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Updated: Sep 15, 2025
Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
Published on: August 25, 2014
From Breath to Brain: NICU Respiratory Interventions and Bedside Brain Signal Entropy Predict Later Autism Risk
Insights
This study identifies infants at high risk for Autism Spectrum Disorder (ASD) using non-invasive measures. Early detection of ASD risk in premature infants is possible before hospital discharge.
Area of Science:
- Neuroscience
- Neonatology
- Developmental Pediatrics
Background:
- Premature infants face risks like hypoxia and inflammation, increasing susceptibility to neurodevelopmental disorders such as Autism Spectrum Disorder (ASD).
- Early identification of infants at risk for ASD is crucial for timely intervention and improved outcomes.
- Developing accurate, non-invasive methods for early ASD risk assessment in neonates is a significant clinical need.
Purpose of the Study:
- To investigate the relationship between respiratory support burden, brain signal variability, inflammation, and the risk of developing ASD in premature infants.
- To identify non-invasive biomarkers for predicting ASD risk in early infancy.
Main Methods:
- Electroencephalography (EEG) was used to measure brain signal entropy in social and nonsocial resting states.
- Saliva samples were collected to assess inflammatory markers (cytokines).
- A novel Prognostic Respiratory Intensity Scoring Metric (PRISM) was calculated to quantify respiratory support needs.
Main Results:
- Higher PRISM scores correlated with increased brain signal entropy in the nonsocial resting state, particularly in female infants, potentially mediated by cytokines.
- This association was not significant in the social resting state, especially for male infants.
- A predictive model combining nonsocial resting state brain signal entropy, sex, and PRISM scores accurately identified infants at risk for ASD (88% accuracy).
Conclusions:
- Non-invasive measures, including EEG and PRISM scores, can effectively identify premature infants at high risk for ASD.
- These findings support the potential for early ASD risk stratification before hospital discharge, enabling prompt intervention.
- Understanding sex-specific differences in brain activity and inflammation may offer insights into ASD etiology.
Abstract:
Premature infants often experience hypoxia and require prolonged ventilation, which can trigger systemic inflammation, damage the developing brain, and increase the risk of neurodevelopmental disorders such as Autism Spectrum Disorder (ASD). Early intervention is key for ensuring optimal outcomes for those with ASD; thus emphasizing the critical importance of accurately identifying infants at risk as early as possible. Here, infants underwent electroencephalography during social (held) and nonsocial (not held) resting state conditions to assess brain signal variability, saliva collection to determine inflammation, calculation of a novel Prognostic Respiratory Intensity Scoring Metric (PRISM) to assess the burden of respiratory support, and ASD testing in toddlerhood. Higher PRISM scores were associated with increased brain signal entropy during the nonsocial resting state. However, this association was not observed in the social resting state condition - particularly for male babies. Interestingly in female infants, we saw that the relationship between brain signal entropy and PRISM scores were potentially mediated by cytokines. Notably, the interaction between nonsocial resting state brain signal entropy, sex, and PRISM scores predicted risk of developing ASD with 88% accuracy. These non-invasive measures can identify infants at the highest risk for an ASD diagnosis before discharge.
