| Literature DB >> 27866946 |
Christoph D Rau1, Milagros C Romay2, Mary Tuteryan2, Jessica J-C Wang3, Marc Santolini4, Shuxun Ren5, Alain Karma4, James N Weiss3, Yibin Wang5, Aldons J Lusis6.
Abstract
We previously reported a genetic analysis of heart failure traits in a population of inbred mouse strains treated with isoproterenol to mimic catecholamine-driven cardiac hypertrophy. Here, we apply a co-expression network algorithm, wMICA, to perform a systems-level analysis of left ventricular transcriptomes from these mice. We describe the features of the overall network but focus on a module identified in treated hearts that is strongly related to cardiac hypertrophy and pathological remodeling. Using the causal modeling algorithm NEO, we identified the gene Adamts2 as a putative regulator of this module and validated the predictive value of NEO using small interfering RNA-mediated knockdown in neonatal rat ventricular myocytes. Adamts2 silencing regulated the expression of the genes residing within the module and impaired isoproterenol-induced cellular hypertrophy. Our results provide a view of higher order interactions in heart failure with potential for diagnostic and therapeutic insights.Entities:
Keywords: MICA; causal modeling; gene network; siRNA mediated knockdown; ventricular myocytes
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Year: 2016 PMID: 27866946 PMCID: PMC5338604 DOI: 10.1016/j.cels.2016.10.016
Source DB: PubMed Journal: Cell Syst ISSN: 2405-4712 Impact factor: 10.304