Identification of novel differentially methylated sites with potential as clinical predictors of impaired respiratory function and COPD
Mairead L. Bermingham,
Rosie M Walker,
Riccardo E Marioni,
Stewart M Morris,
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)
Posted 19 Nov 2018
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.
- Downloaded 250 times
- Download rankings, all-time:
- Site-wide: 106,730
- In genomics: 6,251
- Year to date:
- Site-wide: 140,875
- Since beginning of last month:
- Site-wide: 142,293
Downloads over time
Distribution of downloads per paper, site-wide
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!