Sleep Fragmentation as a Diagnostic Biomarker of Traumatic Brain Injury

Area of Science:

• Neuroscience
• Biomarkers
• Sleep Medicine

Background:

• Sleep disturbances are common and persistent after traumatic brain injury (TBI).
• Current biomarkers for TBI primarily assess structural damage, offering limited functional insight.
• Sleep disturbances are underutilized as clinical indicators of TBI status.

Purpose of the Study:

• To propose sleep fragmentation as a functional, scalable, and underrecognized diagnostic biomarker for TBI.
• To investigate the utility of sleep metrics in distinguishing TBI from control subjects.
• To highlight the potential of non-invasive sleep measures for TBI assessment and monitoring.

Main Methods:

• Utilized a mouse model of diffuse TBI.
• Applied dimensionality reduction and machine learning techniques to sleep data.
• Collected sleep metrics, including sleep-wake transitions and duration, over 48 hours post-injury using actigraphy.

Main Results:

• Summary measures of sleep fragmentation and duration reliably distinguished injured from uninjured animals.
• The number of sleep-wake transitions within 48 hours post-TBI demonstrated a strong diagnostic signal.
• Sleep-based metrics reflect neural network integrity and ongoing physiological disruption.

Conclusions:

• Sleep fragmentation is a promising non-invasive diagnostic biomarker for TBI.
• Sleep metrics offer a behaviorally grounded complement to traditional biomarkers, aligning with precision medicine.
• Further validation could enable sleep metrics for monitoring recovery and stratifying TBI severity.