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pmid:34529670

Identification of key genes and immune infiltration modulated by CPAP in obstructive sleep apnea by integrated bioinformatics analysis.

Cheng Fan · Shiyuan Huang · Chunhua Xiang · Tianhui An · Yi Song

PloS one · 2021 doi:10.1371/journal.pone.0255708

Paper

complete

Experiment

partial

Data

partial

Analysis

partial

Execution

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Identification of key genes and immune infiltration modulated by CPAP in obstructive sleep apnea by integrated bioinformatics analysis.
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10.1371/journal.pone.0255708
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34529670
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Cheng Fan
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Shiyuan Huang
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Chunhua Xiang
[3]
Tianhui An
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Yi Song
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PloS one
year
2021
abstract
Patients with obstructive sleep apnea (OSA) experience partial or complete upper airway collapses during sleep resulting in nocturnal hypoxia-normoxia cycling, and continuous positive airway pressure (CPAP) is the golden treatment for OSA. Nevertheless, the exact mechanisms of action, especially the transcriptome effect of CPAP on OSA patients, remain elusive. The goal of this study was to evaluate the longitudinal alterations in peripheral blood mononuclear cells transcriptome profiles of OSA patients in order to identify the hub gene and immune response. GSE133601 was downloaded from Gene Expression Omnibus (GEO). We identified black module via weighted gene co-expression network analysis (WGCNA), the genes in which were correlated significantly with the clinical trait of CPAP treatment. Finally, eleven hub genes (TRAV10, SNORA36A, RPL10, OBP2B, IGLV1-40, H2BC8, ESAM, DNASE1L3, CD22, ANK3, ACP3) were traced and used to construct a random forest model to predict therapeutic efficacy of CPAP in OSA with a good performance with AUC of 0.92. We further studied the immune cells infiltration in OSA patients with CIBERSORT, and monocytes were found to be related with the remission of OSA and partially correlated with the hub genes identified. In conclusion, these key genes and immune infiltration may be of great importance in the remission of OSA and related research of these genes may provide a new therapeutic target for OSA in the future.
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Transcriptional survey of peripheral blood links lower oxygen saturation during sleep with reduced expressions of CD1D and RAB20 that is reversed by CPAP therapy
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Nevertheless, the exact mechanisms of action, especially the transcriptome effect of CPAP on OSA patients, remain elusive. The goal of this study was to evaluate the longitudinal alterations in peripheral blood mononuclear cells transcriptome profiles of OSA patients in order to identify the hub gene and immune response. GSE133601 was downloaded from Gene Expression Omnibus (GEO). We identified black module via weighted gene co-expression network analysis (WGCNA), the genes in which were correlated significantly with the clinical trait of CPAP treatment. Finally, eleven hub genes (TRAV10, SNORA36A, RPL10, OBP2B, IGLV1-40, H2BC8, ESAM, DNASE1L3, CD22, ANK3, ACP3) were traced and used to construct a random forest model to predict therapeutic efficacy of CPAP in OSA with a good performance with AUC of 0.92. We further studied the immune cells infiltration in OSA patients with CIBERSORT, and monocytes were found to be related with the remission of OSA and partially correlated with the hub genes identified. 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["Neuroactive ligand-receptor interaction", "hsa04080", "21", "5.9E-2", "UTS2R, LHCGR, OXTR, CALCRL, NPY5R, PTGER1, CHRNA4, MLNR, SCTR, LPAR1, TACR2, GRIK2, HTR5A, SSTR4, HCRTR2, RXFP2, P2RY8, HRH1, HRH3, LPAR6, TSHB"], ["Sulfur metabolism", "hsa00920", "3", "7.0E-2", "MPST, ETHE1, SUOX"], ["Transcriptional misregulation in cancer", "hsa05202", "14", "7.2E-2", "NGFR, CSF1R, CDKN1B, ITGAM, FUS, IL1R2, JMJD1C, MLF1, FOXO1, PTK2, SPINT1, TLX1, ITGB7, MET"], ["Proteoglycans in cancer", "hsa05205", "16", "7.2E-2", "ARHGEF12, PDPK1, SRC, LUM, ANK3, HIF1A, PTK2, ACTB, VEGFA, SMO, CTSL, TIMP3, ITGAV, PPP1R12B, MET, WNT2"], ["Ubiquitin mediated proteolysis", "hsa04120", "12", "7.8E-2", "UBE2W, CUL5, UBA7, AIRE, FBXW11, UBE2D2, SYVN1, UBA2, ANAPC4, KEAP1, STUB1, SKP1"], ["Amino sugar and nucleotide sugar metabolism", "hsa00520", "6", "8.8E-2", "CYB5R2, NAGK, GFPT2, GMPPA, PGM3, HK2"]], "row_count": 8, "column_count": 5, "numeric_cells": 23, "header_rows": 1, "locator": 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