ArticleNature aging2025
Refining the generation, interpretation and application of multi-organ, multi-omics biological aging clocks.
Article in Nature aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
16 citing papers in PubMed.
- Biological aging clocks in health and disease.Nature medicine · 2026Review
- Brain-heart-eye axis revealed by multi-organ imaging genetics and proteomics.Nature biomedical engineering · 2026Article
- Amino acid-based biological age clock and its implications for human health and aging.Nature communications · 2026Article
- Article
- Article
- Multi-Omics Signatures of Organ Clocks in Biological Aging and Disease: A Conceptual Framework for Organ-Specific Aging Clocks.Aging cell · 2026Review
- From whole-body to organ-specific biological age clocks.Nature aging · 2026Review
- Proteomic aging clocks in epidemiological studies: advances, applications and prospects.Nature aging · 2026Review
- Associations of Biological Age and Heart Age Accelerations With New-Onset Stroke in Individuals With Cardiovascular-Kidney-Metabolic Syndrome Stages 0-3: Evidence From a Chinese Longitudinal Study.Journal of clinical hypertension (Greenwich, Conn.) · 2026Article
- A deep-learning based biomarker of systemic cellular senescence burden to predict mortality and health outcomes.medRxiv : the preprint server for health sciences · 2026Article
- CardioMetAge estimates cardiometabolic aging and predicts disease outcomes.BMC medicine · 2026Article
- Health Galaxy: A Multi-organ Trajectory-Computing Framework in Type 2 Diabetes.Research (Washington, D.C.) · 2026Article
- MRI-based multi-organ clocks for healthy aging and disease assessment.Nature medicine · 2026Article
- The Roles of EDA2R in Ageing and Disease.Aging cell · 2025Review
- Sleep chart of biological aging clocks across organs and omics.medRxiv : the preprint server for health sciences · 2025Article
- Multi-organ MRI digitizes biological aging clocks across proteomics, metabolomics, and genetics.medRxiv : the preprint server for health sciences · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multi-organ biological aging clocks derived from clinical phenotypes and neuroimaging data have emerged as valuable tools for studying human aging and disease. Plasma proteomics provides an additional molecular dimension to enrich these clocks. In this study, I developed 11 multi-organ proteome-based biological age gaps (ProtBAGs) using 2,448 plasma proteins from 43,498 participants in the UK Biobank. Here I highlight methodological and clinical considerations for developing and using these clocks, including correction for age bias, organ specificity of proteins, sample size and underlying pathologies in the training data, which can affect model generalizability and clinical interpretability. In addition, I integrated 11 ProtBAGs with previously developed nine multi-organ phenotype-based biological age gaps to investigate genetic overlap and causal associations with disease endpoints. Finally, I show that incorporating features across organs improves predictions for systemic disease categories and all-cause mortality. These analyses provide methodological and clinical insights for developing and interpreting these clocks and highlight future avenues toward a multi-organ, multi-omics biological aging clock framework.
Indexed as
Identifiers
40764431What Socratic 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 Socratic graph.