Urine-Based microRNA Aging Clock Predicts Biological Age

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Urine microRNA Aging Clock Linked to Disease Risk

Key Takeaways (Quick Summary)

  • Researchers developed a urine-based microRNA aging clock using extracellular vesicle miRNAs
  • The test predicts chronological age with ~4.4–5.1 years of accuracy
  • Deviations indicate biological age acceleration, linked to chronic disease risk
  • Type 2 diabetes showed a significant association with accelerated aging
  • Offers a non-invasive alternative to blood-based aging biomarkers

A New Non-Invasive Way to Measure Aging Signals

Aging is the most substantial risk factor for chronic diseases, yet most biological age tests rely on blood or tissue samples. In an extensive population-based study published in npj Aging, researchers introduced a urinary microRNA aging clock that estimates age using molecular signals shed into urine, eliminating the need for blood collection.

This approach leverages extracellular vesicle microRNAs (uEV-miRNAs), which reflect age-related biological processes and can be measured at scale in real-world screening settings.

How the Urinary microRNA Aging Clock Works

The study analyzed urine samples from 6,331 adults undergoing cancer screening in Japan. After isolating extracellular vesicles, researchers sequenced small RNAs and identified 407 consistently expressed miRNAs suitable for modeling.

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Using a Light Gradient Boosting Machine (LightGBM) algorithm, the team trained and validated the aging clock across multiple datasets. The model predicted age with a mean absolute error of 4.4–5.1 years, matching or exceeding the accuracy of several blood-based miRNA clocks.

What is a urinary microRNA aging clock?

It is a machine-learning model that estimates biological aging by analyzing age-responsive microRNAs found in urine-derived extracellular vesicles.

Clinical Relevance for HCPs and Nurses

Several top-ranked miRNAs identified by the model were canonical geromiRs, including miR-146a-5p, miR-155-5p, and miR-34a-5p, which are linked to cellular senescence and inflammation. Gene ontology analysis highlighted pathways involved in bone remodelling, immune regulation, and aging biology.

Notably, individuals with type 2 diabetes showed higher biological age acceleration, particularly among middle-aged and older adults. While not diagnostic, ΔAge may help clinicians identify patients at higher risk for aging-related morbidity.

Can urine tests predict biological aging?

Yes, urinary miRNA profiles can estimate aging pace and reflect systemic health risks.

What This Means for Preventive Medicine

Although further validation is needed before routine clinical use, this study positions urinary miRNAs as scalable, non-invasive aging biomarkers. For preventive care, population health monitoring, and longitudinal research, urine-based aging clocks could support risk stratification without clinical burden.

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Source:

nature

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