# Genetic regulation of methylation across East Asian and European populations

**Authors:** Ruize Liu, Tzu-Ting Chen, Yan Xia, Shu-Chin Lin, Tian Ge, Chia-Yen Chen, Yen-Chen Anne Feng, Hailiang Huang, Yen-Feng Lin

PMC · DOI: 10.1038/s41467-026-69372-6 · 2026-02-11

## TL;DR

This study identifies thousands of new genetic links to DNA methylation in East Asian populations, showing how these links are important for understanding diseases.

## Contribution

The study provides a new resource of East Asian-specific methylation quantitative trait loci (mQTLs) and their role in disease heritability.

## Key findings

- Identified 28,978 novel mCpGs specific to East Asian populations.
- Found that mQTLs are enriched for disease and trait heritability, especially in ancestry-matched analyses.
- Discovered that East Asian-specific mQTLs are often driven by low-frequency genetic variants.

## Abstract

Methylation quantitative trait loci (mQTL) studies have predominantly focused on European populations (EUR), limiting understanding of the genetic regulation of DNA methylation in other populations. We conduct an East Asian (EAS) mQTL analysis, integrating data from three independent samples comprising 7619 Han Chinese individuals. We identified 331,048 mCpGs, including 28,978 novel mCpGs in EAS. While observing substantial sharing of mQTL between EUR and EAS, we also identify EAS-specific mQTLs, often driven by variants with low minor allele frequencies in EUR. We found that mQTLs enriched for disease and trait heritability, especially for matched-ancestry mQTLs, underscoring their utility for interpreting GWAS results and highlighting the role of DNA methylation in diseases. Our EAS mQTL resource provides valuable insights into the genetic architecture of DNA methylation and its contribution to complex traits.

Here the authors identify via an East Asian mQTL study (n = 7,619) nearly 29,000 novel mCpG. It shows that mQTLs are strongly enriched for disease heritability, especially when ancestry is matched, underscoring their utility in interpreting GWAS results.

## Full-text entities

- **Genes:** TCF21 (transcription factor 21) [NCBI Gene 6943] {aka POD1, bHLHa23}, CISH (cytokine inducible SH2 containing protein) [NCBI Gene 1154] {aka BACTS2, CIS, CIS-1, G18, SOCS}, CTCF (CCCTC-binding factor) [NCBI Gene 10664] {aka CFAP108, FAP108, MRD21}, APOB (apolipoprotein B) [NCBI Gene 338] {aka FCHL2, FLDB, LDLCQ4, apoB-100, apoB-48}, SH2D1A (SH2 domain containing 1A) [NCBI Gene 4068] {aka DSHP, EBVS, IMD5, LYP, MTCP1, SAP}, CAMK1D (calcium/calmodulin dependent protein kinase ID) [NCBI Gene 57118] {aka CKLiK, CaM-K1, CaMKID}
- **Diseases:** Angina (MESH:D000787), MI (MESH:D009203), cancer (MESH:D009369), CD (MESH:D003424), diabetic kidney disease (MESH:D003928), UC (MESH:D003093), clot (MESH:D013927), EAS (MESH:D000073605), ischemic heart disease (MESH:D017202), UAP (MESH:D000789), neurodevelopmental disorders (MESH:D002658), SCZ (MESH:D012559), IBD (MESH:D015212), cataract (MESH:D002386), T2D (MESH:D003924), cardiac diseases (MESH:D006331), stable angina pectoris (MESH:D060050), T1D (MESH:D003922), cardiovascular disease (MESH:D002318), coronary artery diseases (MESH:D003324), LDSC (MESH:C537770), atherosclerosis (MESH:D050197), diabetes (MESH:D003920)
- **Chemicals:** salicylic acid (MESH:D020156), glucose (MESH:D005947), cholesterol (MESH:D002784), N02BA (-), lipid (MESH:D008055), fats (MESH:D005223), TG (MESH:D014280)
- **Species:** Mus musculus (house mouse, species) [taxon 10090], Homo sapiens (human, species) [taxon 9606]
- **Mutations:** C01D, rs4747971, rs2327429, rs11257657, rs11257655

## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC13002944/full.md

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Source: https://tomesphere.com/paper/PMC13002944