New research reveals that environmental factors, from smoking to socioeconomic status, have a stronger influence on aging and premature mortality than genetics—reshaping our understanding of disease prevention.
Study: Integrating the environmental and genetic architectures of aging and mortality. Image Credit: Shutterstock AI Generator / Shutterstock.com
A recent Nature Medicine study compares the relative contributions of genetics and the environment to aging and premature mortality.
The impact of environmental and genetic factors on human aging
Human aging is a complex process associated with biological and subclinical changes that begin in mid-life, typically between the ages of 40 and 60. Several studies have reported that non-genetic environmental factors can accelerate the aging process and increase the risk of premature mortality by nearly two-fold.
The exposome refers to the total set of interrelated environmental exposures throughout an individual’s life span. Despite previous exposome-wide study designs providing crucial insights into how environmental exposure impacts aging, few large-scale studies have examined potential independent associations between the exposome, population-level mortality, and age-related disease rates.
About the study
The current study compares the contributions of the genome and exposome to premature mortality and major age-related diseases using a robust pipeline developed to evaluate reverse causation and residual confounding.
Initially, an exposome-wide analysis was conducted using United Kingdom population-based data from the U.K. Biobank to systematically determine exposures that are independently linked with risks of premature mortality. Subsequently, a phenome-wide analysis was performed for every mortality-associated exposure to remove exposures that are sensitive to confounding and mismeasurement.
A total of 176 unique exposures were available, common to both men and women. Exposures only associated with a proteomic aging clock were considered, as this enabled the identification of factors exclusively linked to the aging process. The effect of the identified exposomes was assessed in relation to the onset of 25 major age-related diseases.
Genetics vs. environment: Key contributors to aging and mortality
The current study included a total of 436,891 UKB participants from England. An additional 55,676 UKB participants from Scotland and Wales were used as a validation set for final multivariable disease models. After a median of 12.5 years of follow-up, 31,716 deaths were recorded from all causes.
The study cohort presented multiple age-related diseases, including brain cancer and osteoarthritis. Multiple step-wise analyses were conducted, including an exposome-wide association study (XWAS), phenome-wide association study (PheWAS), and hierarchical clustering into a single Cox model. These analyses identified 25 independent exposures associated with proteomic aging, premature mortality, age-related diseases, and biochemical markers of aging.
The primary contributors to aging and premature death were socioeconomic status and deprivation, smoking, the number of household vehicles, physical activity, ethnicity, living with a partner, sleep, as well as mental and physical wellness.
Maternal smoking near the time of birth, as well as height and body size at 10 years of age, were also associated with premature death. Among these factors, current smokers, individuals who more frequently reported feeling tired, and those living in council housing as compared to home ownership were primarily associated with premature death and aging.
Cox proportional hazards models were used to determine whether the identified exposures increased the risk of developing age-related diseases that contribute to premature mortality. Each of the 25 exposures was associated with a wide range of aging biomarkers related to diverse organ systems and mechanistic pathways.
Many interrelated factors connect the environmental architecture of mortality and aging, which individually may not have significantly contributed to the outcome. On average, each exposure was associated with 22 of the 25 biomarkers. For example, smoking status and ethnicity were linked with all 25 biomarkers.
Metabolic risk factors of common diseases, such as obesity and hypertension, were cross-sectionally associated with most of the studied exposures. Thus, many age-related diseases share a common environmental etiology that may contribute to life expectancy, including premature mortality.
Approximately 66% of mortality-associated exposures were not associated with proteomic aging.
The genome and environmental factors have attributed high variability across many disorders. For example, certain diseases, such as all-cause dementia and macular degeneration, Alzheimer’s disease, and certain cancers, including those affecting the prostate and breast, were primarily influenced by polygenic risk. However, diseases such as rheumatoid arthritis, ischemic heart disease, and kidney diseases were more significantly impacted by the exposome.
Conclusions
The current study emphasizes the importance of large biobanks to provide crucial insights into the interplay between genetic and environmental exposures in aging and premature mortality. These findings highlight the potential of environment-focused interventions to prevent premature mortality and the development of numerous age-related diseases.
The exposome shapes distinct patterns of disease and mortality risk, irrespective of polygenic disease risk.”
In the future, causal modeling studies are needed to identify specific exposures of interest.
Journal reference:
- Argentieri, M. A., Amin, N., Nevado-Holgado, A. J., et al. (2025) Integrating the environmental and genetic architectures of aging and mortality. Nature Medicine; 1-10. doi:10.1038/s41591-024-03483-9