Clinical and Basic Evaluation of the Prognostic Value of Uric Acid in Traumatic Brain Injury

Uric Acid Mitigates Cognitive Deficits via TFEB-Mediated Microglial Autophagy in Mice Models of Alzheimer's Disease

Clinical trials have demonstrated the potential neuroprotective effects of uric acid (UA) in Alzheimer's disease (AD). However, the specific mechanism underlying the neuroprotective effect of UA remains unclear. In the present study, we investigated the neuroprotective effect and underlying mechanism of UA in AD mouse models. Various behavioral tests including an elevated plus maze, Barnes maze, and Morris water maze were conducted to evaluate the impact of UA on cognitive function in β-amyloid (Aβ) microinjection and APP23/PS45 double transgenic mice models of AD. Immunohistochemical staining was employed to visualize pathological changes in the brains of AD model mice. Western blotting and immunofluorescence techniques were used to assess levels of autophagy-related proteins and transcription factor EB (TFEB)-related signaling pathways. BV2 cells were used to investigate the association between UA and microglial autophagy. We reported that UA treatment significantly alleviated memory decline in Aβ-induced AD model mice and APP23/PS45 double transgenic AD model mice. Furthermore, UA activated microglia and upregulated the autophagy-related proteins such as LC3II/I ratio, Beclin-1, and LAMP1 in the hippocampus of AD model mice. Similarly, UA protected BV2 cells from Aβ toxicity by upregulating the expressions of Beclin-1, LAMP1, and the LC3II/I ratio, whereas genetic inhibition of TFEB completely abolished these protective effects. Our results indicate that UA may serve as a novel activator of TFEB to induce microglia autophagy and facilitate Aβ degradation, thereby improving cognitive function in AD model mice. Therefore, these findings suggest that UA may be a novel therapeutic agent for AD treatment.

Moderating effects of uric acid and sex on cognition and psychiatric symptoms in asymmetric Parkinson's disease

BACKGROUND

Non-motor symptoms are an important early feature of Parkinson's disease (PD), encompassing a variety of cognitive and psychiatric symptoms that seem to manifest differently depending on motor symptom asymmetry. Different factors, such as uric acid (UA) and sex, seem to influence cognitive and psychiatric expression in PD, however their interplay remains to be better understood.

METHODS

Participants taking part in the Parkinson's Progression Marker Initiative were studied based on the side of motor symptom asymmetry and sex. Three-way interaction modeling was used to examine the moderating effects of sex and UA on cognitive functions and psychiatric symptoms.

RESULTS

Significant three-way interactions were highlighted at 1-year follow-up between motor symptom asymmetry, UA and sex for immediate and long-term memory in female patients exhibiting predominantly left-sided motor symptoms, and for processing speed and sleepiness in female patients exhibiting predominantly right-sided motor symptoms. No significant interactions were observed for male patients. Moreover, female patients exhibiting predominantly right-sided motor symptoms demonstrated lower serum UA concentrations and had overall better outcomes, while male patients with predominantly right-sided motor symptoms demonstrated particularly poor outcomes.

CONCLUSIONS

These findings suggest that in the earliest stages of the disease, UA and sex moderate cognitive functions and psychiatric symptoms differently depending on motor asymmetry, holding important clinical implications for symptom management in patients.

Machine Learning Approaches-Driven for Mortality Prediction for Patients Undergoing Craniotomy in ICU

OBJECTIVES

We aimed to predict the mortality of patients with craniotomy in ICU by using predictive models to extract the high-risk factors leading to the death of patients from a retrospective a study.

METHODS

Five machine-learning (ML) algorithms were applied for training on mortality predictive models with the data from a surgical intensive care unit (ICU) database of the Fujian Provincial Hospital in China. The accuracy, precision, recall, f1 score and the area under the receiver operator characteristic curve (AUC) were used to evaluate the performance of different models, and the calibration of the model was evaluated by brier score.

RESULTS

We demonstrated that eXtreme Gradient Boosting (XGBoost) was more suitable for the task, demonstrating a AUC of 0.84. We analyzed the feature importance with the Local Interpretable Model-agnostic Explanations (LIME) analysis and further identified the high-risk factors of mortality in ICU through this study.

CONCLUSIONS

This study established the mortality predictive model of patients who had undergone craniotomy in ICU. Identification of the factors that had great influence on mortality has the potential to provide auxiliary decision support for clinical medical staff on their practices.

Gout Is Not Just Arthritis: Abnormal Cortical Thickness and Structural Covariance Networks in Gout

Background: Hyperuricemia is the cause of gout. The antioxidant and neuroprotective effects of uric acid seem to benefit some patients with central nervous system injury. However, changes in the brain structure have not been discovered in patients with gout.

Object: Clarify the changes in cortical thickness in patients with gout and the alteration of the structural covariance networks (SCNs) based on cortical thickness.

Methods: We collected structural MRIs of 23 male gout patients and 23 age-matched healthy controls. After calculating and comparing the difference in cortical thickness between the two groups, we constructed and analyzed the cortical thickness covariance networks of the two groups, and we investigated for any changes in SCNs of gout patients.

Results: Gout patients have thicker cortices in the left postcentral, left supramarginal, right medial temporal, and right medial orbitofrontal regions; and thinner cortices were found in the left insula, left superior frontal, right pericalcarine, and right precentral regions. In SCN analysis, between-group differences in global network measures showed that gout patients have a higher global efficiency. In regional network measures, more nodes in gout patients have increased centrality. In network hub analysis, we found that the transfer of the core hub area, rather than the change in number, may be the characteristic of the gout's cortical thickness covariance network.

Conclusion: This is the first study on changes in brain cortical thickness and SCN based on graph theory in patients with gout. The present study found that, compared with healthy controls, gout patients show regional cortical thinning or thickening, and variation in the properties of the cortical thickness covariance network also changed. These alterations may be the combined effect of disease damage and physiological compensation. More research is needed to fully understand the complex underlying mechanisms of gout brain variation.

Decreased serum uric acid in patients with traumatic brain injury or after cerebral tumor surgery

Objectives:

To investigate changes in sUA in patients with TBI or patients after cerebral tumor surgery and the possible mechanism of these changes.

Methods:

This prospective cohort study enrolled patients with TBI or underwent cerebral tumor surgery at West China Hospital, China, from November 2014 to May 2018. Serum UA (sUA) levels, urine excretion, UA oxidant product allantoin and other clinical parameters were assessed.

Results:

100 patients were enrolled for analysis. sUA in patients with TBI or underwent cerebral tumor surgery started to decline from day 1 after injury or surgery compared to control. This decreasing trend continued from day 3 (143.2±59.3 μmol/L, 188.8±49.4 μmol/L vs 287.3±80.2 μmol/L, p<0.0001) until day 7. No difference in urinary UA excretion was found in the TBI group or cerebral tumor surgery group. Urine allantoin and the allantoin to sUA ratio of the TBI group decreased on day 3 compared with the control group. The structural equation model showed that the sUA level was related to the Glasgow coma score (GCS) (r=0.5383, p<0.0001), suggesting the potential association of UA with consciousness level, as well as serum protein and electrolytes including albumin, calcium and phosphate.

Conclusion:

The sUA was decreased in patients with TBI or underwent cerebral tumor surgery.

Clinical predictors of prognosis in patients with traumatic brain injury combined with extracranial trauma

Objective: The purpose of this study was to investigate whether routine blood tests on admission and clinical characteristics can predict prognosis in patients with traumatic brain injury (TBI) combined with extracranial trauma. Methods: Clinical data of 182 patients with TBI combined with extracranial trauma from April 2018 to December 2019 were retrospectively collected and analyzed. Based on GOSE score one month after discharge, the patients were divided into a favorable group (GOSE 1-4) and unfavorable group (GOSE 5-8). Routine blood tests on admission and clinical characteristics were recorded. Results: Overall, there were 48 (26.4%) patients with unfavorable outcome and 134 (73.6%) patients with favorable outcome. Based on multivariate analysis, independent risk factors associated with unfavorable outcome were age (odds ratio [OR], 1.070; 95% confidence interval [CI], 1.018-1.124; p<0.01), admission Glasgow Coma Scale (GCS) score (OR, 0.807; 95% CI, 0.675-0.965; p<0.05), heart rate (OR, 1.035; 95% CI, 1.004-1.067; p<0.05), platelets count (OR, 0.982; 95% CI, 0.967-0.997; p<0.05), and tracheotomy (OR, 15.201; 95% CI, 4.121-56.078; p<0.001). Areas under the curve (AUC) of age, admission GCS, heart rate, tracheotomy, and platelets count were 0.678 (95% CI, 0.584-0.771), 0.799 (95% CI, 0.723-0.875), 0.652 (95% CI, 0.553-0.751), 0.776 (95% CI, 0.692-0.859), and 0.688 (95% CI, 0.606-0.770), respectively. Conclusions: Age, admission GCS score, heart rate, tracheotomy, and platelets count can be recognized as independent predictors of clinical prognosis in patients with severe TBI combined with extracranial trauma.

Metabolomics Analysis of Hippocampus and Cortex in a Rat Model of Traumatic Brain Injury in the Subacute Phase

Traumatic brain injury (TBI) is a complex and serious disease as its multifaceted pathophysiological mechanisms remain vague. The molecular changes of hippocampal and cortical dysfunction in the process of TBI are poorly understood, especially their chronic effects on metabolic profiles. Here we utilize metabolomics-based liquid chromatography coupled with tandem mass spectrometry coupled with bioinformatics method to assess the perturbation of brain metabolism in rat hippocampus and cortex on day 7. The results revealed a signature panel which consisted of 13 identified metabolites to facilitate targeted interventions for subacute TBI discrimination. Purine metabolism change in cortical tissue and taurine and hypotaurine metabolism change in hippocampal tissue were detected. Furthermore, the associations between the metabolite markers and the perturbed pathways were analyzed based on databases: 64 enzyme and one pathway were evolved in TBI. The findings represented significant profiling changes and provided unique metabolite-protein information in a rat model of TBI following the subacute phase. This study may inspire scientists and doctors to further their studies and provide potential therapy targets for clinical interventions.

The Predictive Value of Serum Uric Acid on Acute Kidney Injury following Traumatic Brain Injury

Backgrounds

Acute kidney injury (AKI) is a prevalent nonneurological complication in patients with traumatic brain injury (TBI). We designed this study to explore the association between serum uric acid (SUA) level and the occurrence of AKI following TBI.

Methods

This is a retrospective single-center study. A total of 479 patients admitted with TBI were included in this study. We utilized SUA and other risk factors for AKI to construct a predictive model by performing multivariate logistic regression. 374 patients and 105 patients were, respectively, divided into a training set and validation set. The predictive value of the single SUA and constructed model was evaluated by drawing a receiver operating characteristic (ROC) curve. AKI was diagnosed according to the KIDGO criteria.

Results

79 (21.12%) patients were diagnosed with AKI in the training cohort. The patients in the AKI group are older than those in the non-AKI group (p = 0.01). And the Glasgow Coma Scale (GCS) of the AKI group was lower than that of the non-AKI group (p < 0.001). In a multivariate logistic regression analysis, we found that heart rate (p = 0.041), shock (p = 0.018), serum creatinine (p < 0.001), and serum uric acid (SUA) (p < 0.001) were significant risk factors for AKI. Bivariate correlation analyses showed that serum creatinine was moderately positively correlated with SUA (r = 0.523, p < 0.001). Finally, the area under the receiver operating characteristic curve (AUC) of SUA for predicting AKI in the training set and validation set was 0.850 (0.805-0.895) and 0.869 (0.801-0.938), respectively.

Conclusions

SUA is an effective risk factor for AKI following TBI. Combining SUA with serum creatinine could more accurately identify TBI patients with high risk of developing AKI.

Predictors of acute metabolic decompensation in children with maple syrup urine disease at the emergency department

Acute metabolic decompensation (AMD) of maple syrup urine disease (MSUD) must be promptly recognized and treated. In this study, we aimed to identify simple variables associated with AMD in children with MSUD for use in emergency settings. Data were collected retrospectively from 115 emergency visits of 29 children with MSUD over a 4-year period in a major referral hospital. Variables in visits with and without AMD were compared using t test, Mann-Whitney U test, and chi-square test. Logistic regression was used to identify independent variables associated with decompensations. Cut-off values of laboratory variables were determined with receiver operating characteristic curves and correlations with Spearman's rank correlation. Most important variables independently associated with AMD were poor feeding, malaise, anion gap, and especially uric acid, which correlated with leucine levels. Vomiting, dehydration, neurological signs, ketonuria, and ketoaciduria were also associated with AMD. Although sodium, chloride, and glucose were lower in AMD, they had little diagnostic value.Conclusion: In children with MSUD, uric acid and anion gap are key markers for AMD. Poor feeding and malaise are clues before the onset of neurological symptoms. These simple parameters can help determine the presence of AMD in emergency settings.What is Known:• In maple syrup urine disease, acute metabolic decompensations are characterized by gastrointestinal and neurological findings.• Diagnosis requires detection of significantly elevated leucine, which may take a long time or not be available.What is New:• Poor feeding, malaise, hyperuricemia, and high anion gap are parameters that can help diagnose acute decompensations in children with maple syrup urine disease at emergency departments.• Uric acid may be a biomarker for acute decompensations because of its high sensitivity, specificity, and its strong correlation with leucine.