ID
45628
Description
Principal Investigator: Laura T. Donlin, PhD, Hospital for Special Surgery, New York, NY, USA MeSH: Arthritis, Rheumatoid,Arthritis https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001340 Macrophages tailor their function according to the signals found in tissue microenvironments, assuming a wide spectrum of phenotypes. A detailed understanding of macrophage phenotypes in human tissues is limited. Using single-cell RNA sequencing, we defined distinct macrophage subsets in the joints of patients with the autoimmune disease rheumatoid arthritis (RA), which affects ~1% of the population. The subset we refer to as HBEGF+ inflammatory macrophages is enriched in RA tissues and is shaped by resident fibroblasts and the cytokine tumor necrosis factor (TNF). These macrophages promoted fibroblast invasiveness in an epidermal growth factor receptor-dependent manner, indicating that intercellular cross-talk in this inflamed setting reshapes both cell types and contributes to fibroblast-mediated joint destruction. In an ex vivo synovial tissue assay, most medications used to treat RA patients targeted HBEGF+ inflammatory macrophages; however, in some cases, redirecting them into a state is not expected to resolve inflammation. These data highlight how advances in our understanding of chronically inflamed human tissues and the effects of medications therein can be achieved by studies on local macrophage phenotypes and intercellular interactions. Reprinted from Kuo, Ding et al., Science Translational Medicine 2019, PMID: 31068444, with permission from American Association for the Advancement of Science.
Lien
Mots-clés
Versions (1)
- 02/03/2023 02/03/2023 - Simon Heim
Détendeur de droits
Laura T. Donlin, PhD, Hospital for Special Surgery, New York, NY, USA
Téléchargé le
2 mars 2023
DOI
Pour une demande vous connecter.
Licence
Creative Commons BY 4.0
Modèle Commentaires :
Ici, vous pouvez faire des commentaires sur le modèle. À partir des bulles de texte, vous pouvez laisser des commentaires spécifiques sur les groupes Item et les Item.
Groupe Item commentaires pour :
Item commentaires pour :
Vous devez être connecté pour pouvoir télécharger des formulaires. Veuillez vous connecter ou s’inscrire gratuitement.
dbGaP phs001340 Identification and Targeting of Inflammatory Macrophage-Fibroblast Crosstalk in Rheumatoid Arthritis
The subject consent data table contains subject IDs and consent group information.
- StudyEvent: SEV1
- The subject consent data table contains subject IDs and consent group information.
- This subject sample mapping data table includes a mapping of study subject IDs to sample IDs. Samples are the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs.
- This subject phenotype table includes rheumatoid arthritis (RA) diagnosis.
- This sample attributes table includes body site from which sample was collected, analyte type, TNF treatment status, macrophage coculture, and drug status.
Similar models
The subject consent data table contains subject IDs and consent group information.
- StudyEvent: SEV1
- The subject consent data table contains subject IDs and consent group information.
- This subject sample mapping data table includes a mapping of study subject IDs to sample IDs. Samples are the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs.
- This subject phenotype table includes rheumatoid arthritis (RA) diagnosis.
- This sample attributes table includes body site from which sample was collected, analyte type, TNF treatment status, macrophage coculture, and drug status.
C2348585 (UMLS CUI [1,2])
C0284670 (UMLS CUI [1,2])