14:425– 430.
29. Salonen R, Salonen JT. Progression of carotid atherosclerosis and its
determinants: a population-based ultrasonography study. Atherosclerosis.
1990;81:33– 40.
30. Elkind MS, Cheng J, Boden-Albala B, Paik MC, Sacco RL. Elevated
white blood cell count and carotid plaque thickness: the northern manhattan stroke study. Stroke. 2001;32:842– 849.
31. Wheeler JG, Mussolino ME, Gillum RF, Danesh J. Associations between
differential leucocyte count and incident coronary heart disease: 1764
incident cases from seven prospective studies of 30,374 individuals. Eur
Heart J. 2004;25:1287–1292.
Nasir et al
Downloaded from http://atvb.ahajournals.org/ by guest on June 17, 2017
32. Chapman CM, Beilby JP, McQuillan BM, Thompson PL, Hung J.
Monocyte count, but not C-reactive protein or interleukin-6, is an independent risk marker for subclinical carotid atherosclerosis. Stroke. 2004;
35:1619 –1624.
33. Johnsen SH, Fosse E, Joakimsen O, Mathiesen EB, Stensland-Bugge E,
Njolstad I, Arnesen E. Monocyte count is a predictor of novel plaque
formation: a 7-year follow-up study of 2610 persons without carotid
plaque at baseline the Tromso Study. Stroke. 2005;36:715–719.
34. Schmitz G, Herr AS, Rothe G. T-lymphocytes and monocytes in atherogenesis. Herz. 1998;23:168 –177.
35. Boring L, Gosling J, Cleary M, Charo IF. Decreased lesion formation in
CCR2-/- mice reveals a role for chemokines in the initiation of atherosclerosis. Nature. 1998;394:894 – 897.
36. Libby P. Molecular bases of the acute coronary syndromes. Circulation.
1995;91:2844 –2850.
37. Passlick B, Flieger D, Ziegler-Heitbrock HW. Identification and characterization of a novel monocyte subpopulation in human peripheral blood.
Blood. 1989;74:2527–2534.
38. Belge KU, Dayyani F, Horelt A, Siedlar M, Frankenberger M, Frankenberger B, Espevik T, Ziegler-Heitbrock L. The proinflammatory
CD14⫹CD16⫹DR⫹⫹ monocytes are a major source of TNF.
J Immunol. 2002;168:3536 –3542.
39. Frankenberger M, Sternsdorf T, Pechumer H, Pforte A, Ziegler-Heitbrock
HW. Differential cytokine expression in human blood monocyte subpopulations: a polymerase chain reaction analysis. Blood. 1996;87:
373–377.
40. Skoog T, Dichtl W, Boquist S, Skoglund-Andersson C, Karpe F, Tang R,
Bond MG, de Faire U, Nilsson J, Eriksson P, Hamsten A. Plasma tumour
necrosis factor-alpha and early carotid atherosclerosis in healthy
middle-aged men. Eur Heart J. 2002;23:376 –383.
Monocyte Count and PAD
1971
41. Schlitt A, Heine GH, Blankenberg S, Espinola-Klein C, Dopheide JF,
Bickel C, Lackner KJ, Iz M, Meyer J, Darius H, Rupprecht HJ.
CD14⫹CD16⫹ monocytes in coronary artery disease and their relationship to serum TNF-alpha levels. Thromb Haemost. 2004;92:
419 – 424.
42. Woodward M, Lowe GD, Rumley A, Tunstall-Pedoe H. Fibrinogen as a
risk factor for coronary heart disease and mortality in middle-aged men
and women. The Scottish Heart Health Study. Eur Heart J. 1998;19:
55– 62.
43. Mendall MA, Strachan DP, Butland BK, Ballam L, Morris J, Sweetnam
PM, Elwood PC. C-reactive protein: relation to total mortality, cardiovascular mortality and cardiovascular risk factors in men. Eur Heart J.
2000;21:1584 –1590.
44. Paramo JA, Beloqui O, Roncal C, Benito A, Orbe J. Validation of plasma
fibrinogen as a marker of carotid atherosclerosis in subjects free of
clinical cardiovascular disease. Haematologica. 2004;89:1226 –1231.
45. Lee AJ, Mowbray PI, Lowe GD, Rumley A, Fowkes FG, Allan PL. Blood
viscosity and elevated carotid intima-media thickness in men and women:
the Edinburgh Artery Study. Circulation. 1998;97:1467–1473.
46. Lowe GD. Blood viscosity and cardiovascular disease. Thromb Haemost.
1992;67:494 – 498.
47. Fowkes FG, Pell JP, Donnan PT, Housley E, Lowe GD, Riemersma RA,
Prescott RJ. Sex differences in susceptibility to etiologic factors for
peripheral atherosclerosis. Importance of plasma fibrinogen and blood
viscosity. Arterioscler Thromb. 1994;14:862– 868.
48. Coller BS. Leukocytosis and ischemic vascular disease morbidity and
mortality: is it time to intervene? Arterioscler Thromb Vasc Biol. 2005;
25:658 – 670.
49. Grau AJ, Boddy AW, Dukovic DA, Buggle F, Lichy C, Brandt T, Hacke
W. Leukocyte count as an independent predictor of recurrent ischemic
events. Stroke. 2004;35:1147–1152.
Downloaded from http://atvb.ahajournals.org/ by guest on June 17, 2017
Relationship of Monocyte Count and Peripheral Arterial Disease: Results From the
National Health and Nutrition Examination Survey 1999−2002
Khurram Nasir, Eliseo Guallar, Ana Navas-Acien, Michael H. Criqui and João A.C. Lima
Arterioscler Thromb Vasc Biol. 2005;25:1966-1971; originally published online June 23, 2005;
doi: 10.1161/01.ATV.0000175296.02550.e4
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