OmniAge compendium: 413 aging omic biomarkers and their correlations in blood
The OmniAge package collects 413 aging omic biomarkers in 12 categories; in large blood datasets, mitotic age was associated with clonal hematopoiesis subtypes and causal clocks, and the authors call it an exploratory tool for generating hypotheses. [1]
Automatic summary · not editorially reviewed
The key findings
OmniAge is an R and Python package collecting 413 aging omic biomarkers in 12 categories. [1]
In large blood datasets, mitotic age was associated with clonal hematopoiesis subtypes and causal clocks described as predictive of cancer risk. [1]
Age acceleration from transcriptomic and epigenetic clocks correlated in sorted immune cell types, but this was driven by cell-type heterogeneity. [1]
The source at a glance
- Study type / format
- Abstract describing a biomarker software package and exploratory correlation analyses.
- Population / context
- Large blood datasets and sorted immune cell types analyzed with aging omic biomarkers.
- Summary based on
- Study abstract
- Original publication
- July 28, 2026
OmniAge package: 413 biomarkers in 12 categories
Interest in aging omic biomarkers has grown because they can quantify biological age. Most were derived in blood and fall into many categories, but little is known about how biomarkers from different categories correlate. The authors present OmniAge, an R and Python package with 413 aging omic biomarkers in 12 categories. These include traditional epigenetic clocks, epigenetic mitotic clocks, DNA methylation-based proxies for clonal hematopoiesis and inflammaging, causal clocks, cell-type specific epigenetic clocks and single-cell transcriptomic clocks.
Supporting source [1]
Mitotic age linked to clonal hematopoiesis in blood data
By studying inter-class correlations across large blood datasets, the authors report associations of mitotic age with clonal hematopoiesis subtypes and with causal clocks, which are described as predictive of cancer risk. Using proxies of serum protein levels, they further separated associations with mitotic clocks, clonal hematopoiesis and causal clocks into distinct biological processes mapping to key aging pathways. These are described as associations, not as evidence that one factor causes another.
Supporting source [1]
Immune cell-type heterogeneity drives clock correlation
Applying OmniAge to multi-modal data of sorted immune cell types revealed that age acceleration derived from transcriptomic and epigenetic clocks correlated, but that this correlation was driven by underlying cell-type heterogeneity. In summary, the authors describe OmniAge as an exploratory tool for evaluating large numbers of aging omic biomarkers and for aiding discovery and generating new hypotheses. The abstract does not report a validated product or a causal demonstration.
Supporting source [1]
How to interpret this
This is an abstract only; the full text was not reviewed. The reported links are associations from exploratory analyses, not causal findings, and no human lifespan or clinical benefit is reported.
Based on the study abstract; the full paper, tables and supplementary data were not reviewed.
Source & supporting passages
Du Z, Ling Y, Tong H, Guo X, Teschendorff AE. · europepmc.org · July 28, 2026