ArticleCommunications biology2023
Biological age estimation using circulating blood biomarkers.
Article in Communications biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
51 citing papers in PubMed.
- Longitudinal associations of one-carbon metabolism biomarkers with biological and epigenetic aging in older adults in India.GeroScience · 2026Article
- Explainable Clinical Decision Support for Metabolic Index Prediction in Gout Patients Using GA-Optimized Ensemble Learning Models.Diagnostics (Basel, Switzerland) · 2026Article
- Age-dependent prognostic value of biological age for metastasis and survival in gastrointestinal cancer.Scientific reports · 2026Article
- Hierarchical endpoints and win statistics for geromedicine trials.Nature aging · 2026Review
- Associations of proteomic age clocks with lifestyle risk factors, incident chronic diseases and mortality in two European cohorts.Nature aging · 2026Article
- Review
- Early-life determinants of cardiometabolic outcomes and accelerated biological ageing in Colombia.Aging · 2026Article
- The BHARAT study: a multi-modal, multi-omics investigation of aging signatures in the Indian population.Aging · 2026Observational
- Biological age acceleration, longitudinal change and mortality risk in the Dutch Lifelines cohort.GeroScience · 2026Article
- Accelerated metabolomic aging and its association with social determinants of health in multiple sclerosis.Multiple sclerosis (Houndmills, Basingstoke, England) · 2026Article
- Biological age and immunosenescence in Colombian centenarians.npj aging · 2026Article
- Pregnancy lab test dynamics resemble rejuvenation of some organs and aging of others.Nature communications · 2026Article
- Blood biochemical and gut microbiotic neural network models forecasting human biological age.Aging · 2026Article
- Phenotypic age acceleration and omega-6/omega-3 PUFA ratio in dynamic atrial fibrillation-heart failure transitions: a multistate analysis.The journal of nutrition, health & aging · 2026Article
- Associations of biological ageing and genetic risk with incident abdominal aortic aneurysm.Communications medicine · 2026Article
- Cellular Senescence in the Ascending Aorta and Complexity of Coronary Atherosclerosis.Journal of aging research · 2026Article
- Cardiac and systemic biological age capture complementary aging signals associated with cardiovascular disease.Frontiers in cardiovascular medicine · 2026Article
- Artificial intelligence approaches in biological age prediction: current status and challenges.British journal of biomedical science · 2026Review
- Targeting biological age with bioactive, microbiota-accessible nutritional complexes: a pilot study on healthspan extension in medically healthy adults.Scientific reports · 2025Article
- Do we actually need aging clocks?npj aging · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Biological age captures physiological deterioration better than chronological age and is amenable to interventions. Blood-based biomarkers have been identified as suitable candidates for biological age estimation. This study aims to improve biological age estimation using machine learning models and a feature-set of 60 circulating biomarkers available from the UK Biobank (n = 306,116). We implement an Elastic-Net derived Cox model with 25 selected biomarkers to predict mortality risk (C-Index = 0.778; 95% CI [0.767-0.788]), which outperforms the well-known blood-biomarker based PhenoAge model (C-Index = 0.750; 95% CI [0.739-0.761]), providing a C-Index lift of 0.028 representing an 11% relative increase in predictive value. Importantly, we then show that using common clinical assay panels, with few biomarkers, alongside imputation and the model derived on the full set of biomarkers, does not substantially degrade predictive accuracy from the theoretical maximum achievable for the available biomarkers. Biological age is estimated as the equivalent age within the same-sex population which corresponds to an individual's mortality risk. Values ranged between 20-years younger and 20-years older than individuals' chronological age, exposing the magnitude of ageing signals contained in blood markers. Thus, we demonstrate a practical and cost-efficient method of estimating an improved measure of Biological Age, available to the general population.
Indexed as
Identifiers
What OpenQuestion holds
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 OpenQuestion graph.