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- Title
A cell-type deconvolution meta-analysis of whole blood EWAS reveals lineage-specific smoking-associated DNA methylation changes.
- Authors
You, Chenglong; Wu, Sijie; Zheng, Shijie C.; Zhu, Tianyu; Jing, Han; Flagg, Ken; Wang, Guangyu; Jin, Li; Wang, Sijia; Teschendorff, Andrew E.
- Abstract
Highly reproducible smoking-associated DNA methylation changes in whole blood have been reported by many Epigenome-Wide-Association Studies (EWAS). These epigenetic alterations could have important implications for understanding and predicting the risk of smoking-related diseases. To this end, it is important to establish if these DNA methylation changes happen in all blood cell subtypes or if they are cell-type specific. Here, we apply a cell-type deconvolution algorithm to identify cell-type specific DNA methylation signals in seven large EWAS. We find that most of the highly reproducible smoking-associated hypomethylation signatures are more prominent in the myeloid lineage. A meta-analysis further identifies a myeloid-specific smoking-associated hypermethylation signature enriched for DNase Hypersensitive Sites in acute myeloid leukemia. These results may guide the design of future smoking EWAS and have important implications for our understanding of how smoking affects immune-cell subtypes and how this may influence the risk of smoking related diseases. Smoking-associated DNA methylation changes in whole blood have been reported by many EWAS. Here, the authors use a cell-type deconvolution algorithm to identify cell-type specific DNA methylation signals in seven EWAS, identifying lineage-specific smoking-associated DNA methylation changes.
- Subjects
DNA methylation; DECONVOLUTION (Mathematics); P16 gene; ACUTE myeloid leukemia; EPIGENOMICS; BLOOD cells; BLOOD
- Publication
Nature Communications, 2020, Vol 11, Issue 1, pN.PAG
- ISSN
2041-1723
- Publication type
Article
- DOI
10.1038/s41467-020-18618-y