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Principal component-based clinical aging clocks identify signatures of healthy aging and targets for clinical intervention
A clinical aging clock (PCAge) was developed using Principal Component Analysis (PCA) on clinical data to identify signatures separating healthy and unhealthy aging trajectories. Key findings include:
- Signatures of metabolic dysregulation, cardiac and renal dysfunction, and inflammation predict unsuccessful aging.
- These processes can be impacted using well-established drug interventions.
- A streamlined clock, LinAge, derived from PCAge, maintains equivalent predictive power with substantially fewer features.