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Zierer, J. ; Pallister, T.* ; Tsai, P.C.* ; Krumsiek, J. ; Bell, J.T.* ; Lauc, G.* ; Spector, T.D.* ; Menni, C.* ; Kastenmüller, G.

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

Sci. Rep. 6:37646 (2016)
Verlagsversion DOI
Open Access Gold
Creative Commons Lizenzvertrag
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.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Obstructive Pulmonary-disease; Gene-expression Changes; Chronic Kidney-disease; Adipose-tissue; Uric-acid; Metabolic Syndrome; Dehydroepiandrosterone Dhea; Visceral Fat; Inflammation; Oxytocin
ISSN (print) / ISBN 2045-2322
e-ISSN 2045-2322
Zeitschrift Scientific Reports
Quellenangaben Band: 6, Heft: , Seiten: , Artikelnummer: 37646 Supplement: ,
Verlag Nature Publishing Group
Verlagsort London
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Bioinformatics and Systems Biology (IBIS)
Institute of Computational Biology (ICB)