Souza Maingredy Rodrigues, Moysés-Oliveira Mariana, Porcacchia Allan Saj, Rosa Daniela Santoro, Tufik Sergio, Andersen Monica Levy
Instituto do Sono, Associação Fundo Incentivo à Pesquisa (AFIP), São Paulo, Brazil.
Departamento de Psicobiologia, Universidade Federal de São Paulo, São Paulo, Brazil.
Sleep Breath. 2025 May 7;29(2):178. doi: 10.1007/s11325-025-03341-z.
Obstructive sleep apnea (OSA) and asthma are connected through similar epidemiology, clinical symptoms, pathophysiological features, and risk factors. However, the shared genetic basis of these conditions remains poorly understood. This study sought to identify risk genes that contribute to both OSA and asthma and to explore their associated biological pathways.
This study was conducted using an in silico approach based on publicly available Genome-Wide Association Studies (GWAS) data. Gene sets associated with OSA (2,159 genes) and asthma (786 genes) were manually curated from GWAS results. These lists were subsequently compared to identify intersecting genes, and their statistical significance was assessed using Fisher's Exact Test. Pathway enrichment analysis was conducted utilizing the Benjamini-Hochberg test with a significance threshold set at an adjusted p-value < 0.05.
A total of 187 genes overlapped between OSA and asthma, indicating a significantly higher occurrence than expected by chance. The pathway overrepresentation analysis of these intersecting genes identified processes associated with immune system functions, encompassing human leucocyte antigen (HLA), antigen presentation, cell differentiation, cell signaling, and positive regulation of inflammatory mediators.
This study unveils shared genetic mechanisms associated with OSA and asthma risks, highlighting intricate interactions within pathways governing immune response and inflammation. These findings provide a preliminary step toward understanding the genetic basis of this association; however, their clinical significance remains to be established. Further functional studies and validation in independent cohorts are needed to determine their potential relevance for biomarker development and immune-targeted therapeutic strategies.
阻塞性睡眠呼吸暂停(OSA)和哮喘在流行病学、临床症状、病理生理特征及风险因素方面存在相似之处。然而,这两种疾病共同的遗传基础仍知之甚少。本研究旨在识别导致OSA和哮喘的风险基因,并探索其相关的生物学途径。
本研究采用基于公开可用的全基因组关联研究(GWAS)数据的计算机模拟方法。从GWAS结果中手动筛选出与OSA(2159个基因)和哮喘(786个基因)相关的基因集。随后比较这些列表以识别交集基因,并使用Fisher精确检验评估其统计学意义。利用Benjamini-Hochberg检验进行通路富集分析,显著性阈值设定为校正p值<0.05。
OSA和哮喘之间共有187个基因重叠,表明其出现频率显著高于偶然预期。对这些交集基因的通路过度表达分析确定了与免疫系统功能相关的过程,包括人类白细胞抗原(HLA)、抗原呈递、细胞分化、细胞信号传导以及炎症介质的正调控。
本研究揭示了与OSA和哮喘风险相关的共同遗传机制,突出了免疫反应和炎症调控通路中的复杂相互作用。这些发现为理解这种关联的遗传基础迈出了初步步伐;然而,其临床意义仍有待确定。需要进一步的功能研究和在独立队列中的验证,以确定它们在生物标志物开发和免疫靶向治疗策略方面的潜在相关性。