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Identification of novel differentially methylated sites with potential as clinical predictors of impaired respiratory function and COPD

By Mairead L. Bermingham, Rosie M. Walker, Riccardo E. Marioni, Stewart M Morris, Konrad Rawlik, Yanni Zeng, Archie Campbell, Paul Redmond, Heather C Whalley, Mark J Adams, Prof. Caroline Hayward, Prof. Ian J Deary, Prof. David J Porteous, Prof. Andrew M McIntosh, Kathryn L Evans

Posted 19 Nov 2018
bioRxiv DOI: 10.1101/473629 (published DOI: 10.1016/j.ebiom.2019.03.072)

Background: The causes of poor respiratory function and COPD are incompletely understood, but it is clear that genes and the environment play a role. As DNA methylation is under both genetic and environmental control, we hypothesised that investigation of differential methylation associated with these phenotypes would permit mechanistic insights, and improve prediction of COPD. We investigated genome-wide differential DNA methylation patterns using the recently released 850K Illumina EPIC array in the largest single population sample to date. Methods: Epigenome-wide association studies (EWASs) of respiratory function and COPD were performed in peripheral blood samples from the Generation Scotland: Scottish Family Health Study (GS:SFHS) cohort (N=3,791; 274 COPD cases and 2,928 controls). In independent COPD incidence data (N=150), significantly differentially methylated sites (DMSs; p<3.6*10−8) were evaluated for their added predictive power when added to a model including clinical variables, age, sex, height and smoking history using receiver operating characteristic analysis. The Lothian Birth Cohort 1936 (LBC1936) was used to replicate association (N=895) and prediction (N=178) results. Findings: We identified 29 respiratory function and/or COPD associated DMSs, which mapped to genes involved in alternative splicing, JAK-STAT signalling, and axon guidance. In prediction analyses, we observed significant improvement in discrimination between COPD cases and controls (p<0.05) in independent GS:SFHS (p=0.014) and LBC1936 (p=0.018) datasets by adding DMSs to a clinical model. Interpretation: Identification of novel DMSs has provided insight into the molecular mechanisms regulating respiratory function and aided prediction of COPD risk. Funding: Wellcome Trust Strategic Award 10436/Z/14/Z.

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