Chinese scientists have performed a study on homozygous twins to determine how lifestyle factors – smoking, drinking, physical activity, and diet – affect biological age according to two biological age clocks. Their findings were a mixed bag, but they found evidence for eating lots of fruits and vegetables [1].
DNA methylation clocks
With age, our DNA gets “populated” with methylation marks – that is, methyl groups are added to nucleotides. These methylation marks control epigenetics: the way genes are expressed. DNA methylation clocks use this effect to measure biological age, a physical metric of an organism’s proximity to death, as opposed to chronological age. Other biological age clocks exist, such as ones that are based on blood markers or physical activity.
Although numerous correlations have been found between methylation clocks’ readings and various causes of mortality, the question of just how precise they are remains open. Reliable biological age clocks are desperately needed in longevity research, because if we want to develop anti-aging interventions, we must be able to rapidly measure their impact.
Results could be clearer
Several attempts have been made to link environmental and other external factors to DNA methylation (DNAm) age, with mixed results. For instance, while most studies show that heavy drinking accelerates DNAm aging, one study found no such connection [2]. A systematic review of 61 original studies showed no significant effect of smoking on DNAm age [3], while an American cohort study found that smoking significantly accelerates DNAm aging [4].
This does not mean that methylation clocks are useless. Rather, they are still in their infancy, and we are just beginning to uncover their strengths and limitations, with every new research paper adding to our understanding of their potential.
This new study is especially intriguing because it was done on homozygous twins – meaning the DNA they received from their parents is 100% identical. Working with homozygous twins enables scientists to disregard genetic differences, which play a major role in longevity. In this study, the researchers studied 173 pairs of identical twins of both sexes and various age groups.
Two clocks, four factors
The researchers chose four lifestyle parameters – smokers vs. non-smokers or former smokers; normal vs. heavy drinking; high vs. low physical activity levels, and, finally, consumption of fruits and vegetables (normal or higher vs. insufficient). A binary score was assigned to each parameter (smoker as 0, non-smoker as 1, etc.), and a combined score was calculated for every subject, with 4 being the maximum.
The researchers used two DNA methylation clocks in their study. One, developed by Steve Horvath back in 2013 [5], was the first multi-tissue epigenetic age clock that started it all. This groundbreaking invention is already beginning to show its age and has been surpassed in certain aspects and settings by newer clocks. The second clock, developed by Li et al. in 2018 [6], was originally tested mostly on Chinese subjects, although it demonstrated accuracy in Caucasian subjects as well. The researchers note that Li’s clock is especially well-suited for the Chinese population, from which they drew their subjects.
Quit smoking anyway
The study group’s ethnic composition might be the reason why Li’s clock showed clearer results. While Horvath’s clock failed to show clear correlation with any single factor, Li’s clock demonstrated inverse correlation between DNAm age and three factors: vegetable and fruit intake, physical activity, and the combined score. Horvath’s clock readings were just a tad lower for the healthiest group (an overall score of 4 points) but without reaching the level of statistical significance.
Higher intake of vegetables and fruits had the most significant correlation with DNAm age, while physical activity came close in the second place. The results were generally similar both across the whole group and for pairs of twins, which shows that lifestyle factors might shine through genetics when it comes to aging.
Interestingly, smoking and drinking were not significantly associated with DNAm age in this study. Since we have a trove of data irrefutably proving the detrimental effects of smoking and drinking on our health, this seeming paradox will have to be addressed. Possible explanations are many: for instance, the notoriously low air quality in large Chinese cities might have obscured the effects of smoking. Bundling non-smokers and former smokers into one group might have also muddied the waters. Anyway, if you want to live longer, these results should not be taken as a license to smoke and drink at will.
Conclusion
Among this study’s limitations are its relatively small size and the fact that the lifestyle factors were only assigned a binary score. Yet, twin studies are always exciting because they enable us to see beyond genetic differences. The results of the study pose new questions about the general applicability of DNA methylation age clocks, and which clocks are better than others, but they also confirm the widespread notion that healthy diet and exercise are among the most effective anti-aging interventions available today.
Literature
[1] Peng, H., Gao, W., Cao, W., Lv, J., Yu, C., Wu, T., … & Li, L. (2021). Combined healthy lifestyle score and risk of epigenetic aging: a discordant monozygotic twin study. Aging, 13.
[2] Horvath, S., Gurven, M., Levine, M. E., Trumble, B. C., Kaplan, H., Allayee, H., … & Assimes, T. L. (2016). An epigenetic clock analysis of race/ethnicity, sex, and coronary heart disease. Genome biology, 17(1), 1-23.
[3] Ryan, J., Wrigglesworth, J., Loong, J., Fransquet, P. D., & Woods, R. L. (2020). A systematic review and meta-analysis of environmental, lifestyle, and health factors associated with DNA methylation age. The Journals of Gerontology: Series A, 75(3), 481-494.
[4] Beach, S. R., Dogan, M. V., Lei, M. K., Cutrona, C. E., Gerrard, M., Gibbons, F. X., … & Philibert, R. A. (2015). Methylomic aging as a window onto the influence of lifestyle: tobacco and alcohol use alter the rate of biological aging. Journal of the American geriatrics society, 63(12), 2519-2525.
[5] Horvath, S. (2013). DNA methylation age of human tissues and cell types. Genome biology, 14(10), 1-20.
[6] Li, J., Zhu, X., Yu, K., Jiang, H., Zhang, Y., Wang, B., … & Wu, T. (2018). Exposure to polycyclic aromatic hydrocarbons and accelerated DNA methylation aging. Environmental health perspectives, 126(6), 067005.
