Back

TLR7 inhibition limits cardiac ischemic injury by disrupting ITGAM-dependent immune-endothelial interaction

Li, Y.; Yang, Y.; Park, C.; Ren, B.; Li, R.; Shetty, A. C.; Williams, B.; Li, Z.; Li, Z.; Chao, W.

2026-01-21 immunology
10.64898/2026.01.17.698774 bioRxiv
Show abstract

Percutaneous coronary intervention (PCI) limits ischemic myocardial infarction but also triggers ischemia-reperfusion (I/R) injury in part driven by innate immune activation. Here, we identify Toll-like receptor 7 (TLR7), an endosomal sensor of single-stranded RNA, as a mediator of post-ischemic inflammation and myocardial damage. Pharmacological inhibition of TLR7 with enpatoran reduced myocardial inflammation and infarct size and improved cardiac function in a mouse model of I/R injury when administered before, during, or shortly after ischemia. Single-nucleus RNA sequencing revealed coordinated post-I/R expansion of myeloid cells and distinct inflammatory endothelial subsets enriched for leukocyte-interaction programs, with marked upregulation of Itgam in cardiac leukocytes and endothelial cells and in circulating monocytes. Circulating ITGAM+ monocytes were similarly increased in patients with ST-segment elevation myocardial infarction 24 hours after coronary stenting. Mechanistically, TLR7 activation induced Itgam expression in endothelial cells and leukocytes and promoted their adhesion via ITGAM-ICAM1 interaction under physiological shear stress, whereas ITGAM neutralization disrupted this interaction, reduced immune cell infiltration, and limited ischemic injury. These findings define a TLR7-ITGAM signaling axis as a key driver of endothelial-leukocyte crosstalk in myocardial I/R injury and support TLR7 inhibition as a promising therapeutic strategy to mitigate acute myocardial infarction.

Published in JACC: Basic to Translational Science (predicted rank #15) · training set

Matching journals

The top 6 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.