Abstract
BACKGROUND: Sleep apnea syndrome (SAS) is a prevalent sleep disorder strongly associated with obesity, metabolic dysregulation, and cardiovascular diseases. While its underlying pathophysiological mechanisms remain incompletely understood, genetic factors likely play a pivotal role in SAS pathogenesis. This study investigates the causal relationships between potential drug target genes and SAS using multiple statistical approaches, aiming to provide novel insights for targeted therapeutic development. METHODS: We conducted a comprehensive genetic analysis integrating multiple methodologies to investigate gene-SAS relationships. Using publicly available GWAS and eQTL databases, we performed Mendelian Randomization (MR) analysis with the inverse variance weighted (IVW) method, validated by weighted median and MR-Egger approaches. Summary-data-based MR (SMR) analysis, coupled with HEIDI testing, assessed direct gene expression-SAS associations while controlling for linkage disequilibrium (LD). Colocalization analysis evaluated the probability of shared causal variants between SNPs, gene expression, and SAS. Statistical significance was determined using Benjamini-Hochberg multiple testing correction (FDR < 0.05). Additionally, mediation analysis explored TEX10's influence on SAS through metabolic intermediates including BMI, waist circumference, and HDL cholesterol. RESULTS: We identified 18 candidate drug target genes significantly associated with SAS, with MAPKAPK3, TNXB, MPHOSPH8, and TEX10 showing consistent associations across multiple analyses. TEX10, in particular, exhibited significant associations with SAS risk in blood, cerebral cortex, hippocampus, and basal ganglia (PP.H4 > 0.9). Mediation analysis suggested that TEX10 might influence SAS risk indirectly through BMI, waist circumference, and HDL cholesterol levels. CONCLUSION: Our study identified multiple potential therapeutic targets causally linked to SAS, with TEX10 emerging as a key candidate gene. These findings advance our understanding of SAS pathogenesis and offer promising directions for personalized diagnostics and targeted therapies.