Literature DB >> 28916633

Systems genetics identifies a co-regulated module of liver microRNAs associated with plasma LDL cholesterol in murine diet-induced dyslipidemia.

Alisha R Coffey1,2, Tangi L Smallwood2, Jody Albright3, Kunjie Hua2, Matt Kanke4, Daniel Pomp2, Brian J Bennett1,2,3, Praveen Sethupathy5.   

Abstract

Chronically altered levels of circulating lipids, termed dyslipidemia, is a significant risk factor for a number of metabolic and cardiovascular morbidities. MicroRNAs (miRNAs) have emerged as important regulators of lipid balance, have been implicated in dyslipidemia, and have been proposed as candidate therapeutic targets in lipid-related disorders including atherosclerosis. A major limitation of most murine studies of miRNAs in lipid metabolic disorders is that they have been performed in just one (or very few) inbred strains, such as C57BL/6. Moreover, although individual miRNAs have been associated with lipid phenotypes, it is well understood that miRNAs likely work together in functional modules. To address these limitations, we implemented a systems genetics strategy using the Diversity Outbred (DO) mouse population. Specifically, we performed gene and miRNA expression profiling in the livers from ~300 genetically distinct DO mice after 18 wk on either a high-fat/high-cholesterol diet or a high-protein diet. Large-scale correlative analysis of these data with a wide range of cardio-metabolic end points revealed a co-regulated module of miRNAs significantly associated with circulating low-density lipoprotein cholesterol (LDL-C) levels. The hubs of this module were identified as miR-199a, miR-181b, miR-27a, miR-21_-_1, and miR-24. In sum, we demonstrate that a high-fat/high-cholesterol diet robustly rewires the miRNA regulatory network, and we identify a small group of co-regulated miRNAs that may exert coordinated effects to control circulating LDL-C.

Entities:  

Keywords:  LDL-C; co-regulated modules; diversity outbred mice; dyslipidemia; microRNAs

Mesh:

Substances:

Year:  2017        PMID: 28916633      PMCID: PMC5792136          DOI: 10.1152/physiolgenomics.00050.2017

Source DB:  PubMed          Journal:  Physiol Genomics        ISSN: 1094-8341            Impact factor:   3.107


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