Open AccessAn interdisciplinary approach to characterize peanut‐allergic patients—First data from the FOOD@ consortium
Author(s) -
Worm Margitta,
Alexiou Aikaterina,
Höfer Veronika,
Birkner Till,
Jeanrenaud Alexander C. S. N.,
Fauchère Florent,
Pazur Kristijan,
Steinert Carolin,
ArnauSoler Aleix,
Banerjee Priyanka,
Diefenbach Andreas,
DobbertinWelsch Josefine,
DölleBierke Sabine,
Francuzik Wojciech,
Ghauri Ahla,
Heller Stephanie,
Kalb Birgit,
Löber Ulrike,
Marenholz Ingo,
Markó Lajos,
Scheffel Jörg,
Potapenko Olena,
Roll Stephanie,
Lau Susanne,
Lee YoungAe,
Braun Julian,
Thiel Andreas,
Babina Magda,
Altrichter Sabine,
Forslund Sofia Kirke,
Beyer Kirsten
Publication year - 2022
Publication title -
clinical and translational allergy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.979
H-Index - 37
ISSN - 2045-7022
DOI - 10.1002/clt2.12197
Subject(s) - microbiome , peanut allergy , medicine , food allergy , allergy , dna methylation , immunology , immune system , biomarker , magic bullet , computational biology , bioinformatics , biology , gene , genetics , gene expression
Background Peanut allergy is a frequent cause of food allergy and potentially life‐threatening. Within this interdisciplinary research approach, we aim to unravel the complex mechanisms of peanut allergy. As a first step were applied in an exploratory manner the analysis of peanut allergic versus non‐allergic controls. Methods Biosamples were studied regarding DNA methylation signatures, gut microbiome, adaptive and innate immune cell populations, soluble signaling molecules and allergen‐reactive antibody specificities. We applied a scalable systems medicine computational workflow to the assembled data. Results We identified combined cellular and soluble biomarker signatures that stratify donors into peanut‐allergic and non‐allergic with high specificity. DNA methylation profiling revealed various genes of interest and stool microbiota differences in bacteria abundances. Conclusion By extending our findings to a larger set of patients (e.g., children vs. adults), we will establish predictors for food allergy and tolerance and translate these as for example, indicators for interventional studies.