Lionel B. Ivashkiv

This study shows that Langerhans cells regulate postnatal dermal lymphatic development, which in turn controls adult immune responses.

SPP1hi macrophages in RA synovial fibrin deposits promote tissue hyperplasia.

The paper identifies CX3CR1+ monocytes/macrophages as key drivers of impaired healing after ACLR and suggests they are potential therapeutic targets.

The paper shows IL-4 enhances TNF-induced gene expression in monocytes/macrophages through epigenetic mechanisms, revealing cooperative crosstalk between antagonistic cytokines.

This study identifies a PGE2-cAMP axis that opposes IFN-γ regulation of TNF responses in IL-1β+ macrophages in RA and ICI-arthritis, revealing a novel regulatory mechanism for inflammatory gene expression.

This study identifies how IL-10 suppresses inflammatory gene expression by targeting IRF transcription factors and altering chromatin accessibility and histone marks in human monocytes.

This study identifies granzyme K as a driver of a novel complement activation pathway independent of classical, lectin, or alternative pathways.

This study shows IFN-γ enhances TLR-induced inflammatory gene expression through IRF1, which is critical for synergistic activation of genes like IL6 and TNF in human monocytes.

The paper develops SCENT, a method to create cell-type-specific enhancer-gene maps from single-cell multimodal data, identifying causal variants and genes for diseases.

The paper maps cell-type-specific eQTLs for HLA genes across multiple tissues and identifies dynamic regulation of HLA-DQ genes in immune cells.

The paper deconstructs RA synovium using single-cell data to identify six cell type abundance phenotypes associated with distinct inflammatory states.

A newly identified human macrophage phenotype in RA promotes joint tissue invasiveness and shows variable responses to anti-inflammatory medications.

The paper develops a low-cost microfluidic instrument for scRNA-seq and applies it to profile synovial tissue from a rheumatoid arthritis patient, identifying 16 transcriptomic clusters and fibroblast subpopulations.