Systemic and organ-specific proteomic aging clocks as predictors of cancer incidence and survival: insights from the Finnish Twin Cohort
- 1Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, FINLAND; Minerva Foundation Institute for Medical Research, Helsinki, FINLAN
Abstract
Despite recent evidence of the ability of systemic and organ-specific proteomic aging clocks to predict a large range of age-related diseases, their utility in cancer research remains largely underexplored. In this study, we evaluated the predictive ability of systemic and organ-specific proteomic aging clocks for (i) all-cause mortality, (ii) cancer-related mortality, and (iii) cancer incidence in a sample of Finnish twins (N = 401, mean age at baseline 62.3 years) with Olink proteomic data. Participants were followed for a mean of 10.6 years (SD {+/-} 1.6), with estimates from four systemic and 18 organ-specific proteomic aging clocks calculated at baseline. Cox proportional hazards regression models adjusted for sex and age at baseline identified 15 proteomic aging clocks as significant predictors of all-cause mortality (Ncases = 28) after multiple testing correction (FDR < 0.05), with 11 remaining significant after lifestyle adjustment (Ncases = 27). For several clocks, effect sizes were large, with hazard ratios (HR) approximately doubling per one standard deviation (SD) increase in clock estimates. In predicting cancer-related deaths among participants without a prior cancer diagnosis at baseline (Ncases = 9), only the Immune clock showed a significant positive association after multiple testing correction in basic (HR = 2.94, 95% CI: 1.88-4.59) and lifestyle-adjusted models (HR = 3.31, 95% CI: 1.78-6.17). No associations with cancer incidence (Ncases = 34 basic, Ncases = 31 adjusted) survived multiple testing correction, although several nominal associations were observed. In conclusion, our findings suggest that proteomic aging clocks are strong predictors of all-cause and cancer-specific mortality, independent of lifestyle factors. Proteomic aging clocks may further serve as valuable tools for stratifying cancers by mortality risk.
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BibTeX
@misc{lukander2026systemic,
title = {{Systemic and organ-specific proteomic aging clocks as predictors of cancer incidence and survival: insights from the Finnish Twin Cohort}},
author = {V. M. Lukander and J. M. Kaprio and X. Wang and M. Ollikainen and G. Drouard},
howpublished = {medRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.14.26365410},
url = {https://www.medrxiv.org/content/10.64898/2026.10.14.26365410v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Systemic and organ-specific proteomic aging clocks as predictors of cancer incidence and survival: insights from the Finnish Twin Cohort
AU - V. M. Lukander
AU - J. M. Kaprio
AU - X. Wang
AU - M. Ollikainen
AU - G. Drouard
PY - 2026
DA - 2026/10/14
PB - medRxiv
DO - 10.64898/2026.10.14.26365410
UR - https://www.medrxiv.org/content/10.64898/2026.10.14.26365410v1
AB - Despite recent evidence of the ability of systemic and organ-specific proteomic aging clocks to predict a large range of age-related diseases, their utility in cancer research remains largely underexplored. In this study, we evaluated the predictive ability of systemic and organ-specific proteomic aging clocks for (i) all-cause mortality, (ii) cancer-related mortality, and (iii) cancer incidence in a sample of Finnish twins (N = 401, mean age at baseline 62.3 years) with Olink proteomic data. Participants were followed for a mean of 10.6 years (SD {+/-} 1.6), with estimates from four systemic and 18 organ-specific proteomic aging clocks calculated at baseline. Cox proportional hazards regression models adjusted for sex and age at baseline identified 15 proteomic aging clocks as significant predictors of all-cause mortality (Ncases = 28) after multiple testing correction (FDR < 0.05), with 11 remaining significant after lifestyle adjustment (Ncases = 27). For several clocks, effect sizes were large, with hazard ratios (HR) approximately doubling per one standard deviation (SD) increase in clock estimates. In predicting cancer-related deaths among participants without a prior cancer diagnosis at baseline (Ncases = 9), only the Immune clock showed a significant positive association after multiple testing correction in basic (HR = 2.94, 95% CI: 1.88-4.59) and lifestyle-adjusted models (HR = 3.31, 95% CI: 1.78-6.17). No associations with cancer incidence (Ncases = 34 basic, Ncases = 31 adjusted) survived multiple testing correction, although several nominal associations were observed. In conclusion, our findings suggest that proteomic aging clocks are strong predictors of all-cause and cancer-specific mortality, independent of lifestyle factors. Proteomic aging clocks may further serve as valuable tools for stratifying cancers by mortality risk.
ER -