OmniAge maps aging biomarkers, linking mitotic clocks to clonal hematopoiesis

A new study in Nature Communications reports an ambitious “OmniAge” compendium that maps aging-associated biomarkers across multiple omic layers and then uses that map to trace biological causality. The work by Du, Ling, Tong and colleagues focuses on a long-debated question: how measures of cellular aging relate to clonal expansions in the blood system—specifically clonal hematopoiesis.

Clonal hematopoiesis arises when blood-forming stem cells accumulate mutations and expand into dominant clonal populations. While such expansions are common in older adults, not all are equally risky. The key challenge has been distinguishing which biomarkers merely correlate with clonal hematopoiesis from those that reflect upstream mechanisms driving it.

To address this, the researchers leveraged OmniAge to connect aging signatures to “mitotic clocks,” molecular patterns that track the cumulative number of cell divisions over time. Instead of treating age-related omics as a static snapshot, the team modeled how division-linked processes might predict the emergence and persistence of clones.

Methodologically, the study integrates biomarker discovery with causal inference strategies. By testing whether mitotic-clock–linked features explain variation in clonal hematopoiesis beyond conventional aging measures, the authors argue for a directional relationship rather than a purely observational one.

The results suggest that mitotic clocks capture biological strain that promotes clonal selection in hematopoietic lineages. In other words, accelerated or dysregulated cell division history may create the evolutionary conditions for certain mutant clones to outcompete their neighbors.

The OmniAge framework also provides a unified resource for researchers, consolidating aging-related omics markers that can be interrogated across cohorts. This is positioned as a step toward translating biomarker panels into mechanistic hypotheses that can be tested experimentally.

Crucially, the paper frames clonal hematopoiesis not only as a marker of aging but as a downstream outcome of division-linked processes with identifiable causal footprints. That framing could sharpen risk stratification and guide future interventions aimed at preserving hematopoietic function.

If validated across diverse populations, these findings may help clinicians interpret aging biomarker readouts in terms of underlying cellular history. More broadly, OmniAge may become a template for linking multi-omic aging data to causal pathways across diseases.