Deep molecular phenotypes link complex disorders and physiological insult to CpG methylation Academic Article uri icon

Overview

abstract

  • Epigenetic regulation of cellular function provides a mechanism for rapid organismal adaptation to changes in health, lifestyle, and environment. Associations of cytosine-guanine di-nucleotide (CpG) methylation with clinical endpoints that overlap with metabolic phenotypes suggest a regulatory role for these CpG sites in the body's response to disease or environmental stress. We previously identified 20 CpG sites in an epigenome-wide association study (EWAS) with metabolomics that were also associated in recent EWASs with diabetes-, obesity-, and smoking-related endpoints. To elucidate the molecular pathways that connect these potentially regulatory CpG sites to the associated disease or lifestyle factors, we conducted a multi-omics association study including 2,474 mass-spectrometry based metabolites in plasma, urine, and saliva, 225 NMR based lipid and metabolite measures in blood, 1,124 blood-circulating proteins using aptamer technology, 113 plasma protein N-glycans and 60 IgG-glyans, using 359 samples from the multi-ethnic Qatar Metabolomics Study on Diabetes (QMDiab). We report 138 multi-omics associations at these CpG sites, including diabetes biomarkers at the diabetes-associated TXNIP locus, and smoking-specific metabolites and proteins at multiple smoking-associated loci, including AHRR. Mendelian randomization suggests a causal effect of metabolite levels on methylation of obesity associated CpG sites, i.e. of glycerophospholipid PC(O-36:5), glycine, and a very low density lipoprotein (VLDL-A) on the methylation of the obesity-associated CpG loci DHCR24, MYO5C, and CPT1A, respectively. Taken together, our study suggests that multi-omics-associated CpG methylation can provide functional read-outs for the underlying regulatory response mechanisms to disease or environmental insults.

publication date

  • 2018

Research

keywords

  • Mendelian randomization
    glycomics
    lipidomics
    metabolomics
    methylation
    multi-omics
    proteomics

Identity

Digital Object Identifier (DOI)

  • 10.1093/hmg/ddy006