Speech as a Scalable Aging Biomarker

Machine‑learning analysis of pauses, pitch, rate and lexical organization can estimate a person’s ‘speech‑age gap’ that correlates with epigenetic clocks, MRI markers and plasma p‑tau217. A short voice sample could therefore act as a low‑cost proxy for biological brain and systemic aging and cognitive decline risk across populations. — If validated longitudinally and across populations, voice‑based aging measures could reshape public‑health screening, clinical triage, insurance underwriting and privacy debates because voice is widely collectible and easily deployed.