A Comprehensive Sequencing-Based Analysis of Allelic Methylation Patterns in Hemostatic Genes in Human Liver
Journal article, 2020

Characterizing the relationship between genetic, epigenetic (e.g., deoxyribonucleic acid [DNA] methylation), and transcript variation could provide insights into mechanisms regulating hemostasis and potentially identify new drug targets. Several hemostatic factors are synthesized in the liver, yet high-resolution DNA methylation data from human liver tissue is currently lacking for these genes. Single-nucleotide polymorphisms (SNPs) can influence DNA methylation in cis which can affect gene expression. This can be analyzed through allele-specific methylation (ASM) experiments. We performed targeted genomic DNA- and bisulfite-sequencing of 35 hemostatic genes in human liver samples for SNP and DNA methylation analysis, respectively, and integrated the data for ASM determination. ASM-associated SNPs (ASM-SNPs) were tested for association to gene expression in liver using in-house generated ribonucleic acid-sequencing data. We then assessed whether ASM-SNPs associated with gene expression, plasma proteins, or other traits relevant for hemostasis using publicly available data. We identified 112 candidate ASM-SNPs. Of these, 68% were associated with expression of their respective genes in human liver or in other human tissues and 54% were associated with the respective plasma protein levels, activity, or other relevant hemostatic genome-wide association study traits such as venous thromboembolism, coronary artery disease, stroke, and warfarin dose maintenance. Our study provides the first detailed map of the DNA methylation landscape and ASM analysis of hemostatic genes in human liver tissue, and suggests that methylation regulated by genetic variants in cis may provide a mechanistic link between noncoding SNPs and variation observed in circulating hemostatic proteins, prothrombotic diseases, and drug response.


Martina Olsson Lindvall

University of Gothenburg

Marcela Davila Lopez

University of Gothenburg

Sofia Klasson

University of Gothenburg

Lena Hansson

Novo Nordisk Ltd

Science for Life Laboratory (SciLifeLab)

Staffan Nilsson

University of Gothenburg

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Tara M. Stanne

University of Gothenburg

Christina Jern

University of Gothenburg

Sahlgrenska University Hospital

Thrombosis and haemostasis

2567689X (eISSN)

Vol. 120 2 229-242

Subject Categories

Medical Genetics

Bioinformatics and Systems Biology






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