Biomarkers of AIT: Models of prediction of efficacy
Tiak Ju Tan1, María I. Delgado-Dolset1,2, María M. Escribese2, Domingo Barber2, Janice A. Layhadi1, Mohamed H. Shamji1
1 Immunomodulation and Tolerance Group, Department of National Heart and Lung Institute, Imperial College London, London, UK, and 2 Institute of Applied Molecular Medicine (IMMA), Department of Basic Medical Sciences, Facultad de Medicina, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, Boadilla del Monte, Madrid, Spain
DOI 10.5414/ALX02333E
Abstract
Allergic rhinitis is an IgE-mediated inflammation that remains a clinical challenge, affecting 40% of the UK population with a wide range of severity from nasal discomfort to life-threatening anaphylaxis. It can be managed by pharmacotherapeutics and in selected patients by allergen immunotherapy (AIT), which provides long-term clinical efficacy, especially during peak allergy season. However, there are no definitive biomarkers for AIT efficacy. Here, we aim to summarize the key adaptive, innate, humoral, and metabolic advances in biomarker identification in response to AIT. Mechanisms of efficacy consist of an immune deviation towards TH1-secreting IFN-γ, as well as an induction of IL10+ cTFR and TREG have been observed. TH2 cells undergo exhaustion after AIT due to chronic allergen exposure and correlates with the exhaustion markers PD-1, CTLA-4, TIGIT, and LAG3. IL10+ DCREG expressing C1Q and STAB are induced. KLRG1+ IL10+ ILC2 were shown to be induced in AIT in correlation with efficacy. BREG cells secreting IL-10, IL-35, and TGF-β are induced. Blocking antibodies IgG, IgA, and IgG4 are increased during AIT; whereas inflammatory metabolites, such as eicosanoids, are reduced. There are multiple promising biomarkers for AIT currently being evaluated. A panomic approach is essential to better understand cellular, molecular mechanisms and their correlation with clinical outcomes. Identification of predictive biomarkers of AIT efficacy will hugely impact current practice allowing physicians to select eligible patients that are likely to respond to treatment as well as improve patients’ compliance to complete the course of treatment.
Author Details
Authors
Departments
- 1 Immunomodulation and Tolerance Group, Department of National Heart and Lung Institute, Imperial College London, London, UK, and
- 2 Institute of Applied Molecular Medicine (IMMA), Department of Basic Medical Sciences, Facultad de Medicina, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, Boadilla del Monte, Madrid, Spain
Address
Dr. Mohamed H. Shamji, Immunomodulation and Tolerance Group, Allergy & Clinical Immunology, Inflammation, Repair and Development, National Heart & Lung Institute, Imperial College London, 1st Floor, Room 111, Sir Alexander Fleming Building, South Kensington Campus, London SW7 2AZ, UK
Email:
[email protected]
Citation
Tiak Ju Tan, María I. Delgado-Dolset, María M. Escribese, Domingo Barber, Janice A. Layhadi, and Mohamed H. Shamji.Biomarkers of AIT: Models of prediction of efficacy. Allergologie select. 2022; 6: 267-275. doi: 10.5414/ALX02333E.
