Center for Medical Ethics and Health Policy Staff Publications
Publication Date
8-10-2022
Journal
Bioinformatics
DOI
10.1093/bioinformatics/btac443
PMID
35781319
PMCID
PMC9364381
PubMedCentral® Posted Date
7-4-2022
PubMedCentral® Full Text Version
Author MSS
Published Open-Access
yes
Keywords
Quantitative Trait Loci, Genome-Wide Association Study, Methylation, Phenotype, Genomics, DNA Methylation, Polymorphism, Single Nucleotide
Abstract
Motivation: CpG sites within the same genomic region often share similar methylation patterns and tend to be co-regulated by multiple genetic variants that may interact with one another.
Results: We propose a multi-trait methylation random field (multi-MRF) method to evaluate the joint association between a set of CpG sites and a set of genetic variants. The proposed method has several advantages. First, it is a multi-trait method that allows flexible correlation structures between neighboring CpG sites (e.g. distance-based correlation). Second, it is also a multi-locus method that integrates the effect of multiple common and rare genetic variants. Third, it models the methylation traits with a beta distribution to characterize their bimodal and interval properties. Through simulations, we demonstrated that the proposed method had improved power over some existing methods under various disease scenarios. We further illustrated the proposed method via an application to a study of congenital heart defects (CHDs) with 83 cardiac tissue samples. Our results suggested that gene BACE2, a methylation quantitative trait locus (QTL) candidate, colocalized with expression QTLs in artery tibial and harbored genetic variants with nominal significant associations in two genome-wide association studies of CHD.
Availability and implementation: https://github.com/chenlyu2656/Multi-MRF.
Supplementary information Supplementary data are available at Bioinformatics online.