(OR17-02-26) Metabolites Measured Over the First 7 Days of Life Predict Severe Morbidity or Mortality in Infants Born at <32 Weeks

Monday, July 27, 2026

10:42 AM - 10:54 AM ET

Location: Maryland Ballroom C

Emerging Leaders in Nutrition Science Poster Competition

Presenting Author(s)

Emily C. Hanselman, PhD, RDN

Postdoctoral Fellow
Indiana University
Bloomington, Indiana, United States

Disclosure(s): No relevant financial relationship(s) with ineligible companies to disclose.

Co-Author(s)

SO

Scott P. Oltman

University of California, San Francisco
San Francisco, California, United States
JM

James A. Merchant

University of Iowa College of Public Health
Iowa City, Iowa, United States
EP

Erik S. Parker

School of Public Health-Bloomington, Indiana University
Bloomington, Indiana, United States
AM

Allison M. Momany

University of Iowa
Iowa City, Iowa, United States
JD

John M. Dagle

University of Iowa
Iowa City, Iowa, United States
LS

Louie M. Swander

University of California, San Francisco
San Francisco, California, United States
AC

Angela G. Campbell

School of Public Health-Bloomington, Indiana University
Bloomington, Indiana, United States
ER

Elizabeth E. Rogers

University of California, San Francisco
San Francisco, California, United States
LJ

Laura L. Jeliffe-Pawlowski

New York University
New York, New York, United States
KR

Kelli K. Ryckman

School of Public Health-Bloomington, Indiana University
Bloomington, Indiana, United States

Disclosure(s):

Emily C. Hanselman, PhD, RDN: No relevant financial relationship(s) with ineligible companies to disclose.

Objectives: The very preterm neonate (VPT; < 32 weeks gestational age) is at risk for certain medical morbidities due to their unique physiology, yet our ability to predict which infants will experience severe complications is limited. The objective of this study is to develop and assess a prediction model for VPT infants using metabolites routinely measured in the national newborn screen over the first week of life to predict severe morbidity or mortality at discharge.

Methods: In this prospective longitudinal study, we enrolled 339 VPT infants at University of California San Francisco Benioff Children’s Hospital and University of Iowa Hospitals and Clinics and analyzed cord blood and blood spot specimens at day of life 0, 1.5, 3, 5 and 7 using tandem mass spectrometry per standard newborn screening methodology to assess amino acids and acylcarnitines, key intermediates of metabolism, gluconeogenesis and beta-oxidation. We then performed timepoint-specific penalized logistic regression models using the least absolute shrinkage and selection operator (LASSO) to identify significant metabolite predictors of the composite morbidity (intraventricular hemorrhage, periventricular leukomalacia, necrotizing enterocolitis, retinopathy of prematurity, and bronchopulmonary dysplasia) or mortality outcome. We used mixed-effects logistic regression models with a random effect for individuals to account for repeated measurements within infants.

Results: The model of metabolite profiles measured during the first week of life had a strong predictive performance (AUC > 0.84 at all timepoints) of composite morbidity or mortality. Metabolites whose longitudinal trajectories were associated with the outcome over the first week of life (i.e., dicarboxylic C4 acylcarnitine, C4 acylcarnitine, citrulline and 17-hydroxyprogesterone) remained significant (p < 0.001) after adjustment for time at measurement, gestational age, birth weight, and sample type (cord or venous).

Conclusions: Newborn screen metabolites measured over the first week of life predict severe morbidity or mortality in VPT infants. Metabolic profile models offer a precision approach to the diagnostic and clinical management of this vulnerable population and may lead to the development of new therapeutic agents to improve health outcomes.

Funding Sources: NICHD