Mesenchymal drift may explain how aging cells lose their identity

Study: Mesenchymal drift: A convergent framework for the hallmarks of aging.  AI-generated biomedical illustration showing a transition from organized healthy tissue to fibrotic, inflamed tissue, representing mesenchymal drift during aging. Image Credit: ChatGPT / OpenAI.

A recent review published in the journal Cell proposed mesenchymal drift (MD) as a convergent framework for the hallmarks of aging.

Aging biology has commonly been framed in terms of canonical hallmarks. However, translating the hallmarks of aging into clinical geromedicine is challenging. The hallmarks may not capture the higher-order processes linking cellular dysfunction to organismal- and tissue-level aging. MD is a process of progressive cell-state erosion, in which cells lose aspects of their original lineage identity and acquire or intensify mesenchymal characteristics.

While this adaptability is crucial during embryogenesis or tissue repair, dysregulated or chronic activation has been implicated in aging. Given its capacity to coordinate tissue- and cellular-level processes and its pervasive activation in aged tissues, MD may serve as an organizing principle linking the hallmarks of aging. Importantly, MD is described as a spectrum of partial or hybrid cell states, rather than an all-or-none conversion into mesenchymal cells. In this review, researchers examined evidence linking MD to the hallmarks of aging, proposing MD as a complementary, convergent framework that incorporates them.

MD and the hallmarks of aging are connected

The hallmarks are a widely accepted framework for organizing the systemic, cellular, and molecular processes that contribute to age-related functional decline. A process must fulfill three criteria to qualify as a hallmark: it must manifest during normal aging, accelerate aging when experimentally exacerbated, and reverse or delay aging upon therapeutic modulation. There are three categories of hallmarks: primary, antagonistic, and integrative.

Primary hallmarks, e.g., telomere attrition, genomic instability, induce molecular damage, initiating aging. Antagonistic hallmarks, e.g., cellular senescence, mitochondrial dysfunction, emerge as adaptive responses to curb damage that become detrimental with chronic activation. Integrative hallmarks, e.g., dysbiosis and chronic inflammation, reflect the consequences of damage and maladaptive responses, culminating in tissue dysfunction.

Genomic instability results from endogenous processes, such as replication errors and oxidative damage, as well as exogenous biological, physical, and chemical insults. A growing body of evidence suggests that genomic instability is both a driver and a consequence of MD. Genotoxic stressors, e.g., chemotherapy and irradiation, induce DNA lesions that activate DNA damage response pathways, triggering MD. On the other hand, factors responsible for genomic maintenance are barriers to MD.

Moreover, MD and genomic instability form a self-reinforcing loop, which, in aging tissues, expedites functional decline and fibrotic remodeling. Mitochondrial dysfunction induces MD processes. Excess mitochondrial reactive oxygen species (ROS) activate transcription factors of the epithelial-to-mesenchymal transition (EMT) as well as transforming growth factor (TGF)-β, promoting fibroblast activation and fibrosis.

Mitophagy removes damaged mitochondria. Age-related impairment of mitophagy sustains pro-fibrotic signaling and EMT, whereas its restoration mitigates fibrosis and endothelial-to-mesenchymal transition (EndoMT). Meanwhile, MD reciprocally shapes mitochondrial function and structure. TGF-β triggers mitochondrial DNA damage and a decrease in respiration during myofibroblast activation, stimulating mitochondrial ROS in epithelial cells.

Chronic inflammation remodels tissue microenvironments, promoting progressive dysfunction. MD and inflammation form a bidirectional loop. Inflammatory cytokines induce MD: interleukin (IL)-1β, tumor necrosis factor (TNF)-α, and IL-6 enhance the expression of EMT transcription factors in fibroblast, epithelial, and endothelial populations. In turn, cells undergoing MD secrete cytokines, matrix metalloproteinases, and chemokines, maintaining systemic and local inflammation.

Therapeutic implications

The recognition of MD as a systems-level integrator of aging creates new therapeutic and diagnostic opportunities. Quantification of MD across tissues could enable early detection of maladaptive cellular states, refine stratification of disease risk, and provide biomarkers for monitoring therapeutic response. MD manifests in both the circulation and tissues, offering opportunities to develop biomarkers.

Chemical reprogramming or the induction of Yamanaka factors initiates mesenchymal-to-epithelial transition (MET). During early reprogramming, the suppression of mesenchymal and somatic genes precedes epithelial activation, which creates a brief window to remodel the epigenetic landscape of aged cells without losing cellular identity. This principle, partial reprogramming, conceptually represents the inverse of EMT, counteracts MD, and erases epigenetic age signatures.

Partial reprogramming-induced reset of the aging epigenome and transcriptome can restore cellular functions compromised with age. In mouse models of premature aging, partial reprogramming improves DNA repair capacity. In physiological aging, short-term reprogramming enhances DNA repair pathways. Partial reprogramming also restores the regenerative capacity of several organs, including the liver, heart, retina, brain, and skeletal muscle.

Gene therapy-based reprogramming has been shown to extend lifespan and reverse aging phenotypes in aged mice. Chemical reprogramming approaches similarly reset somatic cell identity toward pluripotency. Moreover, customized regimens induce rejuvenation phenotypes and reverse EMT programs without losing cellular identity. Overall, partial reprogramming can counteract MD and reset several hallmarks of aging. However, the authors caution that these approaches remain largely preclinical and require careful control because of risks such as tumorigenesis, excessive dedifferentiation, tissue-specific effects, and failure to preserve cellular identity.

Concluding remarks

Collectively, MD represents a mechanistic trajectory wherein multiple hallmarks of aging converge. As such, viewing aging through the lens of MD reframes it into a definable process of destabilization of cellular identity across tissues. This perspective also carries significant therapeutic implications. Given that MD integrates cues from metabolic stress, tissue injury, and inflammation, modulating it could simultaneously influence various hallmarks of aging. Further experimental and longitudinal studies are needed to define MD’s hierarchical role in aging biology and determine how safely it can be targeted.

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