Reducing acetylated tau is neuroprotective in brain injury.

Traumatic brain injury (TBI) is the largest non-genetic, non-aging related risk factor for Alzheimer's disease (AD). We report here that TBI induces tau acetylation (ac-tau) at sites acetylated also in human AD brain. This is mediated by S-nitrosylated-GAPDH, which simultaneously inactivates Sirtuin1 deacetylase and activates p300/CBP acetyltransferase, increasing neuronal ac-tau. Subsequent tau mislocalization causes neurodegeneration and neurobehavioral impairment, and ac-tau accumulates in the blood. Blocking GAPDH S-nitrosylation, inhibiting p300/CBP, or stimulating Sirtuin1 all protect mice from neurodegeneration, neurobehavioral impairment, and blood and brain accumulation of ac-tau after TBI. Ac-tau is thus a therapeutic target and potential blood biomarker of TBI that may represent pathologic convergence between TBI and AD. Increased ac-tau in human AD brain is further augmented in AD patients with history of TBI, and patients receiving the p300/CBP inhibitors salsalate or diflunisal exhibit decreased incidence of AD and clinically diagnosed TBI.

Leucine-Rich Alpha-2-Glycoprotein 1 is a Systemic Biomarker of Early Brain Injury and Delayed Cerebral Ischemia After Subarachnoid Hemorrhage.

BACKGROUND: After subarachnoid hemorrhage (SAH), early brain injury (EBI) and delayed cerebral ischemia (DCI) lead to poor outcomes. Discovery of biomarkers indicative of disease severity and predictive of DCI is important. We tested whether leucine-rich alpha-2-glycoprotein 1 (LRG1) is a marker of severity, DCI, and functional outcomes after SAH. METHODS: We performed untargeted proteomics using mass spectrometry in plasma samples collected at < 48 h of SAH in two independent discovery cohorts (n = 27 and n = 45) and identified LRG1 as a biomarker for DCI. To validate our findings, we used enzyme-linked immunosorbent assay and confirmed this finding in an internal validation cohort of plasma from 72 study participants with SAH (22 DCI and 50 non-DCI). Further, we investigated the relationship between LRG1 and markers of EBI, DCI, and poor functional outcomes (quantified by the modified Rankin Scale). We also measured cerebrospinal fluid (CSF) levels of LRG1 and investigated its relationship to EBI, DCI, and clinical outcomes. RESULTS: Untargeted proteomics revealed higher plasma LRG1 levels across EBI severity and DCI in both discovery cohorts. In the validation cohort, the levels of LRG1 were higher in the DCI group compared with the non-DCI group (mean (SD): 95 [44] vs. 72 [38] pg/ml, p < 0.05, Student's t-test) and in study participants who proceeded to have poor functional outcomes (84 [39.3] vs. 72 [43.2] pg/ml, p < 0.05). Elevated plasma LRG1 levels were also associated with markers of EBI. However, CSF levels of LRG1 were not associated with EBI severity or the occurrence of DCI. CONCLUSIONS: Plasma LRG1 is a biomarker for EBI, DCI, and functional outcomes after SAH. Further studies to elucidate the role of LRG1 in the pathophysiology of SAH are needed.

Systemic inflammatory markers of persistent cerebral edema after aneurysmal subarachnoid hemorrhage.

BACKGROUND: Cerebral edema (CE) at admission is a surrogate marker of 'early brain injury' (EBI) after subarachnoid hemorrhage (SAH). Only recently has the focus on the changes in CE after SAH such as delayed resolution or newly developed CE been examined. Among several factors, an early systemic inflammatory response has been shown to be associated with CE. We investigate inflammatory markers in subjects with early CE which does not resolve, i.e., persistent CE after SAH. METHODS: Computed tomography scans of SAH patients were graded at admission and at 7 days after SAH for CE using the 0-4 'subarachnoid hemorrhage early brain edema score' (SEBES). SEBES ≤ 2 and SEBES ≥ 3 were considered good and poor grade, respectively. Serum samples from the same subject cohort were collected at 4 time periods (at < 24 h [T1], at 24 to 48 h [T2]. 3-5 days [T3] and 6-8 days [T4] post-admission) and concentration levels of 17 cytokines (implicated in peripheral inflammatory processes) were measured by multiplex immunoassay. Multivariable logistic regression analyses were step-wisely performed to identify cytokines independently associated with persistent CE adjusting for covariables including age, sex and past medical history (model 1), and additional inclusion of clinical and radiographic severity of SAH and treatment modality (model 2). RESULTS: Of the 135 patients enrolled in the study, 21 of 135 subjects (15.6%) showed a persistently poor SEBES grade. In multivariate model 1, higher Eotaxin (at T1 and T4), sCD40L (at T4), IL-6 (at T1 and T3) and TNF-α (at T4) were independently associated with persistent CE. In multivariate model 2, Eotaxin (at T4: odds ratio [OR] = 1.019, 95% confidence interval [CI] = 1.002-1.035) and possibly PDGF-AA (at T4), sCD40L (at T4), and TNF-α (at T4) was associated with persistent CE. CONCLUSIONS: We identified serum cytokines at different time points that were independently associated with persistent CE. Specifically, persistent elevations of Eotaxin is associated with persistent CE after SAH.

The Spot Sign and Intraventricular Hemorrhage are Associated with Baseline Coagulopathy and Outcome in Intracerebral Hemorrhage.

BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) is the second most prevalent subtype of stroke and has high mortality and morbidity. The utility of radiographic features to predict secondary brain injury related to hematoma expansion (HE) or increased intracranial pressure has been highlighted in patients with ICH, including the computed tomographic angiography (CTA) spot sign and intraventricular hemorrhage (IVH). Understanding the pathophysiology of spot sign and IVH may help identify optimal therapeutic strategies. We examined factors related to the spot sign and IVH, including coagulation status, hematoma size, and location, and evaluated their prognostic value in patients with ICH. METHODS: Prospectively collected data from a single center between 2012 and 2015 were analyzed. Patients who underwent thromboelastography within 24 h of symptom onset and completed follow-up brain imaging and CTA within 48 h after onset were included for analysis. Multivariate logistic regression analyses were performed to identify determinants of the spot sign and IVH and their predictive value for HE, early neurological deterioration (END), in-hospital mortality, and functional outcome at discharge. RESULTS: Of 161 patients, 50 (31.1%) had a spot sign and 93 (57.8%) had IVH. In multivariable analysis, the spot sign was associated with greater hematoma volume (odds ratio [OR] 1.02; 95% confidence interval [CI] 1.00-1.03), decreased white blood cell count (OR 0.88; 95% CI 0.79-0.98), and prolonged activated partial thromboplastin time (OR 1.14; 95% CI 1.06-1.23). IVH was associated with greater hematoma volume (OR 1.02; 95% CI 1.01-1.04) and nonlobar location of hematoma (OR 0.23; 95% CI 0.09-0.61). The spot sign was associated with greater risk of all adverse outcomes. IVH was associated with an increased risk of END and reduced HE, without significant impact on mortality or functional outcome. CONCLUSIONS: The spot sign and IVH are associated with specific hematoma characteristics, such as size and location, but are related differently to coagulation status and clinical course. A combined analysis of the spot sign and IVH can improve the understanding of pathophysiology and risk stratification after ICH.

Early Systemic Glycolytic Shift After Aneurysmal Subarachnoid Hemorrhage is Associated with Functional Outcomes.

BACKGROUND: Aneurysmal subarachnoid hemorrhage (aSAH) leads to a robust systemic inflammatory response. We hypothesized that an early systemic glycolytic shift occurs after aSAH, resulting in a unique metabolic signature and affecting systemic inflammation. METHODS: Control patients and patients with aSAH were analyzed. Samples from patients with aSAH were collected within 24 h of aneurysmal rupture. Mass spectrometry-based metabolomics was performed to assess relative abundance of 16 metabolites involved in the tricarboxylic acid cycle, glycolysis, and pentose phosphate pathway. Principal component analysis was used to segregate control patients from patients with aSAH. Dendrograms were developed to depict correlations between metabolites and cytokines. Analytic models predicting functional outcomes were developed, and receiver operating curves were compared. RESULTS: A total of 122 patients with aSAH and 38 control patients were included. Patients with aSAH had higher levels of glycolytic metabolites (3-phosphoglycerate/2-phosphoglycerate, lactate) but lower levels of oxidative metabolites (succinate, malate, fumarate, and oxalate). Patients with higher clinical severity (Hunt-Hess Scale score ≥ 4) had higher levels of glyceraldehyde 3-phosphate and citrate but lower levels of α-ketoglutarate and glutamine. Principal component analysis readily segregated control patients from patients with aSAH. Correlation analysis revealed distinct clusters in control patients that were not observed in patients with aSAH. Higher levels of fumarate were associated with good functional outcomes at discharge (odds ratio [OR] 1.76, 95% confidence interval [CI] 1.15-2.82) in multivariable models, whereas higher levels of citrate were associated with poor functional outcomes at discharge (OR 0.36, 95% CI 0.16-0.73) and at 3 months (OR 0.35, 95% CI 0.14-0.81). No associations were found with delayed cerebral ischemia. Levels of α-ketoglutarate and glutamine correlated with lower levels of interleukin-8, whereas fumarate was associated with lower levels of tumor necrosis factor alpha. CONCLUSIONS: Aneurysmal subarachnoid hemorrhage results in a unique pattern of plasma metabolites, indicating a shift toward glycolysis. Higher levels of fumarate and lower levels of citrate were associated with better functional outcomes. These metabolites may represent targets to improve metabolism after aSAH.

Soluble Endoglin Stimulates Inflammatory and Angiogenic Responses in Microglia That Are Associated with Endothelial Dysfunction.

Increased soluble endoglin (sENG) has been observed in human brain arteriovenous malformations (bAVMs). In addition, the overexpression of sENG in concurrence with vascular endothelial growth factor (VEGF)-A has been shown to induce dysplastic vessel formation in mouse brains. However, the underlying mechanism of sENG-induced vascular malformations is not clear. The evidence suggests the role of sENG as a pro-inflammatory modulator, and increased microglial accumulation and inflammation have been observed in bAVMs. Therefore, we hypothesized that microglia mediate sENG-induced inflammation and endothelial cell (EC) dysfunction in bAVMs. In this study, we confirmed that the presence of sENG along with VEGF-A overexpression induced dysplastic vessel formation. Remarkably, we observed increased microglial activation around dysplastic vessels with the expression of NLRP3, an inflammasome marker. We found that sENG increased the gene expression of VEGF-A, pro-inflammatory cytokines/inflammasome mediators (TNF-α, IL-6, NLRP3, ASC, Caspase-1, and IL-1ß), and proteolytic enzyme (MMP-9) in BV2 microglia. The conditioned media from sENG-treated BV2 (BV2-sENG-CM) significantly increased levels of angiogenic factors (Notch-1 and TGFß) and pERK1/2 in ECs but it decreased the level of IL-17RD, an anti-angiogenic mediator. Finally, the BV2-sENG-CM significantly increased EC migration and tube formation. Together, our study demonstrates that sENG provokes microglia to express angiogenic/inflammatory molecules which may be involved in EC dysfunction. Our study corroborates the contribution of microglia to the pathology of sENG-associated vascular malformations.

Dynamic Detection of Delayed Cerebral Ischemia: A Study in 3 Centers.

BACKGROUND AND PURPOSE: Delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage negatively impacts long-term recovery but is often detected too late to prevent damage. We aim to develop hourly risk scores using routinely collected clinical data to detect DCI. METHODS: A DCI classification model was trained using vital sign measurements (heart rate, blood pressure, respiratory rate, and oxygen saturation) and demographics routinely collected for clinical care. Twenty-two time-varying physiological measures were computed including mean, SD, and cross-correlation of heart rate time series with each of the other vitals. Classification was achieved using an ensemble approach with L2-regularized logistic regression, random forest, and support vector machines models. Classifier performance was determined by area under the receiver operating characteristic curves and confusion matrices. Hourly DCI risk scores were generated as the posterior probability at time t using the Ensemble classifier on cohorts recruited at 2 external institutions (n=38 and 40). RESULTS: Three hundred ten patients were included in the training model (median, 54 years old [interquartile range, 45-65]; 80.2% women, 28.4% Hunt and Hess scale 4-5, 38.7% Modified Fisher Scale 3-4); 101 (33%) developed DCI with a median onset day 6 (interquartile range, 5-8). Classification accuracy before DCI onset was 0.83 (interquartile range, 0.76-0.83) area under the receiver operating characteristic curve. Risk scores applied to external institution datasets correctly predicted 64% and 91% of DCI events as early as 12 hours before clinical detection, with 2.7 and 1.6 true alerts for every false alert. CONCLUSIONS: An hourly risk score for DCI derived from routine vital signs may have the potential to alert clinicians to DCI, which could reduce neurological injury.

Brain injury, endothelial injury and inflammatory markers are elevated and express sex-specific alterations after COVID-19.

OBJECTIVE: Although COVID-19 is a respiratory disease, all organs can be affected including the brain. To date, specific investigations of brain injury markers (BIM) and endothelial injury markers (EIM) have been limited. Additionally, a male bias in disease severity and mortality after COVID-19 is evident globally. Sex differences in the immune response to COVID-19 may mediate this disparity. We investigated BIM, EIM and inflammatory cytokine/chemokine (CC) levels after COVID-19 and in across sexes. METHODS: Plasma samples from 57 subjects at < 48 h of COVID-19 hospitalization, and 20 matched controls were interrogated for the levels of six BIMs-including GFAP, S100B, Syndecan-1, UCHLI, MAP2 and NSE, two EIMs-including sICAM1 and sVCAM1. Additionally, several cytokines/chemokines were analyzed by multiplex. Statistical and bioinformatics methods were used to measure differences in the marker profiles across (a) COVID-19 vs. controls and (b) men vs. women. RESULTS: Three BIMs: MAP2, NSE and S100B, two EIMs: sICAM1 and sVCAM1 and seven CCs: GRO IL10, sCD40L, IP10, IL1Ra, MCP1 and TNFα were significantly (p < 0.05) elevated in the COVID-19 cohort compared to controls. Bioinformatics analysis reveal a stronger positive association between BIM/CC/EIMs in the COVID-19 cohort. Analysis across sex revealed that several BIMs and CCs including NSE, IL10, IL15 and IL8 were significantly (p < 0.05) higher in men compared to women. Men also expressed a more robust BIM/ EIM/CC association profile compared to women. CONCLUSION: The acute elevation of BIMs, CCs, and EIMs and the robust associations among them at COVID-19 hospitalization are suggestive of brain and endothelial injury. Higher BIM and inflammatory markers in men additionally suggest that men are more susceptible to the risk compared to women.

Inflammation in delayed ischemia and functional outcomes after subarachnoid hemorrhage.

BACKGROUND: Inflammatory mechanism has been implicated in delayed cerebral ischemia (DCI) and poor functional outcomes after subarachnoid hemorrhage (SAH). Identification of cytokine patterns associated with inflammation in acute SAH will provide insights into underlying biological processes of DCI and poor outcomes that may be amenable to interventions. METHODS: Serum samples were collected from a prospective cohort of 60 patients with acute non-traumatic SAH at four time periods (< 24 h, 24-48 h, 3-5 days, and 6-8 days after SAH) and concentration levels of 41 cytokines were measured by multiplex immunoassay. Logistic regression analysis was used to identify cytokines associated with DCI and poor functional outcomes. Correlation networks were constructed to identify cytokine clusters. RESULTS: Of the 60 patients enrolled in the study, 14 (23.3%) developed DCI and 16 (26.7%) had poor functional outcomes at 3 months. DCI was associated with increased levels of PDGF-ABBB and CCL5 and decreased levels of IP-10 and MIP-1α. Poor functional outcome was associated with increased levels of IL-6 and MCP-1α. Network analysis identified distinct cytokine clusters associated with DCI and functional outcomes. CONCLUSIONS: Serum cytokine patterns in early SAH are associated with poor functional outcomes and DCI. The significant cytokines primarily modulate the inflammatory response. This supports earlier SAH studies linking inflammation and poor outcomes. In particular, this study identifies novel cytokine patterns over time that may indicate impending DCI.

Disruption of thrombo-inflammatory response and activation of a distinct cytokine cluster after subarachnoid hemorrhage.

BACKGROUND: Unregulated inflammatory and thrombotic responses have been proposed to be important causes of early brain injury and worse clinical outcomes after subarachnoid hemorrhage (SAH). OBJECTIVE: We hypothesize that SAH is characterized by an increased inflammatory and thrombotic state and disruption of associations between these states. METHODS: This is a retrospective cohort study of 60 patients with SAH. 23 patients with unruptured aneurysms (UA) and 77 patients with traumatic brain injury (TBI) were chosen as controls. Plasma cytokine levels were measured using a 41-plex human immunoassay kit, and cytokine patterns associated with SAH, UA and TBI were identified using statistical and informatics methods. RESULTS: SAH was characterized by an increase in several cytokines and chemokines, platelet-derived factors, and growth factors. Cluster analysis identified several cytokine clusters common in SAH, UA and TBI groups - generally grouped as platelet-derived, vascular and pro-inflammatory clusters. In the UA group, the platelet-derived cluster had an inverse relationship with the inflammatory cluster which was absent in SAH. Additionally, a cluster comprising of growth and colony stimulating factors was unique to SAH. CONCLUSIONS: A cluster of cytokines involved in growth and colony stimulation was unique to SAH. Negative associations between the thrombotic and inflammatory molecules were observed in UA but not in SAH. Further studies to examine the pathophysiology behind the cluster unique to SAH and the associations between the thrombotic and inflammatory cytokines are required.

Early Brain Injury Associated with Systemic Inflammation After Subarachnoid Hemorrhage.

BACKGROUND: Early brain injury (EBI) after aneurysmal subarachnoid hemorrhage (aSAH) is defined as brain injury occurring within 72 h of aneurysmal rupture. Although EBI is the most significant predictor of outcomes after aSAH, its underlying pathophysiology is not well understood. We hypothesize that EBI after aSAH is associated with an increase in peripheral inflammation measured by cytokine expression levels and changes in associations between cytokines. METHODS: aSAH patients were enrolled into a prospective observational study and were assessed for markers of EBI: global cerebral edema (GCE), subarachnoid hemorrhage early brain edema score (SEBES), and Hunt-Hess grade. Serum samples collected at ≤ 48 h of admission were analyzed using multiplex bead-based assays to determine levels of 13 pro- and anti-inflammatory cytokines. Pairwise correlation coefficients between cytokines were represented as networks. Cytokine levels and differences in correlation networks were compared between EBI groups. RESULTS: Of the 71 patients enrolled in the study, 17 (24%) subjects had GCE, 31 (44%) subjects had SEBES ≥ 3, and 21 (29%) had HH ≥ 4. IL-6 was elevated in groups with GCE, SEBES ≥ 3, and HH ≥ 4. MIP1ß was independently associated with high-grade SEBES. Correlation network analysis suggests higher systematic inflammation in subjects with SEBES ≥ 3. CONCLUSIONS: EBI after SAH is associated with increased levels of specific cytokines. Peripheral levels of IL-10, IL-6, and MIP1ß may be important markers of EBI. Investigating systematic correlations in addition to expression levels of individual cytokines may offer deeper insight into the underlying mechanisms related to EBI.

Impact of practice change in reducing venous thromboembolism in neurocritical overweight patients: 2008-2014.

Publications regarding early initiating venous thromboembolism (VTE) prophylaxis have been available since the early 1990s. These recommendations became available in current guidelines on and after 2012. The purpose of this study is to review the practice change in reducing the incidence of VTE in brain injury patients from 2008 to 2014. This was a single-center, retrospective, observational, cohort study. Data was extracted from our data base that included patients over 100 kg from January 2008 to August 2014. Included were all patients admitted with a primary diagnosis of acute brain and spinal injury to neurocritical care unit. Clinical endpoints examined were incidence of bleeding and VTE. A total of 509 patients who met the inclusion criteria were divided into two groups: The previous group (n = 212) included patients from 2008 to 2010, and the recent group (n = 297) included patients from 2011 to 2014. The time for initiating VTE prophylaxis from admission was (median, IQR) 73 h (37-140) vs. 34 h (20-46); p < 0.01. There were no differences in major and minor bleeding complications. Discontinuation of VTE prophylaxis for association with progressive bleeding was not documented in any of the study patients. The incidence of VTE was 10 % (22/212) vs. 5 % (15/297); p = 0.02. In hospital LOS in days was 16 (10-26) vs. 7 (4-15); P < 0.01. In multivariable logistic regression analysis, only the time of the initiation VTE prophylaxis after admission was significantly associated with the occurrence of VTE (median, IQR) 70 h (37-158) vs. 36 h (20-63); OR 1.004, 95 % CI 1.001-1.007; P < 0.01. In this 6-year review of data, early initiation of VTE prophylaxis has decreased the incidence of VTE without clinically documented bleeding complications.

Quantification of Cerebral Edema After Subarachnoid Hemorrhage.

BACKGROUND: Global cerebral edema (GCE) is a manifestation of early brain injury (EBI) after subarachnoid hemorrhage (SAH) and is an independent risk factor for poor outcome. The lack of a quantitative method to measure GCE limits the study of its pathophysiology. The goal of this study is to develop a quantitative surrogate marker that represents GCE after SAH. METHODS: Patients with spontaneous SAH were enrolled into a prospective observational database. Initial CT scans were graded for GCE using established qualitative criteria. Selective sulcal volume (SSV) was defined as total mL of sulcal volumes on axial CT slices above the most cranial section of the lateral ventricles to the last visible section. Using a semiautomatic threshold approach, sulcal regions were traced out with manual adjustments when necessary. The volume of sulci in each slice was calculated and multiplied by the slice thickness and number of slices to calculate the SSV. All volumetric analysis was performed using Medical Image Processing, Analysis and Visualization Version 7.0.1 (MIPAV). RESULTS: A total of 109 subjects were included in our analysis. Mean selective sulcal volumes (SSV) differed between subjects with and without GCE 4.5 and 21.2 mL (P < 0.001). When separated into quartiles, the odds of qualitative GCE increases as SSV decreases. Compared to the highest SSV quartile, smaller SSV was associated with worse clinical outcomes. CONCLUSION: GCE can be quantified using volumetric analysis of SSV measurements on routine CT scans. Smaller SSV on admission is predictive of worse clinical outcomes. SSV may be an important marker of EBI after SAH.

Identification of metabolites associated with preserved muscle volume after aneurysmal subarachnoid hemorrhage due to high protein supplementation and neuromuscular electrical stimulation.

The INSPIRE randomized clinical trial demonstrated that a high protein diet (HPRO) combined with neuromuscular electrical stimulation (NMES) attenuates muscle atrophy and may improve outcomes after aneurysmal subarachnoid hemorrhage We sought to identify specific metabolites mediating these effects. Blood samples were collected from subjects on admission prior to randomization to either standard of care (SOC; N = 12) or HPRO + NMES (N = 12) and at 7 days. Untargeted metabolomics were performed for each plasma sample. Sparse partial least squared discriminant analysis identified metabolites differentiating each group. Correlation coefficients were calculated between each metabolite and total protein per day and muscle volume. Multivariable models determined associations between metabolites and muscle volume. Unique metabolites (18) were identified differentiating SOC from HPRO + NMES. Of these, 9 had significant positive correlations with protein intake. In multivariable models, N-acetylleucine was significantly associated with preserved temporalis [OR 1.08 (95% CI 1.01, 1.16)] and quadricep [OR 1.08 (95% CI 1.02, 1.15)] muscle volume. Quinolinate was also significantly associated with preserved temporalis [OR 1.05 (95% CI 1.01, 1.09)] and quadricep [OR 1.04 (95% CI 1.00, 1.07)] muscle volume. N-acetylserine and ß-hydroxyisovaleroylcarnitine were associated with preserved temporalis or quadricep volume. Metabolites defining HPRO + NMES had strong correlations with protein intake and were associated with preserved muscle volume.

Lysophospholipids Are Associated With Outcomes in Hospitalized Patients With Mild Traumatic Brain Injury.

Mild traumatic brain injury (mTBI) accounts for 70-90% of all TBI cases. Lipid metabolites have important roles in plasma membrane biogenesis, function, and cell signaling. As TBI can compromise plasma membrane integrity and alter brain cell function, we sought to identify circulating phospholipid alterations after mTBI, and determine if these changes were associated with clinical outcomes. Patients with mTBI (Glasgow Coma Score [GCS] ≥13 and loss of consciousness <30 min) were recruited. A total of 84 mTBI subjects were enrolled after admission to a level I trauma center, with the majority having evidence of traumatic intracranial hemorrhage on brain computed tomography (CT). Plasma samples were collected within 24 h of injury with 32 mTBI subjects returning at 3 months after injury for a second plasma sample to be collected. Thirty-five healthy volunteers were enrolled as controls and had a one-time blood draw. Lipid metabolomics was performed on plasma samples from each subject. Fold change of selected lipid metabolites was determined. Multivariable regression models were created to test associations between lipid metabolites and discharge and 6-month Glasgow Outcomes Scale-Extended (GOSE) outcomes (dichotomized between "good" [GOSE ≥7] and "bad" [GOSE ≤6] functional outcomes). Plasma levels of 31 lipid metabolites were significantly associated with discharge GOSE using univariate models; three of these metabolites were significantly increased, while 14 were significantly decreased in subjects with good outcomes compared with subjects with poor outcomes. In multivariable logistic regression models, higher circulating levels of the lysophospholipids (LPL) 1-linoleoyl-glycerophosphocholine (GPC) (18:2), 1-linoleoyl-GPE (18:2), and 1-linolenoyl-GPC (18:3) were associated with both good discharge GOSE (odds ratio [OR] 12.2 [95% CI 3.35, 58.3], p = 5.23 × 10-4; OR 9.43 [95% CI 2.87, 39.6], p = 7.26 × 10-4; and OR 5.26 [95% CI 1.99, 16.7], p = 2.04 × 10-3, respectively) and 6-month (OR 4.67 [95% CI 1.49, 17.7], p = 0.013; OR 2.93 [95% CI 1.11, 8.87], p = 0.039; and OR 2.57 [95% CI 1.08, 7.11], p = 0.046, respectively). Compared with healthy volunteers, circulating levels of these three LPLs were decreased early after injury and had normalized by 3 months after injury. Logistic regression models to predict functional outcomes were created by adding each of the described three LPLs to a baseline model that included age and sex. Including 1-linoleoyl-GPC (18:2) (8.20% improvement, p = 0.009), 1-linoleoyl-GPE (18:2) (8.85% improvement, p = 0.021), or 1-linolenoyl-GPC (18:3) (7.68% improvement, p = 0.012), significantly improved the area under the curve (AUC) for predicting discharge outcomes compared with the baseline model. Models including 1-linoleoyl-GPC (18:2) significantly improved AUC for predicting 6-month outcomes (9.35% improvement, p = 0.034). Models including principal components derived from 25 LPLs significantly improved AUC for prediction of 6-month outcomes (16.0% improvement, p = 0.020). Our results demonstrate that higher plasma levels of LPLs (1-linoleoyl-GPC, 1-linoleoyl-GPE, and 1-linolenoyl-GPC) after mTBI are associated with better functional outcomes at discharge and 6 months after injury. This class of phospholipids may represent a potential therapeutic target.

Peripheral eosinophil trends and clinical outcomes after non-traumatic subarachnoid hemorrhage.

Background/objective: Uncontrolled systemic inflammation after non-traumatic subarachnoid hemorrhage (SAH) is associated with worse outcomes. Changes in the peripheral eosinophil count have been linked to worse clinical outcomes after ischemic stroke, intracerebral hemorrhage, and traumatic brain injury. We aimed to investigate the association of eosinophil counts with clinical outcomes after SAH. Methods: This retrospective observational study included patients with SAH admitted from January 2009 to July 2016. Variables included demographics, modified Fisher scale (mFS), Hunt-Hess Scale (HHS), global cerebral edema (GCE), and the presence of any infection. Peripheral eosinophil counts were examined as part of routine clinical care on admission and daily for 10 days after aneurysmal rupture. Outcome measures included dichotomized discharge mortality, modified Ranked Scale (mRS) score, delayed cerebral ischemia (DCI), vasospasm, and need for ventriculoperitoneal shunt (VPS). Statistical tests included the chi-square test, Student's t-test, and multivariable logistic regression (MLR) model. Results: A total of 451 patients were included. The median age was 54 (IQR 45, 63) years, and 295 (65.4%) were female patients. On admission, 95 patients (21.1%) had a high HHS (>4), and 54 (12.0%) had GCE. A total of 110 (24.4%) patients had angiographic vasospasm, 88 (19.5%) developed DCI, 126 (27.9%) had an infection during hospitalization, and 56 (12.4%) required VPS. Eosinophil counts increased and peaked on days 8-10. Higher eosinophil counts on days 3-5 and day 8 were seen in patients with GCE (p < 0.05). Higher eosinophil counts on days 7-9 (p < 0.05) occurred in patients with poor discharge functional outcomes. In multivariable logistic regression models, higher day 8 eosinophil count was independently associated with worse discharge mRS (OR 6.72 [95% CI 1.27, 40.4], p = 0.03). Conclusion: This study demonstrated that a delayed increase in eosinophils after SAH occurs and may contribute to functional outcomes. The mechanism of this effect and the relationship with SAH pathophysiology merit further investigation.

High-Protein Supplementation and Neuromuscular Electric Stimulation after Aneurysmal Subarachnoid Hemorrhage Increases Systemic Amino Acid and Oxidative Metabolism: A Plasma Metabolomics Approach.

Background: The INSPIRE randomized clinical trial demonstrated that a high protein diet (HPRO) combined with neuromuscular electrical stimulation (NMES) attenuates muscle atrophy and may improve functional outcomes after aSAH. Using an untargeted metabolomics approach, we sought to identify specific metabolites mediating these effects. Methods: Blood samples were collected from subjects on admission prior to randomization to either standard of care (SOC; N=12) or HPRO+NMES (N=12) and at 7 days as part of the INSPIRE protocol. Untargeted metabolomics were performed for each plasma sample. Paired fold changes were calculated for each metabolite among subjects in the HPRO+NMES group at baseline and 7 days after intervention. Changes in metabolites from baseline to 7 days were compared for the HPRO+NMES and SOC groups. Sparse partial least squared discriminant analysis (sPLS-DA) identified metabolites discriminating each group. Pearson's correlation coefficients were calculated between each metabolite and total protein per day, nitrogen balance, and muscle volume Multivariable models were developed to determine associations between each metabolite and muscle volume. Results: A total of 18 unique metabolites were identified including pre and post treatment and differentiating SOC vs HPRO+NMES. Of these, 9 had significant positive correlations with protein intake: N-acetylserine (ρ=0.61, P=1.56×10-3), N-acetylleucine (ρ=0.58, P=2.97×10-3), ß-hydroxyisovaleroylcarnitine (ρ=0.53, P=8.35×10-3), tiglyl carnitine (ρ=0.48, P=0.0168), N-acetylisoleucine (ρ=0.48, P=0.0183), N-acetylthreonine (ρ=0.47, P=0.0218), N-acetylkynurenine (ρ=0.45, P=0.0263), N-acetylvaline (ρ=0.44, P=0.0306), and urea (ρ=0.43, P=0.0381). In multivariable regression models, N-acetylleucine was significantly associated with preserved temporalis [OR 1.08 (95%CI 1.01, 1.16)] and quadricep [OR 1.08 (95%CI 1.02, 1.15)] muscle volume. Quinolinate was also significantly associated with preserved temporalis [OR 1.05 (95%CI 1.01, 1.09)] and quadricep [OR 1.04 (95%CI 1.00, 1.07)] muscle volume. N-acetylserine, N-acetylcitrulline, and b-hydroxyisovaleroylcarnitine were also associated with preserved temporalis or quadricep volume. Conclusions: Metabolites defining the HPRO+NMES intervention mainly consisted of amino acid derivatives. These metabolites had strong correlations with protein intake and were associated with preserved muscle volume.

A generalizable physiological model for detection of Delayed Cerebral Ischemia using Federated Learning.

Delayed cerebral ischemia (DCI) is a complication seen in patients with subarachnoid hemorrhage stroke. It is a major predictor of poor outcomes and is detected late. Machine learning models are shown to be useful for early detection, however training such models suffers from small sample sizes due to rarity of the condition. Here we propose a Federated Learning approach to train a DCI classifier across three institutions to overcome challenges of sharing data across hospitals. We developed a framework for federated feature selection and built a federated ensemble classifier. We compared the performance of FL model to that obtained by training separate models at each site. FL significantly improved performance at only two sites. We found that this was due to feature distribution differences across sites. FL improves performance in sites with similar feature distributions, however, FL can worsen performance in sites with heterogeneous distributions. The results highlight both the benefit of FL and the need to assess dataset distribution similarity before conducting FL.

White matter connectivity for early prediction of Alzheimer's disease.

BACKGROUND: Early diagnosis of Alzheimer's disease (AD) remains challenging. It is speculated that structural atrophy in white matter tracts commences prior to the onset of AD symptoms. OBJECTIVE: We hypothesize that disruptions in white matter tract connectivity precedes the onset of AD symptoms and these disruptions could be leveraged for early prediction of AD. METHODS: Diffusion tensor images (DTI) from 52 subjects with mild cognitive impairment (MCI) were selected. Subjects were dichotomized into two age and gender matched groups; the MCI-AD group (22 subjects who progressed to develop AD) and the MCI-control group (who did not develop AD). DTI images were anatomically parcellated into 90 distinct regions ROIs followed by tractography methods to obtain different biophysical networks. Features extracted from these networks were used to train predictive algorithms with the objective of discriminating the MCI-AD and MCI-control groups. Model performance and best features are reported. RESULTS: Up to 80% prediction accuracy was achieved using a combination of features from the 'right anterior cingulum' and 'right frontal superior medial'. Additionally, local network features were more useful than global in improving the model's performance. CONCLUSION: Connectivity-based characterization of white matter tracts offers potential for early detection of MCI-AD and in the discovery of novel imaging biomarkers.