Genomics of asthma, allergy and chronic rhinosinusitis: novel concepts and relevance in airway mucosa

Abstract

Genome wide association studies (GWASs) have revealed several airway disease-associated risk loci. Their role in the onset of asthma, allergic rhinitis (AR) or chronic rhinosinusitis (CRS), however, is not yet fully understood. The aim of this review is to evaluate the airway relevance of loci and genes identified in GWAS studies. GWASs were searched from databases, and a list of loci associating significantly (p < 10^-8) with asthma, AR and CRS was created. This yielded a total of 267 significantly asthma/AR-associated loci from 31 GWASs. No significant CRS -associated loci were found in this search. A total of 170 protein coding genes were connected to these loci. Of these, 76/170 (44%) showed bronchial epithelial protein expression in stained microscopic figures of Human Protein Atlas (HPA), and 61/170 (36%) had a literature report of having airway epithelial function. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation analyses were performed, and 19 functional protein categories were found as significantly (p < 0.05) enriched among these genes. These were related to cytokine production, cell activation and adaptive immune response, and all were strongly connected in network analysis. We also identified 15 protein pathways that were significantly (p < 0.05) enriched in these genes, related to T-helper cell differentiation, virus infection, JAK-STAT signaling pathway, and asthma. A third of GWAS-level risk loci genes of asthma or AR seemed to have airway epithelial functions according to our database and literature searches. In addition, many of the risk loci genes were immunity related. Some risk loci genes also related to metabolism, neuro-musculoskeletal or other functions. Functions overlapped and formed a strong network in our pathway analyses and are worth future studies of biomarker and therapeutics.

Keywords: Airway epithelium; Allergic rhinitis; Asthma; GWAS; Gene ontology; Pathway.

Fig 1

Flow chart of the study. GWASs were searched from databases (https://www.ebi.ac.uk/gwas/ ) and a list and database of SNPs associating significantly (p < 10^–8 ) with asthma, AR and CRS was formed in 1/2018. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation analysis was performed for protein coding genes connected to SNPs. Airway epithelial expression of genes and corresponding proteins were evaluated by using Gene Cards, Human Protein Atlas (HPA), and literature search from PubMed. Other potential airway functions of the selected set of genes were evaluated from database /literature search. Abbreviations: AR allergic rhinitis, CRS chronic rhinosinusitis, GO Gene Ontology, GWAS genome‐wide association study, HPA Human Protein Atlas, KEGG Kyoto Encyclopedia of Genes and Genomes, SNP single nucleotide polymorphism, TPM Transcripts Per Million

Fig 2

Manhattan plot (https://biorender.com/ ) of the SNPs that were significantly associated (p < 5 × 10–8) with asthma/AR in GWASs

Fig 3

Database and literature analysis of airway expression of the corresponding proteins of the protein coding GWAS‐level genes (n = 170) associating with asthma/AR. a Human protein Atlas (HPA) was used to search for photomicrographs of the proteins and their staining intensity was semi‐quantitatively evaluated by two observers. b HPA results of lung expression in Transcripts per million (TPM). c Literature search results of airway epithelial expression of these genes. Pubmed search was performed by using search terms “(Gene name OR alias) AND epitheli* AND airway/bronc*”, Nasophar = Nasopharyngeal

Fig 4

Functional annotation of the genes corresponding to the SNPs that were significantly associated with asthma/AR in GWASs. We used the whole list of SNPs (Ensemble codes) shown in the Additional file 1 : Table S1. Of these, only SNPs that were connected to protein coding genes were used in this analysis, and only one unique gene associated with one or several SNPs were used. Noncoding genes related to these asthma/AR ‐associated SNPs were excluded in functional annotation. The total number of genes of this functional annotation was 155 genes. a Gene ontology (GO) categories (functional protein categories) that were enriched. b Gene function network interaction of the GO‐categories. The network interaction shows strong interaction between the GO‐categories and indicating regulation functions between each other. c Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enriched among 155 genes. Shades of blue and red indicate significance of the enrichment (all were significant at level p < 0.05), and the size of the dot represents gene count. X‐axis represents the number of genes belonging to the particular category / total number of observed genes (N = 155)

Fig 5

Postulated mechanisms of GWAS‐related genes in lower airways during asthma. Abbreviations: CCR7 C‐C‐motif chemokine receptor 7, DC Dendritic cell, EMT Epithelial‐mesenchymal transition, FCER1A Fc fragment of IgE receptor 1A, FeNO Fractional exhaled nitric oxide, FLG Filaggrin, GATA‐3 GATA binding protein 3, GDSMA Gasdermin A, GDSMB Gasdermin B, HLA Human leukocyte antigen, IgA Immunoglobulin A, IgE Immunoglobulin E, IgG Immunoglobulin G, IgM Immunoglobulin M, IKZF3 Ikaros family zinc finger protein 3, IL Interleukin, ILC2 Group 2 innate lymphoid cells, ILC3 Group 3 innate lymphoid cells, INFγ Interferon gamma, iNOS Inducible nitric oxide synthase, ITGβ8 Integrin Subunit Beta 8, LTD4 Leukotriene D4, MMP9 Matrix metalloproteinase 9, NKT cells Natural killer T cells, ORMDL3 Orosomucoid‐like 3, PGD2 Prostaglandin D2, RORα Retinoid‐Related Orphan Receptor Alpha, SMAD3 SMAD family member 3 (= Mothers against decapentaplegic homolog 3), STAT6 Signal transducer and activator of transcription 6, TFH cell T follicular helper cell, TGFβ Transforming growth factor beta, Th1 T helper type 1, Th2 T helper type 2, Th17 T helper type 17, TLR Toll‐like receptor, TNFα Tumor necrosis factor alpha, TSLP Thymic stromal lymphopoietin, YKL‐40 Chitinase like protein, Remodeling Smooth muscle and/or fibroblast proliferation, fibrosis, EMT etc.