3 RESULTS
Demographic and clinical characteristics of both familial and sporadic cases are shown in Table 3. Germline DNA from peripheral blood leukocytes and somatic DNA from heart tissue was screened in each patient with familial and sporadic CHD, respectively.
Table 3. Demographic and clinical characteristics of familial and sporadic CHD subjects.
Characteristics Sporadic CHD (n=15)
Familial CHD (n=15)
Age ± SD, years 12.6±7.5 14.1±12.01
Male/female 7/8 6/9
Diagnosis, n
Cyanotic heart defect 3 3
Septation defect 12 12
Left-sided obstructive lesion
- -
Mixed lesion - -
Single ventricle - -
4.1 Genetic screening in familial cases
The genetic screening of familial cases revealed a total of 18 variants in the GATA4 gene, including 17 SNPs that were described previously as polymorphisms (Table 4). One variant was located in the untranslated exon 1 (−543C>T) and 1 variant in the exon 6 leading to amino acid substitution
(c.1129A>G; S377G), while 5 variants were in the intronic regions. We found 11 variants located within the 3′UTR region. The remaining identified variant was a novel deep intronic variation (IVS 4, −202C>T) in 1 patient with atrial septal defect. This variant was neither listed in public SNP databases nor in the literature; however, it was also confirmed to be present in 100 chromosomes of healthy controls. Only 1 known synonymous variant (c.63 A>G; E21E) was found in NKX2.5 gene (Table 4).
4.2 Genetic screening in sporadic cases
Mutational screening in sporadic cases showed 17 polymorphic variants in GATA4 gene (Table 4). Two sequence variants are located within exons 1
(−543 C>T) and 6 (c.1129 A>G; S377G), and 5 within intronic regions, including the unknown deep intronic variation (IVS 4, −202C>T) that was found in a patient with TOF. A total of 10 variants were identified in the 3′UTR sequences.
Only two synonymous variants were found in exons 1 (c.63 A>G; E21E) and 2 (c.543 G>A; Q181Q) of NKX2.5 gene. All nucleotide variants found in the pathologic cardiac tissue were also present in the blood sample of familial patients, which demonstrates that they all were constitutional variants.
Table 4. Genetic variants identified by mutational screening of GATA4 and NKX2.5 genes in familial and sporadic CHD patients.
Gene Position Sequence variants
Familial CHD n. of patients
Sporadic CHD n. of patients
Known/Novel variant
GATA4 Exon 1 untraslated
-543 C>T 4 2 Known
Exon 6 c.1129 A>G (S377G)
6 2 Known
IVS 2 -116 T>C 6 4 Known
IVS 2 -64 G>C 7 5 Known
IVS 4 -174 T>C 2 3 Known
IVS 4 -202 C>T 1 1 Novel
IVS 5 +56 C>A 10 11 Known
3'UTR +354 A>C 6 4 Known
3’UTR +414 T>C 0 1 Known
3'UTR +426 C>T 11 8 Known
3'UTR +517 T>C 9 8 Known
3'UTR +532 T>C 12 12 Known
3'UTR +563 C>G 7 4 Known
3'UTR +587 A>G 15 13 Known
3'UTR +852 G>A 3 4 Known
3'UTR +1158 C>T 4 1 Known
3'UTR + 1256 A>T 8 6 Known
3'UTR +1355 G>A 3 1 Known
3'UTR +1521 C>G 1 1 Known
NKX2.5 Exon 1 C.63 A>G (E21E)
8 6 Known
Exon 2 C.543 G>A (Q181Q)
0 2 Known
4.3 miRNA ≡ SNP interactions
Since the majority of SNPs found in our patients fells in the 3′UTR of GATA4, region crucial for the miRNAs’ binding, functional relevance of these variants were assessed.
Several miRNAs presented a binding for the 3′UTR of GATA4 as shown in Table 5. A ΔMFE difference between alleles ≥4 kcal/mol was obtained for the +354 A>C (miR-4299), +587 A>G (miR- 604), +1355 G>A (miR-548v, miR-139- 5p) and +1521 C>G (miR-3125, miR-3928, miR-583). The most relevant difference ΔMFE between alleles (5.74 kcal/mol) was found for miR-604 specifically targeting +587 A>G SNP. Theoretically, this miRNA presents a high affinity for the G allele at the position +587.
Figure 5 shows the predictive binding of miRNA-604 considering the difference of ΔMFE between the alleles and its MFE secondary structures elaborated by RNAcofold. In addition, more miRNAs were predicted to bind to 8 polymorphic targets and their ΔMFEtot is shown in Table 6.
The +1521 C>G SNP showed the highest ΔMFEtot (21.66 kcal/mol) and, therefore, was more likely to have a stronger effect on GATA4 posttranscriptional regulation. Figure 6 illustrates the predictive binding of miR- 583, miR-3125, miR-3928, targeting the +1521 C>G SNP and their MFE secondary structures.
Table 5. MicroRNAs targeting the identified variants in the3’UTR of the GATA4 gene.
SNPs SNP position (3’UTR)
miRNA ΔMFE
wild type
ΔMFE variant
|ΔΔMFE|
rs867858 +354 A>C miR-2117 -17.13 -14.45 2.68 miR-4299 -6.61 -13.60 6.99 rs1062219 +426 C>T miR-324-5p -22.40 -20.37 2.03 rs884662 +517 T>C miR-590-3p -4.69 -1.32 3.37
miR-4328 -5.83 -8.05 2.22
rs904018 +532 T>C miR-643 -16.92 -12.54 4.38 miR-592 -10.84 -12.83 1.99 miR-581 -11.01 -13.00 1.99 miR-3650 -12.32 -14.31 1.99 rs12825 +563 C>G miR-3137 -23.17 -17.04 6.13 miR-1274b -17.12 -13.42 3.70 rs804291 +587 A>G miR-604 -11.72 -17.21 5.49 rs11785481 +1158 C>T miR-3173-5p -20,96 -18,96 2,00 miR-4722-3p -16,01 -14,01 2,00 miR-4763-5p -14,25 -12,33 1,92 miR-3162-3p -11,77 -14,14 2,37 miR-5195-5p -15,02 -13,40 1,62 rs12458 +1256 A>T miR-362-5p -13.87 -10.47 3.40 miR-526b -13.90 -11.06 2.84 miR-502-5p -14.11 -9.39 4.72 miR-500b -10.86 -8.76 2.10 miR-4279 -14.36 -12.69 1.67 miR-556-5p -12.32 -13.74 1.42 rs1062270 +1355 G>A miR-548v -12.57 -7.27 5.30 miR-139-5p -12.07 -6.02 6.05 rs3203358 +1521 C>G miR-3125 -12.52 -7.35 5.17 miR-877 -14.10 -10.83 3.27
miR-613 -7.50 -3.90 3.60
miR-3928 -10.12 -4.95 5.17
miR-583 -9.62 -4.45 5.17
miR-483-5p -12.79 -11.97 0.82 miR-208a -6.97 -10.71 3.74
Figure 5. Predicted binding of miR-604 targeting the +587 T>C (A>G) SNP.
[R] represents the SNP. Dashes represent base matches. Minimum free energy (MFE) and secondary structures are reported for both wild type (WA) and mutated (MA) alleles. miRNA is in red and GATA4 3’UTR is in green.
Table 6. ΔMFEtot for SNPs binding more miRNAs.
SNPs SNP position |ΔMFEtot| miRNAs
rs3203358 +1521 C>G 21.66 miR-3125; miR-877, miR- 613, miR-3928, miR-583, miR-483-5p, miR-208a
rs12458 +1256 A>T 14.85 miR-362-5p, miR-526b,
miR-502-5p, miR-500b, miR-4279, miR-556-5p rs1062270 +1355 G>A 11.03 miR-548v, miR-139-5p rs11785481 +1158 C>T 9.91 miR-3173-5p, miR-4722-5p,
miR-4763-5p, miR-3162-3p, miR-5195-5p
rs904018 +532 T>C 9.64 miR-643, miR-592, miR-581, miR-3650
rs12825 +563 C>G 6.98 miR-3137, miR-1274b
rs867858 +354 A>C 6.98 miR-2117, miR-4299
rs884662 +517 T>C 3.19 miR-590-3p, miR-4328
Figure 6. Predicted binding of miR-3125, miR-3928 and miR-583 targeting the +1521C>G SNP. [S] represents the SNP. Dashes represent base matches.
[R] represents the SNP. Dashes represent base matches. Minimum free energy (MFE) and secondary structures are reported for both wild type allele (WA) and
mutated allele (MA). miRNA is in red and GATA4 3’UTR is in green.
4.4 Functional effect of the +1521C>G SNP on miR-583 binding
We investigated if the +1521 C>G SNP, showing the highest ΔMFEtot (21.66 kcal/mol), has a functional effect on miRNA target interaction by performing a luciferase reporter assay.
HCT116 Dicer−/− cells were co-transfected with luciferase constructs bearing the +1521 C allele or G allele and increasing doses of miR-583, one of the miRNAs with the high ΔMFE binding at the +1521 SNP, in the presence of Renilla reporter gene as internal standard. Negative control miRNA mimic (miR- NC) was also transfected for comparison. The results showed that miR-583 decreased the luciferase activity in cells transfected with +1521 C wild type variant of GATA4 3′UTR, demonstrating for the first time that GATA4 is a miR- 583 target (Figure 7). More interestingly, miR-583 was unable to modify the
luciferase activity in cells transfected with the +1521G variant, suggesting that C>G variation in the miR-583 seed-match sequence strongly affected miR-583 binding.
Figure 7. Luciferase Report Assays to measure the binding ability of miR- 583 on GATA4 3’UTR containing either +1521 C or G alleles. A) Schematic representation of constructs used in the luciferase assay. B) Luciferase activities from co-transfected HCTT116 Dicer-/- cells with pGATA41521G and pGATA41521C reporter vectors and miR-583 mimic at indicated concentration.
Each values, normalized to Renilla values, were expressed as relative changes with respect to the value of the negative control (miR-NC 60nM).
4.5 Case-control study
The four SNPs (+1158 C>T, +1256 A>T, +1355 G>A, +1521 C>G) with the highest |ΔMFEtot| = 9.91, 14.85, 11.03, 21.66 kcal/mol (respectively), were located in a region of 970pb within the 3’UTR of GATA4 gene. The association between the CHD risk and these four SNPs was assessed through a case- control study of 146 CHD patients and 265 control subjects. Demographic and clinical characteristics of the study population are shown in Table 7. The genotype distribution of two SNPs +1158 C>T and +1521C>G was significantly different between cases and controls. Specifically, the frequencies of +1158 CC, CT, and TT genotypes were 84%, 15% and 1% in patients compared with 73%, 24%, and 3% in controls (p<0.04), while frequencies of +1521 CC, CG, and GG genotypes were 59%, 33%, and 8% in patients compared with 52%, 32%, and 16% in controls (p<0.04). Conversely, no significant difference in genotype distribution and allele frequency between cases and controls was observed for the +1256 A>T and +1355 G>A polymorphisms (Table 7).
Logistic regression analysis revealed that the mutated T allele of +1158C>T SNP was associated with a decreased risk for CHD compared to the C wild- type allele (OR 0.53, 95% CI 0.32-0.89; p=0.014). Similarly, the GG genotype for the +1521 C>G polymorphism was associated with a lower risk of CHD (OR
= 0.43, 95% CI 0.22–0.87, p= 0.013) under a recessive model of inheritance, validating the results obtained in the our previous study (Table 8).
Table 7. Demographic and clinical characteristics of the case-control study population.
Characteristics CHD Population (n=146)
Controls (n=265)
Age ± SD, years 6.68±7.79 newborns
Male/female 73/73 147/118
Diagnosis, n
Cyanotic heart defect 56 -
Septation defect 52 -
Left-sided obstructive lesion
6 -
Mixed lesion 30 -
Single ventricle 2 -
Table 8. Genotype distribution of GATA4 polymorphisms in CHD cases and controls.
SNP Genetic Model
p-value Exp (coef.) 95%Lower 95%Upper
+1158 C>T CC vs CT+TT 0.014 0.53 0.32 0.89
+1256 A>T AA vs AT+TT 0.33 0.82 0.54 1.22
+1355 G>A GG vs GA+AA 0.78 0.92 0.51 1.66
+1521 C>G CC+CG vs GG 0.013 0.43 0.22 0.87
4.6 Linkage Disequilibrium and haplotype analysis
The pairwise LD value (D’), corrected for allele frequencies (r2), showed that many loci are in strong disequilibrium (Figure 8).
The haplotype analysis of the four selected polymorphisms reveled 6 haplotype associations in cases and control group, as shown in Table 9. The haplotype T- T-G-C (8% in CHD cases and 13% in the control group) showed a protective role in the development of CHD (OR 0.59, 95% CI 0.36-0.96, p=0.035) compared to the most common haplotype C-A-G-C. Interestingly, the C-A-A-C haplotype, really uncommon in control (0.3%) compared to CHDs (2.4%), was associated with a roughly 4-fold increased risk of CHD (4.33 95% CI 1.1-12.5, p<0.049).
Figure 8. Pairwise Linkage Disequilibrium estimated in CHD population compared to the controls.
Table 9. Haplotype distribution of the four investigated GATA4 SNPs.
No +1158 C>T
+1256 A>T
+1355 G>A
+1521 C>G
Control freq.*
CHD freq.*
OR (95% IC)
p- value
1 C A G C 0.36 0.44 Reference -
2 C A G G 0.23 0.21 0.80 (0.55-1.15) 0.23
3 C T G C 0.17 0.21 0.98 (0.65-1.46) 0.91
4 T T G C 0.13 0.08 0.59 (0.36-0.96) 0.035
5 C A A G 0.07 0.04 0.54 (0.26-1.10) 0.092
6 C A A C 0.003 0.024 4.31 (1.1-12.5) 0.049
4.7 High-throughput DNA sequencing
In order to explore the presence of mutations that might contribute to the CHD
susceptibility, we investigated 17 genes, known to play a role in the CHD pathogenesis, by a high-throughput sequencing. We sequenced, in a single run, a cohort of 12 CHD samples (4 familial and 8 sporadic CHD subjects) by using a MiSeq Illumina platform.
Average amplicon coverage for a cumulative target region of 76,379 pb was 1600X. In terms of individual gene coverage, 7 genes were covered 100%.
Except for three target regions in the ELN gene (with a coverage <50%), all the other target regions in the remaining 10 genes were covered >60%.
In a global analysis of all 12 patients, initial genotype calling generated 2305 distinct genetic variants (797 in the 4 familial CHD patients). Among these variants, 210 were classified as non-synonymous variants by in-silico analysis (148 in sporadic patients and 62 in the familial patients). Specifically, after
additional filters (as above described) we identified 5 rare, non-synonymous, exonic variants in 4 sporadic patients and 3 ones in 2 familial patients. These variants were likely the most involved in the CHD pathogenesis (Table 10).
Table 10. Mutations identified by TSCA sequencing in patients enrolled in the CHD cohort.
Case Phenotype Gene Chr.
position Exon Mutation Protein
substitution SIFT PP2
S.2 VSD NOTCH1 LEFTY2
139412207 226076597
8 1
c.C1438A c.T170A
p.P480T p.V57E
0.05 0.03
0.8 1 S.3 TOF GDF1 18981414 7 c.A1025G p.N342S 0.03 0.9 S.5 TGA MYH6 23871938 11 c.A970T p.I324F 0.04 0.5 S.12 VSD NOTCH1 139413180 6 c.G962A p.C321Y 0.01 1 F.13 TOF CFC1 131355133 5 c.T406A p.C136S 0.01 1 F.14 TOF LEFTY2
NOTCH1
226076607 139401396
1 23
c.C160T c.T3673C
p.P54S p.C1225R
0.05 0.01
1 1
S= sporadic CHD; F= familial CHD; VSD= ventricular septal defect; TOF= tetralogy of Fallot;
TGA= transposition of the great arteries
