Proteomic aging clocks and the risk of mortality among long-term cancer survivors.

Abstract

BACKGROUND To estimate biological age, we developed a proteomic aging clock in cancer-free participants (CaPAC) and examined its association with mortality in long-term cancer survivors (LTCS, >2 years between cancer diagnosis and blood collection) and cancer-free participants in the Atherosclerosis Risk in Communities (ARIC) and Multi-Ethnic Study of Atherosclerosis (MESA) studies. METHODS ARIC measured 4,712 proteins using SomaScan in plasma samples collected at three visits, including Visit 5 (2011-13) from 806 LTCS and 3,699 cancer-free participants, all aged 66-90. Among 2,466 randomly selected cancer-free participants, we developed CaPAC using elastic net regression. Age acceleration was calculated as residuals from CaPAC regressed on chronological age (CaPACAccel). We used multivariable Cox proportional hazards regression to calculate hazard ratios (HRs) for the associations of CaPACAccel with all-cause and cancer mortality in LTCS and all-cause mortality in the remaining cancer-free participants. We replicated the analysis of all-cause mortality in MESA. RESULTS In LCTS, CaPACAccel was associated with increased all-cause mortality in both ARIC [HR (95% CI) per 1 SD = 1.42 (1.24-1.62), p < .001] and MESA [1.62 (1.12-2.33), p = .009]. Also, in ARIC, CaPACAccel was associated with all-cause mortality in breast [1.54 (1.05-2.25), p = .028] and colorectal LTCS [1.96 (1.19-3.22), p = .008]. Additionally, CaPACAccel was associated with cancer mortality in LTCS [1.34 (1.09-1.64), p = .005] in ARIC. In MESA, limited sample size precluded us from examining individual cancers and cause-specific mortality. In cancer-free participants, the associations of CaPACAccel with all-cause mortality were similar across studies. CONCLUSION Proteomic aging clocks hold promise as a predictor of all-cause and cancer mortality in LTCS.