TY - JOUR
T1 - An integrative multiomic network model links lipid metabolism to glucose regulation in coronary artery disease
AU - Cohain, Ariella T.
AU - Barrington, William T.
AU - Jordan, Daniel M.
AU - Beckmann, Noam D.
AU - Argmann, Carmen A.
AU - Houten, Sander M.
AU - Charney, Alexander W.
AU - Ermel, Raili
AU - Sukhavasi, Katyayani
AU - Franzen, Oscar
AU - Koplev, Simon
AU - Whatling, Carl
AU - Belbin, Gillian M.
AU - Yang, Jialiang
AU - Hao, Ke
AU - Kenny, Eimear E.
AU - Tu, Zhidong
AU - Zhu, Jun
AU - Gan, Li Ming
AU - Do, Ron
AU - Giannarelli, Chiara
AU - Kovacic, Jason C.
AU - Ruusalepp, Arno
AU - Lusis, Aldons J.
AU - Bjorkegren, Johan L.M.
AU - Schadt, Eric E.
N1 - Publisher Copyright:
© 2021, The Author(s).
PY - 2021/12/1
Y1 - 2021/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85099749202&partnerID=8YFLogxK
U2 - 10.1038/s41467-020-20750-8
DO - 10.1038/s41467-020-20750-8
M3 - Article
C2 - 33483510
AN - SCOPUS:85099749202
SN - 2041-1723
VL - 12
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 547
ER -