Epigenome-Wide Association Study in Asian Cohort Identifies Novel DNA Methylation Markers for Carotid Intima-Media Thickness.
Carotid-intima media-thickness predicts cardiovascular events and informs mechanistic research on cardiovascular diseases (CVD). However, CVD research remains Eurocentric despite etiological differences across ancestries. Incorporating Asian populations- who face substantial CVD burden with distinct etiological landscape- can enhance our understanding of cIMT biology and subclinical processes linked to CVD. This study aimed to elucidate methylation-based mechanisms of cIMT through DNA methylation profiling integrated with multi-omics data and clinically informative cIMT thresholds, leveraging an Asian cohort to enhance discovery.
We conducted an epigenome-wide association study (EWAS) of cIMT using peripheral blood DNA methylation at ∼850,000 CpG sites in the Asian Health for Life in Singapore (HELIOS) cohort (n=1,357), followed by targeted trans-ancestry meta-analysis with European cohorts (overall n=2,765). Causal inference analyses (summary data-based Mendelian Randomisation [SMR] and colocalisation) evaluated methylation-mediated effects on cIMT, CVD and proximal gene expression. We derived a methylation risk score (MRS) and tested its association with cIMT thresholds indicative of elevated cardiovascular risk (≥75 th percentile for age, sex and ethnicity).
Three novel CpG-cIMT associations were identified (P<9.35E-07). Causal analyses supported cg08227773 methylation-mediated effects on both coronary artery disease risk (P SMR =2.91E-05, coloc PP.H4 =0.91) and NBEAL2 (Neurobeachin-like 2) expression (P SMR =9.13E-08, coloc PP.H4=0.69), a gene implicated in immune dysregulation. MRS of cIMT aggregating the three sentinel CpGs was associated with clinically-informative cIMT elevation (Odds Ratio=2.75 for Q4 vs Q1, 95% CI: 1.47-5.13).
Through Asian-led discovery, this study identifies three novel DNA methylation markers for cIMT that are linked to cIMT elevation above clinically meaningful risk thresholds. Causal inference analyses suggest methylation-mediated CAD risk via NBEAL2 regulation, nominating biologically relevant targets while underscoring the need for larger multi-omics resources to refine mechanisms.
We conducted an epigenome-wide association study (EWAS) of cIMT using peripheral blood DNA methylation at ∼850,000 CpG sites in the Asian Health for Life in Singapore (HELIOS) cohort (n=1,357), followed by targeted trans-ancestry meta-analysis with European cohorts (overall n=2,765). Causal inference analyses (summary data-based Mendelian Randomisation [SMR] and colocalisation) evaluated methylation-mediated effects on cIMT, CVD and proximal gene expression. We derived a methylation risk score (MRS) and tested its association with cIMT thresholds indicative of elevated cardiovascular risk (≥75 th percentile for age, sex and ethnicity).
Three novel CpG-cIMT associations were identified (P<9.35E-07). Causal analyses supported cg08227773 methylation-mediated effects on both coronary artery disease risk (P SMR =2.91E-05, coloc PP.H4 =0.91) and NBEAL2 (Neurobeachin-like 2) expression (P SMR =9.13E-08, coloc PP.H4=0.69), a gene implicated in immune dysregulation. MRS of cIMT aggregating the three sentinel CpGs was associated with clinically-informative cIMT elevation (Odds Ratio=2.75 for Q4 vs Q1, 95% CI: 1.47-5.13).
Through Asian-led discovery, this study identifies three novel DNA methylation markers for cIMT that are linked to cIMT elevation above clinically meaningful risk thresholds. Causal inference analyses suggest methylation-mediated CAD risk via NBEAL2 regulation, nominating biologically relevant targets while underscoring the need for larger multi-omics resources to refine mechanisms.
Authors
Tan Tan, Harris Harris, Maddock Maddock, Tay Tay, Jain Jain, , Mok Mok, Herbrard Herbrard, Schminke Schminke, Xue Xue, Goh Goh, Mina Mina, Teumer Teumer, Lim Lim, Leong Leong, Yeo Yeo, Cheng Cheng, Sim Sim, Sing Sing, Wardlaw Wardlaw, Völzke Völzke, Wong Wong, Cox Cox, Dalan Dalan, Dehghan Dehghan, Loh Loh
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