Reframing the Biological Basis of Neuroprotection Using Functional Genomics: Differentially Weighted, Time-Dependent Multifactor Pathogenesis of Human Ischemic Brain Damage

vCSF Danger-associated Molecular Patterns After Traumatic and Nontraumatic Acute Brain Injury: A Prospective Study

BACKGROUND

Danger-associated molecular patterns (DAMPs) may be implicated in the pathophysiological pathways associated with an unfavorable outcome after acute brain injury (ABI).

METHODS

We collected samples of ventricular cerebrospinal fluid (vCSF) for 5 days in 50 consecutive patients at risk of intracranial hypertension after traumatic and nontraumatic ABI. Differences in vCSF protein expression over time were evaluated using linear models and selected for functional network analysis using the PANTHER and STRING databases. The primary exposure of interest was the type of brain injury (traumatic vs. nontraumatic), and the primary outcome was the vCSF expression of DAMPs. Secondary exposures of interest included the occurrence of intracranial pressure ≥20 or ≥ 30 mm Hg during the 5 days post-ABI, intensive care unit (ICU) mortality, and neurological outcome (assessed using the Glasgow Outcome Score) at 3 months post-ICU discharge. Secondary outcomes included associations of these exposures with the vCSF expression of DAMPs.

RESULTS

A network of 6 DAMPs ( DAMP_trauma ; protein-protein interaction [PPI] P =0.04) was differentially expressed in patients with ABI of traumatic origin compared with those with nontraumatic ABI. ABI patients with intracranial pressure ≥30 mm Hg differentially expressed a set of 38 DAMPS ( DAMP_ICP30 ; PPI P < 0.001). Proteins in DAMP_ICP30 are involved in cellular proteolysis, complement pathway activation, and post-translational modifications. There were no relationships between DAMP expression and ICU mortality or unfavorable versus favorable outcomes.

CONCLUSIONS

Specific patterns of vCSF DAMP expression differentiated between traumatic and nontraumatic types of ABI and were associated with increased episodes of severe intracranial hypertension.

Identifying TBI Physiological States by Clustering Multivariate Clinical Time-Series Data

Determining clinically relevant physiological states from multivariate time-series data with missing values is essential for providing appropriate treatment for acute conditions such as Traumatic Brain Injury (TBI), respiratory failure, and heart failure. Utilizing non-temporal clustering or data imputation and aggregation techniques may lead to loss of valuable information and biased analyses. In our study, we apply the SLAC-Time algorithm, an innovative self-supervision-based approach that maintains data integrity by avoiding imputation or aggregation, offering a more useful representation of acute patient states. By using SLAC-Time to cluster data in a large research dataset, we identified three distinct TBI physiological states and their specific feature profiles. We employed various clustering evaluation metrics and incorporated input from a clinical domain expert to validate and interpret the identified physiological states. Further, we discovered how specific clinical events and interventions can influence patient states and state transitions.

Gut microbiota and transcriptome dynamics in every-other-day fasting are associated with neuroprotection in rats with spinal cord injury

Introduction

Every-other-day fasting (EODF) is a classical intermittent fasting (IF) mode with neuroprotective effects that promotes motor function recovery after spinal cord injury (SCI) in rats. However, its dynamic effects on the gut microbiota and spinal cord transcriptome remain unknown.

Methods

In this study, 16S rRNA sequencing and RNA-seq analysis were used to investigate the effects of ad libitum (AL) and EODF dietary modes on the structural characteristics of rat gut microbiota in rats and the spinal cord transcriptome at various time points after SCI induction.

Results

Our results showed that both dietary modes affected the bacterial community composition in SCI rats, with EODF treatment inducing and suppressing dynamic changes in the abundances of potentially anti-inflammatory and pro-inflammatory bacteria. Furthermore, the differentially expressed genes (DEGs) enriched after EODF intervention in SCI rats were associated with various biological events, including immune inflammatory response, cell differentiation, protein modification, neural growth, and apoptosis. In particular, significant spatiotemporal differences were apparent in the DEGs associated with neuroprotection between the EODF and AL interventions. These DGEs were mainly focused on days 1, 3, and 7 after SCI. The relative abundance of certain genera was significantly correlated with DEGs associated with neuroprotective effects in the EODF-SCI group.

Discussion

Our results showed that EODF treatment may exert neuroprotective effects by modulating the transcriptome expression profile following SCI in rats. Furthermore, gut microbiota may be partially involved in mediating these effects.

Hierarchical Cluster Analysis Identifies Distinct Physiological States After Acute Brain Injury

BACKGROUND

Analysis of intracranial multimodality monitoring data is challenging, and quantitative methods may help identify unique physiological signatures that inform therapeutic strategies and outcome prediction. The aim of this study was to test the hypothesis that data-driven approaches can identify distinct physiological states from intracranial multimodality monitoring data.

METHODS

This was a single-center retrospective observational study of patients with either severe traumatic brain injury or high-grade subarachnoid hemorrhage who underwent invasive multimodality neuromonitoring. We used hierarchical cluster analysis to group hourly values for heart rate, mean arterial pressure, intracranial pressure, brain tissue oxygen, and cerebral microdialysis across all included patients into distinct groups. Average values for measured physiological variables were compared across the identified clusters, and physiological profiles from identified clusters were mapped onto physiological states known to occur after acute brain injury. The distribution of clusters was compared between patients with favorable outcome (discharged to home or acute rehab) and unfavorable outcome (in-hospital death or discharged to chronic nursing facility).

RESULTS

A total of 1704 observations from 20 patients were included. Even though the difference in mean values for measured variables between patients with favorable and unfavorable outcome were small, we identified four distinct clusters within our data: (1) events with low brain tissue oxygen and high lactate-to-pyruvate ratio-values (consistent with cerebral ischemia), (2) events with higher intracranial pressure values without evidence for ischemia (3) events which appeared to be physiologically "normal," and (4) events with high cerebral lactate without brain hypoxia (consistent with cerebral hyperglycolysis). Patients with a favorable outcome had a greater proportion of cluster 3 (normal) events, whereas patients with an unfavorable outcome had a greater proportion of cluster 1 (ischemia) and cluster 4 (hyperglycolysis) events (p < 0.0001, Fisher-Freeman-Halton test).

CONCLUSIONS

A data-driven approach can identify distinct groupings from invasive multimodality neuromonitoring data that may have implications for therapeutic strategies and outcome predictions. These groupings could be used as classifiers to train machine learning models that can aid in the treatment of patients with acute brain injury. Further work is needed to replicate the findings of this exploratory study in larger data sets.

Precision Medicine in Acute Brain Injury: A Narrative Review

Over the past few years, the concept of personalized medicine has percolated into the management of different neurological conditions. Improving outcomes after acute brain injury (ABI) continues to be a major challenge. Unrecognized individual multiomic variations in addition to multiple interacting processes may explain why we fail to observe comprehensive improvements in ABI outcomes even when applied treatments appear to be beneficial logically. The provision of clinical care based on a multiomic approach may revolutionize the management of traumatic brain injury, delayed cerebral ischemia after subarachnoid hemorrhage, acute ischemic stroke, and several other neurological diseases. The challenge is to incorporate all the information obtained from genomic studies, other omic data, and individual variability into a practical tool that can be used to assist clinical decision-making. The effective execution of such strategies, which is still far away, requires the development of protocols on the basis of these complex interactions and strict adherence to management protocols. In this review, we will discuss various omics and physiological targets to guide individualized patient management after ABI.

Does the melatonin receptor 1B gene polymorphism have a role in postoperative delirium?

INTRODUCTION

Patients undergoing cardiac surgery are at high risk for postoperative delirium, which is associated with longer hospital and intensive care lengths of stays, increased morbidity and mortality. Because sleep disturbances are common in delirium, melatonin has been an area of interest in the treatment of delirium. The rs10830963 single nucleotide polymorphism of the melatonin receptor 1B gene can cause pathological dysfunction of this receptor and is associated with delayed morning offset of melatonin. We hypothesized patients undergoing aortic cardiac surgery who have the risk genotype of a melatonin receptor 1B polymorphism would have a higher incidence of postoperative delirium.

METHODS

Ninety-eight patients undergoing aortic root or valve surgery underwent analysis for melatonin receptor 1B single nucleotide polymorphism, rs10830963. Using a validated method, CHART-DEL, all charts were retrospectively reviewed and scored for the presence of delirium while blinded to the results of the melatonin receptor 1B gene polymorphism.

RESULTS

Genotyping for melatonin receptor 1B polymorphism was acceptable in 76 subjects of European descent of which 18 (23.7%) had delirium. Four of seven subjects with the risk genotype had delirium versus only 20.3% of subjects without the risk genotype. This carried an odds ratio of 5.2 (1.0, 26.1), p = 0.050.

CONCLUSION

This observation suggests a role of the risk genotype of a melatonin receptor 1B polymorphism in the development of postoperative delirium. These hypotheses generating results warrant further prospective studies in a larger cohort group with delirium, circadian rhythm and melatonin assessments.