Interaction of obesity and proteins associated with the NLRP3 inflammasome following mild traumatic brain injury.

The NOD-like receptor pyrin domain-containing protein 3 (NLRP3) inflammasome has been associated with worse outcomes from severe traumatic brain injury (TBI). The NLRP3 inflammasome is also strongly associated with other pro-inflammatory conditions, such as obesity. Little is known about the potential effect of mild TBI (mTBI) on the NLRP3 inflammasome and the extent to which modifying factors, such as obesity, may augment the inflammatory response to mTBI. The purpose of this study was to evaluate the association of NLRP3 inflammasome proteins with obese body mass index (BMI ≥ 30) within 24 h of mTBI after presenting to a level 1 trauma center emergency department. This is a secondary analysis of prospectively enrolled patients with mTBI who presented to the emergency department of one U.S. Level 1 trauma center from 2013 to 2018 (n = 243). A series of regression models were built to evaluate the association of NLRP3 proteins obtained from blood plasma within 24 h of injury and BMI as well as the potential interaction effect of higher BMI with NLRP3 proteins (n = 243). A logistic regression model revealed a significant association between IL-18 (p < 0.001) in mTBI patients with obese BMI compared to mTBI patients with non-obese BMI (< 30). Moderation analyses revealed statistically significant interaction effects between apoptotic speck-like protein (ASC), caspase-1, IL-18, IL-1ß and obese BMI which worsened symptom burden, quality of life, and physical function at 2 weeks and 6 months post-injury. Higher acute concentrations of IL-1ß in the overall cohort predicted higher symptoms at 6-months and worse physical function at 2-weeks and 6-months. Higher acute concentrations of IL-18 in the overall cohort predicted worse physical function at 6-months. In this single center mTBI cohort, obese BMI interacted with higher acute concentrations of NLRP3 inflammasome proteins and worsened short- and long-term clinical outcomes.

Evaluating Targeted Therapeutic Response With Predictive Blood-Based Biomarkers in Patients With Chronic Mild Traumatic Brain Injury.

Chronic consequences of mild traumatic brain injury (mTBI) are heterogeneous, but may be treatable with targeted medical and rehabilitation interventions. A biological signature for the likelihood of response to therapy (i.e., "predictive" biomarkers) would empower personalized medicine post-mTBI. The purpose of this study was to correlate pre-intervention blood biomarker levels and the likelihood of response to targeted interventions for patients with chronic issues attributable to mTBI. Patients with chronic symptoms and/or disorders secondary to mTBI >3 months previous (104 days to 15 years; n = 74) were enrolled. Participants completed pre-intervention assessments of symptom burden, comprehensive clinical evaluation, and blood-based biomarker measurements. Multi-domain targeted interventions for specific symptoms and impairments across a 6-month treatment period were prescribed. Participants completed a follow-up testing after the treatment period. An all-possible model's backward logistic regression was built to identify predictors of improvement in relation to blood biomarker levels before intervention. The minimum clinically important difference (MCID) of the change score (post-intervention subtracted from pre-intervention) for the Post-Concussion Symptom Scale (PCSS) to identify treatment responders from non-responders was the primary outcome. The MCID for total PCSS score was 10. The model to predict change in PCSS score over the 6-month intervention was significant (R2 = 0.09; p = 0.01) and identified ubiquitin C-terminal hydrolase L1 (odds ratio [OR] = 2.53; 95% confidence interval [CI], 1.18-5.46; p = 0.02) and hyperphosphorylated tau (p-tau; OR = 0.70; 95% CI, 0.51-0.96; p = 0.03) as significant predictors of symptom improvement beyond the PCSS MCID. In this cohort of chronic TBI subjects, blood biomarkers before rehabilitation intervention predicted the likelihood of response to targeted therapy for chronic disorders post-TBI.

Association of Plasma Biomarkers with Sleep Outcomes and Treatment Response After Mild Traumatic Brain Injury.

Sleep disturbances occur in up to 70% of patients with mild traumatic brain injury (mTBI). Modern mTBI management recommends targeted treatment for the patient's unique clinical manifestations (i.e., obstructive sleep apnea, insomnia). The purpose of this study was to evaluate the association of plasma biomarkers with symptom reports, overnight sleep evaluations, and response to treatment for sleep disturbances secondary to mTBI. This study is a secondary analysis of a prospective multiple interventional trial of patients with chronic issues related to mTBI. Pre- and post-intervention assessments were conducted, including overnight sleep apnea evaluation, the Pittsburgh Sleep Quality Index (PSQI), and blinded analysis of blood biomarkers. Bivariate Spearman correlations were conducted for pre-intervention plasma biomarker concentrations and 1) PSQI change scores and 2) pre-intervention sleep apnea outcomes (i.e., oxygen saturation measures). A backward logistic regression model was built to evaluate the association of pre-intervention plasma biomarkers with improvement in PSQI over the treatment period (p < 0.05). Participants were 36.3 ± 8.6 years old and 6.1 ± 3.8 years from their index mTBI. Participants reported subjective improvements (PSQI = -3.7 ± 3.8), whereas 39.3% (n = 11) had improved PSQI scores beyond the minimum clinically important difference (MCID). PSQI change scores correlated with von Willebrand factor (vWF; ρ = -0.50; p = 0.02) and tau (ρ = -0.53; p = 0.01). Hyperphosphorylated tau correlated with average saturation (ρ = -0.29; p = 0.03), lowest desaturation (ρ = -0.27; p = 0.048), and baseline saturation (ρ = -0.31; p = 0.02). The multi-variate model (R 2 = 0.33; p = 0.001) retained only pre-intervention vWF as a predictor (odds ratio = 3.41; 95% confidence interval, 1.44-8.08; p = 0.005) of improving PSQI scores beyond the MCID. vWF had good discrimination (area under the curve = 0.83; p = 0.01), with an overall accuracy of 77%, sensitivity of 46.2%, and specificity of 90.0%. Validation of vWF as a potential predictive biomarker of sleep improvement post-mTBI could optimize personalized management and healthcare utilization.