George Wehby and colleagues at the University of Iowa in the U.S. will evaluate newborn metabolic biomarkers for their ability to predict gestational age, and identify associations between them and long-term academic achievement. They will analyze existing newborn metabolic profiles and academic tests from almost one million children in Iowa born between 1980 and 2006 to identify the most predictive biomarkers. In the future they will expand their method to developing countries to help estimate gestational age and identify newborns at risk of neurodevelopmental defects. Being able to accurately determine gestational age is critical in preterm birth, which is the leading cause of child death worldwide. And knowing which regions have the highest incidence of preterm births would help better target prevention strategies. In Phase I, they identified candidate biomarkers that can be detected by tandem mass spectrometry using existing dried blood spot samples and based on around 150,000 children born between 1980 and 2006 in Iowa, they developed a predictive model for gestational age. With follow-on funding, through a grant awarded to Kelli Ryckman, their model will be tested using around 2,000 cord blood samples from newborns in Bangladesh, Pakistan and Tanzania, and refine it to improve accuracy by measuring additional biomarkers such as hemoglobin.
More information about Explore New Ways to Measure Fetal and Infant Brain Development (Round 13)