| Literature DB >> 33483510 |
Ariella T Cohain1, William T Barrington2, Daniel M Jordan1,3, Johan L M Bjorkegren4,5, Eric E Schadt6,7, Noam D Beckmann1, Carmen A Argmann1, Sander M Houten1, Alexander W Charney1,8, Raili Ermel9, Katyayani Sukhavasi9, Oscar Franzen10, Simon Koplev1, Carl Whatling11, Gillian M Belbin1,3, Jialiang Yang1, Ke Hao1, Eimear E Kenny1,3, Zhidong Tu1, Jun Zhu1, Li-Ming Gan12, Ron Do1,3, Chiara Giannarelli1,13, Jason C Kovacic13, Arno Ruusalepp9, Aldons J Lusis2.
Abstract
Elevated plasma cholesterol and type 2 diabetes (T2D) are associated with coronary artery disease (CAD). Individuals treated with cholesterol-lowering statins have increased T2D risk, while individuals with hypercholesterolemia have reduced T2D risk. We explore the relationship between lipid and glucose control by constructing network models from the STARNET study with sequencing data from seven cardiometabolic tissues obtained from CAD patients during coronary artery by-pass grafting surgery. By integrating gene expression, genotype, metabolomic, and clinical data, we identify a glucose and lipid determining (GLD) regulatory network showing inverse relationships with lipid and glucose traits. Master regulators of the GLD network also impact lipid and glucose levels in inverse directions. Experimental inhibition of one of the GLD network master regulators, lanosterol synthase (LSS), in mice confirms the inverse relationships to glucose and lipid levels as predicted by our model and provides mechanistic insights.Entities:
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Year: 2021 PMID： 33483510 PMCID： PMC7822923 DOI： 10.1038/s41467-020-20750-8
Source DB: PubMed Journal: Nat Commun ISSN： 2041-1723 Impact factor: 14.919