NPAS4 Polymorphisms Contribute to Coronary Heart Disease (CHD) Risk

As genetic inheritance is an inevitable risk factor in the development of coronary heart disease (CHD), it is critical to identify the polymorphisms of CHD risk. This study explored whether the NPAS4 polymorphisms are related to the CHD risk in the Chinese Han population. Five SNPs in NPAS4 were genotyped using Agena Mass ARRAY from 499 CHD and 500 controls. RT-PCR detected the NPAS4 expression levels in peripheral blood mononuclear cells from 50 CHD and 50 controls. χ2 test compared the distributions of gender, allele and genotypes frequencies between cases and controls. Logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (95% CIs). MDR analyzed the SNP–SNP interactions on risk of CHD. U test compared the differences in gene expression between different groups. The results showed that rs4466842 was correlated with an increased CHD risk in overall, males and age ≤ 60; rs117186164 and rs12785321 were significantly related to an increased CHD risk in male and age ≤ 60, respectively; haplotype Ars117186164Crs4466842 was significantly correlated with an increased CHD risk. SNP–SNP interactions results showed that the best model was the four-locus model was the combination of rs117770654, rs117957381, rs12785321, and rs4466842 (CVC = 10/10, Testing Sensitivity = 0.647). The expression levels of NPAS4 in the case group (0.365 ± 0.139) were significantly lower than that in the control group (0.782 ± 0.224) (P < 0.001). The results revealed that SNPs in NPAS4 may play an important role in the occurrence and development of CHD.


Introduction
Coronary heart disease (CHD) is one of the leading causes of disability and death and tremendous social and financial burden worldwide [1]. The Reports of Cardiovascular Diseases showed that the prevalence of CHD disease in China continues to rise [2]. CHD is a complex multifactorial disease that is affected by genetic factors, environmental factors, and their interactions [3,4]. Epidemiological studies have identified multiple risk factors which contribute to CHD development, such as advanced age, smoking, diabetes, hypertension, hyperlipidemia, obesity, lack of exercise, and dietary factors [5][6][7][8]. Previous family-or twin-based epidemiological studies demonstrated that genetic factors contributed to approximately 40-50% of the risk of CHD [9,10]. However, the genetic mechanism of CHD has not been fully explained. Recently, a large number of studies have revealed that single nucleotide polymorphisms (SNPs) are related to CHD susceptibility [11,12]. As genetic 1 3 inheritance is an inevitable risk factor in the development of CHD, it is critical to identify the SNP locus of CHD risk.
Neuronal Per-Arnt-Sim (PAS) domain protein 4 (Npas4), also known as neuronal transcription factor (NXF) and limbic-enriched PAS domain protein (LE-PAS), is an activitydependent transcription factor belonging to the basic helix loop helix (BHLH)/PAS transcription factor family [13]. Npas4 is thought to be involved in functional regulation of neurons, because significant expression is found in the mature brain. Previous study suggested that NXF induced in response to several neurodegenerative stimuli/excitations for the cell-protection, and thus provided an "on demand" cellprotection system in nervous tissue [14] indicate that sensory stimuli, by inducing NPAS4 and its target gene brain derived neurotrophic factor (Bdnf), differentially control spatial features of neuronal inhibition in a way that restricts the output of the neuron while creating a dendritic environment that is permissive for plasticity [15]. Studies have indicated the functional role for Npas4 in hippocampus [16] and amygdala-dependent [17], cognitive and social neuro-behavior [18] and learning and memory formation [19].
Gene chip and RT-PCR showed that the expression level of NPAS4 was significantly decreased in patients with CHD as compared with the control group. However, the contribution of the polymorphisms of NPAS4 in the risk of CHD remains not reported. Therefore, we performed a case-control study including 499 CHD patients and 505 healthy controls to explore the association between NPAS4 polymorphisms (rs117770654, rs117957381, rs12785321, rs117186164, and rs4466842) of CHD risk in the Chinese Han population.

Subjects
This study was involved with the blood samples of 499 CHD patients and 505 matched healthy controls from the First Affiliated Hospital of Xi'an Jiaotong. All patients were diagnosed with CHD according to standardized electrocardiogram, echocardiography, blood tests and coronary angiography and judged by at least two cardiologists independently. All of the control subjects were randomly recruited from the same hospital during the same period and also underwent a coronary angiogram to confirm no stenosis in their coronary arteries. Individuals were excluded from the study if they had other cardiac diseases (congenital heart disease, cardiomyopathy, concomitant valvular heart disease, or rheumatic heart disease). In addition, patients who had previously received angioplasty, intravenous thrombolysis, coronary artery stents, or coronary artery bypass surgery were also excluded. All the individuals were genetically unrelated Chinese Han people from Shaanxi.

DNA Extraction
We collected 5 mL of fasting peripheral venous blood samples from CHD patients and controls, and placed in ethylene diamine tetraacetic acid (EDTA)-containing tubes. We used the GoldMag-Mini Whole Blood Genomic DNA Purification Kit (GoldMag Co. Ltd. Xi'an City, China) to extract DNA from blood samples of the subjects according to the manufacturer's instructions [20]. We used the spectrophotometer (NanoDrop 2000; Thermo Fisher Scientific, Waltham, MA, USA) to determine the purity and concentration of the extracted DNA.

SNP Selection and Genotyping
The five genetic polymorphisms (rs117770654, rs117957381, rs12785321, rs117186164, and rs4466842) in NPAS4 were screened by HapMap database. The Haploview 4.2 was used to select, and according to Chinese Beijing Han population (CHB), unbalanced r 2 value more than 0.8, and the minor allele frequency (MAF) was greater than 5%. The online software Agena Bioscience Assay Design Suite Version 2.0 (https:// agena cx. com/ online-tools/) was used to design the amplification and unique base extension primers. Applied Biosystems 7500 real-time PCR system was used for the DNA amplification. We used the Agena Mass ARRAY platform (Agena Bioscience, San Diego, CA, USA) to genotype the polymorphisms of the NPAS4 gene according to the protocol described. The Agena Bioscience TYPER software (version 4.0) was used to manage and analyze the genotyping results.

Total RNA Isolation and RT-PCR
Mononuclear cells were obtained from peripheral blood samples (50 CHD patients and 50 controls) through centrifugation (12000 rpm) with erythrocyte lysate and Trizol. Total mononuclear cell RNA was extracted using the Trizol kit (Invitrogen Life Technologies, Carlsbad, USA) according to the manufacturer's instructions. The purity and concentration of RNA was also measured using the spectrophotometer (NanoDrop 2000; Thermo Fisher Scientific, Waltham, MA, USA) to determine. We used the extracted RNA to synthesize complementary DNA (cDNA) with a Reverse Transcription kit (Takara). Realtime polymerase chain reaction (RT-PCR) was performed in an ABI 7500 sequence detector system (Applied Biosystems, CA). Reaction conditions: stage 1: pre-denaturation (95 °C, 30 s); stage 2: 40 cycles of amplification at 95 °C for 3 s, and annealing at 60 °C for 30 s and extension at 72 °C for 30 s. The relative expression levels of NPAS4 was indicated as the expression of the target genes normalized by that ofglyceraldehyde-3-phosphate dehydrogenase (GAPDH) (2 −∆∆Ct ).

Statistical Analysis
We used χ 2 test to compare the distributions of gender between the case group and the control group. The differences in the distribution of gender and age and clinical indicators were analyzed by and Student's t test. We also used χ 2 test to evaluate whether the genotype distribution of each SNP among the control group was in Hardy-Weinberg equilibrium (HWE) and evaluate the differences in the distribution of genotypes and allelic frequencies of these polymorphisms between case and control groups. We used genetic models (co-dominant, dominant, recessive, and additive) and haplotype analyses to evaluate the relationship between NPAS4 polymorphisms. The logistic regression analysis was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) by PLINK software (version 1.07). The Haploview 4.2 software was used to conduct linkage disequilibrium (LD) haplotype blocks and calculate the linkage strength between each pair of SNPs with D′ and r 2 values. The non-parametric test (U) was used to compare the differences in gene expression between different groups. The one-way analysis of variance was used to assess the association between SNPs and NPAS4 expression levels. All statistical analyses were two sided and P value < 0.05 was considered statistically significant. The SPSS 20.0 statistical package (SPSS, Chicago, IL) and Microsoft Excel (Microsoft Corp., Redmond, WA, USA) was to conduct the basic statistical analysis.

Characteristics of Participants
We recruited 499 CHD patients and 505 healthy controls. There were 317 males and 182 females in the case group, and 323 males and 182 females in the control group. The case group consisted of 100 (20.04%) CHD patients with diabetes and 399 (79.96%) without diabetes; 294 (58.92%) CHD patients with hypertension and 205 (41.08%) without hypertension. The χ 2 test results indicated that no significant difference in the distribution of gender was found between the case and control groups (P = 0.886) ( Table 1). The mean ages of the case and control groups were 61.34 and 60.51, respectively. No significant difference was found in the distribution of mean age between cases and controls in study populations (P = 0.191) ( Table 1). There were no significant difference in triglyceride, HDL-C, EO and RDW-CV (P > 0.05) between the patients and controls. However, there were significant differences in some biochemistry and blood test indicators (total protein, albumin, globulin, total bilirubin, direct bilirubin, indirect bilirubin, uric acid, triglyceride, total cholesterol, HDL-C, LDL-C, WBC, NEUT, LYMP, EO, BASO, RBC, hemoglobin, MCV, MCH, RDW, RDW-CV, platelet, plateletcrit) between cases and controls (P < 0.05) ( Table 1). Simultaneously, we also found the mean triglyceride and BASO levels in the case group were higher than the clinical reference values and control group, suggesting that these factors may increase the risk of CHD.

Overall Analysis of NPAS4 Polymorphisms and CHD Risk
The five SNPs (rs117770654, rs117957381, rs12785321, rs117186164, and rs4466842) in NPAS4 were successfully genotyped, and the call rate of genotyping was more than 95%. The genotypes distributions of all SNPs were in line with HWE in both CHD patients and controls (P > 0.05, Table 2). We found that the allele C frequency of the rs4466842 in NPAS4 in CHD patients was higher than the healthy controls (0.442 vs. 0.389, P = 0.016). The rs4466842 was related to an increased risk of CHD (OR 1.25, 95% CI 1.04-1.49). Simultaneously, we found that the heritability of the five SNPs (rs117770654, rs117957381, rs12785321, rs117186164, and rs4466842) were 0.01%, 0.08%, 1.11%, 0.99%, and 2.37%. There was no significant association between other four SNPs and CHD risk.
We performed genetic models analysis to explore the genotype distributions and the correlation between SNPs 1 3 and CHD risk before and after adjusted with age and gender, as shown in Table 3. The results indicated that individual carrying the TT genotype of rs4466842 in NPAS4 was correlated with an increased CHD risk, compared with the CC genotype (OR 1.54, 95% CI 1.06-2.22, P = 0.022; adjusted OR 1.56, 95% CI 1.08-2.25, P = 0.018). We found that the rs4466842 was related to an increased with CHD risk in the dominant model (TT-TC vs. CC:OR 1.34, 95% CI 1.03-1.74, P = 4.70E−10; adjusted OR 1.35, 95% CI 1.04-1.75, P = 0.027) and the additive model (OR 1.25, 95% CI 1.04-1.49, P = 0.016; adjusted OR 1.25, 95% CI 1.05-1.50, P = 0.013). However, no significant correlation was found between other four SNPs and CHD risk.
In addition, we also stratified the analysis according to whether the patients had other comorbidities (diabetes or hypertension), as shown in , P = 0.009) were also association with CHD risk. However, no association between these two SNPs and CHD risk was found in patients with CHD complicated by hypertension and CHD complicated by diabetes. Insignificant association results for other SNPs (rs117770654, rs117957381, and rs117186164) were not shown.

SNP-SNP Interactions
We used the MDR to analysis the SNP-SNP interactions on the risk of CHD, as shown in Fig. 2

NPAS4 Expression Levels
In addition, we detected the NPAS4 expression levels of peripheral monocytes in the case group and the control group (Supplementary Table 1 and Fig. 3). We found that  Fig. 3. We also assessed the correlation between the SNPs (rs4466842, rs117186164 and rs12785321) associated with CHD risk and NPAS4 expression levels. Although there were no significant differences in NPAS4 expression levels between different genotypes of the three SNPs (rs4466842, rs117186164 and rs12785321) groups (P > 0.05). There are significant differences in the NPAS4 expression levels of different genotypes between the case group and the control group ((P < 0.001) (Supplementary Table 1 and Fig. 3).

Discussion
This case-control study explored the relationship between SNPs in NPAS4 and risk of CHD in the Chinese Han population. The results demonstrated that the rs4466842 was correlated with an increased risk of CHD in overall, males and age ≤ 60 years old population. The rs117186164 was related to an increased risk of CHD in the male. Moreover, rs12785321 was significantly correlated with an increased risk of CHD in the age ≤ 60 years old population. The haplotype AC in NPAS4 was significantly correlated with an increased risk of CHD. There is an interaction between these SNPs on risk of CHD. Notably, there was significant difference in the distribution of some clinical indicators level in patients between the case and control groups. NPAS4 is a number of the bHLH-PAS transcription factor family, which is involved in a wide range of physiologic and developmental events [21]. NPAS4 as an activity-dependent transcription factor which is responsible for gearing the expression of target genes involved in neuro-transmission. Previous study revealed the neuro-modulatory role of NPAS4 in crucial pathways involved in neuronal survival and neural signalling hemostasis [22]. The NPAS4 plays a neuroprotective role in ischaemic stroke by limiting progressive neurodegeneration and neuro-inflammation [23]. NPAS4 is expressed in endothelial cells, regulates VE-cadherin expression and regulates sprouting angiogenesis [24]. NPAS4 is a critical regulator of experience-dependent, structural, and functional plasticity at MF-CA3 synapses during contextual memory formation [25]. However, no study is known about the role of NPAS4 in the development of CHD. This study is the first to explore the association between NPAS4 polymorphisms and CHD risk. The results indicated that the rs4466842 in NPAS4 was associated with an increased risk of CHD; rs117186164 and rs12785321 were found to be significantly associated with increased CHD risk only in the male and the age ≤ 60 years old population, respectively. These findings suggested that age and gender are important factors that influence the risk of CHD. Simultaneously, SNP-SNP interactions analysis found that the best four-locus model was the combination of rs117770654, rs117957381, rs12785321, and rs4466842. In addition, we found that the NPAS4 expression levels in the case group was significantly lower than in the control group. The results revealed that the NPAS4 gene may play an important role in the occurrence and development of CHD.
This study is the first to explore the association between NPAS4 polymorphisms and CHD risk in the Chinese Han population. There are some limitations of our study should be mentioned. First, the study population is only the Chinese Han population and the sample size of this study is relatively small, thus the results are needed to confirm. Second, this study did not take into consideration the confounding factors such as smoking, drinking, hypertension, diabetes for CHD risk, as well as the interaction with NPAS4 polymorphisms. Third, this study only in investigated the association between five SNPs in NPAS4 and CHD risk, there may be other SNPs in NPAS4 that are associated with CHD risk but were not assessed for their potential associations. Finally, this study did not elucidate the specific mechanism of the NPAS4 polymorphisms affect the development of CHD.
In conclusion, our results indicated that polymorphisms (rs117186164, rs12785321, and rs4466842) in NPAS4 were significantly correlated with increased the risk of CHD in the Chinese Han population, and the NPAS4 expression levels was significantly different between case and control groups. However, this is the first study to explore and unclear whether those findings will be reproduced in other populations and/or different ethnicities. Therefore, further detailed association studies in larger samples are required to confirm the relationship of polymorphisms in NPAS4 and risk of CHD. And functional studies are required to explore the mechanism of NPAS4 in the development of CHD.