The individual contribution of specific myeloid subsets such as CD1c+ conventional DC (cDC) to perpetuation of rheumatoid arthritis (RA) pathology remains unclear. In addition, the specific innate sensors driving pathogenic activation of CD1c+ cDC in patients with RA and their functional implications have not been characterized. Here, we assessed phenotypical, transcriptional, and functional characteristics of CD1c+ and CD141+ cDC and monocytes from the blood and synovial fluid of patients with RA. Increased levels of CCR2 and the IgG receptor CD64 on circulating CD1c+ cDC was associated with the presence of this DC subset in the synovial membrane in patients with RA. Moreover, synovial CD1c+ cDC are characterized by increased expression of proinflammatory cytokines and high abilities to induce pathogenic IFN-γ+IL-17+CD4+ T cells in vitro. Finally, we identified the crosstalk between Fcγ receptors and NLRC4 as a potential molecular mechanism mediating pathogenic activation, CD64 upregulation, and functional specialization of CD1c+ cDC in response to dsDNA-IgG in patients with RA.
Cristina Delgado-Arévalo, Marta Calvet-Mirabent, Ana Triguero-Martínez, Enrique Vázquez de Luis, Alberto Benguría-Filippini, Raquel Largo, Diego Calzada-Fraile, Olga Popova, Ildefonso Sánchez-Cerrillo, Ilya Tsukalov, Roberto Moreno-Vellisca, Hortensia de la Fuente, Gabriel Herrero-Beaumont, Almudena Ramiro, Francisco Sánchez-Madrid, Santos Castañeda, Ana Dopazo, Isidoro González Álvaro, Enrique Martin-Gayo
Usage data is cumulative from March 2023 through March 2024.
Usage | JCI | PMC |
---|---|---|
Text version | 578 | 149 |
79 | 44 | |
Figure | 114 | 10 |
Supplemental data | 46 | 11 |
Citation downloads | 32 | 0 |
Totals | 849 | 214 |
Total Views | 1,063 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.