MIMOSA: a resource consisting of improved methylome prediction models increases power to identify DNA methylation-phenotype associations.

ABSTRACT: Although DNA methylation (DNAm) has been implicated in the pathogenesis of numerous complex diseases, from cancer to cardiovascular disease to autoimmune disease, the exact methylation sites that play key roles in these processes remain elusive. One strategy to identify putative causal CpG sites and enhance disease etiology understanding is to conduct methylome-wide association studies (MWASs), in which predicted DNA methylation that is associated with complex diseases can be identified. However, current MWAS models are primarily trained using the data from single studies, thereby limiting the methylation prediction accuracy and the power of subsequent association studies. Here, we introduce a new resource, MWAS Imputing Methylome Obliging Summary-level mQTLs and Associated LD matrices (MI

SUBMITTER: Melton HJ 

PROVIDER: S-EPMC11225927 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature