Literature DB >> 28181534

Genomic Variant in IL-37 Confers A Significant Risk of Coronary Artery Disease.

Dan Yin1,2, Duraid Hamied Naji1, Yunlong Xia3, Sisi Li1, Ying Bai4, Guiqing Jiang1, Yuanyuan Zhao1, Xiaojing Wang1, Yufeng Huang1, Shanshan Chen5, Jingjing Fa1, Chengcheng Tan1, Mengchen Zhou1, Yingchao Zhou1, Longfei Wang1, Ying Liu3, Feifei Chen3, Jingqiu Liu3, Qiuyun Chen6,7, Xin Tu1, Chengqi Xu1, Qing K Wang1,6,7.   

Abstract

The interleukin 1 family plays an important role in the immune and inflammatory responses. Coronary artery disease (CAD) is a chronic inflammatory disease. However, the genetic association between IL-37, the seventh member of the IL-1 family, and CAD is unknown. Here we show that a single nucleotide polymorphism in the IL-37 gene (rs3811047) confers a significant risk of CAD. We have performed an association analysis between rs3811047 and CAD in two independent populations with 2,501 patients and 3,116 controls from China. Quantitative RT-PCR analysis has been performed to determine if the IL-37 expression level is influenced by rs3811047. We show that the minor allele A of rs3811047 is significantly associated with CAD in two independent populations under a recessive model (Padj = 5.51 × 10-3/OR = 1.56 in the GeneID Northernern population and Padj = 1.23 × 10-3/OR = 1.45 in the GeneID Central population). The association became more significant in the combined population (Padj = 9.70 × 10-6/OR = 1.47). Moreover, the association remains significant in a CAD case control population matched for age and sex. Allele A of rs3811047 shows significant association with a decreased mRNA expression level of IL-37 (n = 168, P = 3.78 × 10-4). These data suggest that IL37 is a new susceptibility gene for CAD, which provides a potential target for the prevention and treatment of CAD.

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Year:  2017        PMID: 28181534      PMCID: PMC5299598          DOI: 10.1038/srep42175

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


Coronary artery disease (CAD) is the leading cause of morbidity and mortality in the world12. Epidemiological and family studies revealed that CAD has a strong genetic component3. The heritability of CAD was shown to be from 40% to 60%4. Understanding the genetic risk factors of CAD or atherosclerosis (the cause of CAD)5 may provide important information on the biological pathways of CAD pathogenesis. Recently, large-scale genome-wide association studies (GWAS) have identified more than 50 risk loci for CAD and provided new information to the biological pathways that were not associated with traditional risk factors of CAD before6789101112. Although genome-wide approaches have provided novel insights into the genetic basis of CAD etiology, the GWAS risk loci have the modest effects and explain approximately 10% of CAD heritability9. Furthermore, GWAS may miss some specific candidate genetic variants13. Therefore, the genetic architecture of CAD remains to be further defined. Cytokines and chronic inflammation play an important role in the pathogenesis of atherosclerosis and CAD14. Recent studies have found that many variants of genes encoding cytokines, such as IL-6, IL-10, IL-16, IL-17A, IL-18 and IL-33151617181920, are genetically associated with atherosclerosis and CAD in humans. Evidence from animal studies has demonstrated that many cytokines regulated by interleukins participate in the pathological inflammatory processes involved in atherosclerosis21. Interleukin-37 (IL-37/IL-1F7) is a member of the IL-1 cytokine family22, which broadly modulates inflammatory and immune responses23. IL-37 has a caspase-1 site and can be processed by caspase-124. After caspase-1 processing, IL-37 is translocated to the nucleus and reduces the production of pro-inflammatory cytokines in murine RAW cells following LPS stimulation25. In 2010, Nold et al. observed that IL-37 was an anti-inflammatory cytokine, affected a broad spectrum of pro-inflammatory cytokines, and suppressed immune responses26. Subsequently, McNamee et al. observed that IL-37 played a protective and anti-inflammatory role by decreasing recruitment of leukocytes into the inflamed tissue. Furthermore, Ge et al. reported that SNP rs3811047, a functional tagSNP of IL-37, was associated with ankylosing spondylitis, which is an idiopathic inflammatory disease affecting the axial and/or peripheral skeleton with an increased risk of atherosclerosis and cardiovascular mortality and morbidity2728. Based on these data, we hypothesized that IL-37 may play a role in the pathogenesis of CAD and the functional tagSNP of IL-37, rs3811047, may be genetically associated with CAD. In the present study, we genotyped SNP rs3811047 in IL-37 in two independent case control populations of CAD, and performed an association study to test whether the genetic variant in IL37 confers a risk to CAD.

Results

Characteristics of study populations and power analysis

The demographic and clinical characteristics of two independent CAD populations used for case control analysis, including the GeneID Northern population and the GeneID Central population, are shown in Table 1. The GeneID Northern population included 1,038 CAD patients and 1,076 controls. The mean age was 62.01 ± 12.70 in cases and 50.52 ± 16.71 in controls. The proportion of males was 65.51% in cases and 69.33% in controls. The GeneID Central population enrolled 1,463 cases and 2,040 controls. The mean age was 64.21 ± 12.44 in cases and 49.02 ± 13.88 in controls, respectively. The proportion of males was 65.21% and 61.76% in cases and controls, respectively. The percentage of males in cases was higher than in controls because the male gender is a well-known risk factor for the development of CAD. The average age of the control populations is younger than that in the case populations because most controls are study subjects who had free physical examinations offered to active working individuals by their respective working institutions. The differences of age and sex between cases and controls were adjusted in later statistical analysis. To further reduce the confounding of age and sex, we generated a case control population by randomly matching each individual case to a control based on age and sex. The data on demographic and clinical characteristics of the matched case control population are shown in Table 1.
Table 1

Demographic and clinical characteristics of study populations.

CharacteristicsGeneID Northern Population
GeneID Central Population
GeneID Combined Population
Sex- and Age-Matched Population
CADControlCADControlCADControlCADControl
N1,0381,0761,4632,0402,5013,1161,5961,596
Age (years)62.01 ± 12.70***50.52 ± 16.7164.21 ± 12.44***49.02 ± 13.8863.30 ± 13.25***49.54 ± 15.5860.05 ± 11.3560.05 ± 11.35
Male N (%)680 (65.51)746 (69.33)954 (65.21)**1260 (61.76)1,634 (65.33)2,006 (64.38)1,049 (65.73)1,049 (65.73)
Hypertension N (%)594 (57.23)***202 (18.77)1007(68.83)***187 (9.17)1601 (64.01)***389 (12.48)853 (53.45)208 (13.03)
Diabetes N (%)145 (13.99)***84 (7.80)362 (24.74)***74 (3.60)507 (20.27)***158 (5.07)316 (19.80)108 (6.77)
Tch (mmol/L)4.40 ± 1.084.32 ± 1.164.68 ± 0.99**4.45 ± 1.114.56 ± 1.08***4.40 ± 1.074.66 ± 1.12***4.46 ± 1.20
TG (mmol/L)1.62 ± 1.11***1.44 ± 1.071.59 ± 1.14***1.46 ± 1.081.60 ± 1.12***1.45 ± 1.101.57 ± 1.18***1.44 ± 1.11
HDL-c (mmol/L)1.10 ± 0.38**1.17 ± 0.501.14 ± 0.52**1.20 ± 0.551.12 ± 0.40***1.19 ± 0.411.14 ± 0.45**1.19 ± 0.40
LDL-C (mmol/L)2.85 ± 0.81***2.62 ± 0.912.88 ± 0.84***2.62 ± 0.842.87 ± 0.82***2.62 ± 0.882.79 ± 0.76***2.52 ± 0.81

Data are shown as means ± standard deviation (SD) for quantitative variables and n (%) for binary traits.

**P < 0.01 between cases and controls for quantitative variables and percent (%) for qualitative variables.

***P < 0.001 between cases and controls for quantitative variables and percent (%) for qualitative variables.

Under the population parameter setting of the effect size or odds ratio (OR) of 1.2 for CAD29, and the minor allele frequency of 0.209 for rs3811047 (HapMap CHB data sets), our samples provide a statistical power of 70% in the Northern population, and 88% in the Central population to detect an association between rs3811047 and CAD with a type I error of 0.05. The combined population has 2,501 cases and 3,116 controls and can provide a statistical power of 98%. The matched case control population has a power of 83%. Therefore, our GeneID samples are sufficiently large to test the association between SNP rs3811047 and CAD.

Significant association between SNP rs3811047 in IL37 and CAD in two independent Chinese populations

The genotyping data for SNP rs3811047 showed no deviation from the Hardy-Weinberg equilibrium in the control populations (P > 0.05). In the GeneID Northern population, the minor allele A of rs381047 confers a significant risk of CAD (P = 6.72 × 10−4, OR = 2.45) under a recessive model (Table 2). After adjustment for covariates of age, sex, hypertension, diabetes, and lipid concentrations (TG, Tch, LDL-c and HDL-c), the significant association remained (P = 5.51 × 10−3, OR = 1.56).
Table 2

Genotypic analysis of IL-37 SNP rs3811047 with CAD in the GeneID Chinese Han population under three genetic models.

Cohort (N, Case/Control)Genotype
ModelPobsOR (95% CI)PadjOR (95% CI)
 Cases (N)Controls (N)
GeneID Central (1,503/2,040)AA7760Additive1.31 × 10−3n.a0.461.06 (0.91–1.24)
AG402607Dominant0.981.00 (0.87–1.16)0.640.98 (0.89–1.07)
GG9841373Recessive4.72 × 10–41.83 (1.30–2.59)1.23 × 10−31.45 (1.16–1.83)
GeneID Northern (998/1,076)AA4620Additive5.80 × 10−5n.a0.021.27 (1.04–1.55)
AG349310Dominant3.49 × 10−41.39 (1.16–1.66)0.111.10 (0.98–1.24)
GG643746Recessive6.72 × 10−42.45 (1.44–4.17)5.51 × 10−31.56 (1.14–2.13)
GeneID Combined (2,501/3,116)AA12380Additive9.21 × 10−6n.a1.28 × 10−21.16 (1.03–1.30)
AG751917Dominant1.97 × 10−21.14 (1.02–1.28)0.241.04 (0.97–1.11)
GG16272119Recessive2.72 × 10−61.96 (1. 47–2.61)9.70 × 10−61.47 (1.24–1.74)

P, P value from Chi square tests with 2 × 3 contingency tables without adjustment for covariates;

P, P value adjusted by covariates of sex, age, hypertension, T2D and lipid concentrations by multiple logistic regression analysis;

OR, odds ratio;

95% CI, 95% confidence interval;

Additive model = AA/AG/GG; Dominant model = AA + AG/GG; Recessive model = AA/AG + GG.

The association between SNP rs3811047 and CAD is the first time finding, therefore, we need to replicate the finding in another independent population. The replication study using the GeneID Central population showed that SNP rs3811047 was a significant risk factor for CAD (P = 4.72 × 10−4, OR = 1.83; P = 1.23 × 10−3, OR = 1.45) (Table 2) in the GeneID Central populaion, also under the recessive model (Table 2). Therefore, the association between rs3811047 and CAD was independently confirmed in the replication population. Combination of the two independent populations together resulted in a larger population with 2,501 cases and 3,116 controls. The association between SNP rs3811047 and CAD became more significant in the combined population. Minor allele A of SNP rs3811047 showed a much more significant risk of CAD (P = 9.70 × 10−6 with an OR of 1.47) under the recessive model (Table 2). We also analyzed allelic association between SNP rs3811047 and CAD in the combined population (Table 3). A significant allelic association was found between rs3811047 and CAD (P = 3.20 × 10−4, OR = 1.19). After adjustment for covariats of age, sex, hypertension, diabetes, and lipid concentrations (TG, Tch, LDL-c and HDL-c), the significant association remained (P = 0.01, OR = 1.16) (Table 3).
Table 3

Significant allelic association of IL-37 SNP rs3811047 with CAD in the GeneID Chinese Han population.

PopulationN Case/ControlFrequency of Minor Allele A (Case/Control)PhwePobsOR (95% CI)PadjOR (95% CI)
GeneID Combined2,501/3,1160.20/0.170.123.20 × 10−41.19 (1.08–1.31)0.011.16 (1.03–1.30)

P, P value from Hardy-Weinberg equilibrium tests;

P, P value from Chi square tests with 2 × 2 contingency tables without adjustment for covariates;

P, P value adjusted by covariates of sex, age, hypertension, T2D and lipid concentrations by multiple logistic regression analysis;

OR, odds ratio;

95% CI, 95% confidence interval.

The significant association between SNP rs3811047 and CAD remained significant after adjustment for age and sex, suggesting that the differences of age and the percentage of males between cases and controls did not affect the conclusion of our case control analysis. To further minimize the confounding of age and sex, we generated a case control population with each case randomly matched to a control by exact matching or one-by-one matching. Statistical analysis was then carried out to further test whether IL-37 SNP rs3811047 is still significantly associated with CAD. As shown in Table 4, the minor allele A of rs3811047 conferred a significant risk of CAD in the matched case control population under a recessive model (P = 4.57 × 10−9, OR = 2.82) and under an additive model (P = 3.66 × 10−8). The association remained significant after adjustment of other covariates, including hypertension, diabetes, and lipid concentrations (TG, Tch, LDL-c and HDL-c) (P = 2.23 × 10−4, OR = 1.99 under a recessive model; P = 1.02 × 10−3, OR = 1.45 under an additive model) (Table 4). Allelic association analysis also showed that the minor allele A of SNP rs3811047 conferred a significant risk of CAD in the matched case control population before (P = 1.60 × 10−5, OR = 1.31) and after adjustment of hypertension, diabetes, and lipid concentrations (TG, Tch, LDL-c and HDL-c) (P = 6.43 × 10−3, OR = 1.26) (Table 5). We also analyzed the association between rs3811047 and CAD in a male only population and in a female only population, and significant association was identified in both populations (Table 5).
Table 4

Genotypic analysis of IL-37 SNP rs3811047 with CAD in age- and sex-matched case control populations under three genetic models.

Population (N, Case/Control)Genotype
ModelPobsOR (95% CI)PadjOR (95% CI)
 CasesControls
Sex- and age-matched population (1,596/1,596)AA11342Additive3.66 × 10−8n.a1.02 × 10−31.45 (1.15–1.81)
AG471487Dominant0.061.16 (0.99–1.34)0.171.10 (0.96–1.29)
GG10121067Recessive4.57 × 10−92.82 (1.96–4.05)2.23 × 10−41.99 (1.45–3.02)

P, P value from Chi square tests with 2 × 3 contingency tables without adjustment for covariates;

P, P value adjusted by covariates of sex, age, hypertension, T2D and lipid concentrations by multiple logistic regression analysis;

OR, odds ratio;

95% CI, 95% confidence interval;

Additive model = AA/AG/GG; Dominant model = AA + AG/GG; Recessive model = AA/AG + GG.

Table 5

Significant allelic association of IL-37 SNP rs3811047 with CAD in an age- and sex-matched case control population.

PopulationN Case/ControlFrequency of Minor Allele A (Case/Control)PhwePobsOR (95% CI)PadjOR (95% CI)
Age- and sex-matched population1,596/1,5960.22/0.180.861.60 × 10−51.31 (1.16–1.48)6.43 × 10−31.26 (1.08–1.40)
Males1,049/1,0490.22/0.180.811.31 × 10−31.30 (1.12–1.52)0.011.24 (1.05–1.43)
Females547/5470.22/0.180.808.01 × 10−31.33 (1.08–1.64)0.021.28 (1.06–1.45)

P, P value from Hardy-Weinberg equilibrium tests;

P, P value from Chi square tests with 2 × 2 contingency tables without adjustment for covariates;

P, P value adjusted by covariates of sex, age, hypertension, T2D and lipid concentrations by multiple logistic regression analysis;

OR, odds ratio;

95% CI, 95% confidence interval.

Real time RT-PCR analysis idenfified significant association between SNP rs3811047 and the expression level of IL-37 mRNA

We carried out real time RT-PCR to analyze whether the expression level of IL-37 is associated with the genotype of SNP rs3811047 using blood samples from 168 study subjects. The results showed that the expression level of the IL-37 mRNA was significantly different among different genotypes under a recessive genetic model (P = 3.78 × 10−4) (Fig. 1). The expression level of the IL-37 mRNA was significantly lower in carriers with the AA genotype than carriers with GG and GA genotypes (Fig. 1). Together, these results suggest that the minor allele A of SNP rs3811047 is significantly associated with a decreased expression of IL-37.
Figure 1

Assessment of the relationship between IL-37 SNP rs3811047 and the expression level of IL-37 mRNA by real time RT-PCR analysis.

Total RNA samples were isolated from 168 blood samples (lymphocytes), converted into cDNA, and used for real time PCR analysis. Genomic DNA samples were isolated from the 168 study subjects and genotyped for SNP rs3811047 by HRM analysis. A linear regression was used to compare the differences for the mean RQ values between different genotypes (AA and AG + GG) of SNP rs3811047.

Discussion

In the present study, we genotyped SNP rs3811047 in the IL-37 gene in two independent case control populations of CAD, and performed an association study to test whether the genetic variant in IL37 confers risk of CAD. Here we provide genetic evidence that minor allele A of rs3811047 in the IL-37 gene was significantly associated with the risk of CAD in two independent case control populations (Tables 2 and 3). The association between SNP rs3811047 and CAD became even more significant in the combined population (Tables 2 and 3). The association between SNP rs3811047 and CAD remained significant after adjustment of covariates of age, sex, hypertension, diabetes, triglyceride, total cholesterol, LDL-cholesterol and HDL-cholesterol levels (Tables 2 and 3). Significant allelic and genotypic association between SNP rs3811047 and CAD was also identified in a case control population matched by age and sex (Tables 4 and 5). The significant allelic association remained in the separated male population and the female population (Table 5). These data suggest that SNP rs3811047 in IL-37 is a risk factor of CAD independent from age, gender, hypertension, diabetes, and lipid levels. Moreover, we found that the minor allele A of SNP rs3811047 was associated with a decreased expression level of the IL-37 mRNA. These results suggest that IL-37 is a susceptibility gene for CAD. This is the first study that establishes the significant association between an IL-37 variant and CAD. Our studies used cases and controls from the GeneID Chinese Han population. We hope that the significant association between an IL-37 variant and CAD can be replicated in other Chinese populations and even in other ethnic populations. In addition, future studies can also analyze whether the IL-37 variant is also associated with the severity of CAD and other diseases such as ischemic stroke associated with inflammation. SNP rs3811047 was first associated with human leukocyte antigen-B27 positive ankylosing spondylitis in the Chinese population30. The previous study observed that there was an interaction between IL-37 gene and alcohol drinking in ankylosing spondylitis patients in a case-only study31. Ankylosing spondylitis is one of the most common chronic inflammatory autoimmune diseases affecting the axial and/or peripheral skeleton with an estimated prevalence of 0.1–0.9%32. Chronic inflammation and cytokines play important roles in the pathogenesis of atherosclerosis and CAD. There is evidence that ankylosing spondylitis patients have a higher risk of mortality and morbidity compared to the general population and also a higher rate of cardiovascular death28. Several studies also showed that cardiovascular diseases are more common in patients with ankylosing spondylitis3334. These findings suggested that a common mechanism, such as chronic inflammation, may be shared between CAD and ankylosing spondylitis. We hypothesized that the genetic risk factors of ankylosing spondylitis may also play a role in the pathogenesis of atherosclerotic CAD. In the present study, for the first time, we show that SNP rs3811047 in IL-37 is indeed a risk factor for CAD. IL-37 is the seventh member of the IL-1 family, and considered as an anti-inflammatory cytokine which mainly inhibits the expression, production and function of other pro-inflammatory cytokines35. IL-37 is normally expressed at a low level in peripheral blood monocytes, but its expression is rapidly up-regulated in monocytes as well as dendritic cells under an inflammatory context26. This leads to suppression of the production of other IL-1 family of pro-inflammatory cytokines36. Transgenic mice expressing human IL-37 exhibited an anti-inflammatory function by directly inhibiting the production of pro-inflammatory cytokines37. IL-37 was also shown as a key modulator of intestinal inflammation by decreasing IL-1β and TNFα38. In addition, IL-37 effectively inhibits the activation of dendritic cells35. As IL-37 is involved in anti-inflammation, reduced expression of IL-37 associated with SNP rs3811047 as found in this study (Fig. 1) may cause inflammation, increasing risk of atherosclerosis and CAD. In conclusion, through a case control association study in two independent populations with a total of 2,501 cases and 3,116 controls, we found significant association between SNP rs3811047 in the IL37 gene and CAD. We also demonstrated that the minor allele of SNP rs3811047 was associated with a decreased expression level of IL-37. Our results suggest that IL37 is a new susceptibility gene for CAD and that SNP rs3811047 in IL37 is a new genetic risk factor of CAD.

Methods

Study populations

The study subjects were selected from the GeneID database, which is a large ongoing database with clinical data and DNA samples from more than 80,000 Chinese patients and controls. The major goal of GeneID database is to identify susceptibility genes for various cardiovascular diseases in the Chinese Han population7293940. The diagnosis of CAD was based on coronary angiography, and followed the standard guidelines by the ACC/AHA41. The diagnosis was made by more than two independent expert cardiologists. We classified patients with >70% of luminal stenosis in at least one main vessel by coronary angiography, coronary artery bypass graft, percutaneous coronary intervention, and/or a myocardial infarction (MI) as CAD cases41. The diagnosis of MI was based on typical chest pain of ≧30 min duration, characteristic electrocardiographic patterns of acute MI, and significant elevation of cardiac enzymes (creatine kinase-MB, lactate dehydrogenase) and troponin I or T41. We excluded patients with myocardial spasma and myocardial bridge identified by angiography and those subjects with congenital heart disease, childhood hypertension, and type I diabetes mellitus. The study included two independent populations. To avoid geographical confounding, we selected one population with study subjects recruited from Northern China and another population with study subjects recruited from Central China. The GeneID Northern population was enrolled from the Northern area of China and had 1,038 CAD cases and 1,076 controls. The GeneID Central population was enrolled from Wuhan in central China and had 1,463 CAD cases and 2,040 controls. In total, our study population included 2,501 CAD cases and 3,116 controls. All subjects were reported to be of Chinese Han origin by self-description or self-report. The basic demographic and clinical charateristics of the subjects, including the age, gender, hypertension, type 2 diabetes (T2D) and lipid profiles, were obtained from medical records. Hypertension was defined as a systolic blood pressure of ≥140 mm Hg or a diastolic blood pressure ≥90 mm Hg. T2D was diagnosed as a fasting plasma glucose concentration ≥126 mg/dL after at least 8 hours of fasting or a 2-hour plasma glucose level of ≥200 mg/dL during an oral glucose tolerance test (OGTT). This study was approved by the Ethics Committees on human subject research of Huazhong University of Science and Technology and local institutions and conformed to guidelines set forth by the Declaration of Helsinki. Written informed consent was obtained from subjects following instructions approved by the Ethics Committees.

SNP selection and genotyping

We selected a non-synonymous taqSNP (rs3811047 in IL-37) for this study. SNP rs3811047 is located in the second exon and caused a transition of threonine to alanine at the 42th amino acid residue of IL-37. The human genomic DNA of each study subject was extracted from the peripheral whole blood samples using the Wizard Genomic DNA Purification Kit (Promega Corporation). We used the Syto 9 fluorescent dye-based high resolution melt (HRM) method on a Rotor-gene 6200 System (Corbett Life Science) to genotype SNP rs3811047 as described by us1640424344454647. Primers were designed by software Genetool. The fragment flanking rs3811047 was amplified with the forward primer 5′-AGCCCCCTGGAACCAGGC-3′ and the reverse primer 5′-TCAGCCACCCCCATCACC-3′, together with a final concentration of 5 μmol/L Syto 9 fluorescent dye. The polymerase chain reaction (PCR) was performed with a reaction of a total volume of 25 μL containing 2.5 μL of 10 × PCR buffer, 1.5 mmol/L MgCl2, 5 mmol/L dNTPs, 5 pmol of each primer, 25 ng of genomic DNA, 1 μL of Syto 9 fluorescent dye and 1 U of Taq DNA polymerase. The PCR profile was 5 min at 94 °C, 39 cycles of 94 °C for 10 s, 63 °C for 10 s and at 72 °C for 10 s, and a final elongation step at 72 °C for 10 min. Four positive controls were included in each run. The HRM genotyping was verified by direct Sanger sequence analysis of 52 randomly selected samples.

Quantitative RT-PCR analysis

We performed quantitative RT-PCR analysis to evaluate whether SNP rs3811047 was associated with the mRNA expression level of IL-37. The ΔΔCq method was used to determine the difference of the mean expression levels of IL-37 among study subjects with different genotypes for rs3811047162946. Quantitative real-time PCR analysis was carried out according to the MIQE guidelines48. Total RNA samples were extracted from human peripheral blood leukocytes using Trizol reagent (Life Technologies, Gaithersburg, MD). Quantification of RNA samples was performed using a spectrophotometer (NanoDrop, Thermo Scientific, Hudson, NH). One μg of total RNA was used for reverse transcription with Superscript II reverse transcriptase (Life Technologies, Gaithersburg, MD) and oligo (dT)18. A standard two step real-time PCR assay was performed using an ABI 7900-HT Genetic Analyzer (Applied Biosystems, Gaithersburg, MD). Each PCR reaction was performed in a final volume of 10 μL reaction mixture containing 5 μL of 2X PCR master mixture with ROX (Faststart Universal SYBR Green Master Kit, Roche Applied Science, Indianapolis, IN), 2 μL of cDNA, 0.4 μL of 10 pM primers, and 2.6 μL of ddH2O. Each reaction was performed in triplicate. The cycling conditions were 95 °C for 10 minutes and 40 cycles of 95 °C for 15 seconds and 60 °C elongation for 45 seconds. After the PCR reaction, Cq values (threshold cycle) of a target gene (IL-37) (Cq T) or reference gene GAPDH (Cq E) were computed using the RQ Manager program (version 1.3) and SDS (version 2.3). Reaction with a Cq of ≥40 or with the difference between Cq and mean Cq greater than 0.5 were excluded for further analysis. For each individual, the relative expression level △Cq (Cq T-Cq E) of a target gene was normalized with the reference gene and then transformed into relative quantity using RQ formula (RQ = 2−△△Cq, ΔΔCq = individual’s ΔCq-calibrator’s ΔCq)46. The calibrator was a mixed cDNA sample pooled from 10 randomly selected individuals. The RQ value for the calibrator was normalized to 1. After outliers were excluded, linear regression was used to compare the differences for mean RQ values of IL-37 between different genotypes of SNP rs3811047. The sequences for qRT-PCR primers are 5′-AGCTGAAGAAGGAGAAACT-3′ (forward primer) and 5′-CGCCGACTCCAGCATGTTC-3′ (reverse primer) for IL-37 and 5′-AAGGTGAAGGTCGGAGTCAAC-3′ (forward primer) and 5′- GGGGTCATTGATGGCAACAATA -3′ (reverse primer) for GAPDH.

Statistical analysis

We used PS software 3.0.12 to calculate the statistical power and sample sizes for the case-control design (http://biostat.mc.vanderbilt.edu/wiki/Main/PowerSampleSize). The statistical power of a case control study can be calculated with special parameters, including the minor allele frequency (0.209 for rs3811047 in our study), OR, the numbers of cases and controls, and the Type I error of 0.05. The null hypothesis can be rejected if the odds ratio equals 1 with probability (power). The program uses an uncorrected chi-squared statistic method to evaluate the null hypothesis (http://biostat.mc.vanderbilt.edu/wiki/Main/PowerSampleSize). The Hardy-Weinberg linkage disequilibrium test among control groups was performed using PLINK 1.06. For association analysis, χ2 tests were performed using Pearson’s 2 × 2 and 2 × 3 contingency tables to calculate the P values and corresponding odds ratios (OR) with 95% confidential intervals (CI) by PLINK 1.06 as described by us7495051. Multivariate logistic regression analysis was performed to adjust for some risk factors (age, gender, hypertension, diabetes mellitus and lipid concentrations) using SPSS version 17.0. We used a student’s t-test to compare the continuous variables between cases and controls. Linear regression was used to assess the association between gene expression levels and SNP genotypes. A P value of 0.05 or less was considered to be statistically significant.

Additional Information

How to cite this article: Yin, D. et al. Genomic Variant in IL-37 Confers A Significant Risk of Coronary Artery Disease. Sci. Rep. 7, 42175; doi: 10.1038/srep42175 (2017). Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
  51 in total

Review 1.  Cardiovascular profile in ankylosing spondylitis: a systematic review and meta-analysis.

Authors:  Sylvain Mathieu; Laure Gossec; Maxime Dougados; Martin Soubrier
Journal:  Arthritis Care Res (Hoboken)       Date:  2011-04       Impact factor: 4.794

2.  Association of IL-1F7 gene with susceptibility to human leukocyte antigen-B27 positive ankylosing spondylitis in Han Chinese population.

Authors:  Faming Pan; Fangfang Liao; Guo Xia; Rui Ge; Yang Mei; Xiaowu Tang; Heping Pan; Dongqing Ye; Yanfeng Zou; Shengqian Xu; Jianhua Xu
Journal:  Clin Chim Acta       Date:  2009-10-26       Impact factor: 3.786

3.  Genetic analysis of the interleukin-18 system highlights the role of the interleukin-18 gene in cardiovascular disease.

Authors:  Laurence Tiret; Tiphaine Godefroy; Edith Lubos; Viviane Nicaud; David-Alexandre Tregouet; Sandrine Barbaux; Renate Schnabel; Christoph Bickel; Christine Espinola-Klein; Odette Poirier; Claire Perret; Thomas Münzel; Hans-Jurgen Rupprecht; Karl Lackner; François Cambien; Stefan Blankenberg
Journal:  Circulation       Date:  2005-07-25       Impact factor: 29.690

4.  Genome-wide association identifies a susceptibility locus for coronary artery disease in the Chinese Han population.

Authors:  Fan Wang; Cheng-Qi Xu; Qing He; Jian-Ping Cai; Xiu-Chun Li; Dan Wang; Xin Xiong; Yu-Hua Liao; Qiu-Tang Zeng; Yan-Zong Yang; Xiang Cheng; Cong Li; Rong Yang; Chu-Chu Wang; Gang Wu; Qiu-Lun Lu; Ying Bai; Yu-Feng Huang; Dan Yin; Qing Yang; Xiao-Jing Wang; Da-Peng Dai; Rong-Feng Zhang; Jing Wan; Jiang-Hua Ren; Si-Si Li; Yuan-Yuan Zhao; Fen-Fen Fu; Yuan Huang; Qing-Xian Li; Sheng-Wei Shi; Nan Lin; Zhen-Wei Pan; Yue Li; Bo Yu; Yan-Xia Wu; Yu-He Ke; Jian Lei; Nan Wang; Chun-Yan Luo; Li-Ying Ji; Lian-Jun Gao; Lei Li; Hui Liu; Er-Wen Huang; Jin Cui; Na Jia; Xiang Ren; Hui Li; Tie Ke; Xian-Qin Zhang; Jing-Yu Liu; Mu-Gen Liu; Hao Xia; Bo Yang; Li-Song Shi; Yun-Long Xia; Xin Tu; Qing K Wang
Journal:  Nat Genet       Date:  2011-03-06       Impact factor: 38.330

Review 5.  Cardiovascular risk profile of patients with spondylarthropathies, particularly ankylosing spondylitis and psoriatic arthritis.

Authors:  Mike J Peters; Irene E van der Horst-Bruinsma; Ben A Dijkmans; Michael T Nurmohamed
Journal:  Semin Arthritis Rheum       Date:  2004-12       Impact factor: 5.532

6.  Genome-wide association study in Han Chinese identifies four new susceptibility loci for coronary artery disease.

Authors:  Xiangfeng Lu; Laiyuan Wang; Shufeng Chen; Lin He; Xueli Yang; Yongyong Shi; Jing Cheng; Liang Zhang; C Charles Gu; Jianfeng Huang; Tangchun Wu; Yitong Ma; Jianxin Li; Jie Cao; Jichun Chen; Dongliang Ge; Zhongjie Fan; Ying Li; Liancheng Zhao; Hongfan Li; Xiaoyang Zhou; Lanying Chen; Donghua Liu; Jingping Chen; Xiufang Duan; Yongchen Hao; Ligui Wang; Fanghong Lu; Zhendong Liu; Cailiang Yao; Chong Shen; Xiaodong Pu; Lin Yu; Xianghua Fang; Lihua Xu; Jianjun Mu; Xianping Wu; Runping Zheng; Naqiong Wu; Qi Zhao; Yun Li; Xiaoli Liu; Mengqin Wang; Dahai Yu; Dongsheng Hu; Xu Ji; Dongshuang Guo; Dongling Sun; Qianqian Wang; Ying Yang; Fangchao Liu; Qunxia Mao; Xiaohua Liang; Jingfeng Ji; Panpan Chen; Xingbo Mo; Dianjiang Li; Guoping Chai; Yida Tang; Xiangdong Li; Zhenhan Du; Xuehui Liu; Chenlong Dou; Zili Yang; Qingjie Meng; Dong Wang; Renping Wang; Jun Yang; Heribert Schunkert; Nilesh J Samani; Sekar Kathiresan; Muredach P Reilly; Jeanette Erdmann; Xiaozhong Peng; Xigui Wu; Depei Liu; Yuejin Yang; Runsheng Chen; Boqin Qiang; Dongfeng Gu
Journal:  Nat Genet       Date:  2012-07-01       Impact factor: 38.330

7.  Assessment of association of rs2200733 on chromosome 4q25 with atrial fibrillation and ischemic stroke in a Chinese Han population.

Authors:  Lisong Shi; Cong Li; Chuchu Wang; Yunlong Xia; Gang Wu; Fan Wang; Chengqi Xu; Pengyun Wang; Xiuchun Li; Dan Wang; Xin Xiong; Ying Bai; Mugen Liu; Jingyu Liu; Xiang Ren; Lianjun Gao; Binbin Wang; Qiutang Zeng; Bo Yang; Xu Ma; Yanzong Yang; Xin Tu; Qing Kenneth Wang
Journal:  Hum Genet       Date:  2009-12       Impact factor: 4.132

8.  Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease.

Authors:  Heribert Schunkert; Inke R König; Sekar Kathiresan; Muredach P Reilly; Themistocles L Assimes; Hilma Holm; Michael Preuss; Alexandre F R Stewart; Maja Barbalic; Christian Gieger; Devin Absher; Zouhair Aherrahrou; Hooman Allayee; David Altshuler; Sonia S Anand; Karl Andersen; Jeffrey L Anderson; Diego Ardissino; Stephen G Ball; Anthony J Balmforth; Timothy A Barnes; Diane M Becker; Lewis C Becker; Klaus Berger; Joshua C Bis; S Matthijs Boekholdt; Eric Boerwinkle; Peter S Braund; Morris J Brown; Mary Susan Burnett; Ian Buysschaert; John F Carlquist; Li Chen; Sven Cichon; Veryan Codd; Robert W Davies; George Dedoussis; Abbas Dehghan; Serkalem Demissie; Joseph M Devaney; Patrick Diemert; Ron Do; Angela Doering; Sandra Eifert; Nour Eddine El Mokhtari; Stephen G Ellis; Roberto Elosua; James C Engert; Stephen E Epstein; Ulf de Faire; Marcus Fischer; Aaron R Folsom; Jennifer Freyer; Bruna Gigante; Domenico Girelli; Solveig Gretarsdottir; Vilmundur Gudnason; Jeffrey R Gulcher; Eran Halperin; Naomi Hammond; Stanley L Hazen; Albert Hofman; Benjamin D Horne; Thomas Illig; Carlos Iribarren; Gregory T Jones; J Wouter Jukema; Michael A Kaiser; Lee M Kaplan; John J P Kastelein; Kay-Tee Khaw; Joshua W Knowles; Genovefa Kolovou; Augustine Kong; Reijo Laaksonen; Diether Lambrechts; Karin Leander; Guillaume Lettre; Mingyao Li; Wolfgang Lieb; Christina Loley; Andrew J Lotery; Pier M Mannucci; Seraya Maouche; Nicola Martinelli; Pascal P McKeown; Christa Meisinger; Thomas Meitinger; Olle Melander; Pier Angelica Merlini; Vincent Mooser; Thomas Morgan; Thomas W Mühleisen; Joseph B Muhlestein; Thomas Münzel; Kiran Musunuru; Janja Nahrstaedt; Christopher P Nelson; Markus M Nöthen; Oliviero Olivieri; Riyaz S Patel; Chris C Patterson; Annette Peters; Flora Peyvandi; Liming Qu; Arshed A Quyyumi; Daniel J Rader; Loukianos S Rallidis; Catherine Rice; Frits R Rosendaal; Diana Rubin; Veikko Salomaa; M Lourdes Sampietro; Manj S Sandhu; Eric Schadt; Arne Schäfer; Arne Schillert; Stefan Schreiber; Jürgen Schrezenmeir; Stephen M Schwartz; David S Siscovick; Mohan Sivananthan; Suthesh Sivapalaratnam; Albert Smith; Tamara B Smith; Jaapjan D Snoep; Nicole Soranzo; John A Spertus; Klaus Stark; Kathy Stirrups; Monika Stoll; W H Wilson Tang; Stephanie Tennstedt; Gudmundur Thorgeirsson; Gudmar Thorleifsson; Maciej Tomaszewski; Andre G Uitterlinden; Andre M van Rij; Benjamin F Voight; Nick J Wareham; George A Wells; H-Erich Wichmann; Philipp S Wild; Christina Willenborg; Jaqueline C M Witteman; Benjamin J Wright; Shu Ye; Tanja Zeller; Andreas Ziegler; Francois Cambien; Alison H Goodall; L Adrienne Cupples; Thomas Quertermous; Winfried März; Christian Hengstenberg; Stefan Blankenberg; Willem H Ouwehand; Alistair S Hall; Panos Deloukas; John R Thompson; Kari Stefansson; Robert Roberts; Unnur Thorsteinsdottir; Christopher J O'Donnell; Ruth McPherson; Jeanette Erdmann; Nilesh J Samani
Journal:  Nat Genet       Date:  2011-03-06       Impact factor: 38.330

9.  Association of SNP Rs9943582 in APLNR with Left Ventricle Systolic Dysfunction in Patients with Coronary Artery Disease in a Chinese Han GeneID Population.

Authors:  Pengyun Wang; Chengqi Xu; Chuchu Wang; Yanxia Wu; Dan Wang; Shanshan Chen; Yuanyuan Zhao; Xiaojing Wang; Sisi Li; Qin Yang; Qiutang Zeng; Xin Tu; Yuhua Liao; Qing K Wang; Xiang Cheng
Journal:  PLoS One       Date:  2015-05-19       Impact factor: 3.240

Review 10.  Cytokines and atherosclerosis: a comprehensive review of studies in mice.

Authors:  Robert Kleemann; Susanne Zadelaar; Teake Kooistra
Journal:  Cardiovasc Res       Date:  2008-05-16       Impact factor: 10.787

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  11 in total

Review 1.  Interleukin 30 to Interleukin 40.

Authors:  Jovani Catalan-Dibene; Laura L McIntyre; Albert Zlotnik
Journal:  J Interferon Cytokine Res       Date:  2018-10       Impact factor: 2.607

2.  Significant association of rare variant p.Gly8Ser in cardiac sodium channel β4-subunit SCN4B with atrial fibrillation.

Authors:  Hongbo Xiong; Qin Yang; Xiaoping Zhang; Pengxia Wang; Feifei Chen; Ying Liu; Pengyun Wang; Yuanyuan Zhao; Sisi Li; Yufeng Huang; Shanshan Chen; Xiaojing Wang; Hongfu Zhang; Dong Yu; Chencheng Tan; Cheng Fang; Yuan Huang; Gang Wu; Yanxia Wu; Xiang Cheng; Yuhua Liao; Rongfeng Zhang; Yanzong Yang; Tie Ke; Xiang Ren; Hui Li; Xin Tu; Yunlong Xia; Chengqi Xu; Qiuyun Chen; Qing K Wang
Journal:  Ann Hum Genet       Date:  2019-03-01       Impact factor: 1.670

3.  Interleukin-37: A crucial cytokine with multiple roles in disease and potentially clinical therapy.

Authors:  Lijuan Wang; Yanchun Quan; Yongfang Yue; Xueyuan Heng; Fengyuan Che
Journal:  Oncol Lett       Date:  2018-02-07       Impact factor: 2.967

4.  Significant genetic association of a functional TFPI variant with circulating fibrinogen levels and coronary artery disease.

Authors:  Duraid Hamid Naji; Chengcheng Tan; Fabin Han; Yuanyuan Zhao; Junhan Wang; Dan Wang; Jingjing Fa; Sisi Li; Shanshan Chen; Qiuyun Chen; Chengqi Xu; Qing K Wang
Journal:  Mol Genet Genomics       Date:  2017-09-11       Impact factor: 3.291

Review 5.  Potential role of IL-37 in atherosclerosis.

Authors:  Sara McCurdy; Chloe A Liu; Jonathan Yap; William A Boisvert
Journal:  Cytokine       Date:  2017-10-05       Impact factor: 3.861

6.  Lack of association between the APLNR variant rs9943582 with ischemic stroke in the Chinese Han GeneID population.

Authors:  Pengyun Wang; Chuchu Wang; Sisi Li; Binbin Wang; Liang Xiong; Xin Tu; Qing K Wang; Cheng-Qi Xu
Journal:  Oncotarget       Date:  2017-11-21

7.  Functional rare variant in a C/EBP beta binding site in NINJ2 gene increases the risk of coronary artery disease.

Authors:  Pengyun Wang; Yifan Wang; Huixin Peng; Jingjing Wang; Qian Zheng; Pengxia Wang; Jing Wang; Hongfu Zhang; Yufeng Huang; Liang Xiong; Rongfeng Zhang; Yunlong Xia; Qing K Wang; Chengqi Xu
Journal:  Aging (Albany NY)       Date:  2021-12-12       Impact factor: 5.682

8.  Genomic Variants in NEURL, GJA1 and CUX2 Significantly Increase Genetic Susceptibility to Atrial Fibrillation.

Authors:  Pengxia Wang; Weixi Qin; Pengyun Wang; Yufeng Huang; Ying Liu; Rongfeng Zhang; Sisi Li; Qin Yang; Xiaojing Wang; Feifei Chen; Jingqiu Liu; Bo Yang; Xiang Cheng; Yuhua Liao; Yanxia Wu; Tie Ke; Xin Tu; Xiang Ren; Yanzong Yang; Yunlong Xia; Xiaoping Luo; Mugen Liu; He Li; Jingyu Liu; Yi Xiao; Qiuyun Chen; Chengqi Xu; Qing K Wang
Journal:  Sci Rep       Date:  2018-02-19       Impact factor: 4.379

9.  Short-term interleukin-37 treatment improves vascular endothelial function, endurance exercise capacity, and whole-body glucose metabolism in old mice.

Authors:  Dov B Ballak; Vienna E Brunt; Zachary J Sapinsley; Brian P Ziemba; James J Richey; Melanie C Zigler; Lawrence C Johnson; Rachel A Gioscia-Ryan; Rachel Culp-Hill; Elan Z Eisenmesser; Angelo D'Alessandro; Charles A Dinarello; Douglas R Seals
Journal:  Aging Cell       Date:  2019-11-21       Impact factor: 9.304

10.  IL-37 Gene and Cholesterol Metabolism: Association of Polymorphisms with the Presence of Hypercholesterolemia and Cardiovascular Risk Factors. The GEA Mexican Study.

Authors:  Fabiola López-Bautista; Rosalinda Posadas-Sánchez; Christian Vázquez-Vázquez; José Manuel Fragoso; José Manuel Rodríguez-Pérez; Gilberto Vargas-Alarcón
Journal:  Biomolecules       Date:  2020-10-05
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