Large-scale integration of DNA methylation and gene expression array platforms identifies both cis and trans relationships. Issue 12 (2nd December 2022)

• Record Type: Journal Article
• Authors: Lancaster, Eva E.; Vladimirov, Vladimir I.; Riley, Brien P.; Landry, Joseph W.; Roberson-Nay, Roxann; York, Timothy P.
• Is Part Of: Epigenetics. Volume 17:Issue 12(2022)
• Page Start: 1753
• Page End: 1773
• Publication Date: 2022-12-02
• Subjects: Epigenetics -- DNA methylation -- gene expression -- transcriptional regulation -- multi-omics -- data integration; Epigenesis -- Periodicals; Epigenetica; 572.86505
• DOI: 10.1080/15592294.2022.2079293
• Languages: English
• ISSNs: 1559-2294

Abstract

ABSTRACT: Although epigenome-wide association studies (EWAS) have been successful in identifying DNA methylation (DNAm) patterns associated with disease states, any further characterization of etiologic mechanisms underlying disease remains elusive. This knowledge gap does not originate from a lack of DNAm–trait associations, but rather stems from study design issues that affect the interpretability of EWAS results. Despite known limitations in predicting the function of a particular CpG site, most EWAS maintain the broad assumption that altered DNAm results in a concomitant change of transcription at the most proximal gene. This study integrated DNAm and gene expression (GE) measurements in two cohorts, the Adolescent and Young Adult Twin Study (AYATS) and the Pregnancy, Race, Environment, Genes (PREG) study, to improve the understanding of epigenomic regulatory mechanisms. CpG sites associated with GE in cis were enriched in areas of transcription factor binding and areas of intermediate-to-low CpG density. CpG sites associated with trans GE were also enriched in areas of known regulatory significance, including enhancer regions. These results highlight issues with restricting DNAm-transcript annotations to small genomic intervals and question the validity of assuming a cis DNAm–GE pathway. Based on these findings, the interpretation of EWAS results is limited in studies without multi-omic support and further research should identify genomic regions in which GE-associated DNAm is overrepresented. An in-depth characterization of GE-associated CpG sites could improve predictions of the downstream functional impact of altered DNAm and inform best practices for interpreting DNAm–trait associations generated by EWAS.