GATA6 loss-of-function mutation contributes to congenital bicuspid aortic valve

Xu, Ying‐Jia; Di, Ruo-Min; Qiao, Qi; Li, Xiumei; Huang, Ruixuan; Xue, Song; Liu, Xingyuan; Wang, Juan; Yang, Yi‐Qing

doi:10.1016/j.gene.2018.04.018

Cited by 39 publications

(33 citation statements)

References 44 publications

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“…GATA6 mutations in humans also contribute to different CHD types, such as VSD, TOF, and conotruncal heart defects (Kodo and Yamagishi, 2010;Zheng et al, 2012;Wang et al, 2014b;Xu et al, 2018). This study also revealed that GATA6: rs143085291 increased the risk of CHD.…”

Section: Discussionsupporting

confidence: 58%

“…The knockout of these genes could lead to different types of CHDs in mice (Dai, 2002;Cai et al, 2003;Dodou, 2004;Phan et al, 2005;Takeuchi, 2005;Vong et al, 2006;Tsuchihashi et al, 2011). Further studies revealed that the mutations in SHF genes played important roles in human CHDs (Huang et al, 2017;Wang et al, 2017;Li et al, 2018a;Xu et al, 2018;Zhang et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…Although mutations of genes such as GATA4, GATA6, and TBX1 induce various CHDs in humans (Chen et al, 2016;Xu et al, 2018;Zhang et al, 2018), the associations of SHF intronic variations with CHDs remain unclear. This study revealed several intronic SNPs in the gene of SHF associated with CHDs.…”

Section: Introductionmentioning

confidence: 99%

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Intronic Polymorphisms in Gene of Second Heart Field as Risk Factors for Human Congenital Heart Disease in a Chinese Population

Wang

Nie²,

Fan

et al. 2019

DNA and Cell Biology

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Transcriptional factors and signaling factors in the second heart field (SHF) contribute to cardiac development. However, the associations of intronic gene variants in the SHF with congenital heart disease (CHD) remain ununderstood. Ten single nucleotide polymorphisms (SNPs) from our previous sequencing data were selected and then genotyped in 383 CHD patients and 384 healthy controls in a Chinese population. Genotype analyses revealed that minor alleles in TBX1: rs12165908 C > G [odds ratio (OR) = 2.64; 95% confidence interval (CI) = 1.87-3.73, p = 3.03 • 10-8 ] and GATA6: rs143085291 C > T (OR = 2.49; 95% CI = 1.18-5.29, p = 0.01) increased CHD risk significantly. Meanwhile, FGF10: rs78454549 T > C and GATA4: rs13275657 A>G polymorphisms were significantly associated with increased risk of simple CHDs. The minor allele C in GATA4: rs17153694 T > C increased the risk of tetralogy of Fallot, whereas minor alleles in TBX1: rs41298006 G>A, FGF10: rs75629618 C>T, FGF10: rs10461755 G>A, FGF10: rs75632187 A>G, and FGF10: rs12518964 G > A were associated with increased risk of single ventricle. The minor allele T in rs143085291 in GATA6 enhancer decreased the transcription level in luciferase assay. Our findings suggest that intronic SNPs in transcriptional factors and signaling factors in the SHF are significantly associated with increased risk of different CHD types.

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Section: Discussionsupporting

confidence: 58%

Section: Introductionmentioning

confidence: 99%

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Intronic Polymorphisms in Gene of Second Heart Field as Risk Factors for Human Congenital Heart Disease in a Chinese Population

Wang

Nie²,

Fan

et al. 2019

DNA and Cell Biology

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“…In contrast, GATA6 seems more likely to be relevant to BAV. GATA6 variants have been reported in patients with BAV [161,174,175] and these have been at least partially validated, in some cases by in vitro assays (showing that patient variants had reduced transcriptional activity; [174]) and importantly by knocking out Gata6 in mice and showing that BAV results [161]. Of relevance to this review, it was also shown that knockout of Gata6 solely in SHF progenitors was enough to recapitulate the BAV seen in total knockouts [161], highlighting the importance of this lineage in the development of the arterial valve leaflets.…”

Section: The Genomics Of Bavmentioning

confidence: 99%

New Concepts in the Development and Malformation of the Arterial Valves

Henderson

Eley

Chaudhry

2020

JCDD

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Although in many ways the arterial and atrioventricular valves are similar, both being derived for the most part from endocardial cushions, we now know that the arterial valves and their surrounding structures are uniquely dependent on progenitors from both the second heart field (SHF) and neural crest cells (NCC). Here, we will review aspects of arterial valve development, highlighting how our appreciation of NCC and the discovery of the SHF have altered our developmental models. We will highlight areas of research that have been particularly instructive for understanding how the leaflets form and remodel, as well as those with limited or conflicting results. With this background, we will explore how this developmental knowledge can help us to understand human valve malformations, particularly those of the bicuspid aortic valve (BAV). Controversies and the current state of valve genomics will be indicated.

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“…Although only a single prospective study has specifically addressed the deleterious genetic variants in BAV root phenotype patients, several recent studies analyzed the impact of genetic abnormalities in the whole BAV population. Novel deleterious loss-of-function mutations were identified in GATA4, GATA6, and NKX2.5 genes and all showed an association with enhanced susceptibility to a BAV, thus providing insight into the molecular mechanisms underlying the BAV disease [ 33 , 34 , 35 ]. Interestingly, all of the identified mutations did not correlate with the specific BAV aortic phenotype, thus questioning their impact on the aortopathy.…”

Section: Bav–the Clinical Perspectivementioning

confidence: 99%

Novel Approaches for BAV Aortopathy Prediction—Is There a Need for Cohort Studies and Biomarkers?

Girdauskas

Petersen

Neumann³

et al. 2018

Biomolecules

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Bicuspid aortic valve (BAV) disease is the most common congenital malformation of the human heart with a prevalence of 1–2% in the general population. More than half of patients with a BAV present with a dilated proximal aorta (so-called bicuspid aortopathy) which is associated with an enhanced risk of life-threatening aortic complications. Up to now, the pathogenesis of bicuspid aortopathy as well as the risk stratification of aortic complications has not yet been sufficiently clarified. Recent findings have shown that bicuspid aortopathy features phenotypic heterogeneity. Two distinct valvulo-aortic phenotypes, the so-called root phenotype, as well as a dilation of the tubular ascending aorta, coincide with a significantly different risk for aortal complications. However, the phenotype-based classification that is only based on these two clinical forms is not sufficient to estimate the risk of aortal complications in a prognostically relevant way. Therefore, there is growing clinical interest to assess novel approaches in BAV research and to introduce circulating biomarkers as an elegant diagnostic tool to improve risk stratification in BAV aortopathy. A large scale epidemiological cohort study, ranking from apparently healthy individuals to disease patients, and comprehensive biobanks provide the opportunity to study BAV disease and its complications and to identify novel biomarkers for BAV aortopathy surveillance and prognosis. Firstly, the data indicate that several protein-based biomarkers and non-coding RNA molecules, in particular circulating microRNAs, can serve as relevant molecular biomarkers to predict the course of BAV-associated aortopathy. Here, we review the current literature and knowledge about BAV from a clinical point of view, and report about novel approaches in BAV biomarker research.

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GATA6 loss-of-function mutation contributes to congenital bicuspid aortic valve

Cited by 39 publications

References 44 publications

Intronic Polymorphisms in Gene of Second Heart Field as Risk Factors for Human Congenital Heart Disease in a Chinese Population

Intronic Polymorphisms in Gene of Second Heart Field as Risk Factors for Human Congenital Heart Disease in a Chinese Population

New Concepts in the Development and Malformation of the Arterial Valves

Novel Approaches for BAV Aortopathy Prediction—Is There a Need for Cohort Studies and Biomarkers?

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