Int J Clin Exp Med 2015;8(2):2693-2701 www.ijcem.com /ISSN:1940-5901/IJCEM0001660
Original Article Polymorphisms of COL4A1 gene are associated with arterial pulse wave velocity in healthy Han Chinese and Uygur subjects Dilare Adi1,2*, Xiang Xie1,2*, Yang Xiang1,2, Yi-Tong Ma1,2, Yi-Ning Yang1,2, Zhen-Yan Fu1,2, Xiao-Mei Li1,2, Fen Liu2, Bang-Dang Chen2 Department of Cardiology, First Affiliated Hospital of Xinjiang Medical University, Urumqi 830054, People’s Republic of China; 2Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi 830054, People’s Republic of China. *Equal contributors. 1
Received August 1, 2014; Accepted January 13, 2015; Epub February 15, 2015; Published February 28, 2015 Abstract: Pulse wave velocity (PWV) is a noninvasive index of arterial stiffness and an independent predictor of cardiovascular outcomes. Type IV collagen is an important structural component of the vascular basement membrane, thus it is important for the integrity and functions of basement membrane. However, the relationship between genetic polymorphisms of COL4A1 gene and PWV in healthy Han Chinese and Uygur subjects remains unclear. We aimed to investigate the association between PWV and COL4A1 genetic polymorphisms in healthy Han Chinese and Uygur subjects. A total of 1533 subjects (909 Han, 624 Uygur) were selected from the Cardiovascular Risk Survey (CRS) study. Two SNPs (rs605143 and rs565470) were genotyped by using the polymerase chain reaction-restriction fragment length (PCR-RFLP) method. In the Uygur population, the two SNPs (rs605143 and rs565470) were associated with PWV by analyses of a recessive model (p = 0.002, p = 0.008, respectively), and the difference remained significant after multivariate adjustment (p = 0.004, p = 0.001, respectively); the AA genotype of rs605143 was associated with increased PWV value compared with the AG or GG genotype (1543.36 ± 324.79 cm/s vs. 1530.45 ± 314.24 cm/s and 1522.93 ± 316.00 cm/s); and the CC genotype of rs565470 was associated with increased PWV value compared with the CT or TT genotype (1647.90 ± 553.27 cm/s vs. 1506.8 ± 357.35 cm/s and 1488.4 ± 344.32 cm/s). But for healthy Han Chinese subjects, this association was not observed in rs605143 and rs565470 before and after multivariate adjustment. Both rs605143 and rs565470 in the COL4A1 gene are associated with PWV in healthy Uygur subjects, indicating that carriers of the A allele of rs605143 and the C allele of rs565470 have a high risk of Arterial stiffness. Keywords: COL4A1, pulse wave velocity, arterial stiffness, single nucleotide polymorphism
Introduction Central arterial stiffening is a hallmark of the aging process and is a risk marker of morbidity and mortality of cardiovascular disease, especially coronary heart disease [1-3]. Arterial stiffness is defined by a reduction in arterial distensibility and represented by biomarkers that can be measured noninvasively. Pulse wave velocity (PWV), which is dependent on the structural and functional characteristics of the arterial wall and clinically, owing to its time efficacy and technical simplicity is widely used as a goldstandard parameter to assess arterial stiffness [4]. Recent epidemiological studies have shown that PWV is increased in patients with cardio-
vascular conditions such as hypertension, diabetes, metabolic syndrome [5]. Furthermore, PWV is an independent predictor of hypertension [6] and fatal stroke in hypertensive patients [7], end-stage renal disease [8], older adults [9], and the general population [10-12]. There is an increasing recognition that arterial stiffening is influenced by lifestyle (dietary salt consumption and exercise) and is associated with endothelial dysfunction, expression of modified vascular wall matrix proteins, altered vascular smooth muscle cell (SMC) function and vascular inflammation. Furthermore, several lines of evidence suggest that arterial stiffening is influenced by genetic factors. Recently,
COL4A1 and pulse wave velocity a genome-wide association study (GWAS) conducted by Kirill V. Tarasov et al. [13] identified a Single nucleotide polymorphism (SNP) in the COL4A1 gene was significantly associated with increased PWV value, but the full pathogenetic mechanism is not yet elucidated. COL4A1 gene which encodes α1 chain of type IV collagen is a new susceptible gene for coronary artery disease identified in the CARDIoGRAM Consortium [14]. In addition, Yamada Y et al first identified a novel polymorphism in the COL4A1 gene that is significantly associated with the prevalence of myocardial infarction [15]. In previous studies, we observed that polymorphisms of the COL4A1 gene are associated with coronary artery disease in Uygur population of Xinjiang China [16]. The purpose of the present study was to assess the effects of COL4A1 gene polymorphisms on PWV in healthy Han Chinese subjects in the Cardiovascular Risk Survey (CRS) study in Xinjiang, China. Methods Ethical approval This study was approved by the ethics committee of the First Affiliated Hospital of Xinjiang Medical University (Xinjiang, China) and conducted according to the standards of the Declaration of Helsinki. Written informed consent was obtained from each participant. Study population The study population comprised 909 healthy Han Chinese subjects (419 men, 490 women) and of 624 Uygur subjects (400 men, 224 women) who lived in the Xinjiang Uygur Autonomous Region of China and were selected from the Cardiovascular Risk Survey (CRS) study [17, 18]. Briefly, The CRS consisted of 14,618 subjects (5,757 Hans, 4767 Uygurs, and 4094 Kazakhs) and was a multiple-ethnic, community-based, cross-sectional study designed to investigate the prevalence and risk factors for cardiovascular diseases and determine the genetic and environmental contributions to atherosclerosis, CAD, and cerebral infarction of the Chinese Han, Uygur, and Kazakh populations in the Xinjiang of west China from October 2007 to March 2010. Individuals with multiple organ failure syndrome and those whose data
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were incomplete were excluded from this survey. Biochemical analyses The biochemical data collection process was conducted in examination centers at the local hospital of each participant’s residential area. Height and body weight were measured in a standard method. After 5 min of rest, blood pressure was measured three times within 10 min and the median value was used in the statistical analysis. Smoking and drinking was selfreported using a questionnaire described previously [19]. After 12-hour overnight fasting, 5 mL of venous blood was collected into tubes containing ethylene diamine tetra acetic acid and analyzed within 4 hours. Genomic DNA was extracted from peripheral leukocytes using a standard phenol-chloroform method and stored at -80°C for future analysis. We used standard methods for chemical analysis (AR/AVL Clinical Chemistry System; Dimension, Newark, NJ, USA) used by the Clinical Laboratory Department of the First Affiliated Hospital of Xinjiang Medical University. Biochemical markers in serum such as total cholesterol (TC), triglycerides (TG), glucose, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), blood urea nitrogen (BUN), creatinine (Cr) and uric acid were measured. PWV measurement After blood pressure was measured, bilateral brachial-ankle PWV (baPWV) was obtained in a supine position in all subjects using the form ankle-brachial index/PWV (VP1000; Colin Co., Ltd., Komaki, Japan), a device with four cuffs that can simultaneously measure blood pressure levels in the arms and legs, record pulse waves through sensors in the cuffs, store data from the start point of each pulse wave in the right arm and both legs, record the time difference between transmission time to the arm and transmission time to the ankle as “transmission time,” calculate the transmission distance from the right arm to each ankle according to body height, and automatically compute and output the baPWV values by transmission time and transmission distance. As there was a significant positive correlation between the left and right baPWV, we used the mean right/left baPWV value during our analysis [20].
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COL4A1 and pulse wave velocity Table 1. Primer sequences of each SNP SNPs
Polymerase Chain Reaction Primers
60°C
582 bp
Restriction enzyme DraI
60°C
416 bp
BanII
Denaturation temperature Products length
rs605143
Sense 5’AAAGCCATTGCTACCTCA3’ Antisense 5’CTGCTCCTGGTGACTCTG3’ rs565470 Sense 5’GAATGCGATAAGGACAGGG3’ Antisense 5’AGGAAAGGGAGGCACAAAA3’
Table 2. Demographic and clinical characteristics of study participants Study Variables
Han
Uygur
Total
Men
Women
Total
Men
Number (n)
909
419
490
624
400
224
Age (years)
49.50 ± 10.01
49.94 ± 10.52
49.13 ± 9.54
55.95 ± 8.35
55.77 ± 8.46
56.28 ± 8.17 70 (31.3)
EH, n (%)
Women
311 (34.20)
152 (36.30)
159 (32.6)
199 (31.9)
129 (32.3)
Diabetes, n (%)
2 (0.20)
1 (0.2)
1 (0.2)
20 (3.2)
20 (5.0)
0
Smoking, n (%)
260 (28.60)
107 (25.5)
153 (31.2)
178 (28.50)
177 (43.3)
1 (4.0)
Drinking, n (%)
162 (17.80)
68 (16.2)
94 (19.2)
80 (12.8)
79 (19.8)
1 (4.0)
BMI (kg/m2)
24.4 ± 83.36
24.55 ± 3.35
24.42 ± 3.37
25.24 ± 4.32
25.23 ± 3.94
25.26 ± 4.93
SBP (mmHg)
128.74 ± 18.62
129.19 ± 18.89
128.36 ± 18.39
129.96 ± 19.57
130.41 ± 19.56
129.16 ± 19.61
DBP (mmHg)
83.73 ± 14.86
83.68 ± 14.96
83.77 ± 14.79
80.03 ± 13.93
80.57 ± 14.14
79.08 ± 13.52
Glu (mmol /L)
5.03 ± 0.73
5.00 ± 0.73
5.06 ± 0.72
4.83 ± 1.35
4.87 ± 1.58
4.77 ± 0.79
TG (mmol/L)
1.46 ± 1.07
1.49 ± 1.19
1.45 ± 0.94
1.58 ± 1.08
1.57 ± 1.12
1.59 ± 1.02
TC (mmol/L)
4.59 ± 0.97
4.61 ± 1.01
4.57 ± 0.94
4.38 ± 1.06
4.28 ± 1.01
4.55 ± 1.11
HDL (mmol/L)
1.27 ± 0.47
1.29 ± 0.50
1.25 ± 0.44
1.26 ± 0.42
1.28 ± 0.43
1.25 ± 0.41
LDL (mmol/L)
2.91 ± 0.96
2.87 ± 0.93
2.95 ± 0.96
2.88 ± 0.97
2.85 ± 0.95
2.91 ± 1.01
PWV (cm/s)
1426.00 ± 303.88 1422.30 ± 320.08 1429.10 ± 289.61
1513.02 ± 368.17 1531.20 ± 358.36 1480.57 ± 383.78
UA (umol/L)
295.38 ± 80.06
292.86 ± 76.72
297.54 ± 82.82
261.58 ± 73.79
279.23 ± 72.68
230.08 ± 64.84
Cr (mmol/L)
75.47 ± 20.58
72.75 ± 19.15
77.79 ± 21.79
78.34 ± 33.68
85.98 ± 36.67
64.68 ± 21.68
4.90 ± 1.42
4.86 ± 1.45
4.94 ± 1.40
5.37 ± 1.92
5.52 ± 2.07
5.09 ± 1.59
BUN (mmol/L)
Continuous variables are expressed as mean ± SD. Categorical variables are expressed as percentages. BMI, body mass index; BUN, blood urea nitrogen; Cr, creatinine; DBP, diastolic blood pressure; DM, diabetes mellitus; Glu, glucose; TG, triglyceride; TC, total cholesterol; HDL, high density lipoprotein; LDL, low density lipoprotein; EH, essential hypertension; PWV, pulse-wave velocity; SBP, systolic blood pressure; UA, uric acid.
Genotyping of the COL4A1 gene Using Haploview 4.2 software and International HapMap Project website phase I & II database (http://www.hapmap.org), we obtained two tag SNPs: SNP1 (rs605143) and SNP2 (rs565470) by using minor allele frequency (MAF) ≥ 0.05 and linkage disequilibrium patterns with r2 ≥ 0.8 as a cutoff. Genotyping in the present study was confirmed by polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) analysis. Sequence information for use as a reference template was obtained from the Ensembl Genome Browser (Human, number ENSG00000187498). Sequencing primers were designed using Primer Premier 5.0 software, and primer synthesis was performed by Shanghai General Biological Technology Company Limited (Shanghai, China). PCR amplification was performed using 25 uL of 2*powder Taq PCR master mix (Beijing Biotech, Beijing,
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China), 50 ng of genomic DNA, 21 uL of distilled water, 1 uL of each forward and reverse primer in a 50 μL final reaction volume. The thermal cycling conditions were as follows: an initial denaturation step at 95°C for 5 min; 30 cycles of 95°C for 30 s, 60°C for 35 s and 72°C for 1 min was followed by a final extension step of 72°C for 10 min. Thermal cycling was performed using the GeneAmp 9700 system (Applied Biosystems) and. PCR products were digested by restriction enzyme (Fermentas, Beijing, China) in a 20 μL final reaction volume, along with 10 μL of PCR product, 5 U of restriction enzyme, 9 μL of distilled water and 1 μL Solution Buffer, incubated overnight at 37°C. The primer pair sequences, annealing temperatures, resulting fragments and restriction enzymes for the two SNPs are detailed in Table 5. Resulting fragments were separated on a 3.0% agarose gel (Figure 1).
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COL4A1 and pulse wave velocity Table 3. Genotype and Allele distributions of study subjects Variants rs605143 (SNP1) genotype G/G A/G A/A Dominant model GG AG + AA Recessive model AA AG + GG Additive model AG GG + AA Allele G A rs565470 (SNP2) genotype T/T C/T C/C Dominant model TT CC + CT Recessive model CC TT + CT Additive model CT TT + CC Allele T C
Total N (%)
Han Man N (%)
Woman N (%)
Total N (%)
Uygur Man N (%)
Woman N (%)
238 (26.2) 432 (47.5) 239 (26.3)
112 (26.7) 203 (48.4) 104 (24.8)
126 (25.7) 229 (46.7) 135 (27.6)
187 (30.0) 297 (47.6) 140 (22.4)
113 (28.2) 196 (49.0) 91 (22.8)
74 (33.0) 101 (45.1) 49 (21.9)
238 (26.2) 671 (73.8)
112 (26.7) 307 (73.7)
126 (25.7) 364 (74.3)
187 (30.0) 437 (70)
113 (28.2) 287 (71.8)
74 (33.0) 150 (67.0)
239 (26.3) 670 (73.7)
104 (24.8) 315 (75.2)
135 (27.6) 335 (72.4)
140 (22.4) 484 (77.6)
91 (22.8) 309 (77.3)
49 (21.9) 175 (78.1)
432 (47.5) 477 (52.2)
203 (48.4) 216 (51.6)
229 (46.7) 261 (53.3)
297 (47.6) 327 (52.4)
196 (49.0) 204 (51.0)
101 (45.1) 123 (54.9)
908 (49.9) 910 (50.1)
427 (50.9) 411 (49.1)
481 (49.1) 499 (50.9)
671 (53.8) 577 (46.2)
422 (52.8) 378 (47.2)
199 (44.4) 249 (55.6)
527 (58.0) 343 (37.7) 39 (4.3)
252 (60.1) 147 (35.1) 20 (4.8)
275 (56.1) 196 (40.4) 19 (3.9)
308 (49.4) 271 (43.4) 45 (7.2)
192 (48.0) 181 (45.2) 27 (6.8)
116 (51.8) 90 (40.2) 18 (8.0)
527 (58.0) 382 (42.0)
252 (60.1) 167 (39.9)
275 (56.1) 215 (43.9)
308 (49.4) 316 (50.6)
192 (48.0) 208 (52.0)
116 (51.8) 108 (48.2)
39 (4.3) 870 (95.7)
20 (4.8) 399 (95.2)
19 (3.9) 471 (96.1)
45 (7.2) 579 (92.8)
27 (6.8) 373 (93.2)
18 (8.0) 206 (92.0)
343 (37.7) 566 (62.3)
147 (35.1) 272 (64.9)
196 (40.4) 294 (60.0)
271 (43.4) 353 (56.6)
181 (45.2) 219 (54.8)
90 (40.2) 134 (59.8)
1397 (76.8) 421 (23.2)
651 (77.7) 187 (22.3)
746 (76.1) 232 (23.9)
887 (71.1) 361 (28.9)
565 (70.6) 235 (29.4)
322 (71.9) 126 (28.1)
N, number of participants; SNP, single-nucleotide polymorphism.
Statistical analysis The current analysis was performed on individuals whose aortic PWV data were available (n = 1533, 909 of Han and 624 of Uygur). All statistical analyses were performed using SPSS 17.0 software for Windows (SPSS Institute, Chicago, IL, USA). The Hardy-Weinberg equilibrium was assessed by χ2 analysis. All continuous variables were expressed as mean ± standard
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deviation. Differences in frequencies of smoking, drinking, and COL4A1 genotypes were analyzed using the χ2 test or Fisher’s exact test while appropriate. General linear model analysis was undertaken to test for associations between COL4A1 genotypes with PWV value after adjusting for confounding variables. SNP effects with continuous variables were analyzed using linear regression using three models.
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COL4A1 and pulse wave velocity Table 4. Association of COL4A1 gene with PWV for Uygur subjects Mean PWV (cm/s) ± SD Model 1 Model 2 SNP Wild/Rar Allele Homozygous for Rare Allele Heterozygous Homozygous for Wild Allele P (Rec) P (Dom) P (Add) P (Rec) P (Dom) P (Add) rs605143 G/A 1543.36 ± 324.79 1530.45 ± 314.24 1522.93 ± 316.00 0.002 0.363 0.09 0.004 0.672 0.042 rs565470 T/C 1647.90 ± 553.27 1506.8 ± 357.35 1488.40 ± 344.32 0.008 0.195 0.947 0.001 0.119 0.931 Model 1: adjusted model; Model 2: Analysis of covariance adjusted for sex, age; Rec, recessive model; Dom, dominant model; Add, additive model.
Table 5. Association of COL4A1 gene with PWV for Han subjects Mean PWV (cm/s) ± SD Model 1 Model 2 SNP Wild/Rare Allele Homozygous for Rare Allele Heterozygous Homozygous for Wild Allele P (Rec) P (Dom) P (Add) P (Rec) P (Dom) P (Add) rs605143 G/A 1426.41 ± 316.83 1435.60 ± 302.08 1408.02 ± 294.19 0.979 0.289 0.363 0.478 0.553 0.917 rs565470 T/C 1447.05 ± 288.16 1439.70 ± 311.62 1415.46 ± 300.01 0.658 0.221 0.289 0.643 0.205 0.272 Model 1: adjusted model; Model 2: Analysis of covariance adjusted for sex, age; Rec, recessive model; Dom, dominant model; Add, additive model.
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COL4A1 and pulse wave velocity
Figure 1. Restriction fragment length polymorphism analysis for determination of genotype. A. For SNP1, the GG genotype shows two bands of 362 bp and 220 bp (1 and 2); The AG genotype shows three bands of 362 bp, 258 bp and 220 bp (3, 4, 6 and 7), The AA genotype shows three bands of 258 bp, 220 bp and 104 bp (5). B. For SNP2, the TT genotype shows one band of 416 bp (1 and 4); The CT genotype shows two bands of 416 bp and 324 bp (2 and 3); The CC genotype shows one band of 324 bp (5).
Result Characteristics of study participants The study cohort consists of 1533 subjects (909 Han, 624 Uygur). The demographic and clinical characteristics of the study population are shown separately for men and women in Table 1. COL4A1 genotype and allelic frequencies Table 2 shows the distribution of genotypes and alleles of SNPs for the COL4A1 gene. All genotype distributions of the SNPs were in good agreement with the predicted HardyWeinberg equilibrium values (data not shown). Associations with PWV In the healthy Uygur subjects (Table 3), there was a significant difference in PWV value between different genotypes of the two SNPs (all p < 0.05, respectively). The subjects with the AA genotype of the rs605143 had a significantly higher PWV value compared to the subjects with the AG or GG genotype (1543.36 ± 324.79 cm/s vs. 1530.45 ± 314.24 cm/s and 1522.93 ± 316.00 cm/s); and the subjects with the CC genotype of rs565470 had a significantly higher PWV value compared to the subjects with the CT or TT genotype (1647.90 ± 553.27 cm/s vs. 1506.8 ± 357.35 cm/s and 1488.4 ± 344.32 cm/s). After using general linear model analysis, rs605143 and rs565470 were found to be significantly associated with PWV value by analyses of a recessive model before (p = 0.004, p = 0.008, respectively) and after multivariate adjustment of sex and age (p = 0.002, p = 0.008, respectively); and rs605143 was also significantly associated with PWV value in a
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additive model after multivariate adjustment (p = 0.042). However for healthy Han Chinese subjects (Table 4), PWV value showed no significant difference between different genotypes of the two SNPs (all p > 0.05, respectively). After using general linear model analysis, rs605143 and rs565470 were not found to be significantly associated with PWV value before and after multivariate adjustment of key co-variants. Discussion In this study, we found that variation in the COL4A1 gene is significantly associated with PWV value in healthy Uygur subjects in China. Individuals with the AA and the CC genotype had a significantly higher PWV value compared to individuals with other genotypes. This was the first study to investigate the common allelic variants in COL4A1 gene and its association with the PWV value in healthy Han Chinese and Uygur subjects. Increasing arterial stiffness is generally considered to represent the sum of passive stiffness corresponding to the contribution of the inert structural components that mainly results from the breakdown of elastin in the central arterial walls due to the repeated cycles of distension and recoil of the central aorta and collagen deposition and cross-linking. Accumulated evidence generated from Gene expression studies, heritability and linkage analyses and a genome-wide association study (GWAS) were all consistent with the likely involvement of genetic factors in modulating the variability PWV and in the pathophysiology of arterial stiffness. Genes which involved in regulating arterial stiffness can be divided into two classes:
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COL4A1 and pulse wave velocity class 1 includes all non matrix genes that involved with cell proliferation and vascular hypertrophy or those that influence the functional properties, affecting blood pressure control, such as nitric oxide synthase, angiotensin II type 1 receptor, β-adrenergic receptors and C-reactive protein. Class 2 includes genes that involved with the extracellular matrix or those that modulate structural changes in proteins, such as collagen 1, collagen 4, fibrillin 1 [21]. The COL4A1 gene which encodes α1 chain of type IV collagen is belongs to class 2, mapped on the telomeric region of 13q (13q34), and consists of 52 exons [22]. Type IV collagen was derived from glomerular basement membrane by Kefalides in 1966 [23], is an important structural component of the extracellular matrix, and is expressed in all tissues including the vasculature, renal glomerular, and ocular structures [24, 25]. There are 6 different types of type IV collagen α-chains (α1-α6). Each of the six chains of collagen IV has three domains: There is a short 7S domain at the N-terminal; along with collagenous domain occupying the midsection of the molecule, which contains the classic Gly-Xaa-Yaa repeated amino acid sequence and a non-collagenous domain (NC1) is positioned at the C-terminal. These six different collagen type IV alpha chains (α1-α6), form only three sets of triple helical molecules called protomers, which are designated as α1.α1.α2, α3.α4.α4, α5.α5.α6 [14, 26-28], among them α1.α1.α2 is very crucial for the protein. Type IV collagen, a major component of vascular BM, could provide a physical barrier for both soluble molecules and migrating cells and could function as a scaffold that allows for the interaction between pericytes and endothelial cells, thereby contributing to vessel stabilization, and enables the BM to withstand mechanical stress [29].
other factors. However, the mechanisms which may link COL4A1 genetic polymorphisms to PWV value are largely unknown. The possible mechanism of this condition could be related to several aspects: as mentioned above, stiffness of the large arteries which depends on a number of factors, including structural elements such as elastin and collagen, which are the main extracellular matrix proteins of the vessel wall. Type IV collagen is a main extracellular matrix proteins and also a substrate of type 2 matrix metalloprotease. During aging process within arteries, type IV collagen can be synthesized by type 2 matrix metalloprotease and can be modified by glycosylation and chemical attack, as a result vascular basement membrane allows smooth muscle cells to invade the internal elastic membrane and enter the subendothelial space, these smooth muscle cells then proliferate and secrete matrix, resulting in a diffusely thickened intima that interferes with endothelial function [30]. We should note that currently, there is no functional evidence implicating COL4A1 gene as a determinant of PWV value. Further studies are needed to elucidate these possible mechanisms.
Type IV collagen had not previously been considered to be involved in regulating arterial stiffness. Recently, a genome-wide association study (GWAS) indicates that a SNP (rs3742207) in the COL4A1 gene is strongly associated with increased PWV value in two independent populations [13]. In the present study, we also found that the COL4A1 gene polymorphisms was associated with the PWV value, individuals with the AA and the CC genotype had a significantly higher PWV value compared to subjects with other genotypes and this association remains significant after adjustment for sex, age and
None.
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In summary, the results of present study demonstrate that COL4A1 gene polymorphisms are strongly associated with increased PWV value in healthy Uygur subjects in China. Acknowledgements This study was supported financially by grants from the Great Technology Special Item Foundation of Xinjiang, China (201233138) and Natural Science Foundation of Xinjiang, China (2012211A062). Disclosure of conflict of interest
Address correspondence to: Yi-Tong Ma, Department of Cardiology, First Affiliated Hospital of Xinjiang Medical University, Urumqi 830054, People’s Republic of China; Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi 830054, People’s Republic of China. E-mail: myt_xj@sina. com
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Prognostic value of aortic pulse wave velocity as index of arterial stiffness in the general population. Circulation 2006; 113: 664-670. [12] Shokawa T, Imazu M, Yamamoto H, Toyofuku M, Tasaki N, Okimoto T, Yamane K, Kohno N. Pulse wave velocity predicts cardiovascular mortality: findings from the Hawaii-Los Angeles Hiroshima study. Circ J 2005; 69: 259-264. [13] Tarasov KV, Sanna S, Scuteri A, Strait JB, Orrù M, Parsa A, Lin PI, Maschio A, Lai S, Piras MG, Masala M, Tanaka T, Post W, O’Connell JR, Schlessinger D, Cao A, Nagaraja R, Mitchell BD, Abecasis GR, Shuldiner AR, Uda M, Lakatta EG, Najjar SS. COL4A1 Is associated with arterial stiffness by genome-wide association scan. Circ Cardiovasc Genet 2009; 2: 151158. [14] Schunkert H, König IR, Kathiresan S, Reilly MP, Assimes TL, Holm H, Preuss M, Stewart AF, Barbalic M, Gieger C, Absher D, Aherrahrou Z, Allayee H, Altshuler D, Anand SS, Andersen K, Anderson JL, Ardissino D, Ball SG, Balmforth AJ, Barnes TA, Becker DM, Becker LC, Berger K, Bis JC, Boekholdt SM, Boerwinkle E, Braund PS, Brown MJ, Burnett MS, Buysschaert I; Cardiogenics, Carlquist JF, Chen L, Cichon S, Codd V, Davies RW, Dedoussis G, Dehghan A, Demissie S, Devaney JM, Diemert P, Do R, Doering A, Eifert S, Mokhtari NE, Ellis SG, Elosua R, Engert JC, Epstein SE, de Faire U, Fischer M, Folsom AR, Freyer J, Gigante B, Girelli D, Gretarsdottir S, Gudnason V, Gulcher JR, Halperin E, Hammond N, Hazen SL, Hofman A, Horne BD, Illig T, Iribarren C, Jones GT, Jukema JW, Kaiser MA, Kaplan LM, Kastelein JJ, Khaw KT, Knowles JW, Kolovou G, Kong A, Laaksonen R, Lambrechts D, Leander K, Lettre G, Li M, Lieb W, Loley C, Lotery AJ, Mannucci PM, Maouche S, Martinelli N, McKeown PP, Meisinger C, Meitinger T, Melander O, Merlini PA, Mooser V, Morgan T, Mühleisen TW, Muhlestein JB, Münzel T, Musunuru K, Nahrstaedt J, Nelson CP, Nöthen MM, Olivieri O, Patel RS, Patterson CC, Peters A, Peyvandi F, Qu L, Quyyumi AA, Rader DJ, Rallidis LS, Rice C, Rosendaal FR, Rubin D, Salomaa V, Sampietro ML, Sandhu MS, Schadt E, Schäfer A, Schillert A, Schreiber S, Schrezenmeir J, Schwartz SM, Siscovick DS, Sivananthan M, Sivapalaratnam S, Smith A, Smith TB, Snoep JD, Soranzo N, Spertus JA, Stark K, Stirrups K, Stoll M, Tang WH, Tennstedt S, Thorgeirsson G, Thorleifsson G, Tomaszewski M, Uitterlinden AG, van Rij AM, Voight BF, Wareham NJ, Wells GA, Wichmann HE, Wild PS, Willenborg C, Witteman JC, Wright BJ, Ye S, Zeller T, Ziegler A, Cambien F, Goodall AH, Cupples LA, Quertermous T, März W, Hengstenberg C, Blankenberg S, Ouwehand WH, Hall AS, Deloukas P, Thompson JR, Stefansson K, Roberts R, Thorsteinsdottir U, O’Donnell CJ, McPherson R,
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Erdmann J; CARDIoGRAM Consortium, Samani NJ. Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease. J Nat Genet 2011; 43: 333-338. Yamada Y, Kato K, Oguri M, Fujimaki T, Yokoi K, Matsuo H, Watanabe S, Metoki N, Yoshida H, Satoh K, Ichihara S, Aoyagi Y, Yasunaga A, Park H, Tanaka M, Nozawa Y. Genetic risk for myocardial infarction determined by polymorphisms of candidate genes in a Japanese population. J Med Genet 2008; 45: 216-221. Adi D, Xie X, Ma YT, Fu ZY, Yang YN, Li XM, Xiang Y, Liu F, Chen BD. Association of COL4A1 genetic polymorphisms with coronary artery disease in Uygur population in Xinjiang, China. Lipids Health Dis 2013; 12: 153. Xie X, Ma YT, Yang YN, Li XM, Liu F, Huang D, Fu ZY, Ma X, Chen BD, Huang Y. Alcohol consumption and ankle-to-brachial index: results from the cardiovascular risk survey. PLoS One 2010; 5: e15181. Xie X, Ma YT, Yang YN, Fu ZY, Li XM, Huang D, Ma X, Chen BD, Liu F. Polymorphisms in the SAA1/2 gene are associated with carotid intima media thickness in healthy Han Chinese subjects: the cardiovascular risk survey. PLoS One 2010; 5: e13997. Xie X, Ma YT, Fu ZY, Yang YN, Ma X, Chen BD, Wang YH, Liu F. Haplotype Analysis of the CYP8A1 gene associated with myocardial infarction. Clin Appl Thromb Hemost 2009; 15: 574580. Ohnishi H, Saitoh S, Takagi S, Ohata J, Isobe T, Kikuchi Y, Takeuchi H, Shimamoto K. Pulse wave velocity as an indicator of atherosclerosis in impaired fasting glucose. Diabetes Care 2003; 26: 437-440. Yasmin, O’Shaughnessy KM. Genetics of arterial structure and function: towards new biomarkers for aortic stiffness? Clin Sci (Lond) 2008; 114: 661-677. Emanuel BS, Sellinger BT, Gudas LJ, Myers JC. Localization of the human procollagenalpha1(IV) gene to chromosome 13q34 by in situ hybridization. Am J Hum Genet 1986; 38: 3834.
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[23] Kefalides NA. A collagen of unusual composition and a glycoprotein isolated from canine glomerular basement membrane. Biochem Biophys Res Commun 1966; 22: 26-32. [24] LeBleu VS, Macdonald B, Kalluri R. Structure and function of basement membranes. ExpBiol Med 2007; 232: 1121-1129. [25] Urabe N, Naito I, Saito K, Yonezawa T, Sado Y, Yoshioka H, Kusachi S, Tsuji T, Ohtsuka A, Taguchi T, Murakami T, Ninomiya Y. Basement membrane type IV collagen molecules in the choroid plexus, piamater and capillaries in the mouse brain. Arch Histol Cytol 2002; 65: 133143. [26] Boutaud A, Borza DB, Bondar O. Type IV collagen of the glomerular basement membrane: evidence that the chain specificity of network assembly is encoded by the noncollagenous NC1 domains. J Biol Chem 2000; 275: 3071630724. [27] Borza DB, Bondar O, Todd P, Sundaramoorthy M, Sado Y, Ninomiya Y, Hudson BG. Quaternary organization of the good pasture autoantigen, the alpha 3(IV) collagen chain. Sequestration of two cryptic autoepitopes by intrapromoter interactions with the alpha4 and alpha5 NC1 domains. Biol Chem 2002; 277: 4007540083. [28] Borza DB, Bondar O, Ninomiya Y, Sado Y, Naito I, Todd P, Hudson BG. The NC1 domain of collagen IV encodes a novel network composed of the alpha 1, alpha 2, alpha 5, and alpha 6 chains in smooth muscle basement membranes. J Biol Chem 2001; 276: 2853228540. [29] Folkman J, D’Amore PA. Blood vessel formation. What is its molecular basis? Cell 1996; 87: 1153-1155. [30] Chadwick D, Goode J. Ciba Foundation Symposium: The Molecular Biology and Pathology of Elastic Tissues. Chichester: John Wiley & Sons; 1995.
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Original Article Polymorphisms of COL4A1 gene are associated with arterial pulse wave velocity in healthy Han Chinese and Uygur subjects Dilare Adi1,2*, Xiang Xie1,2*, Yang Xiang1,2, Yi-Tong Ma1,2, Yi-Ning Yang1,2, Zhen-Yan Fu1,2, Xiao-Mei Li1,2, Fen Liu2, Bang-Dang Chen2 Department of Cardiology, First Affiliated Hospital of Xinjiang Medical University, Urumqi 830054, People’s Republic of China; 2Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi 830054, People’s Republic of China. *Equal contributors. 1
Received August 1, 2014; Accepted January 13, 2015; Epub February 15, 2015; Published February 28, 2015 Abstract: Pulse wave velocity (PWV) is a noninvasive index of arterial stiffness and an independent predictor of cardiovascular outcomes. Type IV collagen is an important structural component of the vascular basement membrane, thus it is important for the integrity and functions of basement membrane. However, the relationship between genetic polymorphisms of COL4A1 gene and PWV in healthy Han Chinese and Uygur subjects remains unclear. We aimed to investigate the association between PWV and COL4A1 genetic polymorphisms in healthy Han Chinese and Uygur subjects. A total of 1533 subjects (909 Han, 624 Uygur) were selected from the Cardiovascular Risk Survey (CRS) study. Two SNPs (rs605143 and rs565470) were genotyped by using the polymerase chain reaction-restriction fragment length (PCR-RFLP) method. In the Uygur population, the two SNPs (rs605143 and rs565470) were associated with PWV by analyses of a recessive model (p = 0.002, p = 0.008, respectively), and the difference remained significant after multivariate adjustment (p = 0.004, p = 0.001, respectively); the AA genotype of rs605143 was associated with increased PWV value compared with the AG or GG genotype (1543.36 ± 324.79 cm/s vs. 1530.45 ± 314.24 cm/s and 1522.93 ± 316.00 cm/s); and the CC genotype of rs565470 was associated with increased PWV value compared with the CT or TT genotype (1647.90 ± 553.27 cm/s vs. 1506.8 ± 357.35 cm/s and 1488.4 ± 344.32 cm/s). But for healthy Han Chinese subjects, this association was not observed in rs605143 and rs565470 before and after multivariate adjustment. Both rs605143 and rs565470 in the COL4A1 gene are associated with PWV in healthy Uygur subjects, indicating that carriers of the A allele of rs605143 and the C allele of rs565470 have a high risk of Arterial stiffness. Keywords: COL4A1, pulse wave velocity, arterial stiffness, single nucleotide polymorphism
Introduction Central arterial stiffening is a hallmark of the aging process and is a risk marker of morbidity and mortality of cardiovascular disease, especially coronary heart disease [1-3]. Arterial stiffness is defined by a reduction in arterial distensibility and represented by biomarkers that can be measured noninvasively. Pulse wave velocity (PWV), which is dependent on the structural and functional characteristics of the arterial wall and clinically, owing to its time efficacy and technical simplicity is widely used as a goldstandard parameter to assess arterial stiffness [4]. Recent epidemiological studies have shown that PWV is increased in patients with cardio-
vascular conditions such as hypertension, diabetes, metabolic syndrome [5]. Furthermore, PWV is an independent predictor of hypertension [6] and fatal stroke in hypertensive patients [7], end-stage renal disease [8], older adults [9], and the general population [10-12]. There is an increasing recognition that arterial stiffening is influenced by lifestyle (dietary salt consumption and exercise) and is associated with endothelial dysfunction, expression of modified vascular wall matrix proteins, altered vascular smooth muscle cell (SMC) function and vascular inflammation. Furthermore, several lines of evidence suggest that arterial stiffening is influenced by genetic factors. Recently,
COL4A1 and pulse wave velocity a genome-wide association study (GWAS) conducted by Kirill V. Tarasov et al. [13] identified a Single nucleotide polymorphism (SNP) in the COL4A1 gene was significantly associated with increased PWV value, but the full pathogenetic mechanism is not yet elucidated. COL4A1 gene which encodes α1 chain of type IV collagen is a new susceptible gene for coronary artery disease identified in the CARDIoGRAM Consortium [14]. In addition, Yamada Y et al first identified a novel polymorphism in the COL4A1 gene that is significantly associated with the prevalence of myocardial infarction [15]. In previous studies, we observed that polymorphisms of the COL4A1 gene are associated with coronary artery disease in Uygur population of Xinjiang China [16]. The purpose of the present study was to assess the effects of COL4A1 gene polymorphisms on PWV in healthy Han Chinese subjects in the Cardiovascular Risk Survey (CRS) study in Xinjiang, China. Methods Ethical approval This study was approved by the ethics committee of the First Affiliated Hospital of Xinjiang Medical University (Xinjiang, China) and conducted according to the standards of the Declaration of Helsinki. Written informed consent was obtained from each participant. Study population The study population comprised 909 healthy Han Chinese subjects (419 men, 490 women) and of 624 Uygur subjects (400 men, 224 women) who lived in the Xinjiang Uygur Autonomous Region of China and were selected from the Cardiovascular Risk Survey (CRS) study [17, 18]. Briefly, The CRS consisted of 14,618 subjects (5,757 Hans, 4767 Uygurs, and 4094 Kazakhs) and was a multiple-ethnic, community-based, cross-sectional study designed to investigate the prevalence and risk factors for cardiovascular diseases and determine the genetic and environmental contributions to atherosclerosis, CAD, and cerebral infarction of the Chinese Han, Uygur, and Kazakh populations in the Xinjiang of west China from October 2007 to March 2010. Individuals with multiple organ failure syndrome and those whose data
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were incomplete were excluded from this survey. Biochemical analyses The biochemical data collection process was conducted in examination centers at the local hospital of each participant’s residential area. Height and body weight were measured in a standard method. After 5 min of rest, blood pressure was measured three times within 10 min and the median value was used in the statistical analysis. Smoking and drinking was selfreported using a questionnaire described previously [19]. After 12-hour overnight fasting, 5 mL of venous blood was collected into tubes containing ethylene diamine tetra acetic acid and analyzed within 4 hours. Genomic DNA was extracted from peripheral leukocytes using a standard phenol-chloroform method and stored at -80°C for future analysis. We used standard methods for chemical analysis (AR/AVL Clinical Chemistry System; Dimension, Newark, NJ, USA) used by the Clinical Laboratory Department of the First Affiliated Hospital of Xinjiang Medical University. Biochemical markers in serum such as total cholesterol (TC), triglycerides (TG), glucose, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), blood urea nitrogen (BUN), creatinine (Cr) and uric acid were measured. PWV measurement After blood pressure was measured, bilateral brachial-ankle PWV (baPWV) was obtained in a supine position in all subjects using the form ankle-brachial index/PWV (VP1000; Colin Co., Ltd., Komaki, Japan), a device with four cuffs that can simultaneously measure blood pressure levels in the arms and legs, record pulse waves through sensors in the cuffs, store data from the start point of each pulse wave in the right arm and both legs, record the time difference between transmission time to the arm and transmission time to the ankle as “transmission time,” calculate the transmission distance from the right arm to each ankle according to body height, and automatically compute and output the baPWV values by transmission time and transmission distance. As there was a significant positive correlation between the left and right baPWV, we used the mean right/left baPWV value during our analysis [20].
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COL4A1 and pulse wave velocity Table 1. Primer sequences of each SNP SNPs
Polymerase Chain Reaction Primers
60°C
582 bp
Restriction enzyme DraI
60°C
416 bp
BanII
Denaturation temperature Products length
rs605143
Sense 5’AAAGCCATTGCTACCTCA3’ Antisense 5’CTGCTCCTGGTGACTCTG3’ rs565470 Sense 5’GAATGCGATAAGGACAGGG3’ Antisense 5’AGGAAAGGGAGGCACAAAA3’
Table 2. Demographic and clinical characteristics of study participants Study Variables
Han
Uygur
Total
Men
Women
Total
Men
Number (n)
909
419
490
624
400
224
Age (years)
49.50 ± 10.01
49.94 ± 10.52
49.13 ± 9.54
55.95 ± 8.35
55.77 ± 8.46
56.28 ± 8.17 70 (31.3)
EH, n (%)
Women
311 (34.20)
152 (36.30)
159 (32.6)
199 (31.9)
129 (32.3)
Diabetes, n (%)
2 (0.20)
1 (0.2)
1 (0.2)
20 (3.2)
20 (5.0)
0
Smoking, n (%)
260 (28.60)
107 (25.5)
153 (31.2)
178 (28.50)
177 (43.3)
1 (4.0)
Drinking, n (%)
162 (17.80)
68 (16.2)
94 (19.2)
80 (12.8)
79 (19.8)
1 (4.0)
BMI (kg/m2)
24.4 ± 83.36
24.55 ± 3.35
24.42 ± 3.37
25.24 ± 4.32
25.23 ± 3.94
25.26 ± 4.93
SBP (mmHg)
128.74 ± 18.62
129.19 ± 18.89
128.36 ± 18.39
129.96 ± 19.57
130.41 ± 19.56
129.16 ± 19.61
DBP (mmHg)
83.73 ± 14.86
83.68 ± 14.96
83.77 ± 14.79
80.03 ± 13.93
80.57 ± 14.14
79.08 ± 13.52
Glu (mmol /L)
5.03 ± 0.73
5.00 ± 0.73
5.06 ± 0.72
4.83 ± 1.35
4.87 ± 1.58
4.77 ± 0.79
TG (mmol/L)
1.46 ± 1.07
1.49 ± 1.19
1.45 ± 0.94
1.58 ± 1.08
1.57 ± 1.12
1.59 ± 1.02
TC (mmol/L)
4.59 ± 0.97
4.61 ± 1.01
4.57 ± 0.94
4.38 ± 1.06
4.28 ± 1.01
4.55 ± 1.11
HDL (mmol/L)
1.27 ± 0.47
1.29 ± 0.50
1.25 ± 0.44
1.26 ± 0.42
1.28 ± 0.43
1.25 ± 0.41
LDL (mmol/L)
2.91 ± 0.96
2.87 ± 0.93
2.95 ± 0.96
2.88 ± 0.97
2.85 ± 0.95
2.91 ± 1.01
PWV (cm/s)
1426.00 ± 303.88 1422.30 ± 320.08 1429.10 ± 289.61
1513.02 ± 368.17 1531.20 ± 358.36 1480.57 ± 383.78
UA (umol/L)
295.38 ± 80.06
292.86 ± 76.72
297.54 ± 82.82
261.58 ± 73.79
279.23 ± 72.68
230.08 ± 64.84
Cr (mmol/L)
75.47 ± 20.58
72.75 ± 19.15
77.79 ± 21.79
78.34 ± 33.68
85.98 ± 36.67
64.68 ± 21.68
4.90 ± 1.42
4.86 ± 1.45
4.94 ± 1.40
5.37 ± 1.92
5.52 ± 2.07
5.09 ± 1.59
BUN (mmol/L)
Continuous variables are expressed as mean ± SD. Categorical variables are expressed as percentages. BMI, body mass index; BUN, blood urea nitrogen; Cr, creatinine; DBP, diastolic blood pressure; DM, diabetes mellitus; Glu, glucose; TG, triglyceride; TC, total cholesterol; HDL, high density lipoprotein; LDL, low density lipoprotein; EH, essential hypertension; PWV, pulse-wave velocity; SBP, systolic blood pressure; UA, uric acid.
Genotyping of the COL4A1 gene Using Haploview 4.2 software and International HapMap Project website phase I & II database (http://www.hapmap.org), we obtained two tag SNPs: SNP1 (rs605143) and SNP2 (rs565470) by using minor allele frequency (MAF) ≥ 0.05 and linkage disequilibrium patterns with r2 ≥ 0.8 as a cutoff. Genotyping in the present study was confirmed by polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) analysis. Sequence information for use as a reference template was obtained from the Ensembl Genome Browser (Human, number ENSG00000187498). Sequencing primers were designed using Primer Premier 5.0 software, and primer synthesis was performed by Shanghai General Biological Technology Company Limited (Shanghai, China). PCR amplification was performed using 25 uL of 2*powder Taq PCR master mix (Beijing Biotech, Beijing,
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China), 50 ng of genomic DNA, 21 uL of distilled water, 1 uL of each forward and reverse primer in a 50 μL final reaction volume. The thermal cycling conditions were as follows: an initial denaturation step at 95°C for 5 min; 30 cycles of 95°C for 30 s, 60°C for 35 s and 72°C for 1 min was followed by a final extension step of 72°C for 10 min. Thermal cycling was performed using the GeneAmp 9700 system (Applied Biosystems) and. PCR products were digested by restriction enzyme (Fermentas, Beijing, China) in a 20 μL final reaction volume, along with 10 μL of PCR product, 5 U of restriction enzyme, 9 μL of distilled water and 1 μL Solution Buffer, incubated overnight at 37°C. The primer pair sequences, annealing temperatures, resulting fragments and restriction enzymes for the two SNPs are detailed in Table 5. Resulting fragments were separated on a 3.0% agarose gel (Figure 1).
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COL4A1 and pulse wave velocity Table 3. Genotype and Allele distributions of study subjects Variants rs605143 (SNP1) genotype G/G A/G A/A Dominant model GG AG + AA Recessive model AA AG + GG Additive model AG GG + AA Allele G A rs565470 (SNP2) genotype T/T C/T C/C Dominant model TT CC + CT Recessive model CC TT + CT Additive model CT TT + CC Allele T C
Total N (%)
Han Man N (%)
Woman N (%)
Total N (%)
Uygur Man N (%)
Woman N (%)
238 (26.2) 432 (47.5) 239 (26.3)
112 (26.7) 203 (48.4) 104 (24.8)
126 (25.7) 229 (46.7) 135 (27.6)
187 (30.0) 297 (47.6) 140 (22.4)
113 (28.2) 196 (49.0) 91 (22.8)
74 (33.0) 101 (45.1) 49 (21.9)
238 (26.2) 671 (73.8)
112 (26.7) 307 (73.7)
126 (25.7) 364 (74.3)
187 (30.0) 437 (70)
113 (28.2) 287 (71.8)
74 (33.0) 150 (67.0)
239 (26.3) 670 (73.7)
104 (24.8) 315 (75.2)
135 (27.6) 335 (72.4)
140 (22.4) 484 (77.6)
91 (22.8) 309 (77.3)
49 (21.9) 175 (78.1)
432 (47.5) 477 (52.2)
203 (48.4) 216 (51.6)
229 (46.7) 261 (53.3)
297 (47.6) 327 (52.4)
196 (49.0) 204 (51.0)
101 (45.1) 123 (54.9)
908 (49.9) 910 (50.1)
427 (50.9) 411 (49.1)
481 (49.1) 499 (50.9)
671 (53.8) 577 (46.2)
422 (52.8) 378 (47.2)
199 (44.4) 249 (55.6)
527 (58.0) 343 (37.7) 39 (4.3)
252 (60.1) 147 (35.1) 20 (4.8)
275 (56.1) 196 (40.4) 19 (3.9)
308 (49.4) 271 (43.4) 45 (7.2)
192 (48.0) 181 (45.2) 27 (6.8)
116 (51.8) 90 (40.2) 18 (8.0)
527 (58.0) 382 (42.0)
252 (60.1) 167 (39.9)
275 (56.1) 215 (43.9)
308 (49.4) 316 (50.6)
192 (48.0) 208 (52.0)
116 (51.8) 108 (48.2)
39 (4.3) 870 (95.7)
20 (4.8) 399 (95.2)
19 (3.9) 471 (96.1)
45 (7.2) 579 (92.8)
27 (6.8) 373 (93.2)
18 (8.0) 206 (92.0)
343 (37.7) 566 (62.3)
147 (35.1) 272 (64.9)
196 (40.4) 294 (60.0)
271 (43.4) 353 (56.6)
181 (45.2) 219 (54.8)
90 (40.2) 134 (59.8)
1397 (76.8) 421 (23.2)
651 (77.7) 187 (22.3)
746 (76.1) 232 (23.9)
887 (71.1) 361 (28.9)
565 (70.6) 235 (29.4)
322 (71.9) 126 (28.1)
N, number of participants; SNP, single-nucleotide polymorphism.
Statistical analysis The current analysis was performed on individuals whose aortic PWV data were available (n = 1533, 909 of Han and 624 of Uygur). All statistical analyses were performed using SPSS 17.0 software for Windows (SPSS Institute, Chicago, IL, USA). The Hardy-Weinberg equilibrium was assessed by χ2 analysis. All continuous variables were expressed as mean ± standard
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deviation. Differences in frequencies of smoking, drinking, and COL4A1 genotypes were analyzed using the χ2 test or Fisher’s exact test while appropriate. General linear model analysis was undertaken to test for associations between COL4A1 genotypes with PWV value after adjusting for confounding variables. SNP effects with continuous variables were analyzed using linear regression using three models.
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COL4A1 and pulse wave velocity Table 4. Association of COL4A1 gene with PWV for Uygur subjects Mean PWV (cm/s) ± SD Model 1 Model 2 SNP Wild/Rar Allele Homozygous for Rare Allele Heterozygous Homozygous for Wild Allele P (Rec) P (Dom) P (Add) P (Rec) P (Dom) P (Add) rs605143 G/A 1543.36 ± 324.79 1530.45 ± 314.24 1522.93 ± 316.00 0.002 0.363 0.09 0.004 0.672 0.042 rs565470 T/C 1647.90 ± 553.27 1506.8 ± 357.35 1488.40 ± 344.32 0.008 0.195 0.947 0.001 0.119 0.931 Model 1: adjusted model; Model 2: Analysis of covariance adjusted for sex, age; Rec, recessive model; Dom, dominant model; Add, additive model.
Table 5. Association of COL4A1 gene with PWV for Han subjects Mean PWV (cm/s) ± SD Model 1 Model 2 SNP Wild/Rare Allele Homozygous for Rare Allele Heterozygous Homozygous for Wild Allele P (Rec) P (Dom) P (Add) P (Rec) P (Dom) P (Add) rs605143 G/A 1426.41 ± 316.83 1435.60 ± 302.08 1408.02 ± 294.19 0.979 0.289 0.363 0.478 0.553 0.917 rs565470 T/C 1447.05 ± 288.16 1439.70 ± 311.62 1415.46 ± 300.01 0.658 0.221 0.289 0.643 0.205 0.272 Model 1: adjusted model; Model 2: Analysis of covariance adjusted for sex, age; Rec, recessive model; Dom, dominant model; Add, additive model.
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Figure 1. Restriction fragment length polymorphism analysis for determination of genotype. A. For SNP1, the GG genotype shows two bands of 362 bp and 220 bp (1 and 2); The AG genotype shows three bands of 362 bp, 258 bp and 220 bp (3, 4, 6 and 7), The AA genotype shows three bands of 258 bp, 220 bp and 104 bp (5). B. For SNP2, the TT genotype shows one band of 416 bp (1 and 4); The CT genotype shows two bands of 416 bp and 324 bp (2 and 3); The CC genotype shows one band of 324 bp (5).
Result Characteristics of study participants The study cohort consists of 1533 subjects (909 Han, 624 Uygur). The demographic and clinical characteristics of the study population are shown separately for men and women in Table 1. COL4A1 genotype and allelic frequencies Table 2 shows the distribution of genotypes and alleles of SNPs for the COL4A1 gene. All genotype distributions of the SNPs were in good agreement with the predicted HardyWeinberg equilibrium values (data not shown). Associations with PWV In the healthy Uygur subjects (Table 3), there was a significant difference in PWV value between different genotypes of the two SNPs (all p < 0.05, respectively). The subjects with the AA genotype of the rs605143 had a significantly higher PWV value compared to the subjects with the AG or GG genotype (1543.36 ± 324.79 cm/s vs. 1530.45 ± 314.24 cm/s and 1522.93 ± 316.00 cm/s); and the subjects with the CC genotype of rs565470 had a significantly higher PWV value compared to the subjects with the CT or TT genotype (1647.90 ± 553.27 cm/s vs. 1506.8 ± 357.35 cm/s and 1488.4 ± 344.32 cm/s). After using general linear model analysis, rs605143 and rs565470 were found to be significantly associated with PWV value by analyses of a recessive model before (p = 0.004, p = 0.008, respectively) and after multivariate adjustment of sex and age (p = 0.002, p = 0.008, respectively); and rs605143 was also significantly associated with PWV value in a
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additive model after multivariate adjustment (p = 0.042). However for healthy Han Chinese subjects (Table 4), PWV value showed no significant difference between different genotypes of the two SNPs (all p > 0.05, respectively). After using general linear model analysis, rs605143 and rs565470 were not found to be significantly associated with PWV value before and after multivariate adjustment of key co-variants. Discussion In this study, we found that variation in the COL4A1 gene is significantly associated with PWV value in healthy Uygur subjects in China. Individuals with the AA and the CC genotype had a significantly higher PWV value compared to individuals with other genotypes. This was the first study to investigate the common allelic variants in COL4A1 gene and its association with the PWV value in healthy Han Chinese and Uygur subjects. Increasing arterial stiffness is generally considered to represent the sum of passive stiffness corresponding to the contribution of the inert structural components that mainly results from the breakdown of elastin in the central arterial walls due to the repeated cycles of distension and recoil of the central aorta and collagen deposition and cross-linking. Accumulated evidence generated from Gene expression studies, heritability and linkage analyses and a genome-wide association study (GWAS) were all consistent with the likely involvement of genetic factors in modulating the variability PWV and in the pathophysiology of arterial stiffness. Genes which involved in regulating arterial stiffness can be divided into two classes:
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COL4A1 and pulse wave velocity class 1 includes all non matrix genes that involved with cell proliferation and vascular hypertrophy or those that influence the functional properties, affecting blood pressure control, such as nitric oxide synthase, angiotensin II type 1 receptor, β-adrenergic receptors and C-reactive protein. Class 2 includes genes that involved with the extracellular matrix or those that modulate structural changes in proteins, such as collagen 1, collagen 4, fibrillin 1 [21]. The COL4A1 gene which encodes α1 chain of type IV collagen is belongs to class 2, mapped on the telomeric region of 13q (13q34), and consists of 52 exons [22]. Type IV collagen was derived from glomerular basement membrane by Kefalides in 1966 [23], is an important structural component of the extracellular matrix, and is expressed in all tissues including the vasculature, renal glomerular, and ocular structures [24, 25]. There are 6 different types of type IV collagen α-chains (α1-α6). Each of the six chains of collagen IV has three domains: There is a short 7S domain at the N-terminal; along with collagenous domain occupying the midsection of the molecule, which contains the classic Gly-Xaa-Yaa repeated amino acid sequence and a non-collagenous domain (NC1) is positioned at the C-terminal. These six different collagen type IV alpha chains (α1-α6), form only three sets of triple helical molecules called protomers, which are designated as α1.α1.α2, α3.α4.α4, α5.α5.α6 [14, 26-28], among them α1.α1.α2 is very crucial for the protein. Type IV collagen, a major component of vascular BM, could provide a physical barrier for both soluble molecules and migrating cells and could function as a scaffold that allows for the interaction between pericytes and endothelial cells, thereby contributing to vessel stabilization, and enables the BM to withstand mechanical stress [29].
other factors. However, the mechanisms which may link COL4A1 genetic polymorphisms to PWV value are largely unknown. The possible mechanism of this condition could be related to several aspects: as mentioned above, stiffness of the large arteries which depends on a number of factors, including structural elements such as elastin and collagen, which are the main extracellular matrix proteins of the vessel wall. Type IV collagen is a main extracellular matrix proteins and also a substrate of type 2 matrix metalloprotease. During aging process within arteries, type IV collagen can be synthesized by type 2 matrix metalloprotease and can be modified by glycosylation and chemical attack, as a result vascular basement membrane allows smooth muscle cells to invade the internal elastic membrane and enter the subendothelial space, these smooth muscle cells then proliferate and secrete matrix, resulting in a diffusely thickened intima that interferes with endothelial function [30]. We should note that currently, there is no functional evidence implicating COL4A1 gene as a determinant of PWV value. Further studies are needed to elucidate these possible mechanisms.
Type IV collagen had not previously been considered to be involved in regulating arterial stiffness. Recently, a genome-wide association study (GWAS) indicates that a SNP (rs3742207) in the COL4A1 gene is strongly associated with increased PWV value in two independent populations [13]. In the present study, we also found that the COL4A1 gene polymorphisms was associated with the PWV value, individuals with the AA and the CC genotype had a significantly higher PWV value compared to subjects with other genotypes and this association remains significant after adjustment for sex, age and
None.
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In summary, the results of present study demonstrate that COL4A1 gene polymorphisms are strongly associated with increased PWV value in healthy Uygur subjects in China. Acknowledgements This study was supported financially by grants from the Great Technology Special Item Foundation of Xinjiang, China (201233138) and Natural Science Foundation of Xinjiang, China (2012211A062). Disclosure of conflict of interest
Address correspondence to: Yi-Tong Ma, Department of Cardiology, First Affiliated Hospital of Xinjiang Medical University, Urumqi 830054, People’s Republic of China; Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi 830054, People’s Republic of China. E-mail: myt_xj@sina. com
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