Epigenome-wide association study of Chinese monozygotic twins identifies DNA methylation loci associated with estimated glomerular filtration rate

Background DNA methylation (DNAm) has been shown in multiple studies to be associated with the estimated glomerular filtration rate (eGFR). However, studies focusing on Chinese populations are lacking. We conducted an epigenome-wide association study to investigate the association between DNAm and eGFR in Chinese monozygotic twins. Methods Genome-wide DNAm level was detected using Reduced Representation Bisulfite Sequencing test. Generalized estimation equation (GEE) was used to examine the association between Cytosine-phosphate-Guanines (CpGs) DNAm and eGFR. Inference about Causation from Examination of FAmiliaL CONfounding was employed to infer the causal relationship. The comb-p was used to identify differentially methylated regions (DMRs). GeneMANIA was used to analyze the gene interaction network. The Genomic Regions Enrichment of Annotations Tool enriched biological functions and pathways. Gene expression profiling sequencing was employed to measure mRNA expression levels, and the GEE model was used to investigate the association between gene expression and eGFR. The candidate gene was validated in a community population by calculating the methylation risk score (MRS). Results A total of 80 CpGs and 28 DMRs, located at genes such as OLIG2, SYNGR3, LONP1, CDCP1, and SHANK1, achieved genome-wide significance level (FDR < 0.05). The causal effect of DNAm on eGFR was supported by 12 CpGs located at genes such as SYNGR3 and C9orf3. In contrast, the causal effect of eGFR on DNAm is proved by 13 CpGs located at genes such as EPHB3 and MLLT1. Enrichment analysis revealed several important biological functions and pathways related to eGFR, including alpha-2A adrenergic receptor binding pathway and corticotropin-releasing hormone receptor activity pathway. GeneMANIA results showed that SYNGR3 was co-expressed with MLLT1 and had genetic interactions with AFF4 and EDIL3. Gene expression analysis found that SYNGR3 expression was negatively associated with eGFR. Validation analysis showed that the MRS of SYNGR3 was positively associated with low eGFR levels. Conclusions We identified a set of CpGs, DMRs, and pathways potentially associated with eGFR, particularly in the SYNGR3 gene. These findings provided new insights into the epigenetic modifications related to the decline in eGFR and chronic kidney disease.