Atherosclerosis is an inflammatory disease of artery walls in which innate immune cells play an important role. After infiltrating the endothelium, monocytes differentiate into macrophages, take up modified low- density lipoprotein (LDL), and progressively assume a lipid-loaded, """"""""foam cell"""""""" phenotype. Foam cells secrete pro-inflammatory mediators and contribute to lesion progression. Foam cell formation and associated pro- inflammatory behavior involve transcriptional regulation of many genes, but the specific transcriptional regulatory mechanisms controlling these expression changes in response to various lesion-associated stimuli are not well understood. We will identify transcription factors that regulate foam cell formation using a systems biology approach. Murine macrophages will be stimulated with modified LDL in vitro and transcriptionally profiled. The gene expression patterns will be combined with findings from a variety of transcriptomic, proteomic, and genetic association studies to identify a core list of genes associated with macrophage foam cell formation and atherosclerosis. The promoters of these genes will be analyzed in light of genomic evidence for cis-regulatory function (including DNase I hypersensitive sites in macrophages that will be globally mapped by sequencing), to identify transcription factors that may regulate the core gene set. Four or more transcription factors will then be perturbed by knockout or knockdown, to determine their transcriptional regulatory function in the in vitro foam cell model. The long-term goal of this work is to identify the key transcription factors regulating foam cell formation and to characterize their function. This research project is a core element of a four-year career development plan for Dr. Stephen Ramsey to transition to a research career in which he will use the methods of molecular biology and computational biology to study cellular models relevant to cardiovascular disease. The project will be carried out at the Institute for Systems Biology under the mentorship of Dr. Alan Aderem and Dr. Ilya Shmulevich, and in collaboration with Dr. Elizabeth Gold. Drs. Aderem, Shmulevich and Gold have complementary domains of expertise spanning all aspects of the project, including macrophage biology/immunology, molecular cell biology, computational biology, and cardiovascular disease. They are ideally suited to guide Dr. Ramsey's research and career development as described in the training plan. This mentored career development plan will enable Dr. Ramsey to achieve his career goal of becoming an independent investigator in cardiovascular disease-related research, equipped to use experimental and quantitative methods in a synergistic manner.

Public Health Relevance

Atherosclerosis (a leading cause of heart attacks and stroke) is a chronic inflammatory disease of the artery walls. Atherosclerosis involves accumulation of macrophage white blood cells in the artery walls and the transformation of these cells into lipid-loaded """"""""foam cells"""""""" that promote inflammation. This project aims to identify molecules that regulate gene expression changes in foam cells, which may yield new macrophage-specific drug targets for atherosclerosis.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Mentored Quantitative Research Career Development Award (K25)
Project #
5K25HL098807-04
Application #
8206803
Study Section
Special Emphasis Panel (ZHL1-CSR-R (O1))
Program Officer
Scott, Jane
Project Start
2010-01-01
Project End
2013-12-31
Budget Start
2012-01-01
Budget End
2012-12-31
Support Year
4
Fiscal Year
2012
Total Cost
$144,775
Indirect Cost
$10,724
Name
Seattle Biomedical Research Institute
Department
Type
DUNS #
070967955
City
Seattle
State
WA
Country
United States
Zip Code
98109
Yu, Alvin Z; Ramsey, Stephen A (2018) A Computational Systems Biology Approach for Identifying Candidate Drugs for Repositioning for Cardiovascular Disease. Interdiscip Sci 10:449-454
Choudhury, Mudra; Ramsey, Stephen A (2016) Identifying Cell Type-Specific Transcription Factors by Integrating ChIP-seq and eQTL Data-Application to Monocyte Gene Regulation. Gene Regul Syst Bio 10:105-110
Gillespie, Mark A; Gold, Elizabeth S; Ramsey, Stephen A et al. (2015) An LXR-NCOA5 gene regulatory complex directs inflammatory crosstalk-dependent repression of macrophage cholesterol efflux. EMBO J 34:1244-58
Ramsey, Stephen A (2015) An Empirical Prior Improves Accuracy for Bayesian Estimation of Transcription Factor Binding Site Frequencies within Gene Promoters. Bioinform Biol Insights 9:59-69
Vengrenyuk, Yuliya; Nishi, Hitoo; Long, Xiaochun et al. (2015) Cholesterol loading reprograms the microRNA-143/145-myocardin axis to convert aortic smooth muscle cells to a dysfunctional macrophage-like phenotype. Arterioscler Thromb Vasc Biol 35:535-46
Yang, Jichen; Ramsey, Stephen A (2015) A DNA shape-based regulatory score improves position-weight matrix-based recognition of transcription factor binding sites. Bioinformatics 31:3445-50
Dong, Xiaoxi; Yambartsev, Anatoly; Ramsey, Stephen A et al. (2015) Reverse enGENEering of Regulatory Networks from Big Data: A Roadmap for Biologists. Bioinform Biol Insights 9:61-74
Knijnenburg, Theo A; Ramsey, Stephen A; Berman, Benjamin P et al. (2014) Multiscale representation of genomic signals. Nat Methods 11:689-94
Ramsey, Stephen A; Vengrenyuk, Yuliya; Menon, Prashanthi et al. (2014) Epigenome-guided analysis of the transcriptome of plaque macrophages during atherosclerosis regression reveals activation of the Wnt signaling pathway. PLoS Genet 10:e1004828
Meznarich, Jessica; Malchodi, Laura; Helterline, Deri et al. (2013) Urokinase plasminogen activator induces pro-fibrotic/m2 phenotype in murine cardiac macrophages. PLoS One 8:e57837

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