Understanding the Foreign Body Response via Single-Cell Meta-Analysis.
Norah E LiangJennifer B ParkerJohn M LuMichael JanuszykDerrick C WanMichelle F GriffinMichael T LongakerPublished in: Biology (2024)
Foreign body response (FBR) is a universal reaction to implanted biomaterial that can affect the function and longevity of the implant. A few studies have attempted to identify targets for treating FBR through the use of single-cell RNA sequencing (scRNA-seq), though the generalizability of these findings from an individual study may be limited. In our study, we perform a meta-analysis of scRNA-seq data from all available FBR mouse studies and integrate these data to identify gene signatures specific to FBR across different models and anatomic locations. We identify subclusters of fibroblasts and macrophages that emerge in response to foreign bodies and characterize their signaling pathways, gene ontology terms, and downstream mediators. The fibroblast subpopulations enriched in the setting of FBR demonstrated significant signaling interactions in the transforming growth factor-beta (TGF-β) signaling pathway, with known pro-fibrotic mediators identified as top expressed genes in these FBR-derived fibroblasts. In contrast, FBR-enriched macrophage subclusters highly expressed pro-fibrotic and pro-inflammatory mediators downstream of tumor necrosis factor (TNF) signaling. Cell-cell interactions were additionally interrogated using CellChat , with identification of key signaling interactions enriched between fibroblasts and macrophages in FBR. By combining multiple FBR datasets, our meta-analysis study identifies common cell-specific gene signatures enriched in foreign body reactions, providing potential therapeutic targets for patients requiring medical implants across a myriad of devices and indications.
Keyphrases
- single cell
- genome wide
- rna seq
- transforming growth factor
- systematic review
- signaling pathway
- high throughput
- rheumatoid arthritis
- copy number
- dna methylation
- randomized controlled trial
- end stage renal disease
- case control
- mesenchymal stem cells
- adipose tissue
- stem cells
- gene expression
- chronic kidney disease
- computed tomography
- newly diagnosed
- electronic health record
- risk assessment
- peritoneal dialysis
- anti inflammatory
- cell proliferation
- transcription factor
- big data
- deep learning
- artificial intelligence
- bone marrow