Speech clocks decode dementia phenotypes, social exposome, and biological aging.

Speech-based age gaps (SAGs) effectively distinguish dementia types and correlate with biological aging markers across diverse Latin American populations.

• Why it matters: Current biological aging clocks lack scalability and cultural adaptability, limiting their use in global, underrepresented communities. Understanding accessible biomarkers is crucial for early diagnosis and intervention.
• What they did: Researchers developed a large-scale speech clock from 2,928 individuals, using acoustic and linguistic features to estimate age and generate SAGs, which were analyzed across diagnostic groups and biological markers.
• The result: SAGs differentiated healthy controls from dementia patients, correlated with tau proteins, social exposome, and brain aging measures, suggesting SAGs as a scalable, low-cost biomarker for aging and dementia research worldwide.