Back to Search Start Over

Mapping methylation quantitative trait loci in cardiac tissues nominates risk loci and biological pathways in congenital heart disease.

Authors :
Li M
Lyu C
Huang M
Do C
Tycko B
Lupo PJ
MacLeod SL
Randolph CE
Liu N
Witte JS
Hobbs CA
Source :
BMC genomic data [BMC Genom Data] 2021 Jun 10; Vol. 22 (1), pp. 20. Date of Electronic Publication: 2021 Jun 10.
Publication Year :
2021

Abstract

Background: Most congenital heart defects (CHDs) result from complex interactions among genetic susceptibilities, epigenetic modifications, and maternal environmental exposures. Characterizing the complex relationship between genetic, epigenetic, and transcriptomic variation will enhance our understanding of pathogenesis in this important type of congenital disorder. We investigated cis-acting effects of genetic single nucleotide polymorphisms (SNPs) on local DNA methylation patterns within 83 cardiac tissue samples and prioritized their contributions to CHD risk by leveraging results of CHD genome-wide association studies (GWAS) and their effects on cardiac gene expression.<br />Results: We identified 13,901 potential methylation quantitative trait loci (mQTLs) with a false discovery threshold of 5%. Further co-localization analyses and Mendelian randomization indicated that genetic variants near the HLA-DRB6 gene on chromosome 6 may contribute to CHD risk by regulating the methylation status of nearby CpG sites. Additional SNPs in genomic regions on chromosome 10 (TNKS2-AS1 gene) and chromosome 14 (LINC01629 gene) may simultaneously influence epigenetic and transcriptomic variations within cardiac tissues.<br />Conclusions: Our results support the hypothesis that genetic variants may influence the risk of CHDs through regulating the changes of DNA methylation and gene expression. Our results can serve as an important source of information that can be integrated with other genetic studies of heart diseases, especially CHDs.

Details

Language :
English
ISSN :
2730-6844
Volume :
22
Issue :
1
Database :
MEDLINE
Journal :
BMC genomic data
Publication Type :
Academic Journal
Accession number :
34112112
Full Text :
https://doi.org/10.1186/s12863-021-00975-2