A novel whole blood gene expression signature for asthma, dermatitis, and rhinitis multimorbidity in children and adolescents
Background Allergic diseases often occur in combination (multimorbidity). Human blood transcriptome studies have not addressed multimorbidity. Large‐scale gene expression data were combined to retrieve biomarkers and signaling pathways to disentangle allergic multimorbidity phenotypes. Methods Integ...
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| Published in: | Allergy (Copenhagen) Vol. 75; no. 12; pp. 3248 - 3260 |
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Denmark
Blackwell Publishing Ltd
01.12.2020
Wiley |
| Subjects: | |
| ISSN: | 0105-4538, 1398-9995, 1398-9995 |
| Online Access: | Get full text |
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| Summary: | Background
Allergic diseases often occur in combination (multimorbidity). Human blood transcriptome studies have not addressed multimorbidity. Large‐scale gene expression data were combined to retrieve biomarkers and signaling pathways to disentangle allergic multimorbidity phenotypes.
Methods
Integrated transcriptomic analysis was conducted in 1233 participants with a discovery phase using gene expression data (Human Transcriptome Array 2.0) from whole blood of 786 children from three European birth cohorts (MeDALL), and a replication phase using RNA Sequencing data from an independent cohort (EVA‐PR, n = 447). Allergic diseases (asthma, atopic dermatitis, rhinitis) were considered as single disease or multimorbidity (at least two diseases), and compared with no disease.
Results
Fifty genes were differentially expressed in allergic diseases. Thirty‐two were not previously described in allergy. Eight genes were consistently overexpressed in all types of multimorbidity for asthma, dermatitis, and rhinitis (CLC, EMR4P, IL5RA, FRRS1, HRH4, SLC29A1, SIGLEC8, IL1RL1). All genes were replicated the in EVA‐PR cohort. RT‐qPCR validated the overexpression of selected genes. In MeDALL, 27 genes were differentially expressed in rhinitis alone, but none was significant for asthma or dermatitis alone. The multimorbidity signature was enriched in eosinophil‐associated immune response and signal transduction. Protein‐protein interaction network analysis identified IL5/JAK/STAT and IL33/ST2/IRAK/TRAF as key signaling pathways in multimorbid diseases. Synergistic effect of multimorbidity on gene expression levels was found.
Conclusion
A signature of eight genes identifies multimorbidity for asthma, rhinitis, and dermatitis. Our results have clinical and mechanistic implications, and suggest that multimorbidity should be considered differently than allergic diseases occurring alone.
This study compares gene expression from whole blood of European children (4‐16 years) with asthma and/or dermatitis and/or rhinitis to controls without allergy. Eight genes are overlapping among DEGs found in multimorbidity for asthma, dermatitis and rhinitis, which had synergistic effects along the number of co‐occurrent diseases. Results were replicated in North American cohort with similar features. Abbreviations: AstM, asthma multimorbidity; CLC, charcot‐leyden crystal galectin; DEGs, differentially expressed genes; DerM, dermatitis multimorbidity; EMR4P, adhesion G protein‐coupled receptor E4; FRRS1, ferric chelate reductase 1; HRH4, histamine receptor H4; IL1RL1, interleukin 1 receptor like 1; IL5RA, interleukin 5 receptor subunit alpha; RhiM, rhinitis multimorbidity; SIGLEC8, sialic acid binding Ig like lectin 8; SLC29A1, solute carrier family 29 member 1 |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Nathanaël Lemonnier performed the transcriptomic study, led the data production, led data preprocessing and data quality checking, contributed to data analysis plan, made the analyses, contributed to the replication plan, and wrote the paper. Erik Melén is the leader of the BAMSE cohort, contributed to sample selection, made significant comments on data analysis design and results, and led the replication plan. Yale Jiang contributed to the EVA-PR cohort and made significant contribution to the replication analysis. Stéphane Joly and Camille Ménard performed the data production, quality checking, RT-qPCR validation. Daniel Aguilar, Judith Garcia-Aymerich and Stefano Guerra discussed the analysis and the paper. Edna Acosta-Perez, Nadia Boutaoui, Glorisa Canino and Erick Forno contributed to the EVA-PR cohort and the replication study. Anna Bergström, Olena Gruzieva, Inger Kull and Magnus Wickman contributed to the BAMSE cohort. Mariona Bustamante, Juan Ramon González, Jesús Ibarluzea Maurolagoitia and Loreto Santa-Marina Rodriguez contributed to the INMA cohort. Joachim Heinrich and Elisabeth Thiering contributed to the GINIplus cohort. Cezmi Akdis, Mübeccel Akdi, Thomas Keil, Gerard H. Koppelman, Valérie Siroux and Cheng-Jian Xu participated to the discussion of the new data analysis plan and made significant comments on the analysis Wei Chen is a principal investigator of the EVA-PR cohort and the replication analysis. Pierre Hainaut made significant comments on multimorbidity and chronic diseases and the overall interpretation of the results. Marie Standl is the leader of the GINIplus cohort. Jordi Sunyer is the leader of the INMA cohort. Juan C. Celedón is the leader of the EVA-PR cohort and led the replication analysis. Josep M Antó was co-coordinator of MeDALL proposed the new analysis plan on multimorbidity with Jean Bousquet, led the analysis methodology with JB and NL and the overall interpretation of the results. Jean Bousquet was coordinator of MeDALL, proposed the new analysis plan on multimorbidity with Josep M Antó, led the multimorbidity analyses with JMA and NL and wrote the paper with NL. Lemonnier, Melén, Jiang, Celedón, Antó and Bousquet are contributed equally. AUTHOR’S CONTRIBUTION |
| ISSN: | 0105-4538 1398-9995 1398-9995 |
| DOI: | 10.1111/all.14314 |