Toward a Context-Aware Geroscience: Integrating Structural and Social Context into Aging Biology

Area of Science:

• Geroscience
• Social Epidemiology
• Biomarker Development

Background:

• Biological aging hallmarks are targets, but social exposures create uneven distribution.
• Chronic stress, environment, and resource access shape inflammatory, metabolic, and epigenetic pathways, causing aging heterogeneity.
• Geroscience models often overlook social context, leading to biased interpretations of biological variation.

Purpose of the Study:

• To identify and address biases in geroscience research stemming from socially patterned exposures.
• To propose a framework for integrating multilevel influences on biological aging.
• To improve inference, measurement validity, and equitable translation of geroscience interventions.

Main Methods:

• Distinguishing three forms of bias: mechanistic misattribution, biased biomarker construction, and inequitable intervention translation.
• Analyzing how exposure-patterned biological variation can be embedded in aging measurement and interpretation.
• Proposing a multilevel, life-course framework considering structural, environmental, and behavioral determinants.

Main Results:

• Socially patterned exposures systematically influence biological aging pathways, leading to heterogeneity.
• Context-neutral geroscience models can introduce bias by ignoring social determinants.
• Similar biological aging markers can arise from diverse exposure histories and mechanisms.

Conclusions:

• A multilevel, life-course framework is needed to model social, environmental, and behavioral influences on aging.
• Integrating these factors will improve the accuracy of biological aging inference.
• This approach is crucial for valid biomarker development and equitable translation of geroscience interventions across diverse populations.