U.K. research suggests that people of the same chronological age can age at vastly different rates on a molecular level, but it is dynamic and dependent on environment.
The findings frame biological aging as a set of interacting molecular trajectories and could help distinguish growing older healthily from early signatures of disease.
The research, in Science, revealed how molecular aging is far from a uniform process, but rather showed diverse individual trajectories alongside more constant population-level trends.
Understanding variations in these individual trajectories could be crucial for the development of precision medicines and enable early and targeted therapeutic interventions.
“Rather than there being a single molecular roadmap of aging, our study shows that people follow distinct biological journeys,” explained researcher Julia El-Sayed Moustafa, PhD, from King’s College London.
“Two healthy people of the same age can be aging in surprisingly different ways at the molecular level. That raises the possibility of much more personalized approaches to predicting disease risk and maintaining health as we grow older.”
Aging is a dynamic process shaped not only by genetics but also molecular and physiological processes, environment, and disease-mediated change.
Multi-omic profiling can capture this at molecular resolution but realizing its potential requires a robust understanding of how molecular phenotypes change over time within individuals, so that healthy aging trajectories can be distinguished from those signaling pathology.
To examine longitudinal multi-omic trajectories of human aging, El-Sayed Moustafa and co-workers established the MultiMuTHER study within the deeply phenotyped TwinsUK cohort.
The team profiled whole-blood gene expression and 1197 serum metabolites at three or more time points over up to eight years in 335 women.
Through this, they identified 5061 genes and 181 metabolites whose levels changed over time, including many linked with age-related diseases like cardiometabolic and neurodegenerative disorders.
Participants displayed distinct longitudinal trajectories that were sometimes opposite to population-level trends, with the results highlighting the influence of cell type composition, host genetics, biological rhythms, environmental exposures, and cross-omic connectivity.
Molecular changes varied by cell type and were influenced by genetics, biological rhythms, and environmental exposures.
Gene expression and metabolite levels could be highly dependent on context, with 25% of genes and 24% of metabolites associated with seasonality, and a corresponding 26% and 39% associated with circadian variation.
Levels of 128 genes and two metabolites displayed genotype-specific longitudinal changes. Serum levels of the environmental pollutants per- and polyfluoroalkyl substances (PFAS)—also known as “forever chemicals”—decreased over time, consistent with restrictions on their use in the U.K., and showed time-dependent associations with expression of 1.5% of genes and serum levels of three percent of metabolites.
There were also relationships between genes and metabolites associated with cardiometabolic traits and aging.
Of note, there were different trajectories of change between participants with the CXCL9 gene linked to cardiac aging.
Levels of the tumor suppressor gene TP53 also declined in some women as they grew older, potentially affecting their risk of cancer.
“Longitudinal profiling offers insight into the temporal evolution of age-related conditions at the molecular level, and understanding individual variation within these longitudinal patterns will be essential for future precision medicine approaches,” the researchers concluded.
