title: 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 aging. These modules are connected by hubs that potentially trigger comorbidities of age-related diseases. As an example, we identified urate as one of these key players mediating the comorbidity of renal disease with body composition and obesity. Body composition variables are in turn associated with inflammatory IgG markers, mediated by the expression of the hormone oxytocin. Thus, oxytocin potentially contributes to the development of chronic low-grade inflammation, which often accompanies obesity. Our multi-omics graphical model demonstrates the interconnectivity of age-related diseases and highlights molecular markers of the aging process that might drive disease comorbidities.
authors.affiliation: Department of Twin Research and Genetic Epidemiology, Kings College London, London, United Kingdom.|Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Neuherberg, Germany.
authors.forename: Jonas
authors.initials: J
authors.lastname: Zierer
authors.affiliation: Department of Twin Research and Genetic Epidemiology, Kings College London, London, United Kingdom.
authors.forename: Tess
authors.initials: T
authors.lastname: Pallister
authors.affiliation: Department of Twin Research and Genetic Epidemiology, Kings College London, London, United Kingdom.
authors.forename: Pei-Chien
authors.initials: PC
authors.lastname: Tsai
authors.affiliation: Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.|German Center for Diabetes Research (DZD), Neuherberg, Germany.
authors.forename: Jan
authors.initials: J
authors.lastname: Krumsiek
authors.affiliation: Department of Twin Research and Genetic Epidemiology, Kings College London, London, United Kingdom.
authors.forename: Jordana T
authors.initials: JT
authors.lastname: Bell
authors.affiliation: Department of Twin Research and Genetic Epidemiology, Kings College London, London, United Kingdom.|Genos Glycoscience Research Laboratory, Zagreb, Croatia.
authors.forename: Gordan
authors.initials: G
authors.lastname: Lauc
authors.affiliation: Department of Twin Research and Genetic Epidemiology, Kings College London, London, United Kingdom.
authors.forename: Tim D
authors.initials: TD
authors.lastname: Spector
authors.affiliation: Department of Twin Research and Genetic Epidemiology, Kings College London, London, United Kingdom.
authors.forename: Cristina
authors.initials: C
authors.lastname: Menni
authors.affiliation: Department of Twin Research and Genetic Epidemiology, Kings College London, London, United Kingdom.|Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Neuherberg, Germany.|German Center for Diabetes Research (DZD), Neuherberg, Germany.
authors.forename: Gabi
authors.initials: G
authors.lastname: Kastenmüller
mesh_terms: D000375:Aging / Q000473:pathology*; D015897:Comorbidity; D006801:Humans; D055432:Metabolomics; D008954:Models, Biological; D040901:Proteomics