Epigenetic age and long-term cancer risk following a stroke

Abstract

Background: The association between increased cancer risk following a cerebrovascular event (CVE) has been previously reported. We hypothesize that biological age (B-age) acceleration is involved in this association. Our study aims to examine B-age as a novel contributing factor to cancer development post-CVE.

Methods: From our prospective stroke registry (BasicMar), we selected 940 cases with epigenetic data. For this study, we specifically analyzed 648 of these patients who had available data, no prior history of cancer, and a minimum follow-up of 3 months. The primary outcome was cancer incidence. B-age was estimated using DNA methylation data derived from whole blood samples obtained within 24 h of stroke onset, employing various epigenetic clocks (including Hannum, Horvath, PhenoAge, Zhang_BLUP, Zhang_EN, and the mitotic epiTOC). Extrinsic epigenetic age acceleration (EEAA) was calculated as the residuals from the regression of B-age against chronological age (C-age). For epiTOC, the age-adjusted values were obtained by regressing out the effect of age from the raw epiTOC measurements. Estimated white cell counts were derived from DNA methylation data, and these cell fractions were used to compute the intrinsic epigenetic age acceleration (IEAA). Subsequently, we evaluated the independent association between EEAA, IEAA, and cancer incidence while controlling for potential confounding variables.

Results: Among 648 patients with a median follow-up of 8.15 years, 83 (12.8%) developed cancer. Cox multivariable analyses indicated significant associations between Hannum, Zhang, and epiTOC EEAA and the risk of cancer after CVE. After adjusting for multiple testing and competing risks, EEAA measured by Hannum clock maintained an independent association with cancer risk. Specifically, for each year increase in Hannum's EEAA, we observed a 6.0% increased incidence of cancer (HR 1.06 [1.02-1.10], p value = 0.002).

Conclusions: Our findings suggest that epigenetic accelerated aging, as indicated by Hannum's EEAA, may play a significant role in the increased cancer risk observed in CVE survivors.

Keywords: Aging; Cancer; DNA methylation; Epigenetic clock; Stroke.

Fig. 1

Study flowchart. A total of 648 patients were included in the study. Concomitant cancer diagnosis was considered when the diagnosis of cancer was made in the same moment of stroke diagnosis (i.e., during the hospital admission). FU, follow-up; DNAm, DNA methylation

Fig. 2

Age acceleration and presence of cancer. A depicts the distribution of EEAA/IEAA and epiTOC estimations. B compares these estimations between patients with and without incident cancer. Lighter colors and solid contours correspond to EEAA and raw epiTOC values, while darker colors and dashed contours correspond to IEAA and age-adjusted epiTOC. *: p value < 0.05, **: p value < 0.01. BLUP, Best Linear Unbiased Prediction; EN, elastic net; epiTOC, epigenetic Timer Of Cancer

Fig. 3

Estimated immune-cell counts. A shows the distribution (density function) of each cell subset. B represents the correlation between C-age and each cell type, where correlation coefficients have been obtained with Spearman rho. C compares cell proportions between patients with and without incident cancer. *: p value < 0.05. Baso, basophiles; Bmem, memory B cells; Bnv, naïve B cells; CD4Tmem, memory CD4 + T cells; CD4Tnv, naïve CD4 + T cells; CD8Tmem, memory CD8 + T cells; CD8Tnv, naïve CD8 + T cells; Eos, eosinophils; Mono, monocytes; Neu, neutrophils; NK, natural killer; Treg, regulatory T cells

Fig. 4

Cumulative incidence of cancer in the cohort. Values represent the number of patients at risk and the cumulative number of events. A shows the cumulative incidence function in the whole sample, while in B we stratified the incidence by tertile-split Hannum extrinsic epigenetic age acceleration. Time is represented in years. T1, first tertile; T2, second tertile; T3, third tertile

Fig. 5

Independent effect of age acceleration on incident cancer. A shows the hazard ratios and confidence interval for each epigenetic clock (adjusted for sex) and model type (Cox regression and Fine-Gray models). Lighter and darker colors correspond to EEAA and IEAA for each biological age estimations, while for epiTOC represent the raw and age-adjusted values. The red dashed line corresponds to the absence of effect. For EEAA/IEAA, hazard ratios indicate the increased risk of cancer per year of EEAA/IEAA increase. Regarding epiTOC, we present the effects of both raw and C-age-adjusted values for a one-standard-deviation increase in these estimations. B represents the interaction between these estimations and relevant moderators (sex, stroke type, and array type) which have been obtained via Cox regression models. For EEAA/IEAA, HRs indicate the increased risk of cancer per year of EEAA/IEAA increase. *: FDR_BH < 0.05