A recent study from Stanford University reveals that daily behaviours like movement and sleep in midlife can forecast lifespan in vertebrates. Researchers tracked African turquoise killifish throughout their lives, finding early divergences in activity and rest patterns strongly predict longevity. The study was led by Wu Tsai Neuro postdoctoral scholars Claire Bedbrook and Ravi Nath and published in Science. The study was a collaboration supported by the Knight Initiative between the Stanford labs of geneticist Anne Brunet and bioengineer Karl Deisseroth, the study’s senior authors. While the fish shared similar genetics and lived in the same controlled conditions, they aged in very different ways.
These differences were visible in how they swam and rested by early adulthood. These patterns helped predict whether a fish would ultimately have a shorter or longer lifespan. While the study focused on fish, the researchers say that if daily behaviours such as movement and sleep are tracked, it can highlight how ageing progresses in humans. Brunet, the Michele and Timothy Barakett Professor of Genetics at Stanford Medicine said, “Behavior is a wonderfully integrated readout, reflecting what’s happening across the brain and body. Molecular markers are essential, but they capture only slices of biology. With behavior, you see the whole organism, continuously and non-invasively.”
Study Overview
The research monitored 81 killifish from early adulthood to death using automated camera systems. These short-lived fish, with lifespans of 4-8 months, share brain complexity with humans, making them ideal for ageing studies.
Killifish raised in identical conditions still showed unique ageing paths. By midlife (around 70-100 days), long-lived fish swam faster, stayed more active during daylight, and slept mostly at night, while short-lived ones napped during the daytime and moved sluggishly.
Machine learning models used just days of midlife behavioral data to predict lifespan accurately. This noninvasive approach highlights behavior as a holistic indicator of brain-body health.
Behavioural Predictors
Long-lived killifish exhibited vigorous, spontaneous swimming and strict nighttime sleep. Short-lived ones had fragmented sleep across day and night early on, mirroring human sleep disruptions linked to faster ageing.
Researchers identified 100 ‘behavioral syllables’; basic movement units like posture shifts and speeds. Long-lived fish used higher-speed syllables more, tying activity to extended life across species. Daytime activity and circadian sleep aligned with longevity, consistent with studies in flies and mice. These patterns emerged despite genetic uniformity, suggesting lifestyle influences ageing trajectories.
Staged Nature of Ageing
Ageing unfolded not gradually but in 2-6 abrupt stages per fish, each a few days long, followed by stable weeks. Fish progressed through these behavioural phases, like climbing stable plateaus interrupted by quick drops.
This ‘Jenga-like’ model challenges smooth decline views, aligning with human molecular waves in midlife. Transcriptomics at predictive midlife showed liver genes for protein maintenance hyperactive in short-lived fish. Behavioural stages offered stability amid variability. Long-lived fish delayed transitions, implying interventions could extend stable periods.
“We expected ageing to be a slow, gradual process,” said Bedbrook. “Instead, animals stay stable for long periods and then transition very quickly into a new stage. Seeing this staged architecture appear from continuous behavior alone was one of the most exciting discoveries.”
Method Of The Study
The team built an automated system for lifelong video tracking, analysing billions of frames for posture, speed, and rest. This first continuous vertebrate screen captured natural behaviors without disturbance. The study used the killifish model. Multiorgan gene analysis complemented behaviour, highlighting metabolic shifts without inflammation hallmarks.
Relevance For Humans
Wearables now track human movement and sleep like the fish system, potentially spotting early signs of ageing. Midlife patterns could flag risks for cognitive decline or disease, enabling preventive steps.
Sleep quality drops with age in humans, linking to neurodegeneration. Fish daytime napping parallels this. Boosting activity and circadian rhythm might mimic long-lived fish benefits.
Bedbrook said, “With the rise of wearables and long-term tracking in humans, I’m excited to see whether the same principles — early predictors, staged ageing, divergent trajectories — hold true in people.”
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