Aug 2026· The journals of gerontology. Series A, Biological sciences and medical sciences· 0 citations
Medicine
TL;DR
The Met-TL may serve as a promising biomarker of cellular aging, particularly in identifying liver dysfunction, facilitating the development of personalized aging monitoring and anti-aging intervention strategies.
Abstract
Background
Telomere length (TL) is a well-established biomarker of cellular senescence, yet the metabolic profile of TL and its associations with aging-related phenotypes and responses to modifiable lifestyle factors remain unclear.
Methods
TL was measured using quantitative real-time polymerase chain reaction (qPCR) in 282 participants from the West China Health and Aging Cohort (WCHAC). Plasma metabolites were analyzed using Liquid Chromatography-tandem Mass Spectrometry. TL-associated metabolic signatures (Met-TL) were identified through elastic net regression models. Associations between Met-TL and aging-related phenotypes and modifiable lifestyle factors were evaluated using linear and logistic regression models in a larger, non-overlapping sample of 5,957 WCHAC participants. Furthermore, we employed mediation analysis to explore the mediating effects of Met-TL between lifestyle factors and aging-related diseases.
Results
We identified a plasma metabolite signature comprising 26 metabolites explaining 17.5% of TL variance. Met-TL significantly associated with aging-related phenotypes (44 Bonferroni-corrected associations) and modifiable lifestyle factors (4 associations). Notably, Met-TL showed robust associations with steatohepatitis and hepatic biomarkers. Mediation analysis revealed that Met-TL partially explained the protective association between healthy lifestyle and steatohepatitis, with a mediation proportion of 8.2%.
Conclusion
These findings provide novel insights into the metabolic profile of TL in older adults. The Met-TL may serve as a promising biomarker of cellular aging, particularly in identifying liver dysfunction, facilitating the development of personalized aging monitoring and anti-aging intervention strategies.
ABSTRACT Epigenetic aging biomarkers are well‐established hallmarks of biological aging, yet their metabolic underpinnings remain largely unexplored. Here, we characterized metabolic signatures associated with five epigenetic aging biomarkers (HorvathAge, HannumAge, DNAmPhenoAge, DunedinPACE, and DNAmTL) and examined their clinical relevance and potential determinants in 7162 Chinese older adults from two cohorts (primary and validation). We observed both shared and distinct metabolic associations across epigenetic aging biomarkers. Metabolic signatures of epigenetic aging biomarkers were derived using elastic net regression, showing moderate correlations with the corresponding epigenetic aging biomarkers (r = 0.21–0.36 in internal testing set, p < 0.05), with external replication further validating metabolic signatures of DNAmPhenoAge, DunedinPACE, and DNAmTL (r = 0.18–0.29, p < 0.05). These five metabolic signatures of epigenetic age acceleration (EAA) exhibited 279 significant associations with aging‐related phenotypes including higher disease risk, poorer health status, and adverse clinical indicators. Gallstones, chronic kidney disease, and hepatitis, along with renal‐, hepatic‐ and metabolic‐related clinical indicators, were consistently associated with multiple metabolic signatures of EAA. Smoking status, alcohol consumption, body mass index (BMI), and physical activity were identified as modifiable lifestyle factors associated with metabolic signatures of EAA, with BMI showing the most consistent associations. Metabolic signatures of DunedinPACE and DNAmPhenoAA exhibited the most extensive associations with aging‐related phenotypes and modifiable lifestyle factors in both primary and validation cohorts. These findings provide novel insights into the metabolic correlates of epigenetic aging biomarkers and underscore the potential of metabolomics‐informed metrics of epigenetic aging as informative indicators of physiological decline and lifestyle effects.
BACKGROUND
Leukocyte telomere length (LTL) and epigenetic age acceleration (EAA) are widely studied biomarkers of biological aging, but their potential roles in healthspan remain unclear. We evaluated whether genetically proxied LTL and EAA show evidence of potential effects on healthspan.
METHODS
We conducted a two-sample Mendelian randomization study. Genetic instruments for LTL and four EAA biomarkers were obtained from published genome-wide association studies, including up to 472,174 individuals for LTL and approximately 35,000 individuals for each EAA biomarker. Summary statistics for healthspan, defined as age at first diagnosis of any of eight major chronic conditions or death, were derived from 300,447 unrelated European-ancestry participants in the UK Biobank. We used inverse-variance-weighted (IVW) models for the main analysis, with complementary MR estimators and sensitivity analyses to evaluate consistency, pleiotropy, instrument heterogeneity, and robustness.
RESULTS
Genetically proxied longer LTL was associated with extended healthspan (IVW β = 0.106; 95% CI: 0.054-0.158; p = 6.9 × 10-5). The association was robust across multiple sensitivity analyses. In contrast, the four genetically proxied EAA biomarkers did not show consistent MR evidence of an association with healthspan.
CONCLUSIONS
These findings provide genetic evidence consistent with a potential role of LTL in healthspan, while providing little support for comparable associations involving the genetically proxied components of the evaluated EAA biomarkers. The findings do not exclude potential associations with environmentally or physiologically acquired EAA.
Bo-Wen Feng, Robert Yang, Gabriella R. Wang et al.· Annals of Human Genetics· 0 citations
It is found that socioeconomic adversity influences not only inflammatory pathways but also distinct biological aging processes, including metabolomic aging, and that socioeconomic adversity influences not only inflammatory pathways but also distinct biological aging processes.
C. H. Tejera, R. Noroozi, K. A. Walker et al.· medRxiv· 0 citations
Although associations with fibrosis-related outcomes varied according to fibrosis definitions, DNAm aging algorithms may provide additional biological information for mortality risk stratification among individuals with CLD-related phenotypes.
