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

Mairead Bermingham, Rosie Walker, Riccardo Marioni, Stewart Morris, Konrad Rawlik, Yanni Zeng, Archibald Campbell, Paul Redmond, Heather Whalley, Mark James Adams, Caroline Hayward, Ian Deary, David J. Porteous, Andrew McIntosh, Kathryn Evans

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

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. This is the largest single population, whole-genome epigenetic study 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 = 3781; 274 COPD cases and 2919 controls). In independent COPD incidence data (n = 149), 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 28 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 < .05) in independent GS:SFHS (p = .016) and LBC1936 (p = .010) 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. Further studies are needed to assess the causality and clinical utility of identified associations.

Fund
Wellcome Trust Strategic Award 10436/Z/14/Z.
Original languageEnglish
Pages (from-to)576-586
JournalEBioMedicine
Volume43
Early online date29 Mar 2019
DOIs
Publication statusPublished - 4 Jun 2019

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