020 Sleep Quality Affects the Plasma Exosomal MicroRNA Expression Profile in Military Personnel with Traumatic Brain Injury
Bibliographic record
Abstract
Abstract Introduction Disordered sleep is a critical issue facing the US military due to its negative impact on maintaining force readiness, health, and well-being. Traumatic brain injury (TBI) is highly prevalent among military personnel and commonly co-occurs with disturbed sleep: up to 89% of military service members with TBI report poor sleep quality. Disturbed sleep is a hallmark of post-traumatic stress disorder (PTSD), which often coexists with TBI, with upward of 90% of patients with PTSD reporting some form of sleep disturbance. The pathophysiological mechanisms underlying sleep disturbances in TBI patients remain elusive. Exosomal microRNA (exomiRs), which are implicated in intracellular communication, may provide novel insight into molecular networks related to sleep disturbances in TBI patients. Methods ExomiR was extracted from plasma samples of 108 post-9/11 military personnel, and veterans with a history of mild TBI enrolled in a multicenter prospective longitudinal study. ExomiR profiling analysis was conducted using nCounter Human v3 miRNA Expression Panel with 798 microRNA probes. Sleep quality was assessed using the global score on the Pittsburgh Sleep Quality Index (PSQI), and symptoms of PTSD were measured with the PTSD Checklist for DSM-5 (PCL-5). Generalized linear models and Spearman’s correlations were constructed to analyze the relationship between levels of exomiR and global PSQI score. Results We found 17 exomiR that were significantly (P < 0.05) associated with sleep quality and 11 exomiR significantly associated with PTSD symptoms. Two exomiR, has-miR-1268a and has-miR-139-5p, were significantly associated with both sleep quality and PTSD symptoms. The top three significant exomiR associated with sleep quality were hsa-miR-1250-5p (r = 0.2295, p = 0.0171), hsa-miR-3615(r = 0.2207, p = 0.0229), and hsa-miR-122-5p(r = 0.2069, p = 0.0132). Conclusion Overall, these findings suggest that analysis of exosomal miRNA expression may provide novel insights into the underlying pathobiology of sleep quality in military personnel with mild TBI, independent of PTSD symptoms. Further research is needed to understand the biological underpinnings of poor sleep quality in individuals with TBI and to determine causal links. Support (if any) Intramural Research Program at the NINR, Department of Defense, Chronic Effects of Neurotrauma Consortium (CENC) Award W81XWH-13-2-0095 and Department of Veterans Affairs CENC Award I01 CX001135.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".