Hypoxanthine—early biomarker of outcomes in an ovine model of neonatal hypoxic ischemic encephalopathy

BACKGROUND: Hypoxic-ischemic encephalopathy (HIE) is the leading cause of neonatal morbidity and mortality globally. An early tool to diagnose and prognosticate disease could aid in timely intervention and reduction in disease burden. We aimed to identify biomarkers for HIE and define whether these biomarkers are associated with neurologic outcome severity in our ovine model. METHODS: Study Cohort 1 (n = 46) included lambs with HIE induced via umbilical cord occlusion (UCO) and healthy controls (n = 19). Cohort 2 (n = 25 UCO lambs) served as a validation cohort for identified biomarkers. Blood samples collected at multiple early time points were analyzed using untargeted liquid chromatography-mass spectrometry. Biomarkers were considered significant at p < 1e-6. Neurological outcome biomarkers were identified using ordinal logistic regression. RESULTS: A total of 145 hypoxia biomarkers were identified, exhibiting a consistent and reproducible temporal pattern across both cohorts. Hypoxanthine level at 20 min of life showed a strong correlation with the severity of neurologic outcomes. CONCLUSIONS: Hypoxanthine emerged as a significant neurologic outcome biomarker in our study. Our findings support the potential utility of metabolomics for early diagnosis and prognostication in HIE. Further clinical validation is warranted to translate these biomarkers into accessible diagnostic and predictive tools, particularly for resource-limited settings. IMPACT: Our study identified plasma hypoxanthine as an early biomarker for hypoxic-ischemic encephalopathy (HIE) in an ovine model and uncovered a novel correlation between hypoxanthine levels and the severity of neurologic impairment in asphyxiated lambs. These findings highlight the potential of metabolomics in the early detection of HIE, paving the way for improved diagnostic and prognostic strategies. Translating these insights into clinical practice could enable the development of predictive tools for outcome assessment and resource allocation, ultimately enhancing early intervention and optimizing care for neonates at risk of HIE.