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• W4308771832 startingPage "2201465" @default.
• W4308771832 abstract "Obstructive sleep apnoea (OSA) is a highly prevalent disease and a major cause of systemic inflammation leading to neurocognitive, behavioural, metabolic and cardiovascular dysfunction in children and adults. However, the impact of OSA on the heterogeneity of circulating immune cells remains to be determined.We applied single-cell transcriptomics analysis (scRNA-seq) to identify OSA-induced changes in transcriptional landscape in peripheral blood mononuclear cell (PBMC) composition, which uncovered severity-dependent differences in several cell lineages. Furthermore, a machine-learning approach was used to combine scRNAs-seq cell-specific markers with those differentially expressed in OSA.scRNA-seq demonstrated OSA-induced heterogeneity in cellular composition and enabled the identification of previously undescribed cell types in PBMCs. We identified a molecular signature consisting of 32 genes, which distinguished OSA patients from various controls with high precision (area under the curve 0.96) and accuracy (93% positive predictive value and 95% negative predictive value) in an independent PBMC bulk RNA expression dataset.OSA deregulates systemic immune function and displays a molecular signature that can be assessed in standard cellular RNA without the need for pre-analytical cell separation, thereby making the assay amenable to application in a molecular diagnostic setting." @default.
• W4308771832 created "2022-11-15" @default.
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• W4308771832 date "2022-11-10" @default.
• W4308771832 modified "2023-10-14" @default.
• W4308771832 title "Single-cell RNA-seq uncovers cellular heterogeneity and provides a signature for paediatric sleep apnoea" @default.
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• W4308771832 doi "https://doi.org/10.1183/13993003.01465-2022" @default.
• W4308771832 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36356973" @default.
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