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- Title
No convincing association between genetic markers and respiratory symptoms: results of a GWA study.
- Authors
Xiang Zeng; Vonk, Judith M.; Kim de Jong; Xijin Xu; Xia Huo; Boezen, H. Marike; Zeng, Xiang; de Jong, Kim; Xu, Xijin; Huo, Xia
- Abstract
<bold>Background: </bold>Respiratory symptoms are associated with accelerated lung function decline, and increased hospitalization and mortality rates in the general population. Although several environmental risk factors for respiratory symptoms are known, knowledge on genetic risk factors is lacking. We aim to identify genetic variants associated with respiratory symptoms by genome-wide association (GWA) analyses.<bold>Methods: </bold>We conducted the first GWA study on cough, dyspnea and phlegm among 7,976 participants in the LifeLines I cohort and used the LifeLines II cohort (n = 5,260) and the Vlagtwedde-Vlaardingen cohort (n = 1,529) for replication.<bold>Results: </bold>We identified 50 SNPs that were assessed for replication. Rs16918212, located in the alpha-2-macroglobulin pseudogene 1 (A2MP1), was associated with cough in both the identification (odds ratio (OR) = 0.72, p = 5.41 × 10-5) and the meta-analyzed replication cohorts (OR = 0.83, p = 0.033). No other significant replicated associations were found.<bold>Conclusions: </bold>Given that only 1 out of 50 SNPs showed significant replication (i.e. 2%) we conclude that we did not find a convincing association between genetic markers and respiratory symptoms. Since, environmental exposures are important risk factors for respiratory symptoms, the next step is to perform a genome-wide interaction (GWI) study to identify genetic susceptibility loci for respiratory symptoms in interaction with known harmful environmental exposures.
- Subjects
NETHERLANDS; PULMONARY manifestations of general diseases; RESPIRATORY diseases; COUGH diagnosis; DYSPNEA; MACROGLOBULINS; RESPIRATORY disease diagnosis; DEMOGRAPHY; DISEASE susceptibility; LONGITUDINAL method; GENETIC markers; GENETIC testing; DISEASE prevalence; SEQUENCE analysis
- Publication
Respiratory Research, 2017, Vol 18, p1
- ISSN
1465-9921
- Publication type
journal article
- DOI
10.1186/s12931-016-0495-4