Sleep Patterns Can Help Assess Stress


A new study suggests abnormal sleep architecture can be a predictor of stress.

Fragmented sleep patterns can help predict vulnerability to chronic stress, according to a study published in Frontiers in Neuroscience.

The study, conducted by New York University’s Abu Dhabi’s Laboratory of Neural Systems and Behavior, suggests that abnormal sleep architecture can be a predictor of stress. The findings can help to potentially inform the development of a sleep test to help identify those who may be susceptible or resilient to future stress.

According to the study, investigators used a mouse model in order to detect how disruptions in no-rapid eye movement (NREM) sleep results in increased vulnerability to future stress. The researchers analyzed sleep characteristics of both stress-susceptible and stress-resilient mice before and after they experienced chronic social defeat (CSD) stress. The social behavior of the mice post-stress was classified as either those susceptible to stress that displayed social avoidance and those that were resilient to stress.

The study found that pre-CSD mice susceptible to stress displayed increased fragmentation of NREM sleep than non-stress susceptible mice. This was due to increased switching between NREM and wake and shorter average duration of NREM bouts, according to the study. The pre-CSD sleep features from both phenotypes of mice was allowed for prediction of stress susceptibility with more than 80% accuracy.

"Our study is the first to provide an animal model to investigate the relationship between poor sleep continuity and vulnerability to chronic stress and depressive disorders," the study authors wrote. "This marker of vulnerability to stress opens up avenues for many possible future studies that could further explain the underlying molecular processes and neural circuitry that lead to mood disorders."


NYUAD study finds fragmented sleep patterns can predict vulnerability to chronic stress [News Release] January 12, 2021; New York City, New York. Accessed January 12, 2021.

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