ArticleGeroScience2025
A simple blood biomarker based on gene expression describes cardiovascular health-related biological age.
Article in GeroScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- The role of biological age in stroke prediction: evidence from CHARLS and machine learning models.BMC neurology · 2026Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
The need to monitor the aging process as a risk factor for disease and mortality beyond chronological age (CA) has led to numerous investigations into the estimation of the biological age (BA) of individuals. However, the accuracy of BA estimation tools is often judged by their ability to approximate CA, questioning their value in capturing the variance in health status and thus correctly estimating BA. Their biological relevance is often assessed in relation to health outcomes or mortality, underexploiting their potential for real-time monitoring of BA. Furthermore, their complexity may limit their clinical translation to large populations. Here, we describe the gene expression-based age monitoring Clock (GamC), a simple biomarker of aging (BOA), and characterize its biological relevance with synchronous cardiovascular (CV) health-related functional data. GamC is calculated from the expression levels of three genes consistently dysregulated with age in blood (ABLIM1, CCR7, and LEF1). GamC shows moderate but reliable association with CA in three independent cohorts, supported by transcriptome-wide changes. It demonstrates specialized biological meaning, as it specifically describes current physical activity levels, but poorly correlates with autonomic nervous system function, both age-related factors associated with CV health. Finally, it expresses BA monitoring capacity by modestly responding to an effective exercise-based intervention in centenarians. In conclusion, GamC is proposed as a simple and affordable candidate BOA for reporting the individuals' current CV health-related BA, thus promoting its broad translation and application into measures aimed at promoting healthy aging in relation to CV health, the leading cause of death worldwide.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.