Trejo Banos D McCartney DL Patxot M Anchieri L Battram T Christiansen C Costeira R Walker RM Morris SW Campbell A Zhang Q Porteous DJ McRae AF Wray NR Visscher PM Haley CS Evans KL Deary IJ McIntosh AM Hemani G Bell JT Marioni RE Robinson MR 2020 Linking epigenetic marks to clinical outcomes improves insight into molecular processes, disease prediction, and therapeutic target identification. Here, a statistical approach is presented to infer the epigenetic architecture of complex disease, determine the variation captured by epigenetic effects, and estimate phenotype-epigenetic probe associations jointly. Implicitly adjusting for probe correlations, data structure (cell-count or relatedness), and single-nucleotide polymorphism (SNP) marker effects, improves association estimates and in 9,448 individuals, 75.7% (95% CI 71.70-79.3) of body mass index (BMI) variation and 45.6% (95% CI 37.3-51.9) of cigarette consumption variation was captured by whole blood methylation array data. Pathway-linked probes of blood cholesterol, lipid transport and sterol metabolism for BMI, and xenobiotic stimuli response for smoking, showed >1.5 times larger associations with >95% posterior inclusion probability. Prediction accuracy improved by 28.7% for BMI and 10.2% for smoking over a LASSO model, with age-, and tissue-specificity, implying associations are a phenotypic consequence rather than causal. application/pdf https://sonar.ch/global/documents/873 eng info:eu-repo/semantics/altIdentifier/doi/10.1038/s41467-020-16520-1 info:eu-repo/semantics/altIdentifier/pmid/32513961 info:eu-repo/semantics/openAccess Nature communications. - 2020 Adult Algorithms Bayes Theorem Biomarkers Body Mass Index Computer Simulation DNA Methylation Epigenesis, Genetic Humans Molecular Sequence Annotation Organ Specificity Quantitative Trait, Heritable Reproducibility of Results Bayesian reassessment of the epigenetic architecture of complex traits. http://purl.org/coar/resource_type/c_6501