Exposome-wide analysis of human aging mechanisms, age-related diseases, and mortality in a UK population
Keywords: exposome
mortality
environment
exposure
chronic disease
ageing
epidemiology
polygenic risk
aging
exposomics
UK Biobank
cardiometabolic
genomics
genetics

Background: Although it has been recognized that environmental exposures may be the major determinants of human aging and mortality, progress in understanding the impact of the exposome (i.e., the totality of all the non-genetic, external exposures that contribute to health and disease for an individual across the lifecourse) on mortality and age-related morbidity is lacking. In this thesis, I aimed to quantify the effect of the exposome on mortality, aging biomarkers, and chronic diseases.
Methods: I conducted a multi-step, exposome-wide analysis in the UK Biobank (n = 492,569). An exposome-wide association study (XWAS) of all-cause mortality was conducted using independent discovery and replication sets including participants recruited in England (median 12.5 follow-up years), with multiple further analyses conducted to evaluated replicated exposures for reverse causation due to prevalent disease and confounding due to exposome correlation. Remaining exposures were tested in relationship to 25 blood biomarkers related to aging mechanisms, 3 cardiometabolic risk factors (obesity, hypertension, dyslipidemia), and incidence of 25 age-related diseases. Finally, I fitted multivariable Cox models for mortality and each of the 25 disease outcomes, which included age and sex, all independent exposures associated with each outcome, polygenic risk scores (PRS), and clinical risk factors. C-index and R-squared for these models were validated in an independent set of participants from Scotland/Wales (median 13.7 follow-up years).
Findings: I found 55 exposures that were associated with mortality after multiple analysis stages, including factors related to smoking, physical activity, early childhood, social networks, mental health, diet and supplements, air pollution, material deprivation, sociodemographics, and sleep. Each of the 55 exposures was associated with an average of 21/25 aging biomarkers, 11/25 diseases, and 3/3 cardiometabolic risk factors. I found that while age and sex explain 43-47% of the variance in mortality, adding these 55 exposures to the model increased the mortality R-squared estimate to 61-66%. Further adding PRS for 16 noncommunicable diseases only increased the ability to explain mortality by 0.03-0.6%. Finally, adding clinical risk factors to the model further increased explanation of mortality to 67-70%. Proportions of variance explained by age and sex, the exposome, PRS, and clinical factors for the 25 age-related diseases studied are also reported.
Interpretation: These results provide the first comprehensive map of the environmental architecture of mortality, aging mechanisms, and age-related diseases. I identified many environmental exposures that are strongly associated with mortality in the UK Biobank, which seem to influence mortality through modulation of diverse biological mechanisms, cardiometabolic risk factors, and disease multimorbidity. I further demonstrated that aside from age and sex, the exposome explains the greatest amount of variation in mortality risk even after accounting for polygenic disease risk. Further analysis may be needed to establish causality of identified exposures and to detect residual reverse causation bias in exposures not detected via the methods used in this thesis.