IFNG, FCER1A, PCDHB10 expression as a new potential marker of efficacy in grass pollen allergen-specific immunotherapy
| Autor: | Marek Niedoszytko, Ewa Jassem, Agnieszka Maciejewska, Eliza Wasilewska, Jan Romantowski, Marta Chełmińska, Krzysztof Specjalski, Joanna Polanska |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Oncology
medicine.medical_specialty Allergy mRNA Dermatology medicine.disease_cause Allergen allergen Internal medicine Clinical endpoint Immunology and Allergy Medicine Asthma Whole blood Univariate analysis Original Paper allergic rhinitis business.industry Maintenance dose asthma medicine.disease FCER1A RC31-1245 RL1-803 business |
| Zdroj: | Advances in Dermatology and Allergology/Postȩpy Dermatologii i Alergologii Advances in Dermatology and Allergology, Vol 38, Iss 4, Pp 665-672 (2021) |
| ISSN: | 2299-0046 1642-395X |
| Popis: | Introduction Allergen-specific immunotherapy (AIT) is the core treatment in allergic rhinitis and asthma. Although widely used, some patients do not benefit from treatment and there is no efficacy objective marker. Aim To define the profile of gene transcripts during the build-up phase of AIT and their comparison to the control group and then search for a viable efficacy marker in relation to patient symptoms. Material and methods AIT was administered in 22 patients allergic to grass pollen. Analysis of 15 selected transcript expression was performed in whole blood samples taken before AIT (sample A) and after reaching the maintenance dose (sample B). The control group included 25 healthy volunteers (sample C). The primary endpoint was Relative Quantification. The gene expression analysis was followed by clinical evaluation with the use of Allergy Control Score (ACS). Results Comparison between samples A and B of gene expression showed a significant increase in IFNG expression (p = 0.03). In relation to the control group, pretreatment samples from patients showed higher levels of AFAP1L1 (p = 0.006), COMMD8 (p = 0.001), PIK3CD (p = 0.027) and TWIST2 (p = 0.0003) in univariate analysis. A generalized linear regression model was built according to the Bayesian Information Criterion based on the IFNG, FCER1A and PCDHB10 expression pattern for prediction of the AIT outcome. The model showed a correlation in predicted and observed changes in ACS. Conclusions There is a significant change in the expression of IFNG during the build-up phase of AIT. The authors propose an in vitro model of AIT efficacy prediction for further validation. |
| Databáze: | OpenAIRE |
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