Vis enkel innførsel

dc.contributor.authorNustad, Haakon Egdetveit
dc.contributor.authorPage, Christian
dc.contributor.authorReiner, Andrew Henry
dc.contributor.authorZucknick, Manuela
dc.contributor.authorLeBlanc, Marissa
dc.date.accessioned2022-07-25T13:01:52Z
dc.date.available2022-07-25T13:01:52Z
dc.date.created2018-09-21T16:58:03Z
dc.date.issued2018
dc.identifier.citationBMC Proceedings. 2018, 12 (31), 117-122.
dc.identifier.issn1753-6561
dc.identifier.urihttps://hdl.handle.net/11250/3008224
dc.description.abstractBackground A Bayesian mixed model approach using integrated nested Laplace approximations (INLA) allows us to construct flexible models that can account for pedigree structure. Using these models, we estimate genome-wide patterns of DNA methylation heritability (h2), which are currently not well understood, as well as h2 of blood lipid measurements. Methods We included individuals from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study with Infinium 450 K cytosine-phosphate-guanine (CpG) methylation and blood lipid data pre- and posttreatment with fenofibrate in families with up to three-generation pedigrees. For genome-wide patterns, we constructed 1 model per CpG with methylation as the response variable, with a random effect to model kinship, and age and gender as fixed effects. Results In total, 425,791 CpG sites pre-, but only 199,027 CpG sites posttreatment were found to have nonzero heritability. Across these CpG sites, the distributions of h2 estimates are similar in pre- and posttreatment (pre: median = 0.31, interquartile range [IQR] = 0.16; post: median = 0.34, IQR = 0.20). Blood lipid h2 estimates were similar pre- and posttreatment with overlapping 95% credibility intervals. Heritability was nonzero for treatment effect, that is, the difference between pre- and posttreatment blood lipids. Estimates for triglycerides h2 are 0.48 (pre), 0.42 (post), and 0.21 (difference); likewise for high-density lipoprotein cholesterol h2 the estimates are 0.61, 0.68, and 0.10. Conclusions We show that with INLA, a fully Bayesian approach to estimate DNA methylation h2 is possible on a genome-wide scale. This provides uncertainty assessment of the estimates, and allows us to perform model selection via deviance information criterion (DIC) to identify CpGs with strong evidence for nonzero heritability.
dc.description.abstractA Bayesian mixed modeling approach for estimating heritability
dc.language.isoeng
dc.relation.urihttps://bmcproc.biomedcentral.com/articles/10.1186/s12919-018-0131-z
dc.titleA Bayesian mixed modeling approach for estimating heritability
dc.typePeer reviewed
dc.typeJournal article
dc.description.versionpublishedVersion
dc.source.pagenumber117-122
dc.source.volume12
dc.source.journalBMC Proceedings
dc.source.issue31
dc.identifier.doi10.1186/s12919-018-0131-z
dc.identifier.cristin1612274
cristin.unitcode7502,2,2,0
cristin.unitnameSenter for fruktbarhet og helse
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


Tilhørende fil(er)

Thumbnail

Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel