Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

Sparse profiling of CpG methylation in blood by microarrays has identified epigenetic links to common diseases. Here we apply methylC-capture sequencing (MCC-Seq) in a clinical population of ~200 adipose tissue and matched blood samples (Ntotal~400), providing high-resolution methylation profiling (>1.3 M CpGs) at regulatory elements. We link methylation to cardiometabolic risk through associations to circulating plasma lipid levels and identify lipid-associated CpGs with unique localization patterns in regulatory elements. We show distinct features of tissue-specific versus tissue-independent lipid-linked regulatory regions by contrasting with parallel assessments in ~800 independent adipose tissue and blood samples from the general population. We follow-up on adipose-specific regulatory regions under (1) genetic and (2) epigenetic (environmental) regulation via integrational studies. Overall, the comprehensive sequencing of regulatory element methylomes reveals a rich landscape of functional variants linked genetically as well as epigenetically to plasma lipid traits.

Original publication

DOI

10.1038/s41467-019-09184-z

Type

Journal article

Journal

Nature communications

Publication Date

14/03/2019

Volume

10

Addresses

Department of Human Genetics, McGill University, Montréal, QC, H3A 0C7, Canada.

Keywords

Adipose Tissue, Humans, Cardiovascular Diseases, Metabolic Diseases, Lipids, Gene Expression Profiling, Sequence Analysis, DNA, DNA Methylation, Epigenesis, Genetic, CpG Islands, Regulatory Sequences, Nucleic Acid, Polymorphism, Single Nucleotide, Genome, Human, Adult, Aged, Middle Aged, Female, Male, Genome-Wide Association Study, Epigenomics, High-Throughput Nucleotide Sequencing