Using metabolomics to predict severe traumatic brain injury outcome (GOSE) at 3 and 12 months

New insights into metabolism dysregulation after TBI

Traumatic brain injury (TBI) remains a leading cause of death and disability that places a great physical, social, and financial burden on individuals and the health system. In this review, we summarize new research into the metabolic changes described in clinical TBI trials, some of which have already shown promise for informing injury classification and staging. We focus our discussion on derangements in glucose metabolism, cell respiration/mitochondrial function and changes to ketone and lipid metabolism/oxidation to emphasize potentially novel biomarkers for clinical outcome prediction and intervention and offer new insights into possible underlying mechanisms from preclinical research of TBI pathology. Finally, we discuss nutrition supplementation studies that aim to harness the gut/microbiome-brain connection and manipulate systemic/cellular metabolism to improve post-TBI recovery. Taken together, this narrative review summarizes published TBI-associated changes in glucose and lipid metabolism, highlighting potential metabolite biomarkers for clinical use, the cellular processes linking these markers to TBI pathology as well as the limitations and future considerations for TBI "omics" work.

Importance of AIM2 as a serum marker for reflecting severity and predicting a poor outcome of human severe traumatic brain injury: A prospective longitudinal cohort study

BACKGROUND

Absent in melanoma 2 (AIM2) participates in neuroinflammation. Here, the prognostic significance of serum AIM2 was explored in severe traumatic brain injury (sTBI).

METHODS

A total of 135 sTBI patients and 80 healthy controls were recruited in this prospective cohort study. Serum C-reactive protein (CRP) and AIM2 levels were measured. Glasgow Coma Scale (GCS) and Rotterdam computed tomography (CT) classification were recorded as the severity indicators. Prognostic parameters were posttraumatic six-month extended Glasgow outcome scale (GOSE) scores and poor outcome (GOSE scores of 1-4).

RESULTS

As opposed to controls, there were significantly elevated serum AIM2 levels after sTBI. Serum AIM2 levels were independently correlated with serum CRP levels, GCS scores, Rotterdam CT scores, GOSE scores and poor outcome. Also, serum AIM2 levels were efficiently predictive of poor outcome under the receiver operating characteristic (ROC) curve. Under the restricted cubic spline, serum AIM2 levels were linearly correlated with risk of poor outcome. Using subgroup analysis, serum AIM2 levels did not significantly interact with other indices, such as age, gender, alcohol drinking, cigarette smoking, etc. Also, combination model, in which serum AIM2, GCS scores and Rotterdam CT scores were merged, was outlined using nomogram and performed well under calibration curve, ROC curve and decision curve.

CONCLUSIONS

Raised serum AIM2 levels after sTBI, in intimate correlation with systemic inflammation and trauma severity, are independently discriminative of posttraumatic six-month neurological outcome, substantializing serum AIM2 as an inflammatory prognostic biomarker of sTBI.

Update in Pediatric Neurocritical Care: What a Neurologist Caring for Critically Ill Children Needs to Know

Currently nearly one-quarter of admissions to pediatric intensive care units (PICUs) worldwide are for neurocritical care diagnoses that are associated with significant morbidity and mortality. Pediatric neurocritical care is a rapidly evolving field with unique challenges due to not only age-related responses to primary neurologic insults and their treatments but also the rarity of pediatric neurocritical care conditions at any given institution. The structure of pediatric neurocritical care services therefore is most commonly a collaborative model where critical care medicine physicians coordinate care and are supported by a multidisciplinary team of pediatric subspecialists, including neurologists. While pediatric neurocritical care lies at the intersection between critical care and the neurosciences, this narrative review focuses on the most common clinical scenarios encountered by pediatric neurologists as consultants in the PICU and synthesizes the recent evidence, best practices, and ongoing research in these cases. We provide an in-depth review of (1) the evaluation and management of abnormal movements (seizures/status epilepticus and status dystonicus); (2) acute weakness and paralysis (focusing on pediatric stroke and select pediatric neuroimmune conditions); (3) neuromonitoring modalities using a pathophysiology-driven approach; (4) neuroprotective strategies for which there is evidence (e.g., pediatric severe traumatic brain injury, post-cardiac arrest care, and ischemic stroke and hemorrhagic stroke); and (5) best practices for neuroprognostication in pediatric traumatic brain injury, cardiac arrest, and disorders of consciousness, with highlights of the 2023 updates on Brain Death/Death by Neurological Criteria. Our review of the current state of pediatric neurocritical care from the viewpoint of what a pediatric neurologist in the PICU needs to know is intended to improve knowledge for providers at the bedside with the goal of better patient care and outcomes.

Metabolome-Wide Mendelian Randomization Assessing the Causal Role of Serum and Cerebrospinal Metabolites in Traumatic Brain Injury

Previous studies have identified metabolites as biomarkers or potential therapeutic targets for traumatic brain injury (TBI). However, the causal association between them remains unknown. Therefore, we investigated the causal effect of serum metabolites and cerebrospinal fluid (CSF) metabolites on TBI susceptibility through Mendelian randomization (MR). Genetic variants related to metabolites and TBI were extracted from a corresponding genome-wide association study (GWAS). Causal effects were estimated through the inverse variance weighted approach, supplemented by a weighted median, weight mode, and the MR-Egger test. In addition, sensitivity analyses were further performed to evaluate the stability of the MR results, including the MR-Egger intercept, leave-one-out analysis, Cochrane's Q-test, and the MR-PRESSO global test. Metabolic pathway analysis was applied to uncover the underlying pathways of the significant metabolites in TBI. In blood metabolites, substances such as 4-acetaminophen sulfate and kynurenine showed positive links, whereas beta-hydroxyisovalerate and creatinine exhibited negative correlations. CSF metabolites such as N-formylanthranilic acid were positively related, while kynurenate showed negative associations. The metabolic pathway analysis highlighted the potential biological pathways involved in TBI. Of these 16 serum metabolites, 11 CSF metabolites and metabolic pathways may serve as useful circulating biomarkers in clinical screening and prevention, and may be candidate molecules for the exploration of mechanisms and drug targets.

PaCO2 Association with Outcomes of Patients with Traumatic Brain Injury at High Altitude: A Prospective Single-Center Cohort Study

BACKGROUND

Partial pressure of carbon dioxide (PaCO2) is generally known to influence outcome in patients with traumatic brain injury (TBI) at normal altitudes. Less is known about specific relationships of PaCO2 levels and clinical outcomes at high altitudes.

METHODS

This is a prospective single-center cohort of consecutive patients with TBI admitted to a trauma center located at 2600 m above sea level. An unfavorable outcome was defined as a Glasgow Outcome Scale-Extended (GOSE) score < 4 at the 6-month follow-up.

RESULTS

We had a total of 81 patients with complete data, 80% (65/81) were men, and the median (interquartile range) age was 36 (25-50) years. Median Glasgow Coma Scale (GCS) score on admission was 9 (6-14); 49% (40/81) of patients had severe TBI (GCS 3-8), 32% (26/81) had moderate TBI (GCS 12-9), and 18% (15/81) had mild TBI (GCS 13-15). The median (interquartile range) Abbreviated Injury Score of the head (AISh) was 3 (2-4). The frequency of an unfavorable outcome (GOSE < 4) was 30% (25/81), the median GOSE was 4 (2-5), and the median 6-month mortality rate was 24% (20/81). Comparison between patients with favorable and unfavorable outcomes revealed that those with unfavorable outcome were older, (median age 49 [30-72] vs. 29 [22-41] years, P < 0.01), had lower admission GCS scores (6 [4-8] vs. 13 [8-15], P < 0.01), had higher AISh scores (4 [4-4] vs. 3 [2-4], P < 0.01), had higher Acute Physiology and Chronic Health disease Classification System II scores (17 [15-23] vs. 10 [6-14], P < 0.01), had higher Charlson scores (0 [0-2] vs. 0 [0-0], P < 0.01), and had higher PaCO2 levels (mean 35 ± 8 vs. 32 ± 6 mm Hg, P < 0.01). In a multivariate analysis, age (odds ratio [OR] 1.14, 95% confidence interval [CI] 1.1-1.30, P < 0.01), AISh (OR 4.7, 95% CI 1.55-21.0, P < 0.05), and PaCO2 levels (OR 1.23, 95% CI 1.10-1.53, P < 0.05) were significantly associated with the unfavorable outcomes. When applying the same analysis to the subgroup on mechanical ventilation, AISh (OR 5.4, 95% CI 1.61-28.5, P = 0.017) and PaCO2 levels (OR 1.36, 95% CI 1.13-1.78, P = 0.015) remained significantly associated with the unfavorable outcome.

CONCLUSIONS

Higher PaCO2 levels are associated with an unfavorable outcome in ventilated patients with TBI. These results underscore the importance of PaCO2 levels in patients with TBI and whether it should be adjusted for populations living at higher altitudes.

Clinical data mining: challenges, opportunities, and recommendations for translational applications

Clinical data mining of predictive models offers significant advantages for re-evaluating and leveraging large amounts of complex clinical real-world data and experimental comparison data for tasks such as risk stratification, diagnosis, classification, and survival prediction. However, its translational application is still limited. One challenge is that the proposed clinical requirements and data mining are not synchronized. Additionally, the exotic predictions of data mining are difficult to apply directly in local medical institutions. Hence, it is necessary to incisively review the translational application of clinical data mining, providing an analytical workflow for developing and validating prediction models to ensure the scientific validity of analytic workflows in response to clinical questions. This review systematically revisits the purpose, process, and principles of clinical data mining and discusses the key causes contributing to the detachment from practice and the misuse of model verification in developing predictive models for research. Based on this, we propose a niche-targeting framework of four principles: Clinical Contextual, Subgroup-Oriented, Confounder- and False Positive-Controlled (CSCF), to provide guidance for clinical data mining prior to the model's development in clinical settings. Eventually, it is hoped that this review can help guide future research and develop personalized predictive models to achieve the goal of discovering subgroups with varied remedial benefits or risks and ensuring that precision medicine can deliver its full potential.

PaCO2 Association with Traumatic Brain Injury Patients Outcomes at High Altitude: A Prospective Single-Center Cohort Study

Background

partial pressure of carbon dioxide (PaCO2) is generally known to influence outcome in patients with traumatic brain injury (TBI) at normal altitudes. Less is known about specific relationships of PaCO2 levels and clinical outcomes at high altitudes.

Methods

This is a prospective single-center cohort of consecutive TBI patients admitted to a trauma center located at 2600 meter above sea level. An unfavorable outcome was defined as the Glasgow Outcome Scale-Extended (GOSE) < 4 at 6-month follow-up.

Results

81 patients with complete data, 80% (65/81) were men, and median (IQR) age was 36 (25-50) years). Median Glasgow Coma Scale (GCS) on admission was 9 (6-14), 49% (40/81) were severe (GCS: 3-8), 32% (26/81) moderate (GCS 12 - 9), and 18% (15/81) mild (GCS 13-15) TBI. The median (IQR) Abbreviated Injury Score of the Head (AISh) was 3 (2-4). Frequency of an unfavorable outcome (GOSE < 4) was 30% (25/81), median GOSE was 4 (2-5), and 6-month mortality was 24% (20/81). Comparison between patients with favorable and unfavorable outcomes revealed that those with unfavorable outcome were older, median [49 (30-72) vs. 29 (22-41), P < 0.01], had lower admission GCS [6 (4-8) vs. 13 (8-15), P < 0.01], higher AIS head [4 (4-4) vs. 3(2-4), p < 0.01], higher APACHE II score [17(15-23) vs 10 (6-14), < 0.01), higher Charlson score [0(0-2) vs. 0 (0-0), P < 0.01] and higher PaCO2 (mmHg), mean ± SD, 39 ± 9 vs. 32 ± 6, P < 0.01. In a multivariate analysis, age (OR 1.14 95% CI 1.1-1.30, P < 0.01), AISh (OR 4.7 95% CI 1.55-21.0, P < 0.05), and PaCO2 (OR 1.23 95% CI: 1.10-1.53, P < 0.05) were significantly associated with the unfavorable outcomes. When applying the same analysis to the subgroup on mechanical ventilation, AISh (OR 5.4 95% CI: 1.61-28.5, P = 0.017) and PaCO2 (OR 1.36 95% CI: 1.13-1.78, P = 0.015) remained significantly associated with the unfavorable outcome.

Conclusion

Higher PaCO2 levels are associated with an unfavorable outcome in ventilated TBI patients. These results underscore the importance of PaCO2 level in TBI patients and whether it should be adjusted for populations living at higher altitudes.

Importance of serum IRAK3 as a biochemical marker in relation to severity and neurological outcome of human severe traumatic brain injury: A prospective longitudinal cohort study

BACKGROUND

Interleukin-1 receptor-associated kinase 3 (IRAK3) may modulate inflammation in brain immunity. We determined the prognostic role of serum IRAK3 in severe traumatic brain injury (sTBI).

METHODS

In this prospective longitudinal cohort study, serum IRAK3 concentrations of 131 sTBI patients and 131 controls were quantified. Extended Glasgow outcome scale (GOSE) scores of 1-4 at 180 days after trauma signified a poor prognosis. Univariate and multivariate analyses were sequentially adopted to appraise severity correlations and prognosis associations.

RESULTS

There were significantly higher serum IRAK3 concentrations in patients than in controls. Serum IRAK3 concentrations of patients were independently correlated with Glasgow coma scale (GCS) scores, Rotterdam computed tomography (CT) scores and posttraumatic180-day GOSE scores. Also, IRAK3 concentrations were independently associated with 180-day poor prognosis, but not with death. Prognosis prediction model, in which GCS scores, Rotterdam scores and serum IRAK3 concentrations were merged, was portrayed using the nomogram. The model was rather stable, clinically usable and efficiently discriminative of poor prognosis under calibration curve, decision curve and receiver operating characteristic curve.

CONCLUSIONS

A substantial enhancement of serum IRAK3 concentrations after head trauma is independently related to severity and neurological outcome, substantializing serum IRAK3 as a promising prognostic biomarker of sTBI.