Study On Differently Expressed Plasma MicroRNA Of Congenital Heart Disease And Its Association With GATA4 Gene Target Sequence Polymorphism

BackgroundThe birth defects is an important public heath problem and causes serious economic, spiritual and medical burden to individuals, families and society. Congenital heart diseases (CHDs) is one of the commen type of the birth defects and the CHD is a cardiovascular malformation caused by abnormal development of the fetal heart and the great vessels. Its incidence is 40.95/10000 in China but 9.1%o (95%CI:9.0‰～9.2‰) in the other countries. CHDs is one of the most common types of congenital malformation in children, and is also one of the main causes of neonatal and infant mortality. The common CHDs include atrial septal defect (ASD), ventricular septal defect (VSD), patent ductus arteriosus (PDA), tetralogy of Fallot (TOF), transposition of the great arteries (TGA), pulmonary valve atresia (PA), coarctation of the aorta (COA) and tricuspid atresia (TA). Among them, VSD is one of the most common, accounting for about 20% of CHDs. VSD is mainly caused by left and right ventricular septal defect-induced abnormal traffic. Despite the fact that its embryology and physiology have been elucidated, its etiology and pathogenesis are unclear.A microRNA (microRNA) is a post-transcriptional regulatory factor and small single-stranded non-coding RNA molecule,18-22 nucleotides in length. It can pair with 3’non-coding regions of a target gene’s mRNA, and negatively regulate expression of target genes at the posttranscriptional level. It can regulate cell growth, metabolism, differentiation and apoptosis, participating in the growth of the living organism. microRNA plays an important role in many physiological and pathological processes. microRNA genes represent only 1% of human genes. However, sequence analysis suggests that microRNA can potentially regulate 30% of human genes through complex regulatory networks. Recent studies showed that microRNA is involved in embryonic heart development, morphogenesis of the heart, and myocardial cell growth and differentiation, playing an important function in the occurrence and development of cardiovascular disease. It was reported that microRNA is associated with the pathogenesis of CHDs, and it plays an increasingly important role in diagnosis and treatment of heart-related diseases. The microRNA stably expressed in body fluids plays an important role in cardiovascular diseases and tumor occurrence, and circulating microRNA can be used as a potential biomarker for disease diagnosis as it is very stable in serum and cannot be degraded by RNA degrading enzymes. microRNA microarray analysis for gene expression profiles is one of the most important methods used to screen and study the occurrence and development of disease-associated specific microRNAs. We used it here to screen differentially expressed microRNAs in the plasma of patients with VSD and that of VSD-free controls. Meanwhile, quantitative real-time fluorescent polymerase chain reaction (RT-PCR) was used to verify the reliability of microRNA microarray analysis in detecting differentially expressed microRNAs. In addition, we predicted downstream target genes regulated by differentially expressed microRNAs using target gene prediction software, and further analyzed its biological function. It is hoped that this study will provide valuable information for clarifying the pathogenesis of CHDs at the molecular level, and the study can be to identify a plasma microRNA expression profile that can serve as a novel diagnostic biomarker for CHDs detection and to assess its clinical applications in monitoring disease progression.The causes of CHDs are complex, and are not folly understood. Most CHDs (90%) may be related to genetic and environmental factors. A large number of studies have showed that the genetic polymorphism of population can affect the function of related genes and play an important role in disease susceptibility. In recent years, the human genome project has made great achievements. On this basis, the association study between single nucleotide polymorphism and complex disease had made tremendous progress. Association study has also become hot in the post-genomic era. Therefore, based on the sporadic samples in Shandong province and corresponding clinical dates to explore the interaction of CHDs genetic susceptibility, and it is helpful to understand the etiology and pathogenesis of CHDs. In addition, it is very important for improving the prevention and diagnosis CHDs by searching for CHDs susceptibility genetic markers.microRNA can bind to the 3’untranslated region (3’UTR) of its target gene mRNA result in either mRNA degradation or protein translation inhibition. microRNAs regulate the expression of target genes by binding the 3’UTR using its seed region which is conserve in mammalian.Assoeiation studies between core genes and susceptibility of CHDs have pointed out that some pathogenic polymorphism. However, the world wide association results are not pretty consistent, and coding region variants have been extensively explored, while the noncoding variants, which can regulate the dosage of the CHDs associated gene expression, have been largely ingored. Then we investigate the genetic susceptibility of CHDs using the SNPs of microRNA binding sites, and study the underline mechanism of the positive SNPs.Objectives1.To screen and identify the aberrantly expressed plasma microRNAs in VSD compared with matched non-VSD, and to evaluate the value of plasma microRNAs as the identification molecular marker of CHDs, try to figure out the potential role of microRNA as a new molecular marker applied for clinical screening.2.By a thoroughly searching and analyzing of the bio-informatic study, to explore the target genes of differentially expressed plasma microRNAs and their common pathway with corresponding microRNAs and its role in the development of CHDs; to explore gene expression is associated with SNPs within microRNA binding site. the result would contribute to the microRNAs regulating mechanisms, and provide the theoretical guidance and experimental evidence for future gene therapy of CHDs.3.To interrogate SNPs that are located in the correlative microRNAs binding site at the 3’UTR of the GATA4 gene and to determine whether these SNPs are assoeiated with CHDs risk, and then functionally validate SNP rs3203358, which is located in the miR-583 binding site in the 3’UTR of GATA4. Finally, to studied the important role of GATA4 in CHDs and the significance in clinical medicine.Methods1.Patients or participantsThe study was approved by the Ethics Committee of the two hospitals and performed with the written informed consent of all the patients and guardians.Patients with CHDs and CHDs-free participants were selected from the Children’s Hospital of Jinan City (Shandong, China) and the Maternity and Child care Hospital of Taian(Shandong, China) between June 2012 and November 2013. Patients with VSD were enrolled from surgical cardiovascular patients with CHDs diagnosed by ultrasound technique or by intraoperative observation. All the patients had CHDs but without other deformities. Meanwhile, the CHD-free participants in the control group were selected from the centre of health examination. They were from the same areas as the patients with CHDs, but had no CHDs genetic history.1)The detection of plasma microRNAs differentially expressed spectrum with 85 CHDs and 80 CHDs-free participants.In the first place, Three patients with VSD and VSD-free participants were selected for microRNAs microarray analysis; the second, 20 patients with VSD and 15 VSD-free participants were selected to verify the differentially expressed microRNAs using RT-PCR; finally,62 patients with VSD and 62 VSD-free participants were selected to verify the differentially expressed microRNAs using RT-PCR again.2)309 patients with VSD and 408 CHDs-free participants were selected to identify functional polymorphisms within microRNA binding site using Sanger sequence and the risk of CHDs.2.Blood sample collection and plasma preparationThe fasting blood sampling was performed in the morning. Venous blood (4 mL) was collected from each participant in an ethylenediaminetetraacetic acid (EDTA) tube, allowed to stand for 10 min, and then centrifuged at 1500 rpm for 10 min. The upper light yellow liquid was harvested, which was plasma. This was then aliquoted into RNase-free epoxy resin tubes and kept at -80℃.3.microRNA microarrayThree VSDs and three control plasma samples performed Micrornas chip analysis by KangChen Bio-tech Inc. The threshold value for differentially expressed microRNAs was a fold change>1.5 with a value of P<0.05. The raw and normalised microRNA data were available through GEO accession number GSE54675. The candidate microRNAs were further filtered on the basis of expression levels.4.qRT-PCRTotal RNA was polyadenylated and reverse transcribed to cDNA. Real-time PCR was performed in duplicate measurements using SYBR Green PCR kit. The expression levels of candidate microRNAs were normalized to miR-93, and were calculated utilizing the 2-△△Ct method. H2O was used as the negative control.5. foundation and validation of diagnostic model for CHDTo select 8 miRNAs candidates and apply logistic regression model to estimate the risk of being diagnosed with CHD. Validate the diagnostic model in an independent cohort with same design to judge the general efficiency of diagnose CHD with the ROC curve by MedCalc.6.target gene prediction and SNPs screenThe microRNA expression profiling was analysed by bioinformatics methods including to enquiry the target genes of microRNA in the internet with the PieTar, Targetsean and miradna, GO and Pathway analysis. Use the Cytoscape to structure the target gene networks, and through the data mining in stages candidate genes of mirRNA target sequence to analysis the functional SNPs and associated miRNAs.7.Sequencing and detecting the GATA4-3’UTR SNPsTo investigate the correlation between the eight single nucleotide polymorphisms (SNPs) in the 3’UTR of GATA4(rs867858, rs1062219, rs884662, rs904018, rs12825, rsl2458, rsl062270 and rs3203358) and CHDs development by Sanger sequence and constructed the haplotype in CHD and CHD-free, to compare the frequency of different genotype and allele by the chis quare test and unconditional logistic regression models. The odds ratio((OR)and 95% confidence interval(CT) were used to indicate relative risk to CHD and build a haplotype.8.Dual luciferase reporter gene experimentWe constructed reporter plasmids with the mutant and wild-type GATA4 linked to Luciferase (pMIR-GATA41521c and pMIR-GATA41521G). Besides, we also we constructed miRNA-583 mimic recombinant plasmid, which transiently co-transfected Human Embryonic Kidney 293 cell (HEK-293) with \MXRrGATA4\1521c and pMIR-GATA41521G respectively. Using a dual-luciferase reporter system to experimental validation whether or not miR-583 interacts with the 3’UTR of GATA4 1521C>G mRNA.Results1.Plasma microRNA expression determined by microRNA microarray analysis and verificationThe microRNA expression patterns in the plasma of the three patients with VSD and the three VSD-free controls were detected using microRNA microarray analysis by miRCURY LNA Array (version 11.0) to preliminarily identify microRNA expression differences between the patients with VSD and the VSD-free controls. Results showed that compared with the VSD-free controls, the patients with VSD had 36 differentially expressed microRNAs (P<0.05) with 15 upregulated in their expression and 21 downregulated in their expression. Quantitative RT-PCR assays were performed to validate the different expression levels of these 8 microRNAs in plasma of 20 VCD patients and 15 controls, and 62 VCD patients and 62 controls. The results showed that 3 of the 8 microRNAs were not differentially expressed between the VCD patients and the controls; the remaining 5 microRNAs (let-7e-5p, miR-155-5p, miR-222-3p, miR-433 and miR-487b) were differentially expressed between VCD samples and control samples that can be as a biomarker for VSD.2.The diagnostic value of VSD plasma microRNAsArea under the receiver operating characteristic curve (AUC) was used to evaluate diagnostic accuracy of plasma microRNAs(let-7e-5p, miR-155-5p, miR-222-3p, miR-433 and miR-487b), the AUC between 0.678 and 0.832. The result showed that miR-222-3p yielded AUC of 78.32%. The AUC for the 5 microRNAs panel was 95.3% (sensitivity=83.9% and specificity=95.2%), and can improve the efficiency of the diagnosis of VSD. The AUC for 3 microRNAs panel(let-7e-5p, miR-155-5p and miR-222-3p) was 91.0% (sensitivity=82.3% and specificity=90.3%),closing to the AUC of the 5 microRNAs. Joint three VSD diagnosis of microRNAs, more valuable in clinic.3.Target genes of 15 in 36 microRNAs were predicted in three databasesThe target genes of the 36 differentially expressed microRNAs in the VSD and control groups were predicted using three databases including targetscan, mirbase, and Miranda. Among the 36 microRNAs,15 microRNAs corresponded with target genes across three databases.4.GO enrichment analysis and pathway analysis for target genesThe target genes predicted from patients with VSD may be involved in the pathogenesis of the VSD. GO enrichment analysis revealed that these differentially expressed microRNAs were enriched in cardiac right ventricle morphogenesis. The target genes NOTCH1, HAND1, ZFPM2, and GATA3 had the most enriched GO functions, and were related with cardiac right ventricle morphogenesis. They were regulated by let-7e-5p, miR-222-3p and miR-433, which were downregulated in the plasma of patients with VSD (P<0.05). Pathway analysis showed that these target genes were mainly involved in 14 KEGG signaling pathways such as MAPK signaling pathway, correlating with VSD, and the key genes GATA4 cause our attention.5.relationship between GATA4-3’ UTR-SNPs and CHDs susceptibilityWe analyzed 8 SNPs of GATA4 in the microRNA and found that the frequencies of alleles and genotypes, there wew 6 SNPs(rs867858A> C, rs884662T> C, rs12825 C>G, rs12458A> T, rs3203358C> G and rs904018T> C) were significantly different between healthy controls and CHDs patients (P<0.05). Among them, rs867858A> C and rs884662T> C might be the most important risk factors for CHDs. Compared with the rs867858A/A genotype, the individuals with rs867858A/C genotype (OR=1.428,95%CI:1.028-1.982) and rs867858(A/C+C/C) genotype carriers (OR=2.496,95%CI:1.553-0.672) had a higher risk of suffering from CHDs significantly. Compared with the rs884662T/T genotype, the individuals with T/C(OR=1.70,95%CI:1.20-2.409) and C/C genotype (OR=4.628,95%CI: 2.273-9.423) and C allele carriers (OR=2.124,95%CI:1.615-2.794) had a higher risk of suffering from CHDs significantly. rs12458A> T, rs3203358C> G and rs904018T > C might be the most important protective factors for CHDs. Compared with the rs12458A/A genotype, the individuals with rs12458A/T genotype (OR=0.612,95%CI: 0.396-0.939) and rs 12458T/T genotype carriers (OR=0.423,95%CI:0.266-0.672) had a lower risk of suffering from CHDs significantly. Compared with the rs904018T/T genotype, the individuals with T/C(OR=0.529,95%CI:0.338-0.827) and C/C genotype (OR=0.261,95%CI:0.166-0.412) and C allele carriers (OR=0.481,95%CI: 0.387-0.599) had a lower risk of suffering from CHDs. Compared with the rs3203358C/C the individuals with C/G(OR=0.699,95%CI:0.508-0.962) and G/G genotype (OR=0.469,95%CI:0.257-0.854) and G allele carriers (OR=0.673,95%CI: 0.527-0.860) had a lower risk of suffering from CHDs significantly. rsl2825C> G, the OR of G allele carriers is 0.770(95%CI:0.620-0.956,P<0.001), but the genotype of C/G(OR=0.950,95%CI:0.605-1.492,P=0.824) and G/G(OR=0.645,95%CI: 0.406-1.025,P=0.062) might have nothing with CHDs. There were no significant differences of allelic and genotypic frequency distribution of rs1062219, rs1062270 and rs12825(P>0.05).6. linkage disequilibrium test and haplotype analysislinkage disequilibrium test (LDT) results show that, rsl2458-rsl2825-rs867858 close linkage (D’for the 0.81-0.94), rs904018-rs3203358 moderate linkage (D’for 0.95). Haploview show that rs867858, rs904018 and rs884662 are the tagSNPs. haplotype analysis of these sets of the three tagSNPs showed that, ATC haploty(OR=0.581,95%CI:0.567-0.986) and the CCT haplotype(OR=3.698,95%CI: 2.500-5.471). There were difference between the CHDs group and the control group. ATC is the protective haplotype, and CCT is the dangerous haplotype.7.SNP rs3203358 associated with CHDs by affecting the regulation of miR-583 in GATA4.SNP is located in the potential miR-583 binding site by bioinformatic tools. SNP rs3203358C/G affected the activity of luciferase by luciferase reporter assay, This SNP C allele may prevent miR-583 from binding to GATA4 mRNA, resulting in altered regulation of GATA4 expression and increased CHDs risk and.Conclusions1.There are stable expressed microRNAs in human plasma. These characteristics make microRNAs qualified to serve as potential molecular biomarkers, and we found a plasma microRNA panel by screening in high output microarray andvalidating in large sample size cohort that has considerable clinical value in diagnosing VSD. It has excellent performance in discriminating VSD patients from healthy.2.This study analyze the bioinformatics of cellular functions and pathways in the target gene affected by differently expressed microRNAs, screening out of 3 key genes(NOTCHl/GATA3/GATA4),11 SNPs and 23 related miRNAs, which lays foundation for further studies on biological interpretation of microRNAs profiling data in CHDs.3. Six snps of GATA4-3’UTR were associated with the occurrence of CHDs, S867858A> C and rs884662T> C are the dangerous the allele; rs12458A> T, rs3203358C> G and rs904018T> C allele may play a protective role in the occurrence of colorectal cancer. Analysis shows that ATC is the protective haplotype and CCT is the dangerous haplotype.4.The microRNA plasmid pMIR-GATA4-3’UTR (miR-583) was constructed successfully. GATA4 is indeed a target of miR-583.