Thromb Haemost 2021; 121(05): 573-583
DOI: 10.1055/s-0040-1720980
Coagulation and Fibrinolysis

Comparison of DNA Methylation Profiles of Hemostatic Genes between Liver Tissue and Peripheral Blood within Individuals

1  Department of Laboratory Medicine, Institute of Biomedicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
2  Department of Clinical Genetics and Genomics, Sahlgrenska University Hospital, Gothenburg, Sweden
,
Annelie Angerfors*
1  Department of Laboratory Medicine, Institute of Biomedicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
3  Bioinformatics Core Facility, University of Gothenburg, Gothenburg, Sweden
,
Björn Andersson
3  Bioinformatics Core Facility, University of Gothenburg, Gothenburg, Sweden
,
Staffan Nilsson
1  Department of Laboratory Medicine, Institute of Biomedicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
4  Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
,
Marcela Davila Lopez
3  Bioinformatics Core Facility, University of Gothenburg, Gothenburg, Sweden
,
Lena Hansson
5  NovoNordisk, Oxford, United Kingdom
,
Tara M. Stanne**
1  Department of Laboratory Medicine, Institute of Biomedicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
2  Department of Clinical Genetics and Genomics, Sahlgrenska University Hospital, Gothenburg, Sweden
,
Christina Jern**
1  Department of Laboratory Medicine, Institute of Biomedicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
2  Department of Clinical Genetics and Genomics, Sahlgrenska University Hospital, Gothenburg, Sweden
› Author Affiliations
Funding This study was supported by the Swedish Heart and Lung Foundation (20190203), the Swedish Research Council (2018-02543), the Swedish state under the agreement between the Swedish government and the county councils (the ALF-agreement, ALFGBG-720081), the Bioinformatics Long-term Support (WABI), SciLifeLab (Stockholm and Uppsala, Sweden), the Swedish Foundation for Strategic Research (RIF14–0081), the Rune and Ulla Amlövs Foundation for Neurologic Research, the John and Brit Wennerström Foundation for Neurologic Research, the Marcus Borgströms Foundation for Neurologic Research, and the Nilsson-Ehle Endowments.

Abstract

DNA methylation has become increasingly recognized in the etiology of complex diseases, including thrombotic disorders. Blood is often collected in epidemiological studies for genotyping and has recently also been used to examine DNA methylation in epigenome-wide association studies. DNA methylation patterns are often tissue-specific, thus, peripheral blood may not accurately reflect the methylation pattern in the tissue of relevance. Here, we collected paired liver and blood samples concurrently from 27 individuals undergoing liver surgery. We performed targeted bisulfite sequencing for a set of 35 hemostatic genes primarily expressed in liver to analyze DNA methylation levels of >10,000 cytosine-phosphate-guanine (CpG) dinucleotides. We evaluated whether DNA methylation in blood could serve as a proxy for DNA methylation in liver at individual CpGs. Approximately 30% of CpGs were nonvariable and were predominantly hypo- (<25%) or hypermethylated (>70%) in both tissues. While blood can serve as a proxy for liver at these CpGs, the low variability renders these unlikely to explain phenotypic differences. We therefore focused on CpG sites with variable methylation levels in liver. The level of blood–liver tissue correlation varied widely across these variable CpGs; moderate correlations (0.5 ≤ r < 0.75) were detected for 6% and strong correlations (r ≥ 0.75) for a further 4%. Our findings indicate that it is essential to study the concordance of DNA methylation between blood and liver at individual CpGs. This paired blood–liver dataset is intended as a resource to aid interpretation of blood-based DNA methylation results.

Authors' Contributions

M.O.L., T.M.S., and C.J. conceived the research design of the present study. C.J. provided funding and was responsible for sample contribution. M.O.L. isolated gDNA and prepared sequencing libraries. M.O.L., L.H., and M.D.L. acquisitioned and processed the data. A.A., B.A., and S.N. performed the statistical analyses. M.O.L., A.A., and B.A. drafted the figures. M.O.L., A.A., C.J., and T.M.S. interpreted the data. M.O.L., C.J., and T.M.S. drafted the manuscript. All authors intellectually reviewed the manuscript, contributed to the last revision process, and approved the version to be published.


* These authors contributed equally to this work.


** These authors jointly supervised this work.


Supplementary Material



Publication History

Received: 12 March 2020

Accepted: 03 October 2020

Publication Date:
17 November 2020 (online)

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