Exploring the molecular basis of age-related disease comorbidities using a multi-omics graphical model.

ABSTRACT: Although association studies have unveiled numerous correlations of biochemical markers with age and age-related diseases, we still lack an understanding of their mutual dependencies. To find molecular pathways that underlie age-related diseases as well as their comorbidities, we integrated aging markers from four different high-throughput omics datasets, namely epigenomics, transcriptomics, glycomics and metabolomics, with a comprehensive set of disease phenotypes from 510 participants of the TwinsUK cohort. We used graphical random forests to assess conditional dependencies between omics markers and phenotypes while eliminating mediated associations. Applying this novel approach for multi-omics data integration yields a model consisting of seven modules that represent distinct aspects of

SUBMITTER: Zierer J 

PROVIDER: S-EPMC5122881 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature