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CARDIOVASCULAR JOURNAL OF AFRICA • Volume 27, No 4, July/August 2016
232
AFRICA
Small interference (siRNA) transfection and
efficiency
Three pairs of ds siRNA oligonucleotides were obtained from
Gima Biotechnology Company, China (Table 1). Five groups
were designated: a blank control group, a negative control group
and three siRNA groups. Cells were seeded in six-well plates at
1
×
10
5
cells/well, and then 1 μl of siRNA and 2 μl of siRNA-
Mate were added to each well, corresponding to a density of
70 to 80% at the time of transfection. All of the steps were
strictly performed according to the manufacturer’s specifications.
Cells were harvested at 48 hours. The Sp1 siRNA and AP-2
α
expression vectors were transfected into cells in the same way.
Six hours after fluorescein amidite (FAM)-labelled siRNA
transfection, fluorescence was observed under a fluorescence
microscope. The transfection efficiency was determined as:
efficiency
=
number of fluorescent cells
___________________
total number of cells
×
100%.
Semiquantitative RT-PCR
Total RNA was extracted from the cell clones using TRIzol
reagent (Invitrogen). The cDNAs were reverse-transcribed from
total RNA. The primers used are shown in Table 1. The sizes
of the PCR products for AP-2
α
and GAPDH were 385 bp and
496 bp, respectively. PCR products were checked by agarose gel
electrophoresis. The abundance of each mRNA was detected
and normalised to that of GAPDH mRNA.
Western blotting analysis
Cells in all groups were collected after 72 hours, and the
total protein was extracted with RIPA lysis buffer (Beyotime
Institute of Biotechnology). The protein was measured with
the BCA protein assay and diluted with cell lysate to an
equal concentration in each group (40 μg protein/group). A
10% SDS-PAGE analysis was performed. The proteins were
transferred to a PVDF membrane (250 mA, 2 h), blocked with
5% BSA in PBS containing Tween-20 (PBST), and incubated
with a 1:500 dilution of anti-AP-2
α
overnight at 4°C.
The membrane was washed with TBST and incubated
with a peroxidase-conjugated secondary antibody (1:1 000)
for two hours. Specific antibody binding was detected using
a chemiluminescence detection system, according to the
manufacturer’s recommendations. Net intensities of the bands
on the Western blots were quantified using Tanon GIS software.
After development, the membrane was stripped and re-probed
with antibody against
β
-actin (1:1 000) to confirm equal sample
loading.
Statistical analysis
Unless otherwise noted, results are reported as mean
±
standard
deviations (SD). General characteristics in the two groups and
serum ApoM levels for different genotypes were statistically
evaluated using the unpaired Student’s
t
-test (Prism software,
version 4; GraphPad Inc, La Jolla, CA, USA). Significance was
established at a
p
-value
<
0.05.
Results
Association between risk factors for CAD and
ApoM levels in CAD patients
The general characteristics of age- and gender-matched
non-CAD and CAD patients are shown in Table 2. The mean
ages of the non-CAD and CAD patients were 60.80
±
9.27 and
58.18
±
10.43, respectively (
p
>
0.05). The CAD patients had
higher TG (1.97
±
1.28 mmol/l) and FPG levels (6.40
±
2.40
mmol/l), and lower HDL-C levels (1.05
±
0.25 mmol/l) than the
non-CAD patients (all
p
=
0.000).
According to their clinical symptoms and the American
College of Cardiology (ACC)/American Heart Association
(AHA) diagnostic guidelines, patients in the CAD group were
divided into two subgroups: acute coronary syndrome (ACS
group,
n
=
31) and stable angina pectoris (SAP group,
n
=
57).
The Gensini score was calculated for the CAD group and both
CAD subgroups, according to CHD severity (Table 2). The ACS
group had a higher average Gensini score (80.48
±
72.46,
p
=
0.017), higher TC level, and lower ApoM level than the SAP
group (all
p
>
0.05).
Analysis of the serum ApoM lipid levels of the patients
showed that the serum level of ApoM was positively correlated
with HDL-C and negatively correlated with LDL-C and TG
levels (
p
<
0.05). The correlation with TC was not significant
(Table 3).
We used the multiple linear stepwise regression method to
describe the relationship between serum ApoM and HDL-C and
LDL-C levels. Linear dependencies and other related indicators
Table 2. Clinical data for CAD and control groups
Index
CAD
Control
p-
value
All CAD ACS group SAP group
p-value
Number (cases)
88
31
57
88
Age (years)
60.80
±
9.27 61.00
±
8.68 62.96
±
11.22 0.400 58.18
±
10.43 0.081
Male/female
63/25
20/11
25/22
0.091
53/35
0.112
TC (mmol/l)
4.47
±
1.41 5.17
±
1.34 4.34
±
1.44 0.010 4.33
±
0.49 0.299
TG (mmol/l)
1.97
±
1.28 2.20
±
1.27 2.09
±
1.32 0.698 1.02
±
0.37 0.000
#
HDL-C (mmol/l) 1.05
±
0.25 1.05
±
0.21 1.04
±
0.27 0.951 1.32
±
0.21 0.000
#
LDL-C (mmol/l) 2.70
±
1.23 3.01
±
1.48 2.61
±
1.05 0.140 2.53
±
0.41 0.202
FPG (mmol/l)
6.40
±
2.40 8.36
±
4.11 11.58
±
3.88 0.000
*
4.86
±
0.45 0.000
#
ApoM (μg/ml)
9.58
±
4.30 6.55
±
2.74 6.32
±
2.20 0.670 12.22
±
6.59 0.037
Gensini score
80.48
±
72.46 45.96
±
51.00 0.017
*
1 branch
9
16
2 branch
5
21
Data are means
±
SD.
*
Indicates statistical significance (
p
<
0.05) compared with ACS and SAP
group.
#
Indicates statistical significance (
p
<
0.05) compared to the control group with Dunnett’s test.
Because the Gensini scores were skewed distributions, Napierian logarithmic transformation was
applied for normalisation.
CAD, coronary artery disease; ACS, acute coronary syndrome; SAP, stable angina pectoris; TC,
total cholesterol; TG, triglyceride; HDL-C and LDL-C, high- and low-density lipoprotein choles-
terol, respectively; FPG, fasting plasma glucose; ApoM, apolipoprotein M.
Table 3. Multiple linear regression analysis of serum ApoM
Index
Partial regression
coefficient
SD
Standard regression
coefficient
t
-value
p
-value
Constant
3.592
2.081
1.726 0.088
HDL-C
9.767
1.316
0.573
7.421 0.000*
FPG
–0.539
0.138
–0.301
–3.908 0.000*
TG
–0.464
0.217
–0.138
–2.136 0.036*
*Statistical significance (
p
<
0.05).
HDL-C, high-density lipoprotein cholesterol; FPG, fasting plasma glucose;
TG, triglycerides.