Evidence map›Paper›PMID 39081807›Full record

ArticleFrontiers in genetics2024

An integrated bioinformatics analysis to identify the shared biomarkers in patients with obstructive sleep apnea syndrome and nonalcoholic fatty liver disease.

Rou Zhang, Zhijuan Liu, Ran Li, Xiaona Wang, Li Ai, Yongxia Li

Abstract read
In one paragraph

Article in Frontiers in genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Rou ZhangKunming Medical University, Kunming, China.
Zhijuan LiuDepartment of Respiratory Medicine and Critical Care Medicine, The Second Affiliated Hospital of Kunming Medical University, Kunming, China.
Ran LiDepartment of Respiratory Medicine and Critical Care Medicine, The Second Affiliated Hospital of Kunming Medical University, Kunming, China.
Xiaona WangDepartment of Respiratory Medicine and Critical Care Medicine, The Second Affiliated Hospital of Kunming Medical University, Kunming, China.
Li AiDepartment of Respiratory Medicine and Critical Care Medicine, The Second Affiliated Hospital of Kunming Medical University, Kunming, China.
Yongxia LiDepartment of Respiratory Medicine and Critical Care Medicine, The Second Affiliated Hospital of Kunming Medical University, Kunming, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Obstructive sleep apnea (OSA) syndrome and nonalcoholic fatty liver disease (NAFLD) have been shown to have a close association in previous studies, but their pathogeneses are unclear. This study explores the molecular mechanisms associated with the pathogenesis of OSA and NAFLD and identifies key predictive genes. Methods: Using the Gene Expression Omnibus (GEO) database, we obtained gene expression profiles GSE38792 for OSA and GSE89632 for NAFLD and related clinical characteristics. Mitochondrial unfolded protein response-related genes (UPRmtRGs) were acquired by collating and collecting UPRmtRGs from the GeneCards database and relevant literature from PubMed. The differentially expressed genes (DEGs) associated with OSA and NAFLD were identified using differential expression analysis. Gene Set Enrichment Analysis (GSEA) was conducted for signaling pathway enrichment analysis of related disease genes. Based on the STRING database, protein-protein interaction (PPI) analysis was performed on differentially co-expressed genes (Co-DEGs), and the Cytoscape software (version 3.9.1) was used to visualize the PPI network model. In addition, the GeneMANIA website was used to predict and construct the functional similar genes of the selected Co-DEGs. Key predictor genes were analyzed using the receiver operating characteristic (ROC) curve. Results: The intersection of differentially expressed genes shared between OSA and NAFLD-related gene expression profiles with UPRmtRGs yielded four Co-DEGs: Conclusion: In this study, four co-expression differential genes for OSA and NAFLD were obtained, and they can predict the occurrence of both diseases. Transcriptional mechanisms involved in OSA and NAFLD interactions may be better understood by exploring these key genes. Simultaneously, this study provides potential diagnostic and therapeutic markers for patients with OSA and NAFLD.

Indexed as

differentially expressed genesGene Set Enrichment Analysisnonalcoholic fatty liver diseaseobstructive sleep apneaOSAreceiver operating characteristic

Identifiers

PMID39081807
PMCPMC11286465

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.