Abstract
Objectives: Prior studies have demonstrated NF-κB plays an important role in the development and progression of inflammatory diseases. The aim of this study was to investigate whether promoter polymorphisms in NFKB1 and NFKBIA gene are associated with coronary artery disease (CAD) in a Chinese Han population. Methods: A total of 1140 Han CAD patients and 1156 Han control subjects were genotyped for 4 single-nucleotide polymorphisms (SNPs) in the promoter region of NFKBIA gene (rs3138053, rs2233406, rs2233409) and NFKB1 gene (-94 ins/del ATTG, rs28362491) by using the TaqMan SNP genotyping assays, and then NFKBIA haplotype blocks were reconstructed according to our genotyping data. Results: For total, men, and women, the distribution of genotypes, alleles of rs3138053, rs2233406, rs2233409 and haplotype polymorphisms showed no significant difference between CAD cases and controls. None of the studied NFKBIA SNPs were associated with CAD. For total, men, and women, there was significant difference in the distribution of the genotypes (P=0.001, P=0.024, P= 0.022) and alleles (P=0.001, P=0.012, P=0.031) of rs28362491 in CAD cases and controls. For total, men, and women, the rs28362491 was associated with increased risk of CAD in a recessive model after adjustment for covariates (OR=1.505, 95% CI 1.190 to 1.903, P=0.001; OR=1.469, 95% CI 1.082-1.993, P=0.014; OR=1.622, 95% CI 1.118 to 2.352, P=0.011, respectively). Conclusions: In our study, the -94 ins/del ATTG polymorphism in NFKB1 promoter is associated with CAD susceptibility in Chinese Han population, providing a new insight into the genetics of CAD in Chinese Han population.
Keywords: Coronary artery disease, NFKB1 and NFKBIA polymorphism, Chinese Han population
Introduction
The prevalence of coronary artery disease (CAD) has been steadily increasing in China during the past several years. CAD and its main complications are the major causes of morbidity and mortality in China. Epidemiological studies have identified many risk factors for CAD, including age, gender, hypertension, diabetes, smoking, family history, dyslipidemia, and sedentary lifestyle, etc. However, these conventional risk factors can only explain minority of the etiology of CAD, indicating that genetic variation play a role in the inter-individual variation in CAD.
Inflammation is involved in the development and progression of atherosclerosis. Recent studies have identified several genetic polymorphisms in genes encoding pro- and anti-inflammatory cytokines have been associated with atherosclerotic cardiovascular disease [1-4]. The nuclear factor kappa B (NF-κB) family of transcription factors is the major mediator of inflammation, including Rel-A (p65), Rel-B, c-Rel, NF-κB1 (p50), NF-κB2 (p52) [5-7]. NF-κB functions as different complexes of either homodimers or heterodimers, with p65/p50 heterodimer being the most abundant complex and primary inflammatory mediator [6]. NF-κB regulated about 200 target genes, most of them are implicated in inflammation.
In humans, NFkB1 gene, located on chromosome 4q24, encodes p50 protein. P50 has anti-inflammatory properties in the p50 homodimer (p50/p50) by stimulating transcription of anti-inflammatory cytokines like IL-10, while it has proinflammatory effects as part of the p65/p50 heterodimer by increasing transcription of proinflammatory cytokines like TNF and IL-12. The genetic mutation in the promoter region (NFKB1-94 ins/del ATTG) affect the synthesis of p50. Deletion of one ATTG repeat in the promoter region of NFKB1 gene results in lower transcript levels and less p50 synthesis.
In resting cells, NF-κB is sequestered in the cytoplasm by binding to inhibitory proteins of κB family (IκBs), which prevent NF-κB nuclear localization, activation, and inhibit nuclear accumulation. IκBα, encoded by the NFKBIA, is the most abundant and critical inhibitor of NF-κB [8,9]. Upon stimulation, IκBα is degraded, thus unmasking the NF-κB nuclear localization sequence, then freed NF-κB translocate into the nucleus, where it initiates the transcription of proinflammatory genes. In recent years, many studies have demonstrated that polymorphisms in the promoter region of NFKB1 and NFKBIA gene (NFKB1-94 ins/del ATTG, rs28362491; NFKBIA -881A/G, rs3138053; -826C/T, rs2233406; -297C/T, rs2233409) were associated with many inflammatory diseases risk, such as Grave’s disease, Behcet’s disease, systemic lupus erythematosus, and Crohn’s disease [10-13].
Considering the important role played by NF-κB in regulating inflammation response, it raises hypothesis that genetic variation in the promoter region of NFKB1 and NFKBIA gene could be related to the CAD susceptibility. Therefore, the aim of this study was to investigate whether the functional promoter polymorphisms in NFKB1 and NFKBIA gene are associated with CAD in a Chinese Han population.
Methods
Study design and population
This study was a case-control association study conducted at the First Affiliated Hospital of Xinjiang Medical University. A total of 1140 Han patients aged ≥18 diagnosed with CAD at the First Affiliated Hospital of Xinjiang Medical University between January 2008 and December 2014 were enrolled, including 520 women and 620 men. CAD was defined as the presence of at least one significant coronary artery stenosis of more than 50% luminal diameter on coronary angiography. Exclusion criteria were patients who have incomplete inhospital data collection; patients with concomitant congenital heart disease, valvular heart disease, and/or non-ischaemic cardiomyopathy.
We randomly sampled 1156 ethnic and geographic group-matched participants for the control group. All control subjects were obtained from the Cardiovascular Risk Survey (CRS) study and represented a selection of healthy subjects who had previously provided peripheral blood for the extraction of DNA. CRS study has previously been described in detail [13,14]. Control subjects were exposed to the same risk profile of CAD, some have hypertension, and/or DM, and/or hyperlipidemia. Exclusion criteria were: a history of CAD; electrocardiographic signs of CAD; regional wall motion abnormalities; relevant valvular abnormalities in echocardiograms and/or carotid atherogenesis [15].
The present study complies with the Declaration of Helsinki. This study protocol was approved by the Ethics Committee of the First Affiliated Hospital of Xinjiang Medical University, and all participants provided written informed consent to participate in genetic research.
Definition of cardiovascular risk factors
Hypertension was defined as blood pressure levels of 140/90 mmHg or higher or use of antihypertensive medications. Participants were considered diabetic if they reported a physician diagnosis of diabetes or were taking anti-diabetic medication or had fasting/non-fasting glucose ≥126 mg/dL/≥200 mg/dL. Weight and height were used to calculate body mass index (BMI) as weight in kilograms divided by height in meters squared. Persons reporting regular tobacco use in the previous 6 months were considered as current smokers.
Biochemical analysis and DNA extraction
Fasting peripheral blood samples were obtained from all participants following admission for biochemical analysis. Total cholesterol (TC), Low density lipoprotein (LDL), High density lipoprotein (HDL), and Triglycerides (TG) were measured using standard enzymatic methods in the Central Laboratory of the First Affiliated Hospital of Xinjiang Medical University. Genomic DNA was extracted from peripheral vein blood leukocytes using a whole blood genome extraction kit (TIANGEN Bioteck cooperation, Beijing, China) following the manufacturer’s instructions. The DNA samples were shipped to the core laboratory for storage at -80°C until analysis.
Genotyping
All participants were typed for NFKB1 and NFKBIA gene polymorphisms (SNP rs28362491, SNP rs3138053; rs2233406; rs2233409). Genotyping was carried out using the TaqMan® SNP Genotyping Assay (Applied Biosystems). The primers and probes used in the TaqMan® SNP Genotyping Assays (ABI) were chosen based on information at the ABI website (http://myscience.appliedbiosystems.com). The endpoint was read after PCR amplification using an Applied Biosystems 7900HT Sequence Detection system. Genotyping quality was tested by including 6 blinded duplicate samples in each 96-well assay. The average agreement rate was >99%.
Statistical analysis
All statistical analyses were performed with the SPSS for Windows (version 17.0 SPSS Inc. Chicago, IL), a 2-sided P<0.05 was considered to indicate statistical significance. Data were presented as numbers and frequencies for categorical variables and as means ± SD for continuous variables. Baseline characteristics were compared with the chi-square test for categorical variables. Continuous variables were compared using the Student t test between groups. Hardy-Weinberg equilibrium (HWE), genotype and allele frequencies between CAD cases and control subjects were assessed by Chi-square test. Based on the genotype data of the genetic variations, we performed linkage disequilibrium (LD) analysis and haplotype-based case-control analysis, using the software SHEsis (http://analysis.bio-x.cn/SHEsisMain.htm) [16]. In the haplotype-based case-control analysis , we selected the haplotypes on the basis of a frequency >1% among all participants. The odds ratios (ORs) of CAD and 95% confidence intervals (CIs) were calculated to assess the risk associated with each SNP and major risk factors by means of logistic regression models in which CAD was considered as the dependent variable and the SNP genotype as the independent variables according to a recessive model.
Results
Overall, a total of 1140 CAD cases (mean age 59.95±8.77 and 54.4% men) and 1156 CAD-negative controls (mean age 59.38±8.73 and 55.0% men) were included in the present study.
Clinical characteristics of all participants at baseline are presented in Table 1 according to CAD status. For total participants, men, and women, BMI, the plasma concentrations of TC, LDL, TG, and fasting blood glucose, together with the prevalence of hypertension and diabetes were significantly higher in CAD cases than in controls. In addition, age was similar between CAD cases and controls. For total and women participants, the plasma concentrations of HDL were significantly lower in CAD cases than in controls. For men participants, the prevalence of smoking was significantly higher in CAD cases than in controls.
Table 1.
Basic clinical characteristics of study population according to CAD status
| Total | Men | Women | |||||||
|---|---|---|---|---|---|---|---|---|---|
|
|
|||||||||
| CAD | Controls | P value | CAD | Controls | P value | CAD | Controls | P value | |
| Number (n) | 1140 | 1156 | 620 | 636 | 520 | 520 | |||
| Age (years) | 59.95±8.77 | 59.38±8.73 | 0.119 | 58.13±9.55 | 57.65±9.37 | 0.371 | 62.13±7.17 | 61.50±7.35 | 0.164 |
| Sex (male, %) | 620 (54.4%) | 636 (55.0%) | 0.769 | ||||||
| BMI (kg/m2) | 25.78±2.22 | 25.46±2.41 | 0.001* | 26.16±1.66 | 25.90±1.88 | 0.009* | 25.32±2.68 | 24.92±2.84 | 0.019* |
| TG (mmol/L) | 1.58±0.51 | 1.51±0.53 | 0.001* | 1.60±0.55 | 1.52±0.54 | 0.014* | 1.56±0.45 | 1.49±0.52 | 0.012* |
| TC (mmol/L) | 4.60±0.74 | 4.40±0.64 | <0.001* | 4.54±0.74 | 4.40±0.66 | <0.001* | 4.68±0.73 | 4.39±0.61 | <0.001* |
| HDL (mmol/L) | 1.04±0.20 | 1.06±0.22 | 0.006* | 1.03±0.21 | 1.05±0.19 | 0.140 | 1.05±0.20 | 1.08±0.24 | 0.015* |
| LCL (mmol/L) | 2.50±0.62 | 2.32±0.53 | <0.001* | 2.51±0.63 | 2.33±0.54 | <0.001* | 2.49±0.62 | 2.31±0.50 | <0.001* |
| Glu (mmol/L) | 5.51±1.52 | 5.25±1.50 | <0.001* | 5.49±1.51 | 5.25±1.49 | 0.004* | 5.53±1.53 | 5.25±1.52 | 0.003* |
| EH (%) | 52.5 | 37.5 | <0.001* | 48.5 | 38.2 | <0.001* | 57.1 | 36.7 | <0.001* |
| DM (%) | 27.8 | 17.4 | <0.001* | 29.5 | 18.2 | <0.001* | 25.8 | 16.3 | <0.001* |
| Smoke (%) | 33.3 | 27.7 | 0.004 | 61.3 | 50.3 | <0.001* | |||
The alleles and genotypes frequencies of promoter polymorphisms in NFKBIA and NFKB1 gene (rs28362491, rs3138053, rs2233406, rs2233409) between CAD cases and controls are shown in Table 2. All analyzed SNPs were in HWE (P>0.05). Similar distribution of rs3138053, rs2233406, rs2233409 polymorphisms was observed in CAD cases and controls for total, men, and women participants (all P>0.05). We further explored haplotypes to evaluate the combined effect of the studied NFKBIA polymorphisms on CAD susceptibility. Table 3 represents the haplotype analysis of NFKBIA polymorphisms. A total of five haplotypes with frequencies of >1% were observed among all participants. There was no significant difference in the distribution of rs3138053, rs2233406, rs2233409 haplotype frequencies between CAD patients and controls. We did not detect a significant main effect of any haplotypes of rs3138053, rs2233406, and rs2233409 combined on the risk of developing CAD. The LD pattern showed SNP rs3138053 is in strong LD (D’=0.854, r2=+0.709) with SNP rs2233406, and in moderate LD (D’=0.652, r2=+0.357) with SNP rs2233409. However, a different allele and genotype distribution of the rs28362491 polymorphism in CAD cases and controls was observed. For total participants, the distribution of alleles (P=0.001), genotypes (P=0.001) of rs28362491, and the recessive model (P<0.001) differed significantly between CAD cases and controls. When we analyzed the distribution of rs28362491 genotypes separately in men and women (CAD cases and controls), a different distribution of alleles (P=0.012, P=0.001, respectively), genotypes (P=0.024, P=0.022, respectively), and the recessive model (P=0.010, P=0.008, respectively) was observed in both of male and female group.
Table 2.
Genotype and allele distributions of NFKBIA and NFKB1 polymorphisms in CAD cases and controls
| Total | Men | Women | |||||||
|---|---|---|---|---|---|---|---|---|---|
|
|
|
|
|||||||
| Variants | CAD | Controls | P value | CAD | Controls | P value | CAD | Controls | P value |
| rs3138053 | |||||||||
| Genotyping | |||||||||
| AA | 857 (75.2%) | 891 (77.1%) | 0.343 | 466 (75.2%) | 491 (77.2%) | 0.672 | 391 (75.2%) | 400 (76.9%) | 0.411 |
| AG | 256 (22.5%) | 246 (21.3%) | 141 (22.7%) | 134 (21.1%) | 115 (22.1%) | 112 (21.5%) | |||
| GG | 27 (2.4%) | 19 (1.6%) | 13 (2.1%) | 11 (1.7%) | 14 (2.7%) | 8 (1.5%) | |||
| Dominant model | |||||||||
| AA | 857 (75.2%) | 891 (77.1%) | 0.304 | 466 (75.2%) | 491 (77.2%) | 0.427 | 391 (75.2%) | 400 (76.9%) | 0.561 |
| GG+AG | 283 (24.8%) | 265 (22.9%) | 154 (24.8%) | 145 (22.8%) | 129 (24.8%) | 120 (23.1%) | |||
| Recessive model | |||||||||
| GG | 27 (2.4%) | 19 (1.6%) | 0.235 | 13 (2.1%) | 11 (1.7%) | 0.684 | 14 (2.7%) | 8 (1.5%) | 0.205 |
| AG+AA | 1113 (97.6%) | 1137 (98.4%) | 607 (97.8%) | 625 (98.3%) | 506 (97.3%) | 512 (98.5%) | |||
| Allele | |||||||||
| A | 1970 (86.4%) | 2028 (87.7%) | 0.185 | 1073 (86.5%) | 1116 (87.7%) | 0.368 | 897 (86.3%) | 912 (87.7%) | 0.329 |
| G | 310 (13.6%) | 284 (12.3%) | 167 (13.5%) | 156 (12.3%) | 143 (13.7%) | 128 (12.3%) | |||
| rs2233406 | |||||||||
| Genotyping | |||||||||
| CC | 868 (76.1%) | 894 (77.3%) | 0.502 | 480 (77.4%) | 498 (78.3%) | 0.667 | 388 (74.6%) | 396 (76.2%) | 0.735 |
| CT | 246 (21.6%) | 243 (21.0%) | 126 (20.3%) | 128 (20.1%) | 120 (23.1%) | 115 (22.1%) | |||
| TT | 26 (2.3%) | 19 (1.6%) | 14 (2.3%) | 10 (1.6%) | 12 (2.3%) | 9 (1.7%) | |||
| Dominant model | |||||||||
| CC | 868 (76.1%) | 894 (77.3%) | 0.521 | 480 (77.4%) | 498 (78.3%) | 0.734 | 388 (74.6%) | 396 (76.2%) | 0.614 |
| CT+TT | 272 (23.9%) | 262 (22.7%) | 140 (22.6%) | 138 (21.7%) | 132 (25.4%) | 124 (23.8%) | |||
| Recessive model | |||||||||
| TT | 26 (2.3%) | 19 (1.6%) | 0.294 | 14 (2.3%) | 10 (1.6%) | 0.415 | 12 (2.3%) | 9 (1.7%) | 0.660 |
| CT+CC | 1114 (97.7%) | 1137 (98.4%) | 606 (97.7%) | 626 (98.4%) | 508 (97.7%) | 511 (98.3%) | |||
| Allele | |||||||||
| C | 1982 (86.9%) | 2031 (87.8%) | 0.350 | 1086 (87.6%) | 1124 (88.4%) | 0.546 | 896 (86.2%) | 907 (87.2%) | 0.478 |
| T | 298 (13.1%) | 281 (12.2%) | 154 (12.4%) | 148 (11.6%) | 144 (13.8%) | 133 (12.8%) | |||
| rs2233409 | |||||||||
| CC | 891 (78.2%) | 924 (79.9%) | 0.490 | 490 (79.0%) | 503 (79.1%) | 0.882 | 401 (77.1%) | 421 (81.0%) | 0.299 |
| CT | 226 (19.8%) | 214 (18.5%) | 118 (19.0%) | 123 (19.3%) | 108 (20.8%) | 91 (17.5%) | |||
| TT | 23 (2.0%) | 18 (1.6%) | 12 (2.0%) | 10 (1.6%) | 11 (2.1%) | 8 (1.5%) | |||
| Dominant model | |||||||||
| CC | 891 (78.2%) | 924 (79.9%) | 0.305 | 490 (79.0%) | 503 (79.1%) | 0.981 | 401 (77.1%) | 421 (81.0%) | 0.148 |
| CT+TT | 249 (21.8%) | 232 (21.1%) | 130 (21.0%) | 133 (20.8%) | 119 (22.9%) | 99 (29.0%) | |||
| Recessive model | |||||||||
| TT | 23 (2.0%) | 18 (1.6%) | 0.434 | 12 (2.0%) | 10 (1.6%) | 0.672 | 11 (2.1%) | 8 (1.5%) | 0.645 |
| CC+CT | 1117 (98.0%) | 1138 (98.4%) | 608 (98.0%) | 626 (98.4%) | 509 (97.9%) | 512 (98.5%) | |||
| Allele | |||||||||
| C | 2008 (88.1%) | 2062 (89.2%) | 0.233 | 1098 (88.5%) | 1129 (88.8%) | 0.869 | 910 (87.5%) | 933 (89.7%) | 0.112 |
| T | 272 (11.9%) | 250 (10.8%) | 142 (11.5%) | 143 (11.2%) | 130 (12.5%) | 107 (10.3%) | |||
| rs28362491 | |||||||||
| Genotyping | |||||||||
| II | 392 (34.4%) | 441 (38.1%) | 0.001* | 209 (33.7%) | 241 (37.9%) | 0.024* | 183 (35.2%) | 200 (35.2%) | 0.022* |
| ID | 530 (46.5%) | 561 (48.5%) | 283 (45.6%) | 300 (47.2%) | 247 (47.5%) | 261 (47.5%) | |||
| DD | 218 (19.1%) | 154 (13.3%) | 128 (20.6%) | 95 (14.9%) | 90 (17.3%) | 59 (17.3%) | |||
| Dominant model | |||||||||
| II | 392 (34.4%) | 441 (38.1%) | 0.062 | 209 (33.7%) | 241 (37.9%) | 0.126 | 183 (35.2%) | 200 (38.5%) | 0.304 |
| ID+DD | 748 (65.6%) | 715 (61.9%) | 411 (66.3%) | 395 (62.1%) | 337 (64.8%) | 320 (61.5%) | |||
| Recessive model | |||||||||
| DD | 218 (19.1%) | 154 (13.3%) | <0.001* | 128 (20.6%) | 95 (14.9%) | 0.010* | 90 (17.3%) | 59 (11.3%) | 0.008* |
| II+ID | 922 (80.9%) | 1002 (86.7%) | 492 (79.4%) | 541 (85.1%) | 430 (82.7%) | 461 (88.7%) | |||
| Allele | |||||||||
| I | 1314 (54.8%) | 1443 (62.4%) | 0.001* | 701 (56.5%) | 782 (61.5%) | 0.012* | 613 (58.9%) | 661 (63.6%) | 0.031* |
| D | 966 (45.2%) | 869 (37.6%) | 539 (43.5%) | 490 (38.5%) | 427 (41.1%) | 379 (36.4%) | |||
CAD, cornonary artery disease. The P value of genotype was calculated by Fisher’s exact test.
P<0.05.
Table 3.
Distribution frequency of the NFKBIA haplotype in CAD cases and controls
| Variable | Controls (N=1156) | CAD (N=1140) | OR (95% CI) | P value | ||
|---|---|---|---|---|---|---|
|
|
||||||
| n (%) | n (%) | |||||
| 881A/G | 826C/T | 297C/T | ||||
| A | C | C | 82.7 | 82.4 | 1.021 [0.873-1.194] | 0.796 |
| A | C | T | 3.3 | 2.5 | 0.759 [0.536-1.076] | 0.121 |
| G | C | C | 1.3 | 1.3 | 0.949 [0.569-1.582] | 0.840 |
| G | T | C | 3.7 | 3.7 | 0.991 [0.729-1.347] | 0.954 |
| G | T | T | 6.8 | 7.9 | 1.192 [0.954-1.490] | 0.121 |
Univariate and multivariate logistic regression analysis of the association between CAD and multiple parameters are presented in Table 4. The rs28362491 polymorphism was associated with the risk of developing CAD among all participants in a recessive model (OR=1.505, 95% CI 1.190 to 1.903, P=0.001) after adjustment for potential confounders (BMI, smoking, hypertension, diabetes, TC, LDL, HDL, and TG). We further stratified our overall group of subjects based on gender and identified rs28362491 polymorphism was a significant risk factor in both male and female group. In the male group, individuals with NFKB1-94 del/del genotype had 1.469-fold increased risk of developing CAD than individuals with ins/ins + ins/del genotypes (OR=1.469, 95% CI 1.082 to 1.993, P=0.014). Hypertension, smoking, BMI, diabetes, and LDL were also independent predictors of CAD in male group. In the female group, individuals with NFKB1-94 del/del genotype had 1.622-fold increased risk of developing CAD than individuals with ins/ins + ins/del genotypes (OR=1.622, 95% CI 1.118 to 2.352, P=0.011). On the other hand, no significant differences were observed in the association between rs3138053, rs2233406, and rs2233409 polymorphisms and CAD among total participants, men, and women.
Table 4.
Multiple logistic regression analysis for CAD patients and controls (rs28362491)
| Total | Men | Women | |||||||
|---|---|---|---|---|---|---|---|---|---|
|
|
|
|
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| OR | 95% CI | P | OR | 95% CI | P | OR | 95% CI | P | |
| rs28362491 (DD vs II+ID ) | 1.505 | 1.190-1.903 | 0.001* | 1.469 | 1.082-1.993 | 0.014* | 1.622 | 1.118-2.352 | 0.011* |
| BMI | 1.039 | 1.001-1.079 | 0.047* | 1.090 | 1.021-1.164 | 0.010 | 1.024 | 0.976-1.074 | 0.333 |
| Smoking | 1.259 | 1.044-1.517 | 0.016* | 1.543 | 1.223-1.946 | <0.001* | |||
| EH | 1.772 | 1.491-2.107 | <0.001* | 1.475 | 1.168-1.862 | 0.001* | 2.202 | 1.693-2.865 | <0.001* |
| DM | 2.007 | 1.460-2.760 | <0.001* | 2.269 | 1.498-3.436 | <0.001* | 1.715 | 1.034-2.845 | 0.037 |
| TG | 1.092 | 0.922-1.295 | 0.308 | 1.124 | 0.904-1.398 | 0.293 | 1.047 | 0.794-1.379 | 0.745 |
| Glu | 0.940 | 0.862-1.026 | 0.168 | 0.919 | 0.818-1.032 | 0.153 | 0.957 | 0.835-1.097 | 0.525 |
| TC | 1.356 | 1.186-1.549 | <0.001* | 1.158 | .972-1.380 | 0.101 | 1.653 | 1.340-2.039 | <0.001* |
| HDL | 0.727 | 0.481-1.100 | 0.131 | 0.841 | .471-1.500 | 0.557 | 0.633 | 0.347-1.157 | 0.137 |
| LDL | 1.481 | 1.265-1.734 | <0.001* | 1.553 | 1.260-1.914 | <0.001* | 1.433 | 1.119-1.835 | 0.004* |
BMI, body mass index; TG, triglycerides; TC, total cholesterol; HDL, high density lipoprotein; LDL, low density lipoprotein; Glu, glucose; EH, essential hypertension; DM, diabetes mellitus; CAD, coronary artery disease.
Discussion
The most common chronic illness in adults is CAD. Despite the dramatic advances in pharmacological and interventional cardiology, CAD and its main complications remain the major cause of mortality worldwide. CAD is a chronic inflammatory disease resulting from the complex gene-environment interactions. Studies in CAD have demonstrated genetic factors modulate the risk of CAD [17-20]. Because genotypes are not confounded by environmental exposures, identification of the genetic component involved in the atherogenic pathways will be helpful to define real risk factors of CAD and establish therapeutic targets aimed at preventing or treating CAD.
In the present study, we investigated the association between promoter polymorphisms in NFKB1 and NFKBIA gene and CAD risk in a Chinese Han population. NFKB1 and NFKBIA genes were selected based on their crucial role in the inflammatory responses. We have identified that homozygous variant carriage of NFKB1-94 ins/del ATTG polymorphism was associated with increased risk of CAD in Chinese Han population. However, common genetic variants in the promoter of NFKBIA (-881A/G, -826C/T, and -297C/T) do not contribute to the susceptibility to CAD in Chinese Han population.
It is well known that inflammation plays an important role in the development and progression of CAD. NF-κB is an established major transcription regulator of inflammatory responses and regulates the transcription of some 200 target genes. Many of them are involved in inflammation, such as adhesion molecules, interleukins, and chemokines. The role of NF-κB in the inflammation is determined by its subunits. The p50 homodimer has anti-inflammatory ability by inhibiting the transcription of pro-inflammatory cytokines like TNF-α and IL-12, and stimulating the transcription of the anti-inflammatory cytokine IL10, while p65/p50 heterodimer has proinflammatory ability by stimulating the transcription of the pro-inflammatory cytokines.
NFKBIA gene encodes IκBα, which is an important inhibitor of NF-κB and keeps the NF-κB pool mainly in the cytoplasm by inhibiting its nuclear localization and association with DNA. In response to specific stimuli, IκBα is ubiquitinated and degraded, allowing NF-κB to migrate to the nucleus and initiate transcription of its target genes. Genetic variation in NFKBIA has been reported to be associated with a variety of human diseases including inflammatory diseases and cancer. In the present study, three polymorphisms (NFKBIA-881A/G, -826C/T, and -297C/T) located in the promoter region of NFKBIA gene were selected based on their potential functional effects. The -881A/G, -826C/T, and -297C/T are respectively located at putative binding sites for retinoic acid-related orphan receptorα (RORα), CCAAT/enhancer binding protein (C/EBP), and octamer binding transcription factor-1 (Oct-1) [21,22], which may regulate IκBα expression, and hence influence NF-κB activation. Previous studies have shown that these three promoter variants are associated with many inflammatory diseases. A study performed by Balood M et al. [23] reported that NFKBIA-881 AG genotype and -826 TT genotype respectively had a 3.06-fold, 7.08-fold increased risk for multiple sclerosis in Iranian population. Li RN et al. [24] demonstrated that NFKBIA-826 T allele was associated with a significant increased risk of developing rheumatic arthritis in Taiwanese population. Another study performed by Ali S et al. [25] reported that NFKBIA-826 T allele and -297 T allele were significantly associated with bronchopulmonary dysplasia severity in preterm infants, and -826 T allele was also associated with an increased risk for severe respiratory syncytial virus bronchiolitis in preterm infants. In addition, it showed that the genetic variants in the promoter of NFKBIA (-881A/G, -826C/T, and -297C/T) are indeed associated with alterations in promoter driven protein expression, allele-specific and total NFKBIA gene expression, and IκBα protein expression, which provides a mechanical link between genetic variants in the promoter of NFKBIA and susceptibility to childhood respiratory syncytial virus bronchiolitis, and bronchopulmonary dysplasia. To date, only one study investigated the association between NFKBIA promoter polymorphisms and CAD risk in a Turkey population [26], it concluded that NFKBIA-826 TT genotype, together with G-881T-826T-297, A-881T-826T-297 and G881T-826C-297 haplotypes were associated with increased risk of CAD in Turkey population. These reported genetic association studies showing the association between polymorphisms in NFKBIA gene and increased risk of inflammatory diseases were the motivation for us to investigate the impact of these polymorphisms on CAD risk in Chinese Han population, considering the higher prevalence of CAD in China. In the present study, none of the three promoter polymorphisms within NFKBIA gene that we studied showed significant associations with CAD, and we did not observe any association between haplotype polymorphisms of NFKBIA-881A/G, -826C/T, and -297C/T and increased risk of CAD. It is thus reasonable to speculate that the absence of association between the studied NFKBIA SNPs and CAD risk may exclude these SNPs as the underlying mechanism of CAD in Chinese Han population. Our result is inconsistent with previous studies. The lack of replication for genetic association between NFKBIA-881A/G, -826C/T, and -297C/T polymorphisms and CAD risk found in the present study could be attributed to the very low variant allele frequency in the Chinese Han population, reflecting the different genetic background of Chinese Han population from other ethnic groups across different studies.
NFKB1 gene encodes the p50/p105 subunit of NF-κB. NFKB1-94 ins/del ATTG polymorphism is a four base insertion/deletion variant located between two putative key promoter regulatory elements in NFKB1 gene. Deletion of ATTG repeat in the promoter region of NFKB1 gene destroys a transcription factor binding site, leading to lower promoter transcriptional activity and less p50 biosynthesis. Recently, increasing attention has been directed toward the role of NFKB1-94 ins/del ATTG polymorphism as a risk factor in the etiology of cardiovascular disease. Vogel U et al. [27] demonstrated that carriers of the del-allele of NFKB1-94 ins/del ATTG are at higher risk of coronary heart disease (CHD) in three independent prospective studies of generally healthy Caucasians. et al. [28] demonstrated rheumatoid arthritis patients carrying the NFKB1 del/del genotype had a 1.76-fold increased risk for CAD in Spain population. In the present work, we assessed for the first time the potential role of NFKB1-94 ins/del ATTG polymorphism in the risk of CAD in a large cohort of Chinese Han population. We observed that homozygous variant carriage of NFKB1-94 ins/del ATTG polymorphism is associated with the risk of developing CAD in Chinese Han population. This association was remained after adjusting for known traditional cardiovascular risk factors, indicating the NFKB1-94 ins/del ATTG polymorphism may affect the risk of CAD through pathways beyond established risk factors. This association was also not limited by gender in our study. Because when we analyze the distribution of NFKB1-94 ins/del ATTG genotypes separately in women and men (patients and controls), we observed that NFKB1 del/del genotype was an independent risk factor of CAD in both of male and female group. The association of NFKB1 polymorphism and CAD may be related to the fact that the variant genotype containing the deletion has been associated with low expression of p50. As low p50 levels intuitively affect the concentration of p50/p50 more than the concentration of p50/p65, thus NFKB1-94 del/del genotype may contribute to the pathogenesis of CAD by associating with a higher pro-inflammatory response.
Our study has several limitations. First, this is a single-center experience representing a relatively small numbers of patients. Second, our study was only restricted to Chinese Han population, whether our findings can be extended to other races remains to be determined. Third, future studies are needed to examine the impact of NFKB1-94 ins/del ATTG genotype on long-term clinical outcomes in patients with CAD in Chinese Han population.
In conclusion, our study could not validate any association between studied promoter polymorphisms within NFKBIA gene and susceptibility to CAD, suggesting that polymorphisms in NFKBIA gene may not be involved in the pathogenesis of CAD in Chinese Han population. However, we identified an association between the NFKB1-94 ins/del ATTG polymorphism and CAD risk in Chinese Han population. The NFKB1 del/del genotype was independently associated with an increased risk of CAD. Further studies are needed to confirm our results in similar and different populations.
Acknowledgements
This work was supported by the Program of Natural Science Fund of China (serial number: 81160042). The authors are grateful to the study participants.
Disclosure of conflict of interest
None.
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