Dataset Information

An interferon-inducible signature of airway disease from blood gene expression profiling.

ABSTRACT:

Background

The molecular basis of airway remodelling in chronic obstructive pulmonary disease (COPD) remains poorly understood. We identified gene expression signatures associated with chest computed tomography (CT) scan airway measures to understand molecular pathways associated with airway disease.

Methods

In 2396 subjects in the COPDGene Study, we examined the relationship between quantitative CT airway phenotypes and blood transcriptomes to identify airway disease-specific genes and to define an airway wall thickness (AWT) gene set score. Multivariable regression analyses were performed to identify associations of the AWT score with clinical phenotypes, bronchial gene expression and genetic variants.

Results

Type 1 interferon (IFN)-induced genes were consistently associated with AWT, square root wall area of a hypothetical airway with 10 mm internal perimeter (Pi10) and wall area percentage, with the strongest enrichment in AWT. A score derived from 18 genes whose expression was associated with AWT was associated with COPD-related phenotypes including reduced lung function (forced expiratory volume in 1 s percentage predicted β= -3.4; p<0.05) and increased exacerbations (incidence rate ratio 1.7; p<0.05). The AWT score was reproducibly associated with AWT in bronchial samples from 23 subjects (β=3.22; p<0.05). The blood AWT score was associated with genetic variant rs876039, an expression quantitative trait locus for IKZF1, a gene that regulates IFN signalling and is associated with inflammatory diseases.

Conclusions

A gene expression signature with IFN-stimulated genes from peripheral blood and bronchial brushings is associated with CT AWT, lung function and exacerbations. Shared genes and genetic associations suggest viral responses and/or autoimmune dysregulation as potential underlying mechanisms of airway disease in COPD.

SUBMITTER: Yun JH

PROVIDER: S-EPMC9245457 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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Publications

An interferon-inducible signature of airway disease from blood gene expression profiling.

Yun Jeong H JH Lee Sool S Srinivasa Pooja P Morrow Jarrett J Chase Robert R Saferali Aadbida A Xu Zhonghui Z Cho Michael M Castaldi Peter P Hersh Craig P CP

The European respiratory journal 20220519 5

<h4>Background</h4>The molecular basis of airway remodelling in chronic obstructive pulmonary disease (COPD) remains poorly understood. We identified gene expression signatures associated with chest computed tomography (CT) scan airway measures to understand molecular pathways associated with airway disease.<h4>Methods</h4>In 2396 subjects in the COPDGene Study, we examined the relationship between quantitative CT airway phenotypes and blood transcriptomes to identify airway disease-specific gen ...[more]

PMID: 34649980

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Project description:Tuberculosis (TB), caused by infection with Mycobacterium tuberculosis, is a major cause of morbidity and mortality worldwide. Efforts to control it are hampered by difficulties with diagnosis, prevention and treatment. Most people infected with M. tuberculosis remain asymptomatic, termed latent TB, with a 10% lifetime risk of developing active TB disease. Current tests, however, cannot identify which individuals will develop disease. The immune response to M. tuberculosis is complex and incompletely characterized, hindering development of new diagnostics, therapies and vaccines. Here we identify a whole-blood 393 transcript signature for active TB in intermediate and high-burden settings, correlating with radiological extent of disease and reverting to that of healthy controls after treatment. A subset of patients with latent TB had signatures similar to those in patients with active TB. We also identify a specific 86-transcript signature that discriminates active TB from other inflammatory and infectious diseases. Modular and pathway analysis revealed that the TB signature was dominated by a neutrophil-driven interferon (IFN)-inducible gene profile, consisting of both IFN-gamma and type I IFN-alphabeta signalling. Comparison with transcriptional signatures in purified cells and flow cytometric analysis suggest that this TB signature reflects changes in cellular composition and altered gene expression. Although an IFN-inducible signature was also observed in whole blood of patients with systemic lupus erythematosus (SLE), their complete modular signature differed from TB, with increased abundance of plasma cell transcripts. Our studies demonstrate a hitherto underappreciated role of type I IFN-alphabeta signalling in the pathogenesis of TB, which has implications for vaccine and therapeutic development. Our study also provides a broad range of transcriptional biomarkers with potential as diagnostic and prognostic tools to combat the TB epidemic.

Project description:ImportanceTo date, there is no diagnostic test for Kawasaki disease (KD). Diagnosis is based on clinical features shared with other febrile conditions, frequently resulting in delayed or missed treatment and an increased risk of coronary artery aneurysms.ObjectiveTo identify a whole-blood gene expression signature that distinguishes children with KD in the first week of illness from other febrile conditions.Design, setting, and participantsThe case-control study comprised a discovery group that included a training and test set and a validation group of children with KD or comparator febrile illness. The setting was pediatric centers in the United Kingdom, Spain, the Netherlands, and the United States. The training and test discovery group comprised 404 children with infectious and inflammatory conditions (78 KD, 84 other inflammatory diseases, and 242 bacterial or viral infections) and 55 healthy controls. The independent validation group comprised 102 patients with KD, including 72 in the first 7 days of illness, and 130 febrile controls. The study dates were March 1, 2009, to November 14, 2013, and data analysis took place from January 1, 2015, to December 31, 2017.Main outcomes and measuresWhole-blood gene expression was evaluated using microarrays, and minimal transcript sets distinguishing KD were identified using a novel variable selection method (parallel regularized regression model search). The ability of transcript signatures (implemented as disease risk scores) to discriminate KD cases from controls was assessed by area under the curve (AUC), sensitivity, and specificity at the optimal cut point according to the Youden index.ResultsAmong 404 patients in the discovery set, there were 78 with KD (median age, 27 months; 55.1% male) and 326 febrile controls (median age, 37 months; 56.4% male). Among 202 patients in the validation set, there were 72 with KD (median age, 34 months; 62.5% male) and 130 febrile controls (median age, 17 months; 56.9% male). A 13-transcript signature identified in the discovery training set distinguished KD from other infectious and inflammatory conditions in the discovery test set, with AUC of 96.2% (95% CI, 92.5%-99.9%), sensitivity of 81.7% (95% CI, 60.0%-94.8%), and specificity of 92.1% (95% CI, 84.0%-97.0%). In the validation set, the signature distinguished KD from febrile controls, with AUC of 94.6% (95% CI, 91.3%-98.0%), sensitivity of 85.9% (95% CI, 76.8%-92.6%), and specificity of 89.1% (95% CI, 83.0%-93.7%). The signature was applied to clinically defined categories of definite, highly probable, and possible KD, resulting in AUCs of 98.1% (95% CI, 94.5%-100%), 96.3% (95% CI, 93.3%-99.4%), and 70.0% (95% CI, 53.4%-86.6%), respectively, mirroring certainty of clinical diagnosis.Conclusions and relevanceIn this study, a 13-transcript blood gene expression signature distinguished KD from other febrile conditions. Diagnostic accuracy increased with certainty of clinical diagnosis. A test incorporating the 13-transcript disease risk score may enable earlier diagnosis and treatment of KD and reduce inappropriate treatment in those with other diagnoses.

Dataset Information

An interferon-inducible signature of airway disease from blood gene expression profiling.

Background

Methods

Results

Conclusions

Publications

An interferon-inducible signature of airway disease from blood gene expression profiling.

Similar Datasets

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