Lifestyle and Genetic Factors Modify Parent-of-Origin Effects on the Human Methylome

Abstract

Background: parent-of-origin effects (POE) play important roles in complex disease and thus understanding their regulation and associated molecular and phenotypic variation are warranted. Previous studies mainly focused on the detection of genomic regions or phenotypes regulated by POE. Understanding whether POE may be modified by environmental or genetic exposures is important for understanding of the source of POE-associated variation, but only a few case studies addressing modifiable POE exist.

Methods: in order to understand this high order of POE regulation, we screened 101 genetic and environmental factors such as 'predicted mRNA expression levels' of DNA methylation/imprinting machinery genes and environmental exposures. POE-mQTL-modifier interaction models were proposed to test the potential of these factors to modify POE at DNA methylation using data from Generation Scotland: The Scottish Family Health Study(N=2315).

Findings: a set of vulnerable/modifiable POE-CpGs were identified (modifiable-POE-regulated CpGs, N=3). Four factors, 'lifetime smoking status' and 'predicted mRNA expression levels' of TET2, SIRT1 and KDM1A, were found to significantly modify the POE on the three CpGs in both discovery and replication datasets. We further identified plasma protein and health-related phenotypes associated with the methylation level of one of the identified CpGs.

Interpretation: the modifiable POE identified here revealed an important yet indirect path through which genetic background and environmental exposures introduce their effect on DNA methylation, motivating future comprehensive evaluation of the role of these modifiers in complex diseases.

Funding: NSFC (81971270),H2020-MSCA-ITN(721815), Wellcome (204979/Z/16/Z,104036/Z/14/Z), MRC (MC_UU_00007/10, MC_PC_U127592696), CSO (CZD/16/6,CZB/4/276, CZB/4/710), SFC (HR03006), EUROSPAN (LSHG-CT-2006-018947), BBSRC (BBS/E/D/30002276), SYSU, Arthritis Research UK, NHLBI, NIH.

Keywords: DNA methylation; DNA methylation machinery genes; interaction (modification) effect; mQTL; parent-of-origin effect; smoking.

Figure 1

Patterns of classical and modifiable parent-of-origin effect (POE) regulation on DNA methylation. X axis: mQTL genotypes, left purple: paternal allele, right pink: maternal allele. Y axis: methylation level of the regulated CpG. Upper panel: classical POE patterns including parental and complex (dominance) POE patterns. Parental patterns show two levels of methylation depending on the expressed allele and the allelic effect. Complex POE manifests as the two homozygous groups having the same methylation level whereas the heterozygous groups are different. Dashed box: difference between methylation level of heterozygous groups of the mQTL is the hallmark of POE. Bottom: scenarios when the POE is modified by genetic or environmental factors, leading to the alteration of POE for different levels of the modifier.

Figure 2

Design of the study. Cov: covariates fitted in the model. Zeng et al.(2019): the study which reported CpGs regulated by POE and the mQTLs that induce the POE for 586 CpGs (reference 4).

Figure 3

CpGs regulated by the modifiable-POE. a. Proportion of methylation variation explained by different models for the three CpGs regulated by modifiable-POE. The ‘Base model’ accounted for age, sex, cell proportion, smoking variables (‘pack years’ and ‘lifetime smoking status’. These were not included as covariates when they were the tested modifier factor) and principal components of the OMIC (DNA methylation)-relationship-matrix. Mod: modifier; Add: additive genetic effect, Dom: dominance genetic effect. Add x Mod: interaction between additive genetic effect and the modifier; POE x Mod: interaction between parent-of-origin genetic effect and the modifier. b. Distributions of methylation levels of CpGs regulated by modifiable POE (N_CpG=3), CpGs regulated by POE from known mQTLs but the POE is not modifiable (N_CpG=583), CpGs regulated by POE but without an mQTL identified (the CpGs were reported in ref 4: Zeng et al. (2019), N_CpG=398) and randomly selected non-POE CpGs from all QCed array probes (N_CpG=10,000). Unrelated individuals from the GS:SFHS discovery subset were used to produce the plot.

Figure 4

Regional plot of the modifiable-POE affecting cg18035618 and nearby CpGs within a 20kb distance. Top two panels: upper - interaction effect between the POE of cg18035618’s mQTL rs117823351 and ‘predicted mRNA expression levels of SIRT1’, bottom - interaction effect between the POE of cg18035618’s mQTL rs117020124 and ‘lifetime smoking status’; –log10 (P-value): minus log10 P-value (t test) of the POE_mQTL x Modifier interaction effect; Dots show nearby measured CpGs located within a 20kb distance from cg18035618, filling colour represents the correlation of methylation levels with cg18035618: red: positive correlation; blue:negative correlation; white: no significant correlation. Middle panel: genes located within the 40kb genomic region. Bottom panel: correlation matrix between CpGs.

Figure 5

Both environmental and genetic factors significantly modified the POE of mQTLs on cg18036618. a). top:cg18036618 was regulated by the POE of the mQTL rs117020124. bottom: the POE of rs117020124 was modified by lifetime smoking status. The contrast in methylation levels of cg18035618 between heterozygotes of the mQTL rs117020124 is largest in current smoker group. b). top:cg18036618 was regulated by the POE of the mQTL rs117823351. bottom: the POE of rs117823351 was modified by ‘predicted mRNA expression level of SIRT1’. The contrast in methylation levels of cg18035618 between heterozygotes of the mQTL rs117823351 is larger in individuals with low SIRT1 expression. High/low expression: participants with predicted expression levels larger than the median were categorized as the high group.

Figure 6

The three modifiable-POE-targeted CpGs were also significantly regulated by POE_mQTL x SNP interaction effects between the mQTLs and the SNPs used to drive the genetic modifiers. The contrast in methylation levels of the candidate CpGs in mQTL heterozygotes varied depending on the allelic dosage of the SNP used to derive the corresponding genetic modifier. *due to the limitation of sample size, minor homozygous/heterozygous genotype groups were missing in some tests.

Figure 7

Forest plot for phenotypes associated with cg21252175. HDL: high-density lipoprotein. Meta: Meta-analysis performed using the random effect model.