Associations Between Obstructive Sleep Apnea and Metabolic Dysfunction-Associated Fatty Liver Disease: Insights from Comprehensive Mendelian Randomization and Gene Expression Analysis

Abstract

Background: Obstructive sleep apnea (OSA) is linked to metabolic dysfunction-associated fatty liver disease (MAFLD), yet their exact causality and underlying mechanisms remain inconclusive. We aimed to investigate their causal associations and shared biomarkers using Mendelian randomization (MR) and bioinformatics approaches.

Methods: We used OSA-related and MAFLD-related GWAS data to explore their causal relationship and the role of body mass index (BMI) through two-sample and network MR analysis. Gene expression profiles were analyzed to identify intersection genes through differential expression analysis and weighted gene co-expression network analysis (WGCNA). Functional enrichment (GO and KEGG), protein-protein interaction (PPI) networks, and immune cell infiltration analyses (ssGSEA) were performed on the intersecting genes. We then conducted MR analysis to assess the relationship between immune cells and both diseases. Inverse variance weighting (IVW) served as the primary MR method, supplemented by MR-Egger regression, weighted median, and weighted mode.

Results: MR analysis revealed that OSA increased the risk of MAFLD [odds ratio (OR)=1.40, 95% CI 1.14-1.73, p= 0.002], with OSA potentially mediating the effect of BMI on MAFLD, accounting for 62.3% of the mediation. Bioinformatics identified 42 intersection genes. Four hub genes (FOS, EGR1, NR4A1, JUN) were ultimately obtained by PPI network, which were strongly linked to immune cell infiltration. Additionally, three immune cell phenotypes (CD4RA on TD CD4+, HLA DR on CD14+ CD16-monocytes, and HLA DR on CD14+ monocytes) were found to be associated with both OSA and MAFLD.

Conclusion: OSA may causally influence MAFLD and mediate the effect of BMI on MAFLD. Four key genes and three immune cell phenotypes play crucial roles in the shared pathogenesis of both diseases.

Keywords: Mendelian randomization; OSA; bioinformatics; metabolic dysfunction-associated fatty liver disease; obstructive sleep apnea.

Figure 1

Overview and analysis process of our research.

Figure 2

Results of Mendelian randomization. (A) Forward and reverse Mendelian randomization explored the associations between OSA and MAFLD; (B) Network Mendelian randomization study explored the interconnected relationships among BMI, OSA, and MAFLD.

Figure 3

Differential gene expression analysis. ((A) OSA; (B) MAFLD) Volcano plots depict the differential expression genes (DEGs) in OSA and MAFLD; ((C) OSA; (D) MAFLD) Heatmaps illustrate the top 50 DEGs in OSA and MAFLD.

Figure 4

Weighted gene co-expression network analysis. ((A) OSA; (D) MAFLD) Determination of soft threshold powers in OSA and MAFLD. ((B) OSA; (E) MAFLD) Gene cluster trees in OSA and MAFLD. ((C) OSA; (F) MAFLD) Modular-feature relationship in OSA and MAFLD, with numbers in the modules representing correlation coefficients and p-values.

Figure 5

Functional and pathway enrichment analysis. (A) Venn diagram of intersecting analysis of DEGs and key module genes for OSA and MAFLD; (B) GO analysis of intersection genes; (C) KEGG enrichment of intersection genes.

Figure 6

Construction of PPI network and identification of hub genes. (A) PPI network of intersection genes. (B) Hub genes determined by MCC, MNC, Degree, and EPC algorithms. (C and D) Expression profiles of hub genes in OSA and MAFLD; (E and F) ROC curves demonstrate the predictive performance of hub genes in OSA and MAFLD.

Figure 7

Immune cell infiltration analysis. ((A) OSA; (C) MAFLD) Composition of immune cells in OSA and MAFLD; ((B) OSA; (D) MAFLD) Analysis of the correlation between hub genes and various infiltrating immune cells, as well as among infiltrating immune cells. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.

Figure 8

Results of Mendelian randomization of immune cell phenotypes and OSA and MAFLD. (A) Venn diagram of immunophenotypes that OSA and MAFLD; (B) Forest plots of immunophenotypes influencing both OSA and MAFLD.