In a groundbreaking stride towards unraveling the molecular underpinnings of ageing and longevity, researchers have unveiled a comprehensive gene co-expression network that distills the transcriptomic landscape governing mammalian ageing. By leveraging a sophisticated analytical approach, weighted gene co-expression network analysis (WGCNA), the team dissected a vast meta-dataset encompassing diverse rodent tissues, sexes, and experimental conditions. This enabled the identification of 28 robust gene modules, each revealing a tapestry of coordinated genetic expression intricately linked to the ageing process and lifespan modulation.
At the core of this investigation lies the quest to decipher fundamental molecular hallmarks that not only chronicle chronological aging but also prognosticate biological longevity. The modules, consisting of 30 to over 600 co-regulated genes, encapsulate pivotal biological pathways. Significantly, modules enriched with genes implicated in inflammatory responses, mitochondrial function, and extracellular matrix (ECM) remodeling emerged as critical nodes, underscoring their centrality in age-associated physiological transformations.
The analytical rigor was enhanced by independently validating module derivation in both male and female rodents, revealing substantial overlap and thus confirming robustness across sexes. This sexual parity is crucial as it enables the generalization of the findings and paves the way for interventions applicable regardless of sex-specific gene expression nuances. Subsequent filtering affirmed that the modules occupied distinct functional niches with minimal overlap—a testament to the biological coherence of the network architecture.
Delving deeper, the researchers scrutinized the interplay between these modules by examining partial correlations adjusted for chronological age. This revealed functional clustering where immune-related gene modules, encompassing inflammatory and interferon signaling pathways, were segregated distinctly from metabolism-centric modules, including those involved in oxidative phosphorylation and lipid metabolism. Intriguingly, immune modules exhibited positive correlations with advancing age and higher mortality risk, while metabolic modules showcased an inverse relationship, suggesting their protective or resilience-conferring roles.
However, not all modules adhered strictly to this dichotomy; certain pathways related to heat stress response, translational control, and ECM remodeling exhibited co-directional associations with both age and lifespan metrics. This duality implies adaptive or compensatory molecular strategies that potentially mitigate age-related decline. Notably, modules governing protein folding within the endoplasmic reticulum and mechanistic target of rapamycin (mTOR) signaling were associated predominantly with longevity but did not correlate with chronological age, hinting at distinct pathways modulating lifespan independent of conventional aging trajectories.
In a bid to translate these molecular insights into practical biomarkers, the team engineered a suite of multi-tissue transcriptomic clocks anchored to each gene module. These clocks employed elastic net regression to predict chronological age and expected mortality with varying degrees of precision. Remarkably, a composite model amalgamating all module genes rivaled the predictive power of full-transcriptome models, reinforcing the centrality of these modular networks in capturing the essence of molecular ageing.
Individual module clocks displayed moderate predictive accuracies, with median correlation coefficients around 0.41 to 0.44 for their respective targets. By excluding underperforming module clocks, the researchers distilled a robust catalog of 23 functionally annotated clocks. Intriguingly, mortality clocks universally exhibited positive correlations with chronological age and inverse correlations with expected maximum lifespan, consolidating their utility as integrative indicators of biological age and anticipated lifespan.
The translational relevance of these clocks was underscored through validation in in vivo models of acute inflammatory stress. In an experiment involving lipopolysaccharide (LPS) administration to young adult mice, module-specific clocks detected significant transcriptomic age acceleration across immune-related pathways within the brain. This observation aligns with known LPS-induced neuroinflammatory responses, underscoring the sensitivity of these clocks to pathogenic insults that exacerbate biological ageing.
Conversely, the researchers explored the inverse scenario by assessing the impact of caloric restriction—an intervention long acclaimed for its lifespan-extending effects—on the molecular clocks within hepatic tissues. Here, many mortality-linked module clocks detected a reduction in transcriptomic age relative to controls. The most pronounced anti-ageing effects were evident in modules governing oxidative metabolism, lipid handling, and mTOR signaling. These findings coherently reflect the metabolic reprogramming and enhanced bioenergetic efficiency induced by caloric restriction.
Collectively, these results illuminate the multifaceted and pathway-specific modulation of molecular age. By leveraging modular transcriptomic clocks, the study provides a nuanced framework to quantify how distinct biological pathways respond to detrimental insults or health-promoting interventions. The integration of these clocks into ageing research heralds a new era of pathway-informed biomarkers, offering precision tools for evaluating experimental therapeutics and lifestyle modifications aimed at extending healthspan.
Further reinforcing the approach’s robustness, the study assessed transcriptomic age and mortality signatures in genetic models of accelerated ageing. Klotho knockout mice, recognized for their precipitous functional decline, displayed elevated transcriptomic age across multiple tissues as predicted by module-specific mortality clocks. Detailed gene-level analyses pinpointed top contributors driving these pro-mortality changes, unveiling candidate molecular targets linked to pathological ageing phenotypes.
Spatially resolved single-cell analyses using dimensionality reduction techniques further elucidated cellular and tissue-specific ageing dynamics in Klotho knockout models. This high-resolution view revealed pronounced mortality tAge elevations within specific cell populations in kidney and brain tissues, cementing the utility of module-guided transcriptomic clocks in capturing complex, heterogenous ageing signatures across biological hierarchies.
The comprehensive identification and validation of co-regulated gene modules constitute a pivotal advance in the field of ageing biology. By distilling the transcriptomic complexity of ageing into modular components with defined biological functions, this framework enables mechanistic dissection and precise quantification of ageing processes. These insights catalyze opportunities for therapeutic targeting and biomarker development, charting a path toward personalized interventions that modulate molecular ageing trajectories.
This landmark study underscores that molecular age is not a monolithic entity but a composite reflection of diverse, interacting biological pathways. The modular clocks offer a lens to scrutinize the nuanced balance between detrimental and adaptive responses that collectively shape longevity outcomes. Moving forward, incorporation of these transcriptomic modules into longitudinal studies and clinical trials could revolutionize ageing research and promote translational breakthroughs to enhance healthy lifespan in humans.
Beyond scientific insights, the study exemplifies the power of integrative, systems biology approaches in deciphering the intricate genetic networks underpinning complex phenotypes. The integration of multi-tissue, sex-inclusive datasets with advanced computational modeling affirms the importance of holistic perspectives in rendering high-fidelity biomarkers. This paradigm serves as a beacon for future efforts targeting the molecular basis of ageing and related diseases.
In sum, the delineation of universal transcriptomic hallmarks of mammalian ageing through co-regulated gene expression modules transforms our understanding of the molecular determinants of lifespan. The elucidation of pathway-specific molecular clocks provides a versatile toolkit to measure, monitor, and manipulate ageing biology with unprecedented granularity and accuracy. As aging research marches toward clinical translation, this work lays a robust foundation for the next generation of biomarker-driven interventions poised to improve healthspan and longevity.
Subject of Research: Gene co-expression networks and pathway-specific transcriptomic biomarkers of mammalian ageing and longevity.
Article Title: Universal transcriptomic hallmarks of mammalian ageing and mortality.
Article References:
Tyshkovskiy, A., Kholdina, D., Davitadze, M. et al. Universal transcriptomic hallmarks of mammalian ageing and mortality. Nature (2026). https://doi.org/10.1038/s41586-026-10542-3
Image Credits: AI Generated
DOI: https://doi.org/10.1038/s41586-026-10542-3
Tags: biological versus chronological ageing markersextracellular matrix remodeling in ageinggene expression patterns in mammalian ageinginflammatory response genes in ageinglongevity-associated genetic pathwaysmammalian ageing gene co-expression networkmitochondrial dysfunction and ageingmolecular hallmarks of longevityrodent ageing gene modulessex-independent ageing biomarkerstranscriptomic landscape of ageingweighted gene co-expression network analysis WGCNA
