Chinese Medicine, 2010, 1, 69-74
doi:10.4236/cm.2010.13014 Published Online December 2010 (http://www.SciRP.org/journal/cm)
Myocardial Infarction and Intracerebral Hemorrhage in a
Chinese Population: Relationship with Lipoproteins and
Adipokines
Jessica Smith1, Zhenjun Liu2, Huiling Lu1,2, Daowen Wang2, Katherine Cianflone1
1Centre de Recherche Institu t Universitaire de Cardiologie et de Pneumologie de Québec, Québec, Canada
2Tongji Medical Cen tre, HuaZhong University of Science and Tech nology, Wuhan, China
Received June 15, 2010; revised August 23, 2010; accepted September 30, 2010
Abstract
BACKGROUND: Adipokines and inflammatory factors play an important role in disease progression. Two
cardiovascular diseases which have important contributions to mortality and morbidity in China are in-
tracerebral hemorrhage (ICH) and myocardial infarction (MI). Acylation stimulating protein has been shown
in North American populations to have strong associations with risk factors for MI. Complement C3 (C3) a
component of the innate complement immune system is the precursor protein to ASP; C3 has been impli-
cated in the pathogenesis of ICH. OBJECTIVE: In this case-control study we examined the association be-
tween BMI, lipoproteins adiponectin, C3 and ASP) in a Chinese population. METHODS AND RESULTS:
Three groups of subjects were studied: ICH group (N = 41), MI group (N = 60) and a control group (N = 44).
There was no difference in BMI for either ICH or MI compared to controls (Control: 22.3 ± 0.3 kg/m2; ICH:
21.3 ± 0.4 vs MI: 22.5 ± 0.2, ICH and MI versus control pNS). The ICH group had lower LDL-C (Control:
3.21 ± 0.13 mmol/L; ICH: 2.54 ± 0.13; MI: 2.99 ± 0.13; ICH vs control p < 0.05), total cholesterol (Control:
5.06 ± 0.16 mmol/L; ICH: 4.40 ± 0.15 ; MI: 4.51 ± 0.14 ; ICH and MI vs control p < 0.05),, HDL-C (Control:
1.34 ± 0.05 mmol/L; ICH: 1.22 ± 0.06; MI: 0.95 ± 0.04; ICH and MI vs control p < 0.05), and C3 (Control:
2.58  0.21 g/L; ICH: 1.85  0.19; MI: 2.87  0.16; ICH vs control p < 0.05), and higher TG (Control: 1.10 ±
0.07 mmol/L; ICH: 1.77 ± 0.17; MI: 1.61 ± 0.10, ICH and MI vs control p < 0.05), compared to the controls.
The MI group had lower total cholesterol and HDL-C and higher TG and ASP (Control: 33.70  2.07 nM;
ICH: 35.10  2.33; MI: 41.50  1.81; MI vs control p < 0.05) compared to control. CONCLUSION: Chinese
men and women who had an MI displayed elevated ASP unrelated to an increase in the precursor protein, C3.
Chinese men and women with ICH had ASP levels similar to controls yet lower C3 suggesting that C3, and
the regulation of C3 conversion to ASP may be important in ICH disease pathology.
Keywords: Myocardial Infarction, Intracerebral Hemorrhage, Acylation Stimulating Protein, Complement C3,
Adiponectin
1. Introduction
Hemorrhagic stroke, specifically intracerebral hemor-
rhage (ICH), has a high rate of morbidity and mortality
yet it has not received the same intense research interest
as ischemic vascular diseases [1]. In fact, in the past 20
years, little progress has been made to improve disease
outcomes [2]. In Europe and North America there is a
very low incidence of this type of stroke, however, in
China, ICH occurs more frequently [3,4]. Economic and
social changes that are taking place in many Asian coun-
tries, including China, have also led to increasing inci-
dence of ischemic heart diseases, such as myocardial
infarction (MI) [5].
The risk factors for MI are well known in Caucasian
populations and include obesity, hypertension, and high
apolipoprotein B to apolipoprotein A1 (apoB/apoA1)
ratio, as well as other factors [6-8]. While these may be
widespread risk factors, as suggested by the INTER-
HEART study, it is unknown if these same risk factors
will apply to a Chinese population [6,7]. Recently, in-
creasing rates of obesity, as well as high rates of smoking

70 J. SMITH ET AL.
and increasing incidence of insulin resistance and diabe-
tes have begun to coincide with increasing rates of MI in
China [9]. By contrast, Chen et al found that a BMI be-
low 20 was also a risk for factor ischemic heart disease
in the Chinese population [2]. Hypertension, which is
prevalent in the Chinese population, is another major risk
factor for both ICH and MI [10,8]. Taken together, these
risk factors may be responsible for the higher rates of
cardiovascular diseases (CVD) and the development of
CVD at a young age in Chinese individuals [11].
In Caucasian populations, obesity and CVD are asso-
ciated with alterations in several adipose tissue derived
hormones, including acylation stimulating protein
(ASP), its precursor complement C3 (C3), and adi-
ponectin [12]. It is believed that these hormones may
play roles in mediating some co-morbidities of obesity
[12] due to their effects on lipid metabolism. ASP in-
creases the uptake of dietary triglyceride (TG) into
adipose tissue for storage; however, it is believed that
ASP resistance can develop since higher ASP levels are
often associated with delays in TG clearance and the
development of dyslipidemia.
ICH and MI have different etiologies and ICH may not
be associated with lipid disorders. However, the precur-
sor protein to ASP, C3, is a key component of the com-
plement innate immune system and has been implicated
in ICH disease progression. In rodent models, C3 gene
expression has been shown to increase immediately after
the occurrence of an ICH [13] and mice lacking C3 are
protected from further brain damage after ICH [14,10].
In humans who have had an ICH, it was reported that
they had elevated C3 concentrations [14]. Whether ASP
and adiponectin concentrations will be different in indi-
viduals who have had an ICH is unknown. Therefore, our
goal was to evaluate the concentrations of the hormones
ASP, C3 and adiponectin, as well as blood pressure, an-
thropometric measurements and blood lipids, in subjects
who have had MI and ICH in China.
2. Materials and Methods
2.1. Subjects
One hundred and forty-five participants were recruited at
the Tongji Medical Centre, Tongji Hospital, HuaZhong
University of Science and Technology, Wuhan, Hubei,
China to participate in a case-control study. The subjects
were a subset of men and women who had participated in
a multicenter study for the assessment of risk factors of
stroke sponsored by the Ministry of Science and Tech-
nology of China and were included in this analysis based
on the following inclusion criteria: non-diabetic (fasting
plasma glucose less than 7.0 mmol/L or casual plasma
glucose less than 11.1 mmol/L) and age between 45 and
75. Exclusion criteria for all groups included other types
of stroke (cerebral thrombosis, lacunar infarction, tran-
sient ischemic attack, subarachnoid hemorrhage, embolic
brain infarction, brain tumors and cerebrovascular mal-
formation), and severe systemic diseases (collagenosis,
endocrine and metabolic diseases, inflammation, liver,
neoplastic or renal diseases). Forty-four patients were
classified as controls, 41 as having had ICH and 60 as
having had MI. Control participants were in-patients at
the hospital with minor illnesses from the departments of
ophthalmology, gastroenterology, otorhinolaryngology,
and orthopedics and were free of neurological diseases or
CVD. Diagnosis of ICH was based on neurological ex-
amination including CT scan, MRI or both and subjects
were evaluated 1 to 12 months after ICH. Diagnosis of
MI (ST-segment elevation myocardial infarction) was
based on 12-lead ECG and data was collected 1 month
after diagnosis. None of the subjects were taking medi-
cation at the time of the data collection that affected lip-
ids or blood pressure. Informed consent was obtained
and the study was approved by the Tongji Hospital Eth-
ics Committee.
2.2. Anthropometric Measurements
Height and weight were measured using standard meth-
ods. Body mass index (BMI) was calculated as weight
(kg) divided by height squared (m2). Each participant
completed a questionnaire providing health and lifestyle
information including participation in regular exercise
(yes or no), smoking status (non smoker, previous
smoker and current smoker), and medical information on
previous/current diseases and medications. Two meas-
urements each for systolic (SBP) and diastolic blood
pressure (DBP) were taken on two different days. Re-
ported values for SBP and DBP are an average of these
two measurements.
2.3. Lipoproteins
Venous blood samples were collected after an overnight
fast (12 hours) from an antecubital vein. The samples
were centrifuged, aliquoted and frozen at −80 C. Plasma
samples were analyzed for concentrations of nonesteri-
fied fatty acids (NEFA), triglycerides (TG), total choles-
terol (TC), high-density lipoprotein cholesterol (HDL-C),
apolipoprotein B (apoB), apolipoprotein A1 (apoA1),
adiponectin, C3 and ASP. Plasma NEFA was determined
by colorimetric enzymatic assay (WAKO Chemicals,
Tokyo, Japan) and TG was determined via GPO-PAP
method. TC was analyzed by COD-PAP. HDL-C con-
centration was determined using an enzymatic colori-

J. SMITH ET AL.
71
metric assay after precipitation of apoB-containing lipo-
proteins (BCR, Ai-Weihali, autobiochemical analyser).
LDL-C was calculated using the Friedewald formula
[LDL-C = TCHOL – (TG/2·2)–HDL-C]. ApoB and apoA1
were assessed by automated immunoturbidimetric assays
(Tina-quant; Roche Diagnostics, Mannhein, Germany).
Inter-coefficient and intra-coefficient of variation (CV)
for all parameters (except HDL-C) were < 3%. For
HDL-C, inter-CV and intra-CV were < 5%.
2.4. Adipokines
Total adiponectin concentration was measured by en-
zyme-linked immunosorbent assay (ELISA; B-Bridge
International, Phoenix, AZ, USA). Plasma C3 concentra-
tion was determined by turbidimetric assay using a poly-
clonal anti-human antibody specific against C3 (Lin-Fei
Co, Shanghai, China) and plasma ASP concentration was
measured using a sandwich ELISA method previously
described in detail [15]. For adiponectin, complement C3
and ASP assays, intra-assay CVs were <4% and in-
ter-assay CVs were <8%.
2.5. Statistical Analysis
All results are displayed as mean ± SEM (standard error)
unless stated otherwise. ANOVA analyses with Bon-
ferroni post-hoc test was used to compare means of con-
tinuous variables. Kruskal-Wallis ANOVA on Ranks
with Dunn’s post-hoc test was used to compare means of
ordinal variables and non-normally distributed continu-
ous variables, as indicated. Correlations between pa-
rameters were calculated using Pearson correlation coef-
ficient for continuous variables. Adjusted means and
effects of multiple variables on a single dependent vari-
able were determined using multiple regression models.
Adjusted means were compared using multivariate
analysis of variance (MANOVA).
3. Results
3.1. Subject Characteristics & Lipoprotein Profile
Subject characteristics and lipoprotein profiles are pre-
sented in Table 1. No gender differences were found for
the parameters listed in Table 1; therefore, data from
men and women were analyzed together. For the re-
maining data, gender differences, where present, are in-
dicated. The BMI of the ICH group was lower compared
to the MI group yet there was no difference for either
ICH or MI compared to control. The traditional lipopro-
tein risk factors of elevated TG and low HDL-C were
present in both the ICH and MI groups. On the other
hand, there was no presence of hypercholesterolemia,
and, in fact, both ICH and MI groups had lower TC than
controls as well as lower LDL-C in the ICH group com-
pared to the controls and more dense LDL particles esti-
mated by the ratio of LDL-C/apoB. There was no differ-
ence in NEFA, apoA1, apoB or the apoB/apoA1 ratio
between the three groups.
Table 1. Subject characteristic s.
Control ICH MI ANOVA
N 44 41 60
Gender (M/F) 21/23 22/19 38/22
Smoking
(non/previous/current) 30/10/4 22/10/9 31/15/14
Age (years)† 63.5  0.76 60.2  1.41 63.8  0.82 0.24
BMI kg/m2 22.3  0.31 21.3  0.39a 22.5  0.21a 0.01
TC mmol/L 5.06  0.16ab 4.40  0.15a 4.51  0.14b 0.008
TG† mmol/L 1.10  0.07ab 1.77  0.17a 1.61  0.10b <0.001
NEFA† mmol/L 0.23  0.01 0.31  0.03 0.27  0.02 0.14
HDL-C† mmol/L 1.34  0.05a 1.22  0.06b 0.95  0.04ab <0.001
LDL-C mmol/L 3.21  0.13a 2.54  0.13a 2.99  0.13 0.003
apoA1 g/L 1.22  0.03a 1.12  0.04a 1.14  0.03 0.07
apoB†g/L 0.77  0.02 0.75  0.03 0.79  0.03 0.71
B/A1† g/L 0.70  0.02 0.66  0.02 0.64  0.02 0.41
LDL-C/apoB† mmol/g 2.21  0.15a 3.35  0.23a 3.84  0.26 0.007
SBP mmHg 135.9  3.4 147.5  4.0 146.7  3.3 0.04
DBP mmHg 82.9  1.9a 93.9  2.4a 87.5  1.9 0.002
All values expressed as mean  SEM (standard error) except smoking status. Statistical significance assessed by One-way ANOVA with Bon-
ferroni post-hoc test, except for parameters marked with † where Kruskal-Wallis One Way Analysis of Variance on Ranks with Dunn’s
post-hoc test was used due to non-normal distribution. For each parameter, values marked with the same letter indicate p<0.05 for post-hoc
tests.

J. SMITH ET AL.
72
3.2. Hypertension
Chi squared analysis of prevalence of hypertension (de-
fined as SBP/DBP ≥ 140/90 mm Hg) revealed that there
was a difference in the prevalence of hypertension, with
the ICH having significantly higher incidence than con-
trol (p = 0.01). SBP was significantly different by one-
way ANOVA between the three groups. DBP was also
significantly different with the ICH group having a sig-
nificantly higher DBP than controls, even when cor-
rected for BMI (adjusted means; control 82.6  1.87
mmHg; ICH 92.3  2.40; MI 86.9  1.89, p = 0.0003
MANOVA). Both SBP and DBP correlated with BMI
(SBP, R = 0.21, p = 0.02; DBP, R = 0.18, p = 0.04) and
TG (SBP, R = 0.19, p = 0.01; DBP, R = 0.26, p = 0.003)
in a pooled analysis of data from all groups. In addition,
adiponectin correlated with DBP (R = -0.24, p=0.006). In
a multivariate model, with data from all groups pooled,
including BMI, TG and group, only BMI (p = 0.02) and
TG (p = 0.05) significantly contributed to predicting
12.0% (p = 0.002) of the SBP variance; while BMI (p =
0.007), TG (p = 0.03), and group (p = 0.004) all signifi-
cantly and independently predicted 17.2% of DBP (P <
0.001).
3.3. Adipokines
There were no differences in adiponectin as shown in
Figure 1 (Control, 6.10  0.61 mg/mL; ICH, 4.81  0.54;
MI, 6.05  0.45; pNS, Kruskal-Wallis One Way
ANOVA on Ranks), but C3 was lower in the ICH group
compared to both the control and the MI groups (control,
2.58  0.21 g/L; ICH, 1.85  0.19; MI, 2.87  0.16; p <
0.001 ANOVA) (Figure 1). When analyzed separately
for gender, there was a significant difference in C3 con-
centration between men and women with ICH (ICH men
2.42  0.28 g/L vs. ICH women 1.23  0.17 g/L, p<0.05,
ANOVA with post-hoc test) and the differences seen
between control and ICH and between ICH and MI were
solely due to the lower C3 value in ICH women and not
ICH men (data not shown). However, in the control
group, there was no difference in C3 values between men
and women. When data from all groups were pooled C3
significantly correlated with HDL-C (R = –0.23 p =
0.006) and adiponectin correlated with TG (R = –0.21 p
= 0.01) and apoA1 (R = 0.22, p = 0.01).
ASP was higher in the MI group compared to the con-
trol (control, 33.70  2.07 nM; ICH, 35.10  2.33 nM; MI,
41.50  1.81 nM; p = 0.002, Kruskal-Wallis One Way
ANOVA on Ranks). Exercise frequency moderately, yet
significantly, correlated negatively with ASP, even when
adjusted for BMI (adjusted R2 = 0.10, p = 0.003). In ad-
dition, ASP correlated with NEFA (R = 0.21, p = 0.01),
TG (R = 0.22 p = 0.01) and HDL-C (R = –0.26 p =
0
5
10
15
20
25
30
35
40
45
aa
ASP
Control MI
ICH
ASP nM
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
aab b
Control MI
ICH
C3
C3 g/L
0.0
0.1
0.2
0.3
0.4
0.5
aa
%ASP/C3
Control MI
ICH
%ASP/C3
0
1
2
3
4
5
6
7
Adiponectin
Control MI
ICH
adiponectin g/ m L
Figure 1. Acylation stimulating protein (ASP, panel A),
complement component C3 (C3, panel B), the percentage of
ASP to C3 (%ASP/C3, panel C), and adiponectin (panel D)
in control, intracerebral hemorrhagic stroke (ICH) and
myocardial infarction (MI). Results are presented as mean
 standard error of the mean (SEM). Statistical significance
for C3 was assessed by one-way ANOVA with Bonferroni
post-hoc test. Statistical significance for ASP, %ASP/C3
and adiponectin assessed by Kruskal-Wallis One Way
ANOVA on Ranks with Dunn’s post-hoc test due to non-
normal distribution. For each parameter, values marked
with the same letter indicate p < 0.05 for post-hoc tests.
0.002). The %ASP/C3 ratio was significantly lower in
the control group versus the ICH group, suggesting that
the ICH group had either a higher rate of conversion of
C3 to ASP, or decreased degradation or clearance of
ASP (control, 0.32  0.03%; ICH, 0.45  0.05%; MI,
0.33  0.03%; p = 0.005, Kruskal-Wallis One Way
ANOVA on Ranks). Overall, the ICH and MI group had
altered lipoprotein profile, altered adipokines and were
more hypertensive than controls.
4. Discussion
The relationship between blood pressure and MI is well
established and is a continuous, positive relationship
even at levels below the cut-point for clinical hyperten-
sion [8]. There are confounding and additive effects of
obesity, hypertension and dyslipidemia on the risk for MI
and the independent contribution of each of these factors
is difficult to separate. However, in the current study all
of the participants were lean and participants within the
control and MI groups did not have hypertension.
Therefore, dyslipidemia and/or adipokines may poten-
tially be the most prevalent influences for this study.
Several prospective studies on ICH have found a
strong positive relationship between ICH and hyperten-
sion [16,17] and we found supporting evidence of this: a
greater proportion of participants had hypertension in the

J. SMITH ET AL.
73
ICH group compared to control or MI. In addition, DBP
was higher in the ICH group compared to control, and
BMI, TG, and group significantly contributed to predict-
ing DBP. Previous studies have shown that compared to
other stroke subtypes, ICH is more strongly associated
with hypertension [17], possibly because the small ves-
sels of the brain are vulnerable to damage [18]. The ICH
group also had a lower BMI than the other groups and
the effects of hypertension may be particularly relevant
in the context of low BMI [19].
Hypocholesterolemia has also been suggested as a
risk factor for ICH possibly because low cholesterol
levels can adversely affect the integrity of the blood
vessel in the brain, making them more prone to damage,
especially under conditions of hypertension [20,21]. We
did find that our ICH group had lower TC and lower
LDL-C than the controls. Therefore, our ICH group
displayed three potentially exacerbating risk factors for
ICH: low BMI, hypocholesterolemia and hypertension.
These three factors have not been looked at in combi-
nation in predicting the risk of ICH yet all three are
present in our ICH group.
The MI group did not display many of the typical
features of atherogenic dyslipidemia seen in Western
populations: they had lower TC than controls and had
comparable concentrations of NEFA, LDL-C, apoA1,
apoB, and apoB/apoA1 to controls. However, the MI
group did have elevated TG and low HDL-C. Also, the
MI group did not have an elevated BMI, which is typi-
cally seen in Western populations with this disease.
The factors used to identify 10 year risk of CVD by
the Third Report of the National (USA) Cholesterol
Education Program Adult Treatment Panel III are age
(> 45 years for men and > 55 years considered as high
risk), gender (male at higher risk), elevated total cho-
lesterol, low HDL-C, elevated SBP, and smoking
status [8]. Much research has also indicated that high
apoB and low apoA1 may be are better indicators of
risk than cholesterol alone [6]. However, in this Chi-
nese population positive for MI, only a low HDL-C
was present. Therefore, many of the Western criteria
used to calculate the risk for developing CVD may not
be applicable in a lean Chinese population which is
nonetheless at risk for developing CVD. Other,
non-traditional, risk factors may need to be imple-
mented to correctly identify those at risk, such as adi-
pokines. And, in fact, ASP, which has been linked
with CVD in several studies [22], was higher in the MI
group compared to controls.
Very few studies have evaluated adipokines in relation
to ICH although C3 has been implicated in ICH patho-
genesis [23,13,10]. We did see differences in the
%ASP/C3, ASP, and C3 but not adiponectin, as has been
shown with ICH and stroke in a previous study [24].
Söderberg and colleagues found no association of adi-
ponectin with hemorrhagic stroke in an European popu-
lation; however, there were very few cases of hemor-
rhagic stroke included in their analysis [24].
Complement C3, as part of the complement immune
cascade, has been studied post-ICH. C3-deficient mice
are protected from further brain injury due to an inhibi-
tion of the immune cascade [25]. In addition, individuals
who have had ICH had increased complement C3 com-
pared to controls [14], yet in our study individuals who
have had an ICH had lower C3. While we do not know
the concentration of C3 prior to the brain injury, poten-
tially the lower C3 could be a survival bias protecting
individuals who have had ICH. Our study, along with
others, supports further research in the area of C3 in dis-
ease prediction, prevention and treatment.
We also found that, despite lower C3, ASP levels
were maintained suggesting that there was increased
conversion of C3 to ASP, or a decreased clearance or
degradation of ASP in the ICH group. Normally, only
a small proportion of C3 is converted to ASP, and the
concentration of C3 may not be a limiting step in de-
termining the concentration of ASP; however, other
mechanisms may be playing a role. It is interesting to
note that there were distinct patterns of C3 and ASP in
the MI (normal C3, high ASP) and ICH (low C3, nor-
mal ASP) compared to our controls. Thus far, little
research has been conducted on the factors that influ-
ence the rate of conversion of C3 to ASP, or the fac-
tors that influence ASP degradation or clearance.
Therefore, further research is need in this area, not
only in relation to the pharmacokinetics of C3/ASP in
healthy individuals but how these patterns change in
diseases such as ICH and MI. This is the first study to
our knowledge which demonstrates different patterns
of C3 and ASP.
This is the first study to our knowledge to measure
ASP in an ICH group. In addition, we simultaneously
examined several risk factors in both an MI and ICH
population. Further, understanding the risk factors in a
Chinese population, instead of extrapolating data from
animal studies or studies from a North American or
European population, may improve our ability to prevent
and treat these cardiovascular diseases in China.
5. Acknowledgments
JS is supported by a CIHR scholarship. KC is the recipi-
ent of a senior Canada Research Chair position. This
study was supported by grants from CIHR (KC) and Na-
tional Basic Research Program of China (973 Program,
#2006CB503801 to DWW).

J. SMITH ET AL.
74
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