Background:Patients with Prader-Willi syndrome (PWS) have a reduced life expectancy due to inflammation-related disease including cardiovascular disease and diabetes. Abnormal activation of peripheral immune system is postulated as a contributor. However, detailed features of the peripheral immune cells in PWS have not been fully elucidated.
Methods:Serum inflammatory cytokines were measured in healthy controls (n=13) and PWS patients (n=10) using a 65- multiplex cytokine assays. Changes of the peripheral immune cells in PWS was assessed by single-cell RNA sequencing (scRNA-seq) and high-dimensional mass cytometry (CyTOF) using peripheral blood mononuclear cells (PBMCs) from PWS patients (n=6) and healthy controls (n=12).
Results:PWS patients exhibited hyper-inflammatory signatures in PBMCs and monocytes were the most pronounced. Most inflammatory serum cytokines were increased in PWS, including IL-1β, IL-2R, IL-12p70, and TNF-α. The characteristics of monocytes evaluated by scRNA-seq and CyTOF showed that CD16+ monocytes were significantly increased in PWS patients. Functional pathway analysis revealed that CD16+ monocytes upregulated pathways in PWS were closely associated with TNF/IL-1β- driven inflammation signaling. The CellChat analysis identified CD16+ monocytes transmitted chemokine and cytokine signaling to drive inflammatory process in other cell types. Finally, we explored the PWS deletion region 15q11-q13 might be responsible for elevated levels of inflammation in the peripheral immune system.
Conclusion:The study highlights that CD16+ monocytes contributor to the hyper-inflammatory state of PWS which provides potential targets for immunotherapy in the future and expands our knowledge of peripheral immune cells in PWS at the single cell level for the first time.
Keywords:CD16+monocytes; Prader-Willi Syndrome; inflammation; mass cytometry; single-cell RNA sequencing.
CD16+ monocytes are involved in the hyper-inflammatory state of Prader-Willi Syndrome by single-cell transcriptomic analysis
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
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细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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