Obstructive Sleep Apnea (OSA), a global public health concern affecting nearly 1 billion individuals, imposes a profound burden due to its high prevalence—exceeding 50% in certain regions—and its strong association with cardiovascular and metabolic complications, including hypertension, diabetes, and cognitive decline. Despite its clinical significance, OSA remains limited by a lack of targeted therapies, necessitating urgent exploration of novel biomarkers and therapeutic strategies.

Recent breakthroughs in bioinformatics have revolutionized OSA research by unraveling molecular mechanisms through large-scale data integration. Techniques such as genome-wide association studies (GWAS) and pathway analysis enable the identification of key genes and signaling networks, fostering precision diagnostics and early intervention. However, translating these discoveries into clinical practice requires interdisciplinary collaboration to bridge basic science and patient care.

This Research Topic aims to accelerate the translation of cutting-edge OSA research into clinical applications by fostering cross-disciplinary dialogue. Building on the success of the first issue, we seek to disseminate innovative findings that enhance the understanding of OSA pathophysiology, improve risk stratification, and drive the development of personalized treatment strategies. By showcasing diverse methodologies—from bioinformatics-driven discoveries to clinical trials—we strive to elevate awareness of OSA's multifaceted impact and catalyze collaborative solutions to improve patient outcomes.

The following article types are welcome for submission to this Research Topic: Brief Research Report, Case Report, Clinical Trial, Data Report, Methods, Mini Review, Opinion, Original Research, Perspective, Review, Study Protocol, and Systematic Review. Specific topics of interest include, but are not limited to:
o Advanced insights into the pathophysiology of OSA and mechanisms underlying associated comorbidities
o Development of bioinformatics-driven biomarkers for early detection
o Genomic and transcriptomic analyses utilizing GWAS, machine learning, or network modeling
o Multidisciplinary interventions integrating bioinformatics with clinical practice
o Clinical trials and real-world evidence regarding OSA management strategies

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