Rationale: Monocyte infiltration into the subintimal space and its intracellular lipid accumulation are the most prominent features of atherosclerosis. To understand the pathophysiology of atherosclerotic disease, we need to understand the characteristics of lipid-laden foamy macrophages in the subintimal space during atherosclerosis. Objective: We sought to examine the transcriptomic profiles of foamy and nonfoamy macrophages isolated from atherosclerotic intima. Methods and Results: Single-cell RNA sequencing analysis of CD45 + leukocytes from murine atherosclerotic aorta revealed that there are macrophage subpopulations with distinct differentially expressed genes involved in various functional pathways. To specifically characterize the intimal foamy macrophages of plaque, we developed a lipid staining-based flow cytometric method for analyzing the lipid-laden foam cells of atherosclerotic aortas. We used the fluorescent lipid probe BODIPY493/503 and assessed side-scattered light as an indication of cellular granularity. BODIPY hi SSC hi foamy macrophages were found residing in intima and expressing CD11c. Foamy macrophage accumulation determined by flow cytometry was positively correlated with the severity of atherosclerosis. Bulk RNA sequencing analysis showed that compared with nonfoamy macrophages, foamy macrophages expressed few inflammatory genes but many lipid-processing genes. Intimal nonfoamy macrophages formed the major population expressing IL (interleukin)-1β and many other inflammatory transcripts in atherosclerotic aorta. Conclusions: RNA sequencing analysis of intimal macrophages from atherosclerotic aorta revealed that lipid-loaded plaque macrophages are not likely the plaque macrophages that drive lesional inflammation.
Bibliographical noteFunding Information:
This work is dedicated to the memory of Cheolho Cheong. We appreciate Erica Lantelme and Dorjan Brinja for fluorescence-activated cell sorting sorting and also thank Inhyuk Jung, Soo Young Cho, and Sung Ho Park for technical assistance and scientific comments, respectively. We thank McDonnell Genome Institute and Genome Technology Access Center in the Department of Genetics at Washington University School of Medicine for help with genomic analysis. We thank Dr Eunwoo Nam of Medical statistical office at the Hanyang University College of Medicine for statistical advice.
This work was supported by grants from the Bio and Medical Technology Development Program of the National Research Foundation and funded by the Korean government (Ministry of Health and Welfare, Ministry of Science and ICT, No. 2016M3A9D5A01952413 and 2018R1A2B6003393 to J.-H. Choi and 2015M3A9B6029138 to G.T. Oh), the Korean Health Technology R&D Project (HI15C0399 to J.-H. Choi), Ministry of Health, Welfare, and Family Affairs, and Canadian Institutes of Health Research (CIHR; FRN 125933 to C. Cheong, CIHR Foundation 148363 and Canada Research Chair 950-231335 to N.G. Seidah), American Heart Association grant 17POST33410473 to J.W. Williams and Government of Russian Federation grant 074-U01 to K. Zaitsev. Genome Technology Access Center at Washington University School of Medicine is partially supported by National Cancer Institute Cancer Center Support grant No. P30 CA91842 to the Siteman Cancer Center and by ICTS/CTSA grant No. UL1TR002345 from the National Center for Research Resources (NCRR)—a component of the National Institutes of Health (NIH)—and NIH Roadmap for Medical Research. This publication is solely the responsibility of the authors and does not necessarily represent the official views of NCRR or NIH.
© 2018 American Heart Association, Inc.
Copyright 2019 Elsevier B.V., All rights reserved.
- Flow cytometry
- Foam cells
PubMed: MeSH publication types
- Journal Article
- Research Support, N.I.H., Extramural
- Research Support, Non-U.S. Gov't