Mining Epidemiological Data for Correlations with Longevity
The exposome is the set of environmental exposures that can affect health, aging, and longevity. As presently considered by epidemiologists, the exposome can include lifestyle choices, as well as the burden of infections, particulate air pollution, and so forth. Confusingly, the concept has also been expanded to include internal factors such as hormone levels, oxidative stress, inflammation, and presence of age-related disease. Here, researchers demonstrate the sort of investigation of the exposome that can be accomplished with a large epidemiological database such as the UK Biobank. Most of the correlations reported are much as one would expect, but a couple of them are surprising.
Environmental factors are associated with human longevity, but their specificity and causality remain mostly unclear. By integrating the innovative "exposome" concept developed in the field of environmental epidemiology, this study aims to determine the components of exposome causally linked to longevity using Mendelian randomization (MR) approach.
A total of 4,587 environmental exposures extracting from 361,194 individuals from the UK biobank, in exogenous and endogenous domains of exposome were assessed. We examined the relationship between each environmental factor and two longevity outcomes (i.e., surviving to the 90th or 99th percentile age) from various cohorts of European ancestry. Significant results after false discovery rates correction underwent validation using an independent exposure dataset.
Out of all the environmental exposures, eight age-related diseases and pathological conditions were causally associated with lower odds of longevity, including coronary atherosclerosis (odds ratio = 0.77), ischemic heart disease (0.66), angina (0.73), Alzheimer's disease (0.80), hypertension (0.70), type 2 diabetes (0.88), high cholesterol (0.81), and venous thromboembolism (0.92). After adjusting for genetic correlation between different types of blood lipids, higher levels of low-density lipoprotein cholesterol (0.72) was associated with lower odds of longevity, while high-density lipoprotein cholesterol (1.36) showed the opposite.
Genetically predicted sitting/standing height was unrelated to longevity, while higher comparative height size at age 10 was negatively associated with longevity. Greater body fat, especially the trunk fat mass, and never eat sugar or foods/drinks containing sugar were adversely associated with longevity, while education attainment showed the opposite.
In conclusion, the present study supports that some age-related diseases as well as education are causally related to longevity and highlights several new targets for achieving longevity, including management of venous thromboembolism, appropriate intake of sugar, and control of body fat. Our results warrant further studies to elucidate the underlying mechanisms of these reported causal associations.
What the heck? Avoiding sugar is bad? Seems counterintuitive. Also, the study found smoking behavior non-predictive for longevity. That raises questions about the validity of the study, IMO.