Epigenome-scale comparison of DNA methylation between blood leukocytes and bronchial epithelial cells

Predicting locus-specific DNA methylation levels in cancer and paracancer tissues

Aim: To predict base-resolution DNA methylation in cancerous and paracancerous tissues. Material & methods: We collected six cancer DNA methylation datasets from The Cancer Genome Atlas and five cancer datasets from Gene Expression Omnibus and established machine learning models using paired cancerous and paracancerous tissues. Tenfold cross-validation and independent validation were performed to demonstrate the effectiveness of the proposed method. Results: The developed cross-tissue prediction models can substantially increase the accuracy at more than 68% of CpG sites and contribute to enhancing the statistical power of differential methylation analyses. An XGBoost model leveraging multiple correlating CpGs may elevate the prediction accuracy. Conclusion: This study provides a powerful tool for DNA methylation analysis and has the potential to gain new insights into cancer research from epigenetics.

The complexity in DNA methylation analysis of allergic diseases

PURPOSE OF REVIEW

This review aims to report all the recent studies that are implicated in DNA methylation analysis in the field of allergy and to underline the complexity of the study methodologies and results.

RECENT FINDINGS

Although the growing number of DNA methylation studies have yet to point to a specific mechanism, herein we provide an overview of the majority of pathways considered to be implicated and highlight particular genes, like KNH2 , ATPAF2 and ZNF385A , for their potential as biomarkers.

SUMMARY

The epigenetic profile of respiratory allergic diseases, and particularly DNA methylation, has been investigated in various populations, so as to gain a better understanding of its role in pathogenesis. Through our analysis, multiple links are presented between differential DNA methylation loci and IgE sensitization, lung functionality and severity of the disease. Additionally, associations of this epigenetic change with maternal asthma, age, sex and environmental factors are described, thus uncovering specific gene families that, after further examination could be used as methylation biomarkers in cases of allergic disease.