# Predicting Neurodevelopmental Outcomes in Premature Infants with Multi-omic Measures (PRENOP)

> **NIH NIH F32** · UNIVERSITY OF CONNECTICUT STORRS · 2020 · $68,482

## Abstract

Abstract
Each year, an estimated 15 million babies are born preterm (<37 weeks' gestational age [GA])
globally. These preterm infants are exposed to repeated stressful and often painful procedures or
treatments as part of routine life-saving care within the neonatal intensive care unit (NICU). These
stressful exposures result in altered methylation patterns and gene expression that have been
associated with numerous negative sequelae for the infant and may be irreversible, including, blunted
or exaggerated stress reactivity, increased risk for negative behavior patterns and alterations in brain
microstructure. Understanding the epigenetic modifications that regulate persistent changes in gene
expression may lead to interventions that would improve outcomes for these infants giving them the
opportunity to enjoy a better life. The proposed application aims to rigorously examine: 1) genome-
wide methylation longitudinally; 2) changes in gene expression longitudinally; 3) absolute telomere
length, an innovative stress biomarker which has not, to our knowledge, been investigated serially
post-NICU discharge will be measured at multiple time points from birth through 24-months-
corrected-age during follow-up clinic visits; 4) associations between methylation, gene expression,
telomere length and neurodevelopmental outcomes. This innovative combination of measurements
has the potential to generate essential knowledge that may prove critical to improving
neurodevelopmental outcomes for this vulnerable population.

## Key facts

- **NIH application ID:** 9913380
- **Project number:** 5F32NR018591-02
- **Recipient organization:** UNIVERSITY OF CONNECTICUT STORRS
- **Principal Investigator:** SHARON Goldrich CASAVANT
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $68,482
- **Award type:** 5
- **Project period:** 2019-05-13 → 2021-05-12

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9913380

## Citation

> US National Institutes of Health, RePORTER application 9913380, Predicting Neurodevelopmental Outcomes in Premature Infants with Multi-omic Measures (PRENOP) (5F32NR018591-02). Retrieved via AI Analytics 2026-06-11 from https://api.ai-analytics.org/grant/nih/9913380. Licensed CC0.

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