Measuring biological age, how old a person’s body really is, as opposed to how many candles were on their last birthday cake, has become one of the most active areas of aging research. But the tools available have largely been single-modal: epigenetic clocks based on DNA methylation, proteomic clocks built from blood proteins, or metabolomic clocks tracking small-molecule profiles. Each captures one dimension of aging, leaving the broader picture incomplete.
A new Preview article published July 9 in Cell (DOI: 10.1016/j.cell.2026.06.018) by Seda Koyuncu, Dunja Petrovic, and David Vilchez of the University of Cologne examines the state of the field and highlights a recent landmark study that moves beyond single-modal approaches toward integrated, multimodal frameworks for measuring human aging.
A Three-Tiered Framework
The Preview focuses on a companion research article published in the same issue of Cell by Li, Jiang, and colleagues, a large-scale study of 2,019 Chinese individuals aged 18 to 91 that introduces a three-tiered aging measurement system. The framework includes a Core Capacity Clock (CC-clock) based on clinical physiological decline, a Multimodal Clock (MM-clock) that integrates clinical data with multi-omics and organ-associated signatures, and organ-specific clocks that measure aging rates in individual tissues.
The key finding from the original research: coagulation-factor accumulation in the blood emerges as a driver of multi-organ senescence and systemic inflammation, a causal pathway identified through the multimodal framework itself.
Why Multimodal Matters
The Preview argues that human aging is fundamentally a heterogeneous, multi-system process that unfolds differently across molecular, tissue, and physiological levels, and that this heterogeneity exists not just between individuals but within them. Different organs in the same person age at different rates. The liver reaches a critical aging inflection point around age 40, while the brain’s aging accelerates around age 50.
Single-modal clocks, whether epigenetic, proteomic, or metabolomic, each capture a piece of this picture but miss the interactions between systems. A multimodal approach that integrates clinical phenomics, multiple omics layers, and organ-specific signatures can capture not only when a person is aging but where and how fast in different systems.
Challenges Ahead
The Preview does not shy away from the field’s limitations. Existing single-omics clocks provide incomplete views, and validating multimodal clocks across diverse populations remains a major challenge, the Li et al. clocks were built on a Chinese cohort, and population specificity is a known concern. Coordinating standardized data collection across multiple cohorts is difficult. And perhaps most fundamentally, distinguishing molecular changes that drive aging from those that merely correlate with it remains an open problem.
The translational gap is also wide: moving from clock predictions, however accurate, to actionable clinical interventions is a separate challenge that the field has only begun to address.
A Framework for the Future
The Preview positions multimodal clocks not as a replacement for existing tools but as an integrative layer above them. The authors write that the combination of clinical, molecular, and organ-specific data into unified frameworks represents “the next frontier in biological age measurement”, one that could eventually allow clinicians to measure biological age across scales, identify which organ systems are aging fastest in a given individual, and target interventions accordingly.
Source: Koyuncu, S., Petrovic, D., & Vilchez, D. “Bridging omics and physiology to build multimodal clocks of human aging.” Cell 189(14), 4190-4192 (2026). DOI: 10.1016/j.cell.2026.06.018
Referenced research: Li, Jiang et al. “Multimodal clocks of human aging.” Cell (2026). DOI: 10.1016/j.cell.2026.04.025