Behavioral Blueprint of Aging Revealed in African Turquoise Killifish

A new study has revealed a behavioral blueprint of aging in African turquoise killifish, enabling the prediction of a fish's age and lifespan based on early-life behavioral patterns. Vertebrate aging is a complex process influenced by numerous factors, and behavior offers insights into an animal's internal state, reflecting aging across various species.

Developing the Behavioral Tracking Platform

Researchers Claire Bedbrook and colleagues developed a high-resolution platform for continuous behavioral recording. This sophisticated system monitored the naturally short-lived killifish, which have a lifespan of a few months, from adolescence (3-4 weeks old) until death.

Using machine learning and computer vision, the platform mapped behavioral changes throughout adulthood. This comprehensive analysis determined if these patterns predict aging and lifespan, and identified distinct adult life stages.

Early Behavioral Patterns Signal Lifespan Differences

The study found that individual killifish follow distinct aging trajectories, with differences in behavior observed early in life between long-lived and short-lived individuals.

These early-life distinctions provide crucial insights into an animal's future longevity. Specifically, the researchers observed clear contrasts:

• Long-lived fish exhibited higher activity levels, faster movement, and more vigorous bursts of movement compared to those with shorter lifespans.
• Long-lived individuals largely confined their sleep to nighttime.
• Short-lived fish displayed increased daytime sleep and more disrupted activity patterns.

A "Behavioral Clock" for Age and Lifespan Prediction

By applying a machine learning model to these extensive behavioral measurements, termed a "behaviorome," the researchers successfully created a "behavioral clock." This innovative clock could estimate a fish's age using only its daily movement and activity patterns.

The model also demonstrated that, from early adulthood, these behavioral patterns could reliably forecast whether a fish would have a relatively short or long lifespan.