The Application of Neurodiagnostic Studies to Inform the Acute Management of a Newborn Presenting With Sarbamoyl Shosphate Synthetase 1 Deficiency

Seizure Characteristics and EEG Features in Intoxication Type and Energy Deficiency Neurometabolic Disorders in the Pediatric Intensive Care Unit: Single-Center Experience Over 10 Years

BACKGROUND

Acute metabolic crises in inborn errors of metabolism (such as urea cycle disorders, organic acidemia, maple syrup urine disease, and mitochondrial disorders) are neurological emergencies requiring management in the pediatric intensive care unit (PICU). There is a paucity of data pertaining to electroencephalograms (EEG) characteristics in this cohort. We hypothesized that the incidence of background abnormalities and seizures in this cohort would be high. Neuromonitoring data from our center's PICU over 10 years are presented in this article.

METHODS

Data were collected by retrospective chart review for patients with the aforementioned disorders who were admitted to the PICU at our institution because of metabolic/neurologic symptoms from 2008 to 2018. Descriptive statistics (χ2 test or Fisher's exact test) were used to study the association between EEG parameters and outcomes.

RESULTS

Our cohort included 40 unique patients (8 with urea cycle disorder, 7 with organic acidemia, 3 with maple syrup urine disease, and 22 with mitochondrial disease) with 153 admissions. Presenting symptoms included altered mentation (36%), seizures (41%), focal weakness (5%), and emesis (28%). Continuous EEG was ordered in 34% (n = 52) of admissions. Twenty-three admissions were complicated by seizures, including eight manifesting as status epilepticus (seven nonconvulsive and one convulsive). Asymmetry and focal slowing on EEG were associated with seizures. Moderate background slowing or worse was noted in 75% of EEGs. Among those patients monitored on EEG, 4 (8%) died, 3 (6%) experienced a worsening of their Pediatric Cerebral Performance Category (PCPC) score as compared to admission, and 44 (86%) had no change (or improvement) in their PCPC score during admission.

CONCLUSIONS

This study shows a high incidence of clinical and subclinical seizures during metabolic crisis in patients with inborn errors of metabolism. EEG background features were associated with risk of seizures as well as discharge outcomes. This is the largest study to date to investigate EEG features and risk of seizures in patients with neurometabolic disorders admitted to the PICU. These data may be used to inform neuromonitoring protocols to improve mortality and morbidity in inborn errors of metabolism.

COSIME: Cooperative multi-view integration and Scalable and Interpretable Model Explainer

Single-omics approaches often provide a limited view of complex biological systems, whereas multiomics integration offers a more comprehensive understanding by combining diverse data views. However, integrating heterogeneous data types and interpreting the intricate relationships between biological features-both within and across different data views-remains a bottleneck. To address these challenges, we introduce COSIME (Cooperative Multi-view Integration and Scalable Interpretable Model Explainer). COSIME uses backpropagation of Learnable Optimal Transport (LOT) to deep neural networks, enabling the learning of latent features from multiple views to predict disease phenotypes. In addition, COSIME incorporates Monte Carlo sampling to efficiently estimate Shapley values and Shapley-Taylor indices, enabling the assessment of both feature importance and their pairwise interactions-synergistically or antagonistically-in predicting disease phenotypes. We applied COSIME to both simulated data and real-world datasets, including single-cell transcriptomics, single-cell spatial transcriptomics, epigenomics, and metabolomics, specifically for Alzheimer's disease-related phenotypes. Our results demonstrate that COSIME significantly improves prediction performance while offering enhanced interpretability of feature relationships. For example, we identified that synergistic interactions between microglia and astrocyte genes associated with AD are more likely to be active at the edges of the middle temporal gyrus as indicated by spatial locations. Finally, COSIME is open-source and available for general use.

Unraveling the Link: Seizure Characteristics and Ammonia Levels in Urea Cycle Disorder During Hyperammonemic Crises

BACKGROUND

This retrospective clinical study performed at a single clinical center aimed to identify the prevalence of seizures in individuals with urea cycle disorders (UCDs) with and without hyperammonemic (HA) crises. In addition, we sought to correlate the utility of biochemical markers and electroencephalography (EEG) in detecting subclinical seizures during HA.

METHODS

Medical records of individuals with UCDs enrolled in Urea Cycle Disorders Consortium Longitudinal Study (UCDC-LS) (NCT00237315) at Children's National Hospital between 2006 and 2022 were reviewed for evidence of clinical and subclinical seizuress during HA crises, and initial biochemical levels concurrently.

RESULTS

Eighty-five individuals with UCD were included in the analyses. Fifty-six of the 85 patients (66%) experienced HA crises, with a total of 163 HA events. Seizures are observed in 13% of HA events. Among all HA events with concomitant EEG, subclinical seizures were identified in 27% of crises of encephalopathy without clinical seizures and 53% of crises with clinical seizures. The odds of seizures increases 2.65 (95% confidence interval [CI], 1.51 to 4.66) times for every 100 μmol/L increase in ammonia and 1.14 (95% CI, 1.04 to 1.25) times for every 100 μmol/L increase in glutamine.

CONCLUSIONS

This study highlights the utility of EEG monitoring during crises for patients presenting with clinical seizures or encephalopathy with HA. During HA events, measurement of initial ammonia and glutamine can help determine risk for seizures and guide EEG monitoring decisions.

Fifteen years of urea cycle disorders brain research: Looking back, looking forward

Urea cycle disorders (UCD) are inherited diseases resulting from deficiency in one of six enzymes or two carriers that are required to remove ammonia from the body. UCD may be associated with neurological damage encompassing a spectrum from asymptomatic/mild to severe encephalopathy, which results in most cases from Hyperammonemia (HA) and elevation of other neurotoxic intermediates of metabolism. Electroencephalography (EEG), Magnetic resonance imaging (MRI) and Proton Magnetic resonance spectroscopy (MRS) are noninvasive measures of brain function and structure that can be used during HA to guide management and provide prognostic information, in addition to being research tools to understand the pathophysiology of UCD associated brain injury. The Urea Cycle Rare disorders Consortium (UCDC) has been invested in research to understand the immediate and downstream effects of hyperammonemia (HA) on brain using electroencephalogram (EEG) and multimodal brain MRI to establish early patterns of brain injury and to track recovery and prognosis. This review highlights the evolving knowledge about the impact of UCD and HA in particular on neurological injury and recovery and use of EEG and MRI to study and evaluate prognostic factors for risk and recovery. It recognizes the work of others and discusses the UCDC's prior work and future research priorities.