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A cell-type deconvolution meta-analysis of whole blood EWAS reveals lineage-specific smoking-associated DNA methylation changes.

Chenglong YouSijie WuShijie C ZhengTianyu ZhuHan JingKen FlaggGuangyu WangLi JinSi-Jia WangAndrew E Teschendorff
Published in: Nature communications (2020)
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.
Keyphrases
  • dna methylation
  • smoking cessation
  • genome wide
  • gene expression
  • single cell
  • machine learning
  • bone marrow
  • copy number
  • cell therapy
  • immune response
  • mesenchymal stem cells