Abstract
Background In the realm of immunological disorders, allergic rhinitis (AR) persists as a prevalent condition, yet its molecular underpinnings remain only partially deciphered, necessitating deeper exploration. This study pioneers in bridging this knowledge gap, unveiling intricate molecular markers and pathways pivotal to AR's pathophysiology, thereby steering the scientific community towards novel diagnostic and prognostic frontiers. Employing rigorous bioinformatics analyses, similar to methodologies applied in studies on endometriosis and age-related macular degeneration, we delved into the molecular landscape, identifying 21 hypoxia-related differential expression genes (HRDEGs) and constructing a robust LASSO diagnostic model, a methodology that stands out for its precision in capturing clinical heterogeneity.Methods Our approach encompassed a comprehensive analysis of differential gene expressions, focusing particularly on HRDEGs, and their subsequent integration into a logistic regression model to ascertain their diagnostic and prognostic efficacy. Key findings revealed a high expression of genes such as CPT1C and MMP1 in the AR group, underscoring their significance in AR's molecular signature. Furthermore, the constructed LASSO model demonstrated high accuracy, highlighting genes like CPT1C, CWF19L1, MED17, and MMP1 as reliable biomarkers.Results Interestingly, the study also unearthed a nuanced interplay between AR and other systemic conditions, suggesting that the molecular mechanisms underlying allergic inflammation could influence the pathophysiology of various respiratory diseases3. These insights not only contribute to the academic discourse but also hold profound therapeutic potential, particularly in the realm of personalized medicine.Conclusions In conclusion, this research illuminates the molecular complexities of AR, offering substantial evidence for the involvement of specific genes and pathways in its pathogenesis. The implications of these discoveries are far-reaching, promising to revolutionize AR management through more tailored therapeutic strategies and underscoring the need for further investigations in larger, more diverse cohorts.