EWAS Atlas: a curated knowledgebase of epigenome-wide association studies

Abstract

Epigenome-Wide Association Study (EWAS) has become increasingly significant in identifying the associations between epigenetic variations and different biological traits. In this study, we develop EWAS Atlas (http://bigd.big.ac.cn/ewas), a curated knowledgebase of EWAS that provides a comprehensive collection of EWAS knowledge. Unlike extant data-oriented epigenetic resources, EWAS Atlas features manual curation of EWAS knowledge from extensive publications. In the current implementation, EWAS Atlas focuses on DNA methylation—one of the key epigenetic marks; it integrates a large number of 329 172 high-quality EWAS associations, involving 112 tissues/cell lines and covering 305 traits, 1830 cohorts and 390 ontology entities, which are completely based on manual curation from 649 studies reported in 401 publications. In addition, it is equipped with a powerful trait enrichment analysis tool, which is capable of profiling trait-trait and trait-epigenome relationships. Future developments include regular curation of recent EWAS publications, incorporation of more epigenetic marks and possible integration of EWAS with GWAS. Collectively, EWAS Atlas is dedicated to the curation, integration and standardization of EWAS knowledge and has the great potential to help researchers dissect molecular mechanisms of epigenetic modifications associated with biological traits.

Quantitative Epigenetics: A New Avenue for Crop Improvement

“…EWAS is based on linkage disequilibrium (LD) mapping, which utilizes natural population and historic recombination events and thus can accomplish high-resolution mapping. A number of EWAS studies have been conducted in humans, which identified that epigenetic modifications are associated with several human diseases like Parkinson's disease [84], coronary artery disease [85], Alzheimer's disease [86] and Type 2 diabetes [87], Moreover, to gather the extensive knowledge generated through EWAS in human, EWAS Atlas has also been developed [88]. However, there is a limited number of EWAS performed in plants, and so far, a single EWAS study identified epigenetic modification associated with a mantled abnormality in oil palm [44].…”

Mining the Selective Remodeling of DNA Methylation in Promoter Regions to Identify Robust Gene-Level Associations with Phenotype

“…EWAS opens the door for researchers to study complex diseases, allowing us to find several previously undiscovered disease-related methylation sites, providing more epigenetic mechanisms for the pathogenesis of complex diseases [12,13]. Since 2009 when the first EWAS study was published, EWAS research has grown exponentially in recent years, reaching 618 publications in 2019 [12]. Due to the availability of whole blood DNA methylation data, most of the materials for most current EWAS studies are focused on whole blood tissues [12].…”

“…Similar to GWAS (Genome-wide association study), EWAS compares the variation between patients and healthy people at the DNA methylation level and associates epigenetic variation with complex diseases as well as interprets the pathogenic cause of complex diseases at the epigenetic level [11]. EWAS opens the door for researchers to study complex diseases, allowing us to find several previously undiscovered disease-related methylation sites, providing more epigenetic mechanisms for the pathogenesis of complex diseases [12,13]. Since 2009 when the first EWAS study was published, EWAS research has grown exponentially in recent years, reaching 618 publications in 2019 [12].…”

“…Since 2009 when the first EWAS study was published, EWAS research has grown exponentially in recent years, reaching 618 publications in 2019 [12]. Due to the availability of whole blood DNA methylation data, most of the materials for most current EWAS studies are focused on whole blood tissues [12].…”

Edge sparse PCA based on gene network for correcting cell type heterogeneity in epigenome-wide association studies

“…The EWAS model selects CpG sites that are easily affected by environmental factors through screening a large number of CpG sites. Standard EWAS generally uses whole blood data, which means the value of methylation data contains information on heterogeneous cell composition [4,5]. Existing research has shown that epigenome information is greatly affected by cell changes.…”