Our lab recently described a role for JAK-STAT signaling in the maintenance of quiescence during the murine hair cycle. Research into signaling pathways and cytokines/growth factors involved in the mammalian hair cycle has not focused extensively on the JAK-STAT pathway. In this thesis, I investigated the upstream effector(s) and downstream mechanisms of JAK-STAT signaling in the HFSC during telogen, using a variety of methods, including murine conditional mutants of the JAK-STAT pathway, pharmacological and immunological techniques. The mechanism through which OSM exerts this effect is via JAK-STAT5 signaling downstream of the OSM receptor, which is antagonized by pharmacological JAK inhibition. Conditional epidermal ablation of OSMR or STAT5 during early- and mid-telogen (P42 – P60) shortens the telogen phase significantly, and inhibition of macrophages by way of neutralizing antibodies, small molecule inhibitors, and genetic ablation (with Csf1r-CreER::R26-iDTR mice) during telogen also promotes hair growth. Single-cell RNA sequencing of dermal immune cells across murine telogen identified a distinct subset of TREM2+ macrophages that are enriched for OSM, and gene-set analysis suggests these “trichophages” are similar to the microglia of the central nervous system. I show that this distinct subset of TREM2+ macrophages predominate during early- and mid-telogen, where they produce Oncostatin M (OSM), which is sufficient to maintain quiescence of hair follicle stem cells (HFSCs). Proliferation of HFSCs and hair growth is associated with depletion of this subset of TREM2+ macrophages. Interestingly, macrophage markers and OSM were found to be upregulated in the balding scalp of males with androgenetic alopecia, suggesting that this mechanism is physiologically relevant in the control of human hair cycling.
Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/D8SX7RQN |
Date | January 2018 |
Creators | Wang, Etienne Cho Ee |
Source Sets | Columbia University |
Language | English |
Detected Language | English |
Type | Theses |
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