TY - JOUR
T1 - IgE-Mediated Peanut Allergy
T2 - Current and Novel Predictive Biomarkers for Clinical Phenotypes Using Multi-Omics Approaches
AU - Czolk, Rebecca
AU - Klueber, Julia
AU - Sørensen, Martin
AU - Wilmes, Paul
AU - Codreanu-Morel, Françoise
AU - Skov, Per Stahl
AU - Hilger, Christiane
AU - Bindslev-Jensen, Carsten
AU - Ollert, Markus
AU - Kuehn, Annette
N1 - Funding Information:
Supported by the Luxembourg National Research Fund on PRIDE program grants PRIDE/11012546/NEXTIMMUNE and PRIDE17/11823097/MICROH; supported by the Personalized Medicine Consortium grant APSIS, PMC/2017/02 and by the Ministry of Research, Luxembourg.
Publisher Copyright:
© Copyright © 2021 Czolk, Klueber, Sørensen, Wilmes, Codreanu-Morel, Skov, Hilger, Bindslev-Jensen, Ollert and Kuehn.
PY - 2021/1/28
Y1 - 2021/1/28
N2 - Food allergy is a collective term for several immune-mediated responses to food. IgE-mediated food allergy is the best-known subtype. The patients present with a marked diversity of clinical profiles including symptomatic manifestations, threshold reactivity and reaction kinetics. In-vitro predictors of these clinical phenotypes are evasive and considered as knowledge gaps in food allergy diagnosis and risk management. Peanut allergy is a relevant disease model where pioneer discoveries were made in diagnosis, immunotherapy and prevention. This review provides an overview on the immune basis for phenotype variations in peanut-allergic individuals, in the light of future patient stratification along emerging omic-areas. Beyond specific IgE-signatures and basophil reactivity profiles with established correlation to clinical outcome, allergenomics, mass spectrometric resolution of peripheral allergen tracing, might be a fundamental approach to understand disease pathophysiology underlying biomarker discovery. Deep immune phenotyping is thought to reveal differential cell responses but also, gene expression and gene methylation profiles (eg, peanut severity genes) are promising areas for biomarker research. Finally, the study of microbiome-host interactions with a focus on the immune system modulation might hold the key to understand tissue-specific responses and symptoms. The immune mechanism underlying acute food-allergic events remains elusive until today. Deciphering this immunological response shall enable to identify novel biomarker for stratification of patients into reaction endotypes. The availability of powerful multi-omics technologies, together with integrated data analysis, network-based approaches and unbiased machine learning holds out the prospect of providing clinically useful biomarkers or biomarker signatures being predictive for reaction phenotypes.
AB - Food allergy is a collective term for several immune-mediated responses to food. IgE-mediated food allergy is the best-known subtype. The patients present with a marked diversity of clinical profiles including symptomatic manifestations, threshold reactivity and reaction kinetics. In-vitro predictors of these clinical phenotypes are evasive and considered as knowledge gaps in food allergy diagnosis and risk management. Peanut allergy is a relevant disease model where pioneer discoveries were made in diagnosis, immunotherapy and prevention. This review provides an overview on the immune basis for phenotype variations in peanut-allergic individuals, in the light of future patient stratification along emerging omic-areas. Beyond specific IgE-signatures and basophil reactivity profiles with established correlation to clinical outcome, allergenomics, mass spectrometric resolution of peripheral allergen tracing, might be a fundamental approach to understand disease pathophysiology underlying biomarker discovery. Deep immune phenotyping is thought to reveal differential cell responses but also, gene expression and gene methylation profiles (eg, peanut severity genes) are promising areas for biomarker research. Finally, the study of microbiome-host interactions with a focus on the immune system modulation might hold the key to understand tissue-specific responses and symptoms. The immune mechanism underlying acute food-allergic events remains elusive until today. Deciphering this immunological response shall enable to identify novel biomarker for stratification of patients into reaction endotypes. The availability of powerful multi-omics technologies, together with integrated data analysis, network-based approaches and unbiased machine learning holds out the prospect of providing clinically useful biomarkers or biomarker signatures being predictive for reaction phenotypes.
KW - endotypes
KW - food allergy
KW - peanut allergy
KW - phenotypes
KW - predictive biomarker
UR - http://www.scopus.com/inward/record.url?scp=85101054273&partnerID=8YFLogxK
UR - https://www.ncbi.nlm.nih.gov/pubmed/33584660
U2 - 10.3389/fimmu.2020.594350
DO - 10.3389/fimmu.2020.594350
M3 - Review article
C2 - 33584660
AN - SCOPUS:85101054273
SN - 1664-3224
VL - 11
SP - 594350
JO - Frontiers in Immunology
JF - Frontiers in Immunology
M1 - 594350
ER -