Identification and Validation of Prognostic Factors of Lipid Metabolism in Obstructive Sleep Apnea

Lu, Ping; Wang, Xiaodi; Dai, Bing

doi:10.3389/fgene.2021.747576

Cited by 3 publications

(4 citation statements)

References 54 publications

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“…Our data demonstrated the immune cell changes of VAT in the OSA group. Consistent with previous findings (Peng et al, 2021), monocyte-macrophages accounted for the highest proportion of immune cell types, followed by CD8 T cells. The changes in M1 and M2 macrophage proportion showed a significant difference between OSA and the control group.…”

Section: Discussionsupporting

confidence: 92%

“…Hence, the results of the bioinformatic analysis are not always reliable, especially in small sample datasets, experimental validation is necessary to increase confidence. In addition, we did not further establish an immune-related diagnostic model for OSA when compared to previous studies (Li et al, 2017;Gu et al, 2019;Cao et al, 2021;Peng et al, 2021;Liu et al, 2022), because of the invasive procedures for harvesting VAT.…”

Section: Discussionmentioning

confidence: 88%

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CD40LG and GZMB were correlated with adipose tissue macrophage infiltration and involved in obstructive sleep apnea related metabolic dysregulation: Evidence from bioinformatics analysis

Ming

Cai²,

Li³

et al. 2023

Front. Genet.

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Both obesity and obstructive sleep apnea (OSA) can lead to metabolic dysregulation and systemic inflammation. Similar to obesity, increasing evidence has revealed that immune infiltration in the visceral adipose tissue (VAT) is associated with obstructive sleep apnea-related morbidity. However, the pathological changes and potential molecular mechanisms in visceral adipose tissue of obstructive sleep apnea patients need to be further studied. Herein, by bioinformatics analysis and clinical validation methods, including the immune-related differentially expressed genes (IRDEGs) analysis, protein-protein interaction network (PPI), functional enrichment analysis, a devolution algorithm (CIBERSORT), spearman’s correlation analysis, polymerase chain reaction (PCR), Enzyme-linked immunosorbent assay (ELISA) and immunohistochemistry (IHC), we identified and validated 10 hub IRDEGs, the relative mRNA expression of four hub genes (CRP, CD40LG, CCL20, and GZMB), and the protein expression level of two hub genes (CD40LG and GZMB) were consistent with the bioinformatics analysis results. Immune infiltration results further revealed that obstructive sleep apnea patients contained a higher proportion of pro-inflammatory M1 macrophages and a lower proportion of M2 macrophages. Spearman’s correlation analysis showed that CD40LG was positively correlated with M1 macrophages and GZMB was negatively correlated with M2 macrophages. CD40LG and GZMB might play a vital role in the visceral adipose tissue homeostasis of obstructive sleep apnea patients. Their interaction with macrophages and involved pathways not only provides new insights for understanding molecular mechanisms but also be of great significance in discovering novel small molecules or other promising candidates as immunotherapies of OSA-associated metabolic complications.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 88%

CD40LG and GZMB were correlated with adipose tissue macrophage infiltration and involved in obstructive sleep apnea related metabolic dysregulation: Evidence from bioinformatics analysis

Ming

Cai²,

Li³

et al. 2023

Front. Genet.

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“…All the above reports confirmed OSA/IH induces the disorder of adipocytes (the body’s metabolic regulatory organ). Several studies have focused on the effects of OSA on dyslipidemia and lipid metabolism ( Barros and García-Río,2019 ; Peng et al, 2021 ). These data suggest that IH induces hyperlipidemia, and results in the up-regulation of genes involved in lipid biosynthesis in the liver and adipose tissue, and increased lipoprotein secretion.…”

Section: Discussionmentioning

confidence: 99%

Potential regulatory role of miRNA and mRNA link to metabolism affected by chronic intermittent hypoxia

Duan

Zhang²,

Liu³

et al. 2022

Front. Genet.

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Aim: Intermittent hypoxia (IH) is the prominent feature of obstructive sleep apnea (OSA) pathophysiology, which is an in dependent risk factor of cardiovascular complications. The effects of IH on adipocyte metabolism were explored by high-throughput sequencing technology.Methods: Plasma was collected from OSA patients and control group to perform mRNA sequencing. 3T3-L1 cells were differentiated into adipocytes then subjected to a 5%–21% O2 hypoxic environment (IH) for 24 h. High-throughput sequencing method was used to determine differential mRNA and miRNA patterns in fat cells exposed to IH. We then performed Gene Ontology (GO) analysis, identified relevant KEGG pathways and miRNA-target-pathways.Results: Sequencing data showed that OSA affected the expression of 343 mRNAs in the plasma. At the same time, we found that IH affected the expression of 3034 mRNAs in the adipocytes. In addition, 68 differentially expressed mRNAs were overlapped in plasma from OSA patient and IH-induced adipocyte model. We observe that 68 differential genes could be connected to 49 reciprocally expressed miRNAs. We showed that IH significantly reduced the expression of miR-182-5p and miR-30c-2-3p. KEGG predicted that the function of expressed miR-182-5p and miR-30c-2-3p was enriched to AKT signaling pathway. Notably, IH activated PI3K/AKT pathway in fat cells.Conclusion: Our results demonstrated that IH might induce adipocyte metabolism by regulating miR-182-5p and miR-30c-2-3p.

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“…Yuanyuan Cao et al [ 8 ] screened and identified potential biomarkers of OSA and its related diseases by microarray analysis. Peng Lu et al [ 9 ] established and validated the prognostic model of OSA based on microarray datasets and relevant bioinformatics analysis, providing a basis for further research on the molecular mechanism and potential targets of lipid metabolism regulation of OSA. However, few studies have involved gene markers related to different severity of OSA.…”

Section: Introductionmentioning

confidence: 99%

Identification of the Novel Gene Markers Based on the Gene Profile among Different Severity of Obstructive Sleep Apnea

Ren

Sui

et al. 2022

Computational and Mathematical Methods in Medicine

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Obstructive sleep apnea (OSA) is caused by repeated blockage of the upper respiratory airways during sleep. The traditional evaluation methods for OSA severity are yet limited. This study aimed to screen gene signatures to effectively evaluate OSA severity. Expression profiles of peripheral blood mononuclear cells in the different severities of OSA patients were accessed from Gene Expression Omnibus (GEO) database. A total of 446 differentially expressed genes (DEGs) were screened among the varying severities of OSA samples by analysis of variance (ANOVA) test. A total of 1,152 DEGs were screened between the pre- and post-treatment OSA samples by using t test. Overlap of the two groups of DEGs was selected (88 DEGs) for Metascape enrichment analysis. Afterwards, Mfuzz package was used to perform soft clustering analysis on these 88 genes, by which 6 clusters were obtained. It was observed that the gene expression condition of the cluster 3 was positively associated with OSA severity degree; also, the gene expression condition in cluster 4 was negatively correlated with OSA severity. A total of 10 gene markers related to OSA progression were selected from cluster 3 and cluster 4. Their expression levels and correlation were analyzed. The marker genes in cluster 3 and cluster 4 were examined, finding that most genes were significantly correlated with apnea hypopnea index (AHI). An accurate and objective assessment of the severity of OSA is of great significance for formulating follow-up treatment strategies for patients with OSA. In this paper, a set of marker genes that can detect the severity of OSA were screened by bioinformatics methods, which could be jointly used with the traditional OSA diagnostic index to achieve a more reliable OSA severity evaluation.

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Identification and Validation of Prognostic Factors of Lipid Metabolism in Obstructive Sleep Apnea

Cited by 3 publications

References 54 publications

CD40LG and GZMB were correlated with adipose tissue macrophage infiltration and involved in obstructive sleep apnea related metabolic dysregulation: Evidence from bioinformatics analysis

CD40LG and GZMB were correlated with adipose tissue macrophage infiltration and involved in obstructive sleep apnea related metabolic dysregulation: Evidence from bioinformatics analysis

Potential regulatory role of miRNA and mRNA link to metabolism affected by chronic intermittent hypoxia

Identification of the Novel Gene Markers Based on the Gene Profile among Different Severity of Obstructive Sleep Apnea

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