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Erschienen in: BMC Cardiovascular Disorders 1/2017

Open Access 01.12.2017 | Research article

Association study to evaluate TFPI gene in CAD in Han Chinese

verfasst von: Ying Zhao, Yanbo Yu, Maowei Shi, Xi Yang, Xueqi Li, Feng Jiang, Yundai Chen, Xiaoli Tian

Erschienen in: BMC Cardiovascular Disorders | Ausgabe 1/2017

Abstract

Background

Tissue factor pathway inhibitor (TFPI) is the main physiological inhibitor of TF-induced blood coagulation process, and may play essential roles in the pathogenesis of major adverse cardiac events. This study was designed to determine whether the variation of TFPI was related with coronary artery disease (CAD) in the Han Chinese populations.

Methods

A total of 1271 patients with coronary atherosclerosis and 1287 normal individuals from northern China were enrolled in the present study. Four tagging single-nucleotide polymorphisms (SNPs) (rs7586970, rs6434222, rs10153820 and rs8176528) from TFPI were selected and genotyped by direct sequencing. And the genotypes of the above SNPs were determined in all these participants.

Results

In the populations from Beijing and Harbin, no significant case-control differences in the frequencies of TFPI polymorphism (rs10153820 and rs8176528) were observed between CAD patients and controls. Meanwhile, two SNPs of TFPI (rs7586970 and rs6434222) were found to be associated with CAD in both groups. In stratified analyses based on gender, smoking, hypertension, diabetes mellitus and hyperlipidemia, we further determined that the investigated genetic variations of the TFPI genes seemed to be related with diabetes mellitus in CAD patients.

Conclusions

Genetic variations of the TFPI genes seem to be related with CAD, which likely cooperate with metabolic risk factor (diabetes mellitus) and play critical roles in the pathogenesis of coronary artery disease.
Abkürzungen
TFPI
Tissue factor pathway inhibitor
CAD
Coronary artery disease
LACI
Lipoprotein associated coagulation inhibitor
PCI
Percutaneous coronary intervention
CPR
Culprit plaque rupture.

Background

Over the past few years, coronary artery disease (CAD) has become a major public health problem and has been associated with increased mortality globally [1]. Evidence shows that atherosclerosis, a chronic inflammatory disease of the arterial vessel wall, is the main cause of CAD [2, 3]. During the atherosclerotic process, chronic inflammatory responses are often related with the development of thrombus-mediated acute coronary events. Rupture or erosion of atherosclerotic plaques or endothelial cell damage can cause exposure of subendothelial procoagulants such as tissue factor (TF) to circulating blood, followed by the activation of the coagulation process, leading to thrombin formation and subsequent acute coronary occlusion [4].
TF mediated activation of the coagulation cascade is inhibited by its endogenous physiological inhibitor, tissue factor pathway inhibitor (TFPI) [5, 6]. TFPI is constitutively synthesized by the microvascular endothelial cells. Most of the TFPI is bound to the vascular endothelium and only 20–30% of TFPI is in free forms. TFPI is a circulating, Kunitz-type protease inhibitor, acting as a natural anticoagulant that plays a major role in atherosclerotic plaques [6]. Studies showed that the administration of exogenous TFPI or of the TFPI gene could reduce the restenosis and prevent the immediate thrombus formation after balloon injury to the rabbit aortic neointima [79]. Meanwhile, heterozygous TFPI deficiency in atherosclerosis-prone mice exhibited a greater atherosclerotic burden, increased plaque tissue factor activity and decreased time to occlusive thrombosis after photochemical vascular injury [10, 11]. These studies indicate that TFPI attenuates TF activity and acts as a potential modulator of both atherosclerosis and arterial thrombosis.
Besides simply counteracting the role of TF, experimental data describes certain novel roles for TFPI, such as innate immunity, angiogenesis and lipid metabolism. In a cecal ligation and puncture model of peritonitis, recombinant human TFPI treated mice showed decreased plasma IL-6 levels and subsequently the mortality rate was improved [12]. Exogenous TFPI at higher physiological concentrations inhibits endothelial cell migration and tube formation in vitro, showing effects of inhibiting angiogenesis [13, 14]. Besides, TFPI could bind to lipoprotein and therefore was called lipoprotein associated coagulation inhibitor (LACI). In a murine model of flow cessation, upregulation of TFPI has been shown to reduce the development of arterial thrombosis and inhibit vascular remodeling associated with flow interruption [15]. On the contrary, TFPI deficiency demonstrated a greater atherosclerotic burden in atherosclerosis-prone Apo E (−/−) mice [11]. Furthermore, association studies demonstrated that TFPI was significantly higher with older age, male gender, increased low-density lipoprotein(LDL), current smoking and diabetes [16, 17].
The mechanism of coronary artery disease is of a complicated nature. Consistent findings indicated a role for TFPI in the pathogenesis of atherosclerosis development, not only counteracting the role of TF but also acting as an anti-inflammatory, anti-angiogenic and lipid-lowering substance. Searching for the genetic variants has been recognized as an essential strategy for the prediction, prevention and individualized treatment of CAD. Hence, in this study, we are determined to explore whether TFPI polymorphisms could influence the risk of CAD in the Han Chinese populations. We selected four tagging SNPs of TFPI (rs7586970, rs6434222, rs10153820 and rs8176528). The frequencies of TFPI were evaluated in Chinese CAD patients from two geographically isolated regions of northern China.

Methods

Population and the definition of risk factors

The cases in the present study were hospitalized patients who accepted X-ray coronary angiography for diagnostic purposes from two medical centers located in Beijing and Harbin. The normal controls were selected among hospital employees and blood donors with normal X-ray coronary angiography from the two medical centers. All subjects were Han Chinese coming from northern China. The inclusion and exclusion criteria of CAD and the diagnostic criteria for relevant risk factors were clearly stated in our previous study [18].
This study was registered at the website www.​clinicaltrials.​gov (NCT 02961127) and was approved by the clinical ethical committee of the PLA General Hospital and the ethical committee of Harbin Medical University. And all subjects gave written informed consent before participation.

Genotyping of SNPs

Details on genotyping have previously been described [18]. Human genomic DNA was extracted from EDTA-anticoagulated blood sample on the Magna Pure LC Instrument [19]. In view of the hapmap (CHB + JPT), the four tagging single-nucleotide polymorphisms (SNPs) of TFPI (rs7586970, rs6434222, rs10153820 and rs8176528) were selected. DNA fragments of 120-180 bp containing the above SNPs were selected and amplified by PCR, with the corresponding primers listed in Table 1.
Table 1
The pairs of PCR primers for amplifications of SNPs for TFPI
SNP
Gene
Position
primer
rs8176528
TFPI
intron
forward: 5′- CAGTTCGTGTAGGGTTACTCAT −3’
reverse:5′- CCAGAGACTTTATGAGTGTCT −3’
rs10153820
TFPI
5′ upstream region
forward: 5′-CGTTGGAGGTCTCTCTTAGT-3’
reverse:5′- CTGGGCTGAGTAGCCAAGTT-3’
rs6434222
TFPI
intron
forward: 5′-GTTTGGTTCAAGAGAGGAACT-3’
reverse:5′- CATGACTCAGCTGCCAGGACT-3’
rs7586970
TFPI
Serine to Asn
forward: 5′- GAAGGCGTTCAGAAAGACTTGGT-3’
reverse:5′-CCCTCAGCATTGACCACAGT-3’
The amplified DNA fragments were subsequently purified by PEG precipitation and subjected to direct sequencing with a BigDye v3.1 kit and running on ABI 3130XL.

Statistical analysis

Values are expressed as the mean ± standard deviation or otherwise stated. Univariate analysis of the general characteristics of the population involves the independent Student t test or chi-square test as applicable. Genotype distribution for single SNPs was analyzed for departure from the Hardy-Weinberg equilibrium using the chi-square test. All statistical analyses involved use of SPSS statistical package version 17.0 (SPSS Inc., Chicago, IL, UAS). The significance level was taken to be p < 0.05.

Results

Characteristics of the study population

The clinical characteristics of all the included individuals are shown in Table 2. Two pairs of CAD patients and non-CAD normal controls were recruited among the Han Chinese from the two hospitals in Beijing and Harbin. One pair (Population 1) was collected from northern China while the other (Population 2) was collected from north-eastern China. Population 1 consisted of 808 cases and 829 non-CAD controls whereas Population 2 consisted of 463 cases and 458 non-CAD controls. Both Population 1 and Population 2 were age and gender matched. The risk factors were compared between cases and normal controls by t test (age and BMI) and Chi-square test (gender, smoking, hypertension, diabetes mellitus and hyperlipidemia).
Table 2
Characteristics of study populations
 
Population 1
 
Population 2
 
case (n = 808)
control (n = 829)
P value
case (n = 463)
control (n = 458)
P value
age (year)
60.36 ± 10.22
61.12 ± 12.01
0.166
54.06 ± 8.76
53.27 ± 9.06
0.175
male
634 (78.5%)
647 (78.0%)
0.837
335 (72.4%)
332 (72.5%)
0.963
BMI (kg/m2)
25.70 ± 3.28
24.97 ± 3.08
<0.001
25.56 ± 3.26
24.20 ± 2.89
<0.001
smoking
367 (45.4%)
111 (13.4%)
<0.001
269 (58.1%)
232 (50.7%)
<0.001
Hypertension
528 (65.3%)
311 (37.5%)
<0.001
294 (63.5%)
118 (25.8%)
<0.001
diabetes mellitus
225 (27.8%)
104 (12.5%)
<0.001
125 (27.0%)
30 (6.6%)
<0.001
hyperlipidemia
439 (54.3%)
521 (62.8%)
<0.001
314 (67.8%)
181 (39.5%)
<0.001
The data were presented as mean ± SEM (standard error of the mean) for age and BMI as well as No.(percentage) for other factors. P values for age and BMI were calculated from t-test comparing case and control groups within population. P values for gender, smoking, hypertension, diabetes mellitus, hyperlipidemia were calculated from Chi-square test within population. BMI: body mass index, which is calculated by body weight (Kg)/ height2 (m2)

Genotype distribution and genotype association analysis

In both populations from Beijing and Harbin, no significant deviation among the four tagging SNPs of TFPI was found by the Hardy-Weinberg equilibrium test. The distribution of the TFPI genotype among patients and normal controls in both regions is demonstrated in Table 3. No statistically significant differences in the frequencies of rs8176528 and rs10153820 were obtained between CAD cases and non-CAD controls (rs8176528, p = 0.146 for population 1 and 0.486 for population 2; rs10153820, p = 0.792 for population 1 and 0.959 for population 2, Table 3), while statistically significant differences were obtained in the frequencies of rs6434222 and rs7586970 between the two populations from Beijing and Harbin (rs6434222, p < 0.001 for population 1 and population 2; rs7586970, p = 0.020 for population 1 and 0.018 for population 2, Table 3).
Table 3
Frequency of TFPI polymorphism in CAD population from two regions
  
Population 1
 
Population 2
 
SNP
genotype
CAD n (%)
Non-CAD n (%)
P
CAD n (%)
Non-CAD n (%)
P
rs8176528
 
808
829
 
463
458
 
 
GG
656 (81.2)
694 (83.7)
0.146
380 (82.1)
384 (83.8)
0.486
 
AA
GA
40 (5.0)
112 (13.8)
46 (5.6)
89 (10.7)
 
18 (3.9)
65 (14.0)
21 (4.6)
53 (11.6)
 
Allelic A frequency (%)
11.8
10.9
 
10.9
10.3
 
rs10153820
 
808
829
 
463
458
 
 
GG
415 (51.4)
420 (50.7)
0.792
285 (61.6)
286 (62.5)
0.959
 
AA
GA
48 (5.9)
345 (42.7)
56 (6.7)
353 (42.6)
 
81 (17.5)
97 (20.9)
79 (17.2)
93 (20.3)
 
Allelic A frequency (%)
27.3
28.0
 
27.9
27.4
 
rs6434222
 
808
829
 
463
458
 
 
TT
433 (53.6)
496 (59.8)
<0.001
235 (50.7)
285 (62.2)
<0.001
 
AA
TA
48 (5.9)
327 (40.5)
99 (11.9)
234 (28.3)
 
11 (2.4)
217 (46.9)
60 (13.1)
113 (24.7)
 
Allelic A frequency (%)
26.2
26.1
 
25.8
25.4
 
rs7586970
 
808
829
 
463
458
 
 
TT
681 (84.3)
703 (84.8)
0.020
384 (82.9)
391 (85.4)
0.018
 
CC
TC
36 (4.5)
91 (11.2)
57 (6.9)
69 (8.3)
 
21 (4.5)
58 (12.6)
32 (7.0)
35 (7.6)
 
Allelic C frequency (%)
10.1
11.0
 
10.8
10.8
 
Calculations are performed with comparison of three different genotypes. Values are the number (percentage) of subjects. Significant differences were drawn in frequencies of rs7586970 and rs6434222 between CAD cases and non-CAD controls
For better understanding the link between the investigated SNPs and other risk factors in CAD patients, we further performed stratification analyses based on gender, smoking, medical history of hypertension, hyperlipidemia and diabetes mellitus. Due to the influence of diabetes mellitus, a significant difference in the frequencies of TFPI SNPs was obtained in individuals with CAD compared to controls without CAD in our study (shown in Table 4). No obvious differences in the frequencies were obtained for any genotype based on gender (Table 5), smoking (Table 6), hypertension (Table 7), or hyperlipidemia (Table 8).
Table 4
Frequencies of TFPI polymorphisms in two populations according to diabetes mellitus
SNP
genotype
Population 1
Population 2
diabetes mellitus
Non- diabetes mellitus
diabetes mellitus
Non- diabetes mellitus
CAD n (%)
Non-CAD n(%)
P
CAD n (%)
Non-CAD n (%)
P
CAD n (%)
Non-CAD n (%)
P
CAD n (%)
Non-CAD n (%)
P
Rs8176528
GG
225
104
0.417
583
725
<0.001
125
30
0.726
338
428
0.003
199
76
457
618
65
18
315
366
(88.4)
(73.1)
(78.4)
(85.2)
(52)
(60.0)
(93.2)
(85.5)
AA
9
5
 
31
41
 
9
2
 
9
19
 
(4.0)
(4.8)
(5.3)
(5.7)
(7.2)
(6.7)
(2.7)
(4.4)
GA
17
23
 
95
66
 
51
10
 
14
43
 
(7.6)
(22.1)
(16.3)
(9.1)
(40.8)
(33.3)
(4.1)
(10.1)
Rs10153820
GG
225
104
0.002
583
725
0.063
125
30
0.038
338
428
0.392
103
67
312
353
86
15
199
271
(45.8)
(64.4)
(53.5)
(48.7)
(68.8)
(50.0)
(58.9)
(63.3)
AA
27
13
 
21
43
 
19
4
 
62
75
 
(12.0)
(12.5)
(3.6)
(5.9)
(15.2)
(13.3)
(18.3)
(17.5)
GA
95
24
 
250
329
 
20
11
 
77
82
 
(42.2)
(23.1)
(42.9)
(45.4)
(16.0)
(36.7)
(22.8)
(19.2)
225
104
583
725
125
30
338
428
Rs6434222
TT
107
53
0.803
326
443
<0.001
65
17
0.675
170
268
<0.001
(47.6)
(51.0)
(55.9)
(61.1)
(52.0)
(56.7)
(50.3)
(62.6)
AA
21
8
 
27
91
 
5
2
 
6
58
 
(9.3)
(7.7)
(4.6)
(12.6)
(4.0)
(6.6)
(1.8)
(13.6)
TA
97
43
 
230
191
 
55
11
 
162
102
 
(43.1)
(41.3)
(39.5)
(26.3)
(44.0)
(36.7)
(47.9)
(23.8)
225
104
583
725
125
30
338
428
Rs7586970
TT
161
76
0.926
520
627
0.043
67
13
0.065
317
378
0.027
(71.6)
(73.1)
(89.2)
(86.5)
(53.6)
(43.3)
(93.8)
(88.3)
CC
13
5
 
23
52
 
13
8
 
8
24
 
(5.8)
(4.8)
(3.9)
(7.2)
(10.4)
(26.7)
(2.4)
(5.6)
TC
51
23
 
40
46
 
45
9
 
13
26
 
(22.6)
(22.1)
(6.9)
(6.3)
(36.0)
(30.0)
(3.8)
(6.1)
Calculations were performed with comparison of three different genotypes. Values are the number (percentage) of subjects. After stratification analysis based on diabetes mellitus, significant association was found between genotype distributions and CAD in CAD patients and non-CAD controls
Table 5
Frequencies of TFPI polymorphisms in two populations according to genders
SNP
genotype
Population 1
Population 2
men
women
men
women
CAD n (%)
Non-CAD n (%)
P
CAD n (%)
Non-CAD n (%)
P
CAD n (%)
Non-CAD n (%)
P
CAD n (%)
Non-CAD n (%)
P
Rs8176528
GG
634
647
0.281
174
182
0.484
335
332
0.327
128
126
0.913
512
538
144
156
273
281
107
103
(80.8)
(83.2)
(82.8)
(85.7)
(81.5)
(84.7)
(83.6)
(81.7)
AA
33
37
 
7
9
 
13
15
 
5
6
 
(5.2)
(5.7)
(4.0)
(5.0)
(3.9)
(4.5)
(3.9)
(4.8)
GA
89
72
 
23
17
 
49
36
 
16
17
 
  
(14.0)
(11.1)
 
(13.2)
(9.3)
 
(14.6)
(10.8)
 
(12.5)
(13.5)
 
Rs10153820
GG
634
647
0.838
174
182
0.343
335
332
0.988
128
126
0.782
306
319
109
101
204
201
81
85
(48.3)
(49.3)
(62.6)
(55.5)
(60.9)
(60.5)
(63.3)
(67.4)
AA
41
45
 
7
11
 
59
60
 
22
19
 
(6.4)
(7.0)
(4.0)
(6.0)
(17.6)
(18.1)
(17.2)
(15.1)
GA
287
283
 
58
70
 
72
71
 
25
22
 
(45.3)
(43.7)
(33.4)
(38.5)
(21.5)
(21.4)
(19.5)
(17.5)
Rs6434222
TT
634
647
<0.001
174
182
0.003
335
332
<0.001
128
126
0.001
312
379
121
117
166
214
69
71
(49.2)
(58.6)
(69.5)
(64.3)
(49.6)
(64.5)
(53.9)
(56.3)
AA
41
73
 
7
26
 
7
41
 
4
19
 
(6.5)
(11.3)
(4.1)
(14.3)
(2.0)
(12.3)
(3.1)
(15.1)
TA
281
195
 
46
39
 
162
77
 
55
36
 
(44.3)
(30.1)
(26.4)
(21.4)
(48.4)
(23.2)
(43.0)
(28.6)
Rs7586970
TT
634
647
0.068
174
182
0.263
335
332
0.056
128
126
0.084
537
549
144
154
293
289
91
102
(84.7)
(84.9)
(82.8)
(84.6)
(87.5)
(87.0)
(71.1)
(81.0)
CC
28
44
 
8
13
 
10
21
 
11
11
 
(4.4)
(6.8)
(4.6)
(7.2)
(3.0)
(6.4)
(8.6)
(8.7)
TC
69
54
 
22
15
 
32
22
 
26
13
 
(10.9)
(8.3)
(12.6)
(8.2)
(9.5)
(6.6)
(20.3)
(10.3)
Calculations were performed with comparison of three different genotypes. Values are the number (percentage) of subjects. After stratification analysis based on gender, no significant association was found between genotype distributions and CAD in CAD patients and non-CAD controls
Table 6
Frequencies of TFPI polymorphisms in two populations according to smoking status
SNP
genotype
Population 1
Population 2
smoking
Non- smoking
smoking
Non- smoking
CAD n (%)
Non-CAD n (%)
P
CAD n (%)
Non-CAD n (%)
P
CAD n (%)
Non-CAD n (%)
P
CAD n (%)
Non-CAD n (%)
P
Rs8176528
GG
367
111
0.695
441
718
0.273
269
232
0.581
194
226
0.063
298
93
358
601
233
194
147
190
(81.2)
(83.8)
(81.2)
(83.7)
(86.6)
(83.6)
(75.8)
(84.1)
AA
18
6
 
22
40
 
7
9
 
11
12
 
(4.9)
(5.4)
(5.0)
(5.6)
(2.6)
(3.9)
(5.7)
(5.3)
GA
51
12
 
61
77
 
29
29
 
36
24
 
(13.9)
(10.8)
(13.8)
(10.7)
(10.8)
(12.5)
(18.5)
(10.6)
Rs10153820
GG
367
111
0.998
441
718
0.827
269
232
0.871
194
226
0.988
184
56
231
364
164
146
121
140
(50.1)
(50.5)
(52.4)
(50.7)
(61.0)
(62.9)
(62.4)
(61.9)
AA
20
6
 
28
50
 
48
41
 
33
38
 
(5.4)
(5.4)
(6.3)
(7.0)
(17.8)
(17.7)
(17.0)
(16.9)
GA
163
49
 
182
304
 
57
45
 
40
48
 
(44.5)
(44.1)
(41.3)
(42.3)
(21.2)
(19.4)
(20.6)
(21.2)
Rs6434222
TT
367
111
0.021
441
718
<0.001
269
232
<0.001
194
226
<0.001
178
64
255
432
136
132
99
153
(48.5)
(57.7)
(57.8)
(60.2)
(50.6)
(56.9)
(51.0)
(67.7)
AA
20
11
 
28
88
 
7
39
 
4
21
 
(5.4)
(9.9)
(6.3)
(12.3)
(2.6)
(16.8)
(2.1)
(9.3)
TA
169
36
 
158
198
 
126
61
 
91
52
 
(46.1)
(32.4)
(35.9)
(27.5)
(46.8)
(26.3)
(46.9)
(23.0)
Rs7586970
TT
367
111
0.749
441
718
0.064
269
232
0.081
194
226
0.202
306
92
375
611
221
194
163
197
(83.4)
(82.9)
(85.0)
(85.1)
(82.2)
(83.7)
(84.0)
(87.2)
CC
17
7
 
19
50
 
12
18
 
9
14
 
(4.6)
(6.3)
(4.3)
(7.0)
(4.4)
(7.7)
(4.6)
(6.2)
TC
44
12
 
47
57
 
36
20
 
22
15
 
(12.0)
(10.8)
(10.7)
(7.9)
(13.4)
(8.6)
(11.4)
(6.6)
Calculations were performed with comparison of three different genotypes. Values are the number (percentage) of subjects. After stratification analysis based on smoking status, no significant association was found between genotype distributions and CAD in CAD patients and non-CAD controls
Table 7
Frequencies of TFPI polymorphisms in two populations according to hypertension
SNP
genotype
Population 1
Population 2
hypertension
Non-hypertension
hypertension
Non-hypertension
CAD n (%)
Non-CAD n (%)
P
CAD n (%)
Non-CAD n (%)
P
CAD n (%)
Non-CAD n (%)
P
CAD n (%)
Non-CAD n (%)
P
Rs8176528
GG
528
311
0.074
280
518
0.403
294
118
0.477
169
340
0.707
428
271
228
423
238
100
142
284
(81.1)
(87.1)
(81.4)
(81.7)
(81.0)
(84.7)
(84.0)
(83.5)
AA
26
10
 
14
36
 
13
6
 
5
15
 
(4.9)
(3.2)
(5.0)
(6.9)
(4.4)
(5.1)
(3.0)
(4.4)
GA
74
30
 
38
59
 
43
12
 
22
41
 
(14.0)
(9.7)
(13.6)
(11.4)
(14.6)
(10.2)
(13.0)
(12.1)
Rs10153820
GG
528
311
0.327
280
518
0.381
294
118
0.744
169
340
0.797
268
174
147
246
175
75
110
211
(50.8)
(55.9)
(52.5)
(47.5)
(59.5)
(63.6)
(65.1)
(62.1)
AA
31
18
 
17
38
 
54
19
 
27
60
 
(5.8)
(5.8)
(6.1)
(7.3)
(18.4)
(16.1)
(16.0)
(17.6)
GA
229
119
 
116
234
 
65
24
 
32
69
 
(43.4)
(38.3)
(41.4)
(45.2)
(22.1)
(20.3)
(18.9)
(20.3)
Rs6434222
TT
528
311
<0.001
280
518
0.002
294
118
<0.001
169
340
<0.001
274
194
159
302
146
60
89
225
(51.9)
(62.4)
(56.8)
(58.3)
(49.7)
(50.8)
(52.7)
(66.2)
AA
33
37
 
15
62
 
8 (2.7)
21
 
3
39
 
(6.3)
(11.9)
(5.4)
(12.0)
 
(17.8)
(1.8)
(11.5)
TA
221
80
 
106
154
 
140
37
 
77
76
 
(41.8)
(25.7)
(37.8)
(29.7)
(47.6)
(31.4)
(45.5)
(22.3)
Rs7586970
TT
528
311
0.250
280
518
0.078
294
118
0.312
169
340
0.158
448
262
233
441
241
98
143
293
(84.8)
(84.2)
(83.3)
(85.2)
(82.0)
(83.1)
(84.6)
(86.2)
CC
23
21
 
13
36
 
14
9
 
7
23
 
(4.4)
(6.8)
(4.6)
(6.9)
(4.8)
(7.6)
(4.1)
(6.8)
TC
57
28
 
34
41
 
39
11
 
19
24
 
(10.8)
(9.0)
(12.1)
(7.9)
(13.2)
(9.3)
(11.3)
(7.0)
Calculations were performed with comparison of three different genotypes. Values are the number (percentage) of subjects. After stratification analysis based on hypertension, no significant association was found between genotype distributions and CAD in CAD patients and non-CAD controls
Table 8
Frequencies of TFPI polymorphisms in two populations according to hyperlipidemia
SNP
genotype
Population 1
Population 2
hyperlipidemia
Non- hyperlipidemia
hyperlipidemia
Non- hyperlipidemia
CAD n (%)
Non-CAD n (%)
P
CAD n (%)
Non-CAD n (%)
P
CAD n (%)
Non-CAD n (%)
P
CAD n (%)
Non-CAD n (%)
P
Rs8176528
GG
439
521
0.074
369
308
0.651
314
181
0.580
149
277
0.166
356
447
300
247
269
157
111
227
(81.1)
(85.8)
(81.3)
(80.2)
(85.7)
(86.7)
(74.5)
(81.9)
AA
21
25
 
19
21
 
10
8
 
8
13
 
(4.8)
(4.8)
(5.1)
(6.8)
(3.2)
(4.4)
(5.4)
(4.7)
GA
62
49
 
50
40
 
35
16
 
30
37
 
(14.1)
(9.4)
(13.6)
(13.0)
(11.1)
(8.9)
(20.1)
(13.4)
Rs10153820
GG
439
521
0.301
369
308
0.848
314
181
0.788
149
277
0.688
217
251
198
169
196
110
89
176
(49.4)
(48.2)
(53.7)
(54.9)
(62.4)
(60.8)
(59.7)
(63.5)
AA
20
36
 
28
20
 
53
35
 
28
44
 
(4.6)
(6.9)
(7.6)
(6.5)
(16.9)
(19.3)
(18.8)
(15.9)
GA
202
234
 
143
119
 
65
36
 
32
57
 
(46.0)
(44.9)
(38.7)
(38.6)
(20.7)
(19.9)
(21.5)
(20.6)
439
521
369
308
314
181
149
277
Rs6434222
TT
252
321
0.002
181
175
<0.001
158
125
<0.001
77
160
<0.001
(57.4)
(61.6)
(49.1)
(56.8)
(50.3)
(69.1)
(51.7)
(57.8)
AA
28
58
 
20
41
 
6
19
 
5
41
 
(6.4)
(11.1)
(5.4)
(13.3)
(1.9)
(10.5)
(3.4)
(14.8)
TA
159
142
 
168
92
 
150
37
 
67
76
 
(36.2)
(27.3)
(45.5)
(29.9)
(47.8)
(20.4)
(44.9)
(27.4)
Rs7586970
TT
439
521
0.117
369
308
0.125
314
181
0.064
149
277
0.073
372
449
309
254
252
160
132
231
(84.7)
(86.2)
(83.7)
(82.5)
(80.3)
(88.4)
(88.6)
(83.4)
CC
19
32
 
17
25
 
16
6
 
5
26
 
(4.3)
(6.1)
(4.6)
(8.1)
(5.1)
(3.3)
(3.4)
(9.4)
TC
48
40
 
43
29
 
46
15
 
12
20
 
(11.0)
(7.7)
(11.7)
(9.4)
(14.6)
(8.3)
(8.0)
(7.2)
Calculations were performed with comparison of three different genotypes. Values are the number (percentage) of subjects. After stratification analysis based on hyperlipidemia, no significant association was found between genotype distributions and CAD in CAD patients and non-CAD controls

Discussion

Our present study investigated four tagging SNPs of TFPI in CAD Han Chinese patients from two medical centers in Beijing and Harbin. We demonstrated for the first time that significant differences were drawn in the frequencies of rs7586970 and rs6434222 between CAD cases and non-CAD controls from two geographically isolated regions. For better understanding the interaction between genetic variations and other risk factors, stratification analysis was further applied and significant differences in four genotype distributions were found in patients with type 2 diabetes mellitus compared with non-DM controls. These results provided the first evidence that genetic variations of the TFPI genes are associated with the risk of CAD in Han Chinese patients.
The possible interactions between the genetic variations and the onset of CAD have been increasingly studied over the past few years. These studies strongly suggest that genetic variations can contribute to the pathogenesis of CAD, thereby may act as an indicator to predict the onset of the disease. CAD is a chronic inflammatory process resulting from the interactions between lipoprotein metabolism, plaque rupture and thrombosis [20]. Due to the complicated etiology, exploring the possible genetic polymorphisms may be beneficial to understand the variant individual susceptibility to risk factors that cause CAD. In one study, whole genome scans were performed trying to identify the candidate genetic loci related with hypertension, hyperlipidemia, low HDL levels and diabetes [21]. However, up to now, few genetic loci with obvious susceptibility of CAD have been confirmed, emphasizing the diversity and complexity of the disease.
The TFPI gene comprises 9 exons separated by 8 introns with a promoter region. Mature TFPI molecule comprises three tandem Kunitz-type domains. The comprising elements of TFPI are listed as follows: a negatively charged NH2-terminal region connected by the first Kunitz-type domain (K1), a linker domain, a second Kunitz-type domain (K2), a second linker domain, the third Kunitz-type domain (K3) and a positively charged COOH-terminal basic region. As is known, the majority of TFPI is synthesized by vascular endothelial cells and smooth muscle cells [22, 23]. TFPI co-localizes with endothelial cells and macrophages in human atherosclerotic plaques, where it may modulate atherosclerosis and arterial thrombosis by attenuating TF activity [24, 25]. Several investigations focusing on the association between polymorphisms of the TFPI and cardiovascular diseases have been done to make clear the crucial role of TFPI. For instance, in Germany, the polymorphisms of P151L located in TFPI have been put forward in patients with venous thrombosis [26]. Another study carried out in France screened the TFPI gene, V264 M for point sequence variations among patients with acute coronary syndrome. Unfortunately, the result did not demonstrate that the variations of TFPI contribute to acute coronary syndromes [27]. Whether TFPI variations are associated with the susceptibility of CAD still remains unclear.
To explore the link between TFPI gene variations and coronary heart disease, the detection of 4 tagging SNPs (rs7586970, rs6434222, rs10153820 and rs8176528) was executed in this study. And we found that frequencies of rs7586970 and rs6434222 showed significant difference in Chinese CAD patients, indicating that the information of the TFPI gene polymorphism was helpful for evaluating the risk of developing coronary heart disease in Han Chinese. Previously, Jia Yu et al. investigated the link between TFPI-2 gene variations and atherosclerosis in the Chinese population, and two SNPs (rs59805398 and rs34489123) and 5 haplotypes were confirmed to be correlated with CAD. Moreover, TFPI-2 gene polymorphisms might not predict the severity of coronary atherosclerosis [28]. Trine B. Opstad et al. demonstrated a significant influence of the TFPI polymorphisms on thrombin generation, which might be an outcome of the reported genotype-induced alterations in the blood TFPI levels, suggesting a modified risk of atherothrombosis in patients holding the TFPI-399 and TFPI-33 polymorphisms [29]. Didier et al. found that the T-287C variations in the 5′ regulatory region of the TFPI gene were correlated with significant upregulation of the TFPI molecules, suggesting a positive influence of this polymorphism on the TFPI antigen expression. Though the study demonstrated that the T-287C variations were not correlated with an increased incidence of coronary artery disease, the results have not excluded the possibility that other gene variations in the TFPI may influence this incidence [30]. In the present study, the results showed for the first time that TFPI gene polymorphism (rs7586970 and rs6434222) could substantially influence the risk of atherosclerosis in Han Chinese.
Most previous studies supported that the higher levels of TFPI is associated with male gender, increased LDL, smoking and diabetes, all of which are widely accepted as cardiovascular risk factors [31]. Hence, we further investigated whether certain selected SNPs in the TFPI gene was related with cardiovascular risk factors (e.g. gender, smoking, medical history of hypertension, diabetes mellitus and hyperlipidemia) among our enrolled participants. And we found that the investigated genetic polymorphisms of the TFPI genes seemed to be related with diabetes mellitus in our enrolled CAD Han Chinese patients.
The association between CAD and diabetes mellitus has been well established. However, the detailed underlying mechanism accounting for this association has not been fully investigated. Evidence showed that patients with diabetes mellitus were related with faster aortic stenosis progression, endothelial dysfunction, higher coronary artery calcium scores and aortic valve calcification [32, 33]. The accelerated atherosclerotic process presented in patients with type 2 diabetes mellitus might be a consequence of permanent blood hyperglycemia [34]. Chronic blood hyperglycemia may result in the glycosylation of albumin, which has been confirmed to promote the production of TFPI in endothelial cells and monocytes [35]. In chronic hyperglycemia particularly in patients with microalbuminuria, the binding of advanced glycated end products could promote the infiltration of peripheral monocytes into the early atherosclerotic lesions and therefore induce an intravascular oxidative stress response, resulting in increased TFPI activity in vitro [36, 37]. Several studies reported that significantly higher TFPI plasma levels have been found in CAD patients complicated with T2DM compared to uncomplicated CAD patients [3840]. Increased TFPI plasma levels reflect endothelial damage or impaired binding of TFPI to vascular endothelial cells by glycosaminoglycans since TFPI is predominantly produced by vascular endothelium [16, 37]. Thus, the possible expression alterations of TFPI due to genetic polymorphisms, might lead to a hypercoagulable state in CAD patients, which might be more essential for CAD patients complicated with diabetes.
In our study, the possible link between TFPI genetic polymorphism and other metabolic risk factors (e.g. gender, smoking, hypertension and hyperlipidemia) was investigated, and the results showed no evidence indicating a relationship between TFPI variations and those risk factors. However, it should be noteworthy that the participants were volunteers selected from two regions of China, and may not stand for the whole population. Hence, the association of TFPI with cardiovascular risk factors should be analyzed in more ethnic groups and in larger populations in our future studies. In addition, one recent meta-analysis demonstrated that the traditional risk factors associated with culprit plaque rupture (CPR) may vary depending on the clinical presentation of the patients. For example, hypertension was the sole clinical risk factor accounting for the ST-elevated myocardial infarction (STEMI), while advanced age, diabetes mellitus and hyperlipidemia were the candidate clinical predictors in unstable angina and non ST-elevated myocardial infarction (NSTEMI). Whether the association between TFPI polymorphism and risk factors vary depending on different clinical presentations remains unknown [41]. Further investigations are needed to make clear whether TFPI variations are related with certain subtypes of CAD.

Conclusions

In summary, we identified two new variations located in the TFPI gene among the present population of Han Chinese CAD patients. In addition, genetic polymorphisms of the TFPI gene are likely to be related with type 2 diabetes mellitus in CAD patients. Further investigations are needed to define whether interventions that target TFPI expression and activity by SNPs might retard or reverse the progression of CAD in Han Chinese patients.

Acknowledgements

We are very grateful for the helpful contribution from the Department of Human Population Genetics, Institute of Molecular Medicine of Peking University.

Funding

This study was funded by a grant from National Natural Science Foundation of China (81670486) and the research foundation for young scientist of Jinan Military General Hospital (2016QN03).

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
This study was approved by the clinical ethical committee of the PLA General Hospital and the ethical committee of Harbin Medical University. Written informed consent was obtained from all the participants before enrollment.
Not applicable.

Competing interests

The authors have no financial or other relationship that might lead to a conflict of interest.

Publisher’s Note

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://​creativecommons.​org/​licenses/​by/​4.​0/​), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated.
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Metadaten
Titel
Association study to evaluate TFPI gene in CAD in Han Chinese
verfasst von
Ying Zhao
Yanbo Yu
Maowei Shi
Xi Yang
Xueqi Li
Feng Jiang
Yundai Chen
Xiaoli Tian
Publikationsdatum
01.12.2017
Verlag
BioMed Central
Erschienen in
BMC Cardiovascular Disorders / Ausgabe 1/2017
Elektronische ISSN: 1471-2261
DOI
https://doi.org/10.1186/s12872-017-0626-y

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