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Nasal airway transcriptome-wide association study of asthma reveals genetically driven mucus pathobiology.

ABSTRACT: To identify genetic determinants of airway dysfunction, we performed a transcriptome-wide association study for asthma by combining RNA-seq data from the nasal airway epithelium of 681 children, with UK Biobank genetic association data. Our airway analysis identified 95 asthma genes, 58 of which were not identified by transcriptome-wide association analyses using other asthma-relevant tissues. Among these genes were MUC5AC, an airway mucin, and FOXA3, a transcriptional driver of mucus metaplasia. Muco-ciliary epithelial cultures from genotyped donors revealed that the MUC5AC risk variant increases MUC5AC protein secretion and mucus secretory cell frequency. Airway transcriptome-wide association analyses for mucus production and chronic cough also identified MUC5AC. These cis-expression variants were associated with trans effects on expression; the MUC5AC variant was associated with upregulation of non-inflammatory mucus secretory network genes, while the FOXA3 variant was associated with upregulation of type-2 inflammation-induced mucus-metaplasia pathway genes. Our results reveal genetic mechanisms of airway mucus pathobiology.

SUBMITTER: Sajuthi SP

PROVIDER: S-EPMC8960819 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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Nasal airway transcriptome-wide association study of asthma reveals genetically driven mucus pathobiology.

Sajuthi Satria P SP Everman Jamie L JL Jackson Nathan D ND Saef Benjamin B Rios Cydney L CL Moore Camille M CM Mak Angel C Y ACY Eng Celeste C Fairbanks-Mahnke Ana A Salazar Sandra S Elhawary Jennifer J Huntsman Scott S Medina Vivian V Nickerson Deborah A DA Germer Soren S Zody Michael C MC Abecasis Gonçalo G Kang Hyun Min HM Rice Kenneth M KM Kumar Rajesh R Zaitlen Noah A NA Oh Sam S Rodríguez-Santana José J Burchard Esteban G EG Seibold Max A MA

Nature communications 20220328 1

To identify genetic determinants of airway dysfunction, we performed a transcriptome-wide association study for asthma by combining RNA-seq data from the nasal airway epithelium of 681 children, with UK Biobank genetic association data. Our airway analysis identified 95 asthma genes, 58 of which were not identified by transcriptome-wide association analyses using other asthma-relevant tissues. Among these genes were MUC5AC, an airway mucin, and FOXA3, a transcriptional driver of mucus metaplasia ...[more]

PMID: 35347136

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Project description:IntroductionAsthma with airway mucus hypersecretion is an inadequately characterized variant of asthma. While several studies have reported that hypersecreting patients may carry genetic variants in the cystic fibrosis transmembrane conductance regulator (CFTR) gene, many of those studies have been questioned for their numerous limitations and contradictory results.Objectives(1) To determine the presence of genetic variants of the CFTR gene in patients with asthma with and without airway mucus hypersecretion. (2) To identify the clinical, inflammatory and functional characteristics of the asthma phenotype with airway mucus hypersecretion.MethodComparative multicentre cross-sectional descriptive study that included 100 patients with asthma (39 hypersecretors and 61 non-hypersecretors). Asthmatic hypersecretion was defined as the presence of cough productive of sputum on most days for at least 3 months in 2 successive years. The patients were tested for fractional exhaled nitric oxide, spirometry, induced sputum cell count, total immunoglobulin E (IgE), peripheral blood eosinophil count, C-reactive protein, blood fibrinogen and blood albumin and underwent a skin prick test. Asthma control and quality of life were assessed by the Asthma Control Test and Mini Asthma Quality of Life questionnaires, respectively. Blood DNA samples were collected from the patients and next-generation sequencing using a MiSeq sequencer and the Illumina platform was used for the CFTR gene analysis.ResultsGenetic differences were observed in the c.1680-870T>A polymorphism of the CFTR gene, significantly more evident in hypersecretors than in non-hypersecretors: 78.94% vs. 59.32% in the majority allele and 21.05% vs. 40.67% in the minority allele (p = 0.036). Clinically, asthma hypersecretors compared to non-hypersecretors were older (57.4 years vs. 49.4 years; p = 0.004); had greater asthma severity (58.9% vs. 23.7%; p = 0.005); experienced greater airway obstruction (FEV1/FVC% 64.3 vs. 69.5; p = 0.041); had poorer asthma control (60% vs. 29%; p = 0.021); had lower IgE levels (126.4 IU/mL vs. 407.6 IU/mL; p = 0.003); and were less likely to have a positive prick test (37.5% vs. 68.85%; p = 0.011).ConclusionThe results suggest that patients with asthma and with mucus hypersecretion (1) may have a different phenotype and disease mechanism produced by an intronic polymorphism in the CFTR gene (NM_000492.3:c.1680-870T>A), and (2) may have a poorer clinical outcome characterized by severe disease and poorer asthma control with a non-allergic inflammatory phenotype.

Project description:Background: Asthma is common chronic inflammatory disease of the airways with a heterogenous clinical presentation. Individual differences in asthma susceptibility remain poorly understood, although genetics is thought to play a major role. Aim: To build a polygenic risk score (PRS) for asthma and determine whether predictive genetic variants can be epigenomically linked to specific pathophysiological mechanisms. Methods: PRSs were constructed using data from genome-wide association studies and performance was validated using data generated in the Rotterdam Study, a Dutch prospective cohort of 14,926 individuals. Outcomes used were asthma, childhood-onset asthma, adulthood-onset asthma, eosinophilic asthma and exacerbations. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-Seq) data from 14 primary cell types, including lung epithelial cells and T lymphocytes was used for epigenomic PRS partitioning. Results: All PRSs successfully predicted risk to develop asthma and related outcomes, with the strongest predictive power (2.42 odds ratios per PRS standard deviation, area under the curve of 0.736) achieved for childhood-onset asthma. PRSs allowed for stratification of the Rotterdam Study cohort into groups at low or high risk to develop asthma. PRS partitioning using genome-wide epigenomic profiles identified 5 clusters of variants within gene regulatory regions linked to specific asthma-relevant cells, genes and biological pathways. Conclusions: PRSs can predict whether individuals in a Dutch cohort developed asthma and asthma-related phenotypes, which is most effective for childhood-onset asthma. Importantly, we show that PRS partitioning based on epigenomics data dissects a genetic risk score into blocks of regulatory variants with differential predictive power, which likely represent distinct genetically driven disease pathways. These findings have potential implications for personalized risk mitigation and treatment strategies.

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Nasal airway transcriptome-wide association study of asthma reveals genetically driven mucus pathobiology.

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Nasal airway transcriptome-wide association study of asthma reveals genetically driven mucus pathobiology.

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