Galectin-10 in serum extracellular vesicles reflects asthma pathophysiology.

BACKGROUND: Novel biomarkers (BMs) are urgently needed for bronchial asthma (BA) with various phenotypes and endotypes. OBJECTIVE: We sought to identify novel BMs reflecting tissue pathology from serum extracellular vesicles (EVs). METHODS: We performed data-independent acquisition of serum EVs from 4 healthy controls, 4 noneosinophilic asthma (NEA) patients, and 4 eosinophilic asthma (EA) patients to identify novel BMs for BA. We confirmed EA-specific BMs via data-independent acquisition validation in 61 BA patients and 23 controls. To further validate these findings, we performed data-independent acquisition for 6 patients with chronic rhinosinusitis without nasal polyps and 7 patients with chronic rhinosinusitis with nasal polyps. RESULTS: We identified 3032 proteins, 23 of which exhibited differential expression in EA. Ingenuity pathway analysis revealed that protein signatures from each phenotype reflected disease characteristics. Validation revealed 5 EA-specific BMs, including galectin-10 (Gal10), eosinophil peroxidase, major basic protein, eosinophil-derived neurotoxin, and arachidonate 15-lipoxygenase. The potential of Gal10 in EVs was superior to that of eosinophils in terms of diagnostic capability and detection of airway obstruction. In rhinosinusitis patients, 1752 and 8413 proteins were identified from EVs and tissues, respectively. Among 11 BMs identified in EVs and tissues from patients with chronic rhinosinusitis with nasal polyps, 5 (including Gal10 and eosinophil peroxidase) showed significant correlations between EVs and tissues. Gal10 release from EVs was implicated in eosinophil extracellular trapped cell death in vitro and in vivo. CONCLUSION: Novel BMs such as Gal10 from serum EVs reflect disease pathophysiology in BA and may represent a new target for liquid biopsy approaches.

From drug repositioning to target repositioning: prediction of therapeutic targets using genetically perturbed transcriptomic signatures.

MOTIVATION: A critical element of drug development is the identification of therapeutic targets for diseases. However, the depletion of therapeutic targets is a serious problem. RESULTS: In this study, we propose the novel concept of target repositioning, an extension of the concept of drug repositioning, to predict new therapeutic targets for various diseases. Predictions were performed by a trans-disease analysis which integrated genetically perturbed transcriptomic signatures (knockdown of 4345 genes and overexpression of 3114 genes) and disease-specific gene transcriptomic signatures of 79 diseases. The trans-disease method, which takes into account similarities among diseases, enabled us to distinguish the inhibitory from activatory targets and to predict the therapeutic targetability of not only proteins with known target-disease associations but also orphan proteins without known associations. Our proposed method is expected to be useful for understanding the commonality of mechanisms among diseases and for therapeutic target identification in drug discovery. AVAILABILITY AND IMPLEMENTATION: Supplemental information and software are available at the following website [http://labo.bio.kyutech.ac.jp/~yamani/target_repositioning/]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.