Microstructural and Biomechanical Determinants of Biological Aging

Area of Science:

• Cardiovascular Research
• Aging Biology
• Biomedical Engineering

Background:

• Pulmonary artery aging involves structural and mechanical changes.
• Quantitative models for predicting normative aging are lacking.
• Vascular and lung aging are mechanistically linked.

Purpose of the Study:

• To develop a multimodal model for predicting biological age using pulmonary artery aging signatures.
• To integrate structural (collagen fiber orientation, straightness) and mechanical (pulse wave velocity) parameters.
• To investigate sex dimorphism in vascular aging prediction.

Main Methods:

• Utilized two-photon imaging and mechanical measurements in C57BL6 mice (6-24 months).
• Developed a support vector regression (SVR) model incorporating collagen fiber orientation (von Mises distribution) and straightness.
• Integrated vascular mechanical parameters, including pulse wave velocity (PWV).
• Assessed lung mechanics for independent predictive contributions.

Main Results:

• Microstructure-only model achieved R² = 0.596, MAE = 3.43 months.
• Combined model (microstructure + PWV) improved prediction to R² = 0.834, MAE = 2.26 months (40.1% enhancement).
• Females showed stronger predictive signal (R² = 0.960) compared to males (R² = 0.658) based on collagen.
• Lung mechanics did not add significant independent predictive value beyond vascular data.

Conclusions:

• Established a multimodal framework for quantifying vascular biological age.
• Demonstrated the integration of structural and mechanical aging signatures for accurate age prediction.
• Highlighted significant sex dimorphism in the contribution of vascular microstructure to aging prediction.