A genetic variant in a homocysteine metabolic gene that increases the risk of congenital cardiac septal defects in Han Chinese populations

Abstract

Elevated homocysteine levels are known to be a risk factor for congenital cardiac septal defects (CCSDs), but the mechanism underlying this effect is unknown. The genetic variants that were significantly associated with circulating homocysteine concentrations have been systematically identified through the genome-wide association studies of one-carbon core metabolites. To examine the role of the genome-wide significant homocysteine related variants in the occurrence of CCSDs, we investigated the association between these variants and CCSDs in Han Chinese populations. Five variants of the genome-wide significant homocysteine-related genes were selected for analysis in two stages of case-controlled studies with a total of 904 CCSD patients and 997 controls. SYT9 expression was detected in human cardiovascular tissue using qRT-PCR. The intronic variant rs11041321 of the SYT9 gene was associated with an increased risk of developing CCSDs in both the separate and combined case-controlled studies. Combined samples from the two stage cohorts had a significant elevation in CCSD risk for the T allele (OR = 1.43, P = 2.6 × 10 ), CT genotype and TT genotype (CT: OR = 1.30, TT: OR = 2.21; P = 1 × 10 ) compared with the wild-type C allele and CC genotype, respectively. The risky T allele carriers exhibited decreased SYT9 mRNA expression, compared with wild-type C allele carriers. The intronic SYT9 variant rs11041321, which exhibits a significant genome-wide association with circulating homocysteine, was associated with the occurrence of CCSDs. This finding helps to characterize the unexpected role of SYT9 in homocysteine metabolism and the development of CCSDs, which further highlighted the interplay of diet, genetics, and human birth defects. © 2017 IUBMB Life, 69(9):700-705, 2017.

Gestational palmitic acid suppresses embryonic GATA-binding protein 4 signaling and causes congenital heart disease

“…Our study found that increased maternal PA levels caused VSD and ASD phenotypes in mice, which was in accordance with the maternal hyperhomocysteine-induced and GATA4 mutation-induced CHD phenotypes in humans. 42 , 43 , 44 , 45 , 46 These phenomena suggest that PA signals have a crosstalk with homocysteine signals and synergistically regulate GATA4 signals. Besides septal defects, GATA4 mutations have also been reported to be associated with complex CHDs.…”

Epigenomic signature of major congenital heart defects in newborns with Down syndrome

“…Although we did not find any significant DMRs associated with DS-CHD after FDR correction, the nominally significant DMRs were enriched for genes implicated in cardiac processes, suggesting that at least some of the DMRs may reflect true epigenetic mechanisms associated with DS-CHD development. In particular, Males Only DMRs selected by machine learning feature selection were able to distinguish CHD from non-CHD samples and frequently mapped to genes associated with CHDs or cardiomyopathies, including FUNDC1 [71], ETV5 [72,73], SYT9 [74], CAMTA1 [75], GRIA4 [76], and IGF1R [77][78][79][80]. Additionally, DMRs that contributed to enrichment for heart-related gene ontology terms included TNNI3, a cardiac-specific gene that codes for cardiac troponin I, whose absence leads to severe pediatric cardiomyopathy [81], and GATA4, which encodes a member of the GATA family of zinc finger transcription factors, are essential for mammalian cardiac development, and whose sequence variants have been identified in individuals with CHDs [82].…”

Epigenomic signature of major congenital heart defects in newborns with Down syndrome

“…Although we did not find any significant DMRs associated with DS-CHD after FDR correction, the nominally significant DMRs were enriched for genes implicated in cardiac processes, suggesting that at least some of the DMRs may reflect true epigenetic mechanisms associated with DS-CHD development. In particular, Males Only DMRs selected by machine learning feature selection were able to distinguish CHD from non-CHD samples and frequently mapped to genes associated with CHDs or cardiomyopathies, including FUNDC1 [ 71 ], ETV5 [ 72 , 73 ], SYT9 [ 74 ], CAMTA1 [ 75 ], GRIA4 [ 76 ], and IGF1R [ 77 – 80 ]. Additionally, DMRs that contributed to enrichment for heart-related gene ontology terms included TNNI3 , a cardiac-specific gene that codes for cardiac troponin I, whose absence leads to severe pediatric cardiomyopathy [ 81 ], and GATA4, which encodes a member of the GATA family of zinc finger transcription factors, are essential for mammalian cardiac development, and whose sequence variants have been identified in individuals with CHDs [ 82 ].…”