Does genetic predisposition modify the effect of lifestyle-related factors on DNA methylation?

Chenglong Yu; Allison M Hodge; Ee Ming Wong; Jihoon E Joo; Enes Makalic; Daniel F Schmidt; Daniel D Buchanan; Gianluca Severi; John L Hopper; Dallas R English; Graham G Giles; Roger L Milne; Melissa C Southey; Pierre-Antoine Dugué

doi:10.1080/15592294.2022.2088038

Does genetic predisposition modify the effect of lifestyle-related factors on DNA methylation?

Epigenetics. 2022 Dec;17(12):1838-1847. doi: 10.1080/15592294.2022.2088038. Epub 2022 Jun 20.

Authors

Chenglong Yu¹, Allison M Hodge^{2

3}, Ee Ming Wong^{1

4}, Jihoon E Joo^{5

6}, Enes Makalic³, Daniel F Schmidt³, Daniel D Buchanan^{5

6

7}, Gianluca Severi^{8

9}, John L Hopper³, Dallas R English^{2

3}, Graham G Giles^{1

2

3}, Roger L Milne^{1

2

3}, Melissa C Southey^{1

2

4}, Pierre-Antoine Dugué^{1

2

3}

Affiliations

¹ Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
² Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.
³ Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.
⁴ Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, Victoria, Australia.
⁵ Colorectal Oncogenomics Group, Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, Victoria, Australia.
⁶ University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Victoria, Australia.
⁷ Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, Victoria, Australia.
⁸ Centre de Recherche en Epidémiologie et Santé des Populations (CESP, Inserm U1018), Facultés de Médecine Universités Paris-Saclay, Uvsq, Villejuif, France.
⁹ Department of Statistics, Computer Science and Applications "G. Parenti", University of Florence, Firenze, Italy.

Abstract

Lifestyle-related phenotypes have been shown to be heritable and associated with DNA methylation. We aimed to investigate whether genetic predisposition to tobacco smoking, alcohol consumption, and higher body mass index (BMI) moderates the effect of these phenotypes on blood DNA methylation. We calculated polygenic scores (PGS) to quantify genetic predisposition to these phenotypes using training (N = 7,431) and validation (N = 4,307) samples. Using paired genetic-methylation data (N = 4,307), gene-environment interactions (i.e., PGS × lifestyle) were assessed using linear mixed-effects models with outcomes: 1) methylation at sites found to be strongly associated with smoking (1,061 CpGs), alcohol consumption (459 CpGs), and BMI (85 CpGs) and 2) two epigenetic ageing measures, PhenoAge and GrimAge. In the validation sample, PGS explained ~1.4% (P = 1 × 10^-14), ~0.6% (P = 2 × 10^-7), and ~8.7% (P = 7 × 10^-87) of variance in smoking initiation, alcohol consumption, and BMI, respectively. Nominally significant interaction effects (P < 0.05) were found at 61, 14, and 7 CpGs for smoking, alcohol consumption, and BMI, respectively. There was strong evidence that all lifestyle-related phenotypes were positively associated with PhenoAge and GrimAge, except for alcohol consumption with PhenoAge. There was weak evidence that the association of smoking with GrimAge was attenuated in participants genetically predisposed to smoking (interaction term: -0.022, standard error [SE] = 0.012, P = 0.058) and that the association of alcohol consumption with PhenoAge was attenuated in those genetically predisposed to drink alcohol (interaction term: -0.030, SE = 0.015, P = 0.041). In conclusion, genetic susceptibility to unhealthy lifestyles did not strongly modify the association between observed lifestyle behaviour and blood DNA methylation. Potential associations were observed for epigenetic ageing measures, which should be replicated in additional studies.

Keywords: CpG site; DNA methylation; epigenetic ageing; gene–environment interaction; lifestyle; polygenic score.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Alcohol Drinking / genetics
Body Mass Index
DNA Methylation*
Epigenesis, Genetic
Genetic Predisposition to Disease*
Humans
Smoking / adverse effects
Smoking / genetics

Grants and funding

MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian NHMRC grants 209057, 251553, and 504711 and by infrastructure provided by Cancer Council Victoria. The nested case–control methylation studies were supported by the NHMRC grants 1011618, 1026892, 1027505, 1050198, 1043616, and 1074383. This work was further supported by NHMRC grant 1164455. M.C.S. is a recipient of a Senior Research Fellowship from the NHMRC (GTN1155163).