bioRxivDevelopmental BiologyPreprint
Human Bone Marrow Adipose Tissue is a Hematopoietic Niche for Leptin-DrivenMonopoiesis
Zinger YangiD, Amruta Samant, Anand DesaiiD, Tiffany DeSouzaiD, Haley CirkaiD, Mai Ceesay, David M. KostyraiD, Shannon JoyceiD, Lyne KhairiD, Javier Solivan-RiveraiD, Rachel Ziegler, Nathalia Ketelut Carneiro, Linus T Tsai, Michael A. BrehmiD, Louis M. MessinaiD, Katherine A Fitzgerald, Evan D Rosen, Silvia CorveraiD, Tammy NguyeniD
Abstract
During aging, adipose tissue within the bone marrow expands while the trabecular red marrow contracts. The impact of these changes on blood cell formation remains unclear. To address this question, we performed single-cell and single-nuclei transcriptomic analysis on adipose-rich yellow bone marrow (BMY) and adipose-poor trabecular red marrow (BMR) from human subjects undergoing lower limb amputations. Surprisingly, we discovered two distinct hematopoietic niches, in which BMY contains a higher number of monocytes and progenitor cells expressing genes associated with inflammation. To further investigate these niches, we developed an in-vitro organoid system that maintains features of the human bone marrow. We find cells from BMY are distinct in their expression of the leptin receptor, and respond to leptin stimulation with enhanced proliferation, leading to increased monocyte production. These findings suggest that the age-associated expansion of bone marrow adipose tissue drives a pro-inflammatory state by stimulating monocyte production from a spatially distinct, leptin-responsive hematopoietic stem/progenitor cell population. SignificanceThis study reveals that adipose tissue within the human bone marrow is a niche for hematopoietic stem and progenitor cells that can give rise to pro-inflammatory monocytes through leptin signaling. Expansion of bone marrow adipose tissue with age and stress may thus underlie inflammageing.
- organism: human
- assay: scRNA-seq
- assay: spatial transcriptomics
- research focus: cell type annotation
- research focus: differential expression
- approach: statistical model
- Citations
- 1
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