Biomarker Prediction For longevity considering measurement age. Evidence From Swedish AMORIS Cohort
Abstract
Background: Metabolic biomarkers are linked to subsequent mortality. In prior work we have shown how individuals reaching exceptional ages have more favorable biomarker profiles earlier in life than shorter lived peers. However, the role of age at measurement for common metabolic biomarkers remain unclear, if midlife values are more predictive than values at older ages? This study describes how metabolic biomarkers relate to absolute probabilities to reach advanced ages and how age at measurement matter.
Methods: 44884 individuals born 1893-1920 from the Swedish Apolipoprotein-Related Mortality Risk (AMORIS) cohort was included. Total cholesterol (TC), triglycerides, and glucose were measured during 1985–1996, with. Individuals were followed date of death in registers until December 31, 2020. Using flexible parametric models, we estimated sex-specific probabilities of reaching average lifespan, above average lifespan (age 90), and exceptional age (100) for biomarker values measured at different ages.
Results: Glucose had an inverted-J association with survival, triglycerides an almost linear shape, and TC an inverted-U pattern. The highest survival probability was observed at glucose values around 4.6-4.8 mmol/L for both sexes, independent of measurement age. Triglycerides associated with higher-than-average survival to age 90 varied by measurement age: in women, the upper threshold increased with age (<0.99, 1.13, and 1.32 mmol/L at age 65, 70, 75), but in men it declined (<2.10, 1.90, and 1.35 mmol/L, respectively).
Conclusions: Metabolic biomarkers show distinct associations with survival probabilities, but for some markers optimal values varies with sex and age at measurement. This highlights the need for sex- and age-specific interpretation of biomarkers for survival to extreme ages.
Key messages: • From a population perspective, metabolic biomarkers could capture long-term physiological resilience and shape the probability of reaching advanced ages.
• Our findings highlight the importance of consistent monitoring of metabolic biomarker profiles in older populations in clinical practices.
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BibTeX
@article{zhang2026biomarker,
title = {{Biomarker Prediction For longevity considering measurement age. Evidence From Swedish AMORIS Cohort}},
author = {Y Zhang and S Murata and K Schmidt-Mende and M Ebeling and K Modig},
journal = {The European Journal of Public Health},
year = {2026},
month = oct,
doi = {10.1093/eurpub/ckag169.112},
url = {https://doi.org/10.1093/eurpub/ckag169.112},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - Biomarker Prediction For longevity considering measurement age. Evidence From Swedish AMORIS Cohort
AU - Y Zhang
AU - S Murata
AU - K Schmidt-Mende
AU - M Ebeling
AU - K Modig
PY - 2026
DA - 2026/10/01
JO - The European Journal of Public Health
DO - 10.1093/eurpub/ckag169.112
UR - https://doi.org/10.1093/eurpub/ckag169.112
AB - Background: Metabolic biomarkers are linked to subsequent mortality. In prior work we have shown how individuals reaching exceptional ages have more favorable biomarker profiles earlier in life than shorter lived peers. However, the role of age at measurement for common metabolic biomarkers remain unclear, if midlife values are more predictive than values at older ages? This study describes how metabolic biomarkers relate to absolute probabilities to reach advanced ages and how age at measurement matter. Methods: 44884 individuals born 1893-1920 from the Swedish Apolipoprotein-Related Mortality Risk (AMORIS) cohort was included. Total cholesterol (TC), triglycerides, and glucose were measured during 1985–1996, with. Individuals were followed date of death in registers until December 31, 2020. Using flexible parametric models, we estimated sex-specific probabilities of reaching average lifespan, above average lifespan (age 90), and exceptional age (100) for biomarker values measured at different ages. Results: Glucose had an inverted-J association with survival, triglycerides an almost linear shape, and TC an inverted-U pattern. The highest survival probability was observed at glucose values around 4.6-4.8 mmol/L for both sexes, independent of measurement age. Triglycerides associated with higher-than-average survival to age 90 varied by measurement age: in women, the upper threshold increased with age (<0.99, 1.13, and 1.32 mmol/L at age 65, 70, 75), but in men it declined (<2.10, 1.90, and 1.35 mmol/L, respectively). Conclusions: Metabolic biomarkers show distinct associations with survival probabilities, but for some markers optimal values varies with sex and age at measurement. This highlights the need for sex- and age-specific interpretation of biomarkers for survival to extreme ages. Key messages: • From a population perspective, metabolic biomarkers could capture long-term physiological resilience and shape the probability of reaching advanced ages. • Our findings highlight the importance of consistent monitoring of metabolic biomarker profiles in older populations in clinical practices.
SN - 1101-1262
SN - 1464-360X
ER -