Background: Neuroprognostication in neonates with neonatal encephalopathy (NE) may be enhanced by early serial measurement of a panel of four brain-specific biomarkers.
Methods: To evaluate serum biomarkers, 40 NE samples and 37 healthy neonates from a biorepository were analyzed. Blood samples were collected at 0-6, 12, 24, 48, and 96 h of life. MRI provided a short-term measure of injury. Long-term outcomes included death or a Bayley III score at 17-24 months of age.
Results: Glial fibrillary acidic protein (GFAP), ubiquitin c-terminal hydrolase-L1 (UCH-L1), and Tau peaked at 0-6 h of life, while neurofilament light chain (NFL) peaked at 96 h of life. These four marker concentrations at 96 h of life differentiated moderate/severe from none/mild brain injury by MRI, while GFAP and Tau showed early discrimination. For long-term outcomes, GFAP, NFL, Tau, and UCH-L1 could differentiate a poor outcome vs good outcome as early as 0-6 h of life, depending on the Bayley domain, and a combination of the four markers enhanced the sensitivity and specificity. Machine learning trajectory analyses identified upward trajectory patients with a high concordance to poor outcomes.
Conclusion: GFAP, NFL, Tau, and UCH-L1 may be of neuroprognostic significance after NE.
Impact: Serial measurements of GFAP, NFL, Tau, and UCH-L1 show promise in aiding the bedside clinician in making treatment decisions in neonatal encephalopathy. The panel of four neuroproteins increased the ability to predict neurodevelopmental outcomes. The study utilized a trajectory analysis that enabled predictive modeling. A panel approach provides the bedside clinician with objective data to individualize care. This study provides the foundation to develop a point of care device in the future.
© 2022. The Author(s), under exclusive licence to the International Pediatric Research Foundation, Inc.