Common and organ-specific biological age gaps in UK Biobank multi-omics analysis
In UK Biobank data, the authors refined a common biological age gap and organ-specific age gaps from 78 physiological and biochemical measures; these gaps showed distinct molecular signatures, and combined multi-omics risk scores improved prediction of 5- and 10-year disease incidence and survival. [1]
Automatic summary · not editorially reviewed
The key findings
The analysis used UK Biobank data from 501,623 participants and 78 physiological and biochemical phenotypes to refine a common and organ-specific biological age gaps. [1]
CBAG-associated omics markers were enriched in chromatin active regions and ubiquitously expressed proteins, while OSBAG signals concentrated in organ-specific elements and proteins. [1]
Multi-omics risk scores combining polygenic, proteomic and metabolomic markers improved prediction of 5- and 10-year disease incidence and survival outcomes. [1]
The source at a glance
- Study type / format
- Abstract of a multi-omics association analysis in a cohort
- Population / context
- UK Biobank participants (n=501,623) with 78 physiological and biochemical phenotypes.
- Summary based on
- Study abstract
- Publication status
- Preprint · peer-review status not confirmed
- Original publication
- August 11, 2026
UK Biobank measures split into common and organ-specific gaps
The abstract describes an analysis of UK Biobank data from 501,623 participants using 78 physiological and biochemical phenotypes. From these, the authors refined two metrics: a common biological age gap (CBAG) for global aging patterns and organ-specific biological age gaps (OSBAGs) for localized patterns. The abstract reports that CBAG correlated strongly with established aging indicators and chronic disease endpoints, while OSBAGs showed targeted links to specific organ dysfunctions.
Supporting source [1]
Distinct molecular signatures for common versus organ-specific gaps
Genome-wide, proteome-wide and metabolome-wide association studies identified distinct molecular signatures for these aging phenotypes. Markers linked to CBAG were enriched in chromatin active regions across diverse cell types and in ubiquitously expressed proteins, whereas OSBAG signals were more concentrated in organ-specific functional elements and proteins. Multi-omics risk scores combining polygenic, proteomic and metabolomic markers improved prediction of 5- and 10-year disease incidence and survival outcomes.
Supporting source [1]
Abstract-only scope and biomarker database
The authors describe their approach as prioritizing a list of putative causal biomarkers and as laying the foundation for precision-driven anti-aging interventions; the abstract does not report an intervention or a tested treatment. All genetic, proteomic and metabolomic associations were integrated into the HONOR database. Only the abstract was reviewed, not the full text, so study design details, adjustment for confounders and the strength of causal claims cannot be checked here.
Supporting source [1]
How to interpret this
Only the abstract was reviewed; the full text was not reviewed. Design details, confounder adjustment and the basis for calling biomarkers putative causal cannot be checked. No intervention was tested, so anti-aging benefits are not shown.
Based on the study abstract; the full paper, tables and supplementary data were not reviewed.
Source & supporting passages
Wang S, Huang H, Li Y, Song Q, Yuan L, Yang Y, Sun R, Hu Y, Xiong C, Ni T, Liu Y, Zhang G, Ruiz-Linares A, Liu F, Peng Q. · europepmc.org · August 11, 2026