According to a recent study, key aging transitions occur at two particular ages, impacting disease risk.
A recent study published in Nature Aging has shed light on the nonlinear molecular changes associated with aging, identifying two critical transition points that impact disease risk. The research, which employed a longitudinal multi-omics approach, involved 108 participants aged 25 to 75 years (median age: 55.7 years), with a BMI range of 19.1 to 40.8 kg/m2 and 51.9% female participants. The median follow-up period was 1.7 years, with a maximum follow-up duration of 6.8 years.
Researchers collected various omics data, including transcriptomics, proteomics, metabolomics, lipidomics, and microbiome profiling, from a total of 5,405 biological samples (1,440 blood samples, 926 stool samples, 1,116 skin swabs, 1,001 oral swabs, and 922 nasal swabs). The analysis revealed that 81.03% of the 11,305 molecular features exhibited nonlinear patterns of change during at least one age stage compared to baseline, while only 6.6% showed linear changes during aging.
Significant dysregulation was observed at two critical transition points, approximately at ages 44 and 60. Distinct molecular and functional pathways were associated with these transitional periods. The transition around age 60 was characterized by changes in immune regulation, carbohydrate metabolism, kidney function, and skin and muscle stability. The transition around age 44 was associated with alterations in cardiovascular disease risk factors, lipid metabolism, alcohol metabolism, and skin and muscle stability.
The study highlighted that processes such as oxidative stress, mRNA stability, and autophagy became more pronounced after the age of 60, suggesting that the risks for diseases like cardiovascular disease, type 2 diabetes, and kidney dysfunction increase nonlinearly with age, particularly after 60 years.
The researchers emphasized the importance of understanding the alterations in molecules, such as transcripts, proteins, metabolites, and cytokines, for elucidating the mechanisms of aging and identifying potential therapeutic targets for aging-related diseases. However, they acknowledged several limitations, including the lack of detailed behavioral data (e.g., physical activity, alcohol, and caffeine intake) and the limited generalizability of the cohort.
The study authors concluded that further research with larger cohorts is necessary to validate and expand upon these findings, which could help capture the full complexity of aging.
Full list of disclosures can be found in the original study.
