Back

Interleukin-10-producing monocytes contribute to sex differences in pain resolution in mice and humans.

Sim, J.; O'Guin, E.; Monahan, K.; Sugimoto, C.; McLean, S.; Albertorio-Saez, L.; Zhao, Y.; Dagenais, A.; Laumet, S.; Bernard, M.; Folger, J. K.; Robison, A. J.; Linnstaedt, S. D.; Laumet, G.

2023-11-05 immunology
10.1101/2023.11.03.565129 bioRxiv
Show abstract

Pain is closely associated with the immune system, which exhibits sexual dimorphism. For these reasons, neuro-immune interactions are suggested to drive sex differences in pain pathophysiology. However, our understanding of peripheral neuro-immune interactions on sex differences in pain resolution remains limited. Here, we have shown, in both a mouse model of inflammatory pain and in humans following traumatic pain, that males had higher levels of interleukin (IL)-10 than females, which were correlated with faster pain resolution. Following injury, we identified monocytes (CD11b+ Ly6C+ Ly6G-F4/80mid) as the primary source of IL-10, with IL-10-producing monocytes being more abundant in males than females. In a mouse model, neutralizing IL-10 signaling through antibodies, genetically ablating IL-10R1 in sensory neurons, or depleting monocytes with clodronate all impaired the resolution of pain hypersensitivity in both sexes. Furthermore, manipulating androgen levels in mice reversed the sexual dimorphism of pain resolution and the levels of IL-10-producing monocytes. These results highlight a novel role for androgen-driven peripheral IL-10-producing monocytes in the sexual dimorphism of pain resolution. These findings add to the growing concept that immune cells play a critical role in resolving pain and preventing the transition into chronic pain. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=135 SRC="FIGDIR/small/565129v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@6e158corg.highwire.dtl.DTLVardef@148c8b5org.highwire.dtl.DTLVardef@1711d2dorg.highwire.dtl.DTLVardef@132a755_HPS_FORMAT_FIGEXP M_FIG C_FIG

Published in Science Immunology (predicted rank #1) · training set

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.