SENMAYO BASED AGING SIGNATURE (SEN-AGE) IN CANCER SURVIVORS - Analyzing Aging Biomarker and 4-Year Mortality

Sep 29, 2026

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SENMAYO gene set signatures for senescent cells were used to build a Sen-Age aging signature in the Health and Retirement Study (HRS) cohort. Using 2016 blood-based measurements of 125 SenMayo genes, Lasso regression selected 97 genes to model chronological age in controls. In 609 cancer survivors, Sen-Age correlated with age (r=0.46). Cox proportional hazards analyses assessed 4-year mortality (N=112), adjusting for age, sex, and race, then additional factors (education, smoking, BMI, inflammation, comorbidities). Sen-Age predicted higher mortality risk and stronger robustness after adjustment.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages1

Reading Time3 min

AccessFree to download

Background

Data and Model Construction

Gene selection and Sen-Age training

Association Analyses

Correlation with chronological age

Mortality prediction with Cox regression

Robustness Checks and Interpretation

FAQs

What is the Sen-Age signature and how is it derived?

Sen-Age is an aging signature built from SenMayo gene-set measurements. Lasso regression selected 97 genes from 2016 control participants to model chronological age.

How does Sen-Age relate to chronological age in cancer survivors?

In 609 cancer survivors, Sen-Age showed a correlation of 0.46 with chronological age.

Does Sen-Age predict 4-year mortality among cancer survivors?

Yes. Sen-Age was associated with increased 4-year mortality risk in cancer survivors (HR 1.47, p=0.0008), and the association remained robust after additional adjustment (HR 1.31, p=0.02).

What does the study conclude about Sen-Age as a biomarker?

The findings support Sen-Age as a potential biomarker of aging and mortality risk in cancer survivors.

Sep 29, 2026

Upload by Aurelia