Causal benefits of 25 dietary intakes on epigenetic ageing: a Mendelian randomisation study

Abstract

DNA methylation GrimAge acceleration (DMGA) and intrinsic epigenetic age acceleration (IEAA) are important physiological markers for assessing the ageing process. Evidence from cross-sectional studies suggests that some dietary intake is associated with DMGA and IEAA. However, the causal relationship between them has yet to be elucidated. This Mendelian randomisation study uses genetic variants associated with different dietary intakes as instrumental variables to explore the causal benefits of multiple dietary intakes on DMGA and IEAA. Cheese intake, dark chocolate intake, average weekly red wine intake, dried fruit intake, fresh fruit intake, porridge intake, cereal intake, and liver intake had a negative causal association with DMGA, and poultry intake and doughnut intake had a positive causal association with DMGA (p < 0.05). Muesli and bran cereal intake had a negative causal association with IEAA, and pineapple intake had a positive causal association with IEAA (p < 0.05). Dietary intake positively causally associated with IEAA or DMGA may have accelerated biological ageing; conversely, dietary intake negatively causally associated with IEAA or DMGA may have contributed to delaying biological ageing. Based on genetic evidence, this study demonstrated some significant causal benefits of dietary intake on DMGA and IEAA, suggesting the possibility of intervening in DNA methylation acceleration and epigenetic age acceleration by adjusting these food intakes, thereby promoting health and delaying ageing. However, the findings of this study are exploratory and preliminary and need to be supported and validated by evidence from further clinical studies and mechanistic studies.

Keywords:

• Dietary
• DNA methylation GrimAge acceleration
• intrinsic epigenetic age acceleration
• causal benefit

Acknowledgments

We sincerely thank the original researchers of all the GWAS databases used in this study. With all these open-source data, we were able to implement this MR study.

Ethical approval and consent to participate

Not applicable.

Consent for publication

All authors unanimously approved the publication of this manuscript.

Authors’ contributions

Conceptualization, Kaixi Ding.; Wei Jiang.; And Shangjing Wuke.; methodology, Wei Jiang. And Kaixi Ding.; software, Wei Jiang.; Shangjing Wuke.; And Kaixi Ding.; validation, Wei Jiang. And Kaixi Ding.; writing—original draft preparation, Kaixi Ding.; Wei Jiang. And Shangjing Wuke.; writing—review and editing, Wei Jiang. And Kaixi Ding.; visualisation, Wei Jiang.; supervision, Ming Lei.; project administration, Ming Lei.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

All GWAS datasets covered in the article are available online (https://gwas.mrcieu.ac.uk/). For appropriate reasons, readers may request access to the remaining causal effect estimates from the corresponding author. The TwoSampleMR R package used in this study is available online on the web at https://mrcieu.github.io/TwoSampleMR/.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.