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

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 4712 proteins using SomaScan in plasma samples collected at 3 visits, including Visit 5 (2011-2013) from 806 LTCS and 3699 cancer-free participants, all aged 66-90. Among 2466 randomly selected cancer-free participants, we developed CaPAC using elastic net regression. Age acceleration was calculated as residuals of CaPAC regressed on chronological age (CaPAC_Accel). We used multivariable Cox proportional hazards regression to calculate hazard ratios (HRs) for the associations of CaPAC_Accel 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, CaPAC_Accel was associated with increased all-cause mortality in both ARIC (HR per 1 SD = 1.42, 95% confidence interval [CI] = 1.24 to 1.62; P <. 001) and MESA (1.62, 1.12 to 2.33; P =. 009). Also, in ARIC, CaPAC_Accel was associated with all-cause mortality in breast (1.54, 1.05 to 2.25; P =. 028) and colorectal LTCS (1.96, 1.19 to 3.22; P =. 008). Additionally, CaPAC_Accel was associated with cancer mortality in LTCS (1.34, 1.09 to 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 CaPAC_Accel 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.