Asthma diagnosis using integrated analysis of eosinophil microRNAs

• Published in: Allergy (Copenhagen) Vol. 74; no. 3; pp. 507 - 517
• Main Authors: Rodrigo‐Muñoz, José M., Cañas, José A., Sastre, Beatriz, Rego, Natalia, Greif, Gonzalo, Rial, Manuel, Mínguez, Pablo, Mahíllo‐Fernández, Ignacio, Fernández‐Nieto, Mar, Mora, Inés, Barranco, Pilar, Quirce, Santiago, Sastre, Joaquín, Pozo, Victoria
• Format: Journal Article
• Language: English
• Published: Denmark Blackwell Publishing Ltd 01.03.2019
• Subjects: Asthma; Asthma - blood; Asthma - diagnosis; Asthma - etiology; biomarker; Biomarkers; Case-Control Studies; Computational Biology - methods; Diagnosis; eosinophil; Eosinophils - immunology; Eosinophils - metabolism; Female; Gene Expression Profiling; High-Throughput Nucleotide Sequencing; Humans; Leukocytes (eosinophilic); Male; Medical diagnosis; microRNA; MicroRNAs; MicroRNAs - genetics; miRNA; Real-Time Polymerase Chain Reaction; Regression analysis; Reproducibility of Results; Respiratory tract; Respiratory tract diseases; ROC Curve; Severity of Illness Index; diagnosis; microRNA; asthma; biomarker; eosinophil
• ISSN: 0105-4538; 1398-9995; 1398-9995
• DOI: 10.1111/all.13570

Background Asthma is a syndrome characterized by airway inflammation and obstruction. Due to its heterogeneity, the difficulties in asthma diagnosis and treatment make the discovery of new biomarkers a focus of research. So, we determined the differential miRNA expression of eosinophils between healthy and asthmatic patients and to establish a differentially expressed miRNA profile detectable in sera for use as biomarker. Methods MicroRNAs from peripheral eosinophils from healthy and asthmatic subjects were isolated and analyzed by next‐generation sequencing and confirmed by quantitative PCR in 29 asthmatics and 10 healthy individuals. The levels of serum miRNAs were performed by quantitative PCR in 138 asthmatics and 39 healthy subjects. Regression analysis and Random Forest models were performed. Results We found a set of miRNAs whose expression differs between eosinophils from asthmatics and healthy subjects. These miRNAs can classify asthmatics into two clusters that differed in the number of eosinophils and periostin concentration in serum. Some of these miRNAs were also confirmed in sera, as miR‐185‐5p which discriminates asthmatics from healthy subjects. Together with other two miRNAs, miR‐185‐5p allowed us to create a logistic regression model to discriminate better both conditions and a Random Forest model that can even sort the asthmatics into intermittent, mild persistent, moderate persistent, and severe persistent asthma. Conclusion Our data show that miRNAs profile in eosinophils can be used as asthma diagnosis biomarker in serum and that this profile is able to rank asthma severity. Eosinophils from asthmatics present a different profile in microRNAs (miRNAs) compared to eosinophils from healthy subjects. As eosinophils obtention from patients is not a standardized method, we analyzed these miRNAs in serum showing that miRNAs profile expression in this biofluid can be used for asthma diagnosis and for severity classification.