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eQTM (expression quantitative trait methylation) Atlas: a comprehensive resource of over 11 million DNA methylation-gene expression associations through across 11 tissues and 4 diseases

Aditya SriramiD, Soyeon KimiD, Rebecca I. Caldino BohniD, Wei CheniD, Tianhao LiuiD, Molin YueiD, Niyati JainiD, Brandon L. PierceiD, Roby JoehanesiD, Daniel A LevyiD, Étienne PatiniD, Lluís Quintana‐MurciiD, Hyun Jung ParkiD, Juan Carlos CeledoniD

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Abstract

MotivationEpigenome-wide association studies (EWAS) have identified numerous DNA methylation (DNAm) CpG sites associated with complex traits and diseases, but interpretation of those CpG sites remains challenging because in EWAS, CpGs are mostly linked to nearby genes based only on genomic proximity. Expression quantitative trait methylation (eQTM) analyses connect DNAm CpGs with statistically associated gene expression levels. However, a comprehensive, searchable resource integrating eQTMs across diverse tissues and disease contexts has been lacking. ResultsWe developed the eQTM Atlas, a web-based resource that manually curates more than 11 million DNAm-gene expression associations from eight cohorts, covering 11 tissue types, four broad disease contexts, 173,886 unique CpG probes and 20,231 unique genes. The Atlas supports gene- or CpG-searches by tissue or disease type and finding associated CpG or genes, visualization of cis- and trans-eQTMs through genome browser, heatmap interfaces across various tissues, and cohort-level data downloads. By integrating eQTM results with EWAS resources, the eQTM Atlas enables users to connect disease- or trait-associated CpGs to statistically associated genes rather than relying solely on proximity-based gene annotation, supporting functional interpretation of EWAS findings and generation of disease-specific regulatory hypotheses. Availability and implementationThe eQTM Atlas is freely available at https://shiny.crc.pitt.edu/eqtm_browser/. The web interface is implemented in R Shiny and hosted through the University of Pittsburgh Center for Research Computing (CRC). Source code is available at https://github.com/ads303/eQTM-Atlas.

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Claude Opus 5.5 · xhigh effort · 8 Nov 2026 · from the full text of version 1 (10 Jun 2026) · CC BY 4.0

eQTM Atlas, an R Shiny resource, curates over 11 million DNA methylation-gene expression associations from eight cohorts and 11 tissues to annotate EWAS CpGs beyond proximity.

Epigenome-wide association study (EWAS) databases usually assign CpGs to genes by genomic proximity, which can miss distal expression-associated genes and leaves many array CpGs with no gene. The Atlas provides a searchable, tissue- and disease-aware catalog of cis and trans expression quantitative trait methylation (eQTM) links, which the authors present as the first such database.

Key results

  1. ShownThe curated catalog combines more than 11 million cis and trans eQTM associations across 11 tissue types and four broad disease contexts, standardized so they can be searched, visualized and downloaded.

    Eight cohorts, approximately 4,379 individuals, 173,886 unique CpG probes and 20,231 unique genes. Cis-eQTMs are defined as the gene lying near the CpG, typically within 1 Mb of the TSS; trans covers more distant genes on the same or another chromosome. GTEx contributes cis-eQTMs for eight tissues. · Abstract; Data summary of eQTM Atlas

  2. ShownThe authors' own eQTM analyses in EVA-PR nasal epithelium, from children with and without asthma, add a large trans-eQTM set unique to the Atlas. White blood cell eQTMs from largely overlapping participants allow comparison across tissues.

    EVA-PR trans-eQTMs exceed 9 million associations. Analyses were run in four subgroups: atopic asthma plus controls, atopic asthma only, controls only, and asthma and controls combined. Subgroup sample sizes are not given in the text. · Data summary of eQTM Atlas

  3. SuggestedProximity-based EWAS annotation leaves many array CpGs without any gene. The Atlas pairs EWAS Open Platform records with eQTM genes so that EWAS CpGs can be annotated by expression association, filtered by cohort and trait.

    16.8% of 850K array CpGs (151,037 of 897,322) fall outside gene or promoter boundaries. As of May 2026, the linked EWAS Open Platform holds 862,697 associations drawn from 1204 publications, spanning 898 phenotypes and 248 tissue or cell types. No direct comparison of eQTM and proximity annotation is reported. · Connecting to EWAS; Web design and interface

  4. SuggestedA worked query of cg20372759, the CpG most strongly associated with atopy in EVA-PR, returns a large gene set that appears specific to nasal epithelium, including the asthma-related gene CST1, along with linked airway-epithelium EWAS traits.

    2,112 associated eQTM genes in EVA-PR and 6 linked EWAS diseases/traits (five diseases, one phenotype), all reported in nasal or airway epithelial cells. In the heatmap the associations appear specific to nasal epithelium. This is a single illustrative query with no formal enrichment test. · CpG search example

  5. SuggestedGene-centric queries separate local from distal regulation and tissue-restricted from shared patterns. CST1 shows many trans CpGs, mainly in nasal epithelium, whereas PAX8 is associated with CpGs broadly across tissues.

    PAX8 is significantly associated with CpGs in all 11 tissues. CST1 trans-eQTM CpGs in EVA-PR nasal epithelium are shown as a Manhattan plot over the 22 autosomes (X and Y excluded). Counts of CpGs for CST1 or PAX8 are not reported. · Identifying eQTM DNAm CpGs through gene search

Methods, data and reproducibility

Genome-wide eQTM summary statistics (CpG, gene, coordinates, effect size, P value, FDR) were collected mostly from original study authors under inclusion rules (human, at least 100 samples, HumanMethylation450 or EPIC arrays). They were standardized and served through an R Shiny app with search, genome browser, heatmap, EWAS-linking, download and upload tabs.

  • Full curated eQTM collection: eight cohorts, 11 tissue types, four broad disease contexts · human · n = approximately 4,379 individuals
  • GTEx cis-eQTMs for eight tissues (whole blood, lung, colon, breast, muscle, ovary, prostate, testis) · human (GTEx Consortium)
  • EVA-PR nasal epithelium cis and trans eQTMs from Puerto Rican children with and without asthma, analyzed in four case/control subgroups · human
  • EVA-PR white blood cell eQTMs from largely overlapping participants, for comparison with nasal epithelium · human
  • Other published eQTM studies covering colon, monocytes, skeletal tissue, whole blood and children's blood · human
  • EWAS Open Platform (EWAS Atlas) CpG-trait associations, integrated for EWAS-to-eQTM gene lookup · n = 862,697 associations from 1204 publications
  • EPIC (850K) array CpG probe annotation, used to quantify CpGs outside gene or promoter regions · n = 897,322 CpGs
Methods & tools
R Shiny, locuszoomr, shinyjs, HumanMethylation450 BeadChip array, MethylationEPIC (EPIC) BeadChip array, Illumina NextSeq 500 and HiSeq 2000 sequencing, EWAS Open Platform / EWAS Atlas, University of Pittsburgh CRC HTC cluster (hosting)
Code
https://github.com/ads303/eQTM-Atlas
Data & accessions
https://shiny.crc.pitt.edu/eqtm_browser/https://ngdc.cncb.ac.cn/ewas/atlas/index
Software & environment
Web app built in R Shiny with the locuszoomr and shinyjs packages; no R or package version numbers and no container specification are stated.
Assay conditions & compute
Served from the HTC (high throughput computing) cluster at the University of Pittsburgh CRC; no hardware, memory or runtime figures are reported.
Reproducibility gaps
Most curated results were obtained directly from the original study authors. User uploads require an institutional MTA/DTA. Only open summary statistics are hosted now; access-controlled data is planned but not yet available.
Limitations (4)
  • Only openly shareable summary statistics are hosted at present. Access-controlled, individual-level results from contributing investigators are planned but not yet offered. · stated by the authors
  • eQTM links vary strongly with tissue and disease state, so the genes associated with a CpG in one cohort or tissue may not carry over to another context. · stated by the authors
  • The scope counts are internally inconsistent: eight cohorts or studies are reported, yet 18 eQTM studies are said to be retained after curation, and the EWAS resources are described as covering 1908 studies in one place and 1,906 in another. · noted in this summary
  • No benchmark shows that eQTM-based annotation improves enrichment or gene prioritization over proximity annotation. The associations are correlational, trans-eQTMs come largely from EVA-PR without reported replication, and cross-cohort thresholds and covariates are not described. · noted in this summary

Who should read:Read this if you need tissue- or disease-specific genes for EWAS CpGs, or want a searchable store of cis and trans methylation-expression associations, especially for asthma and nasal epithelium.

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