New research will help health-care practitioners to more accurately diagnose disease and illness in newborn babies from urine samples, according to a study by researchers at the University of Alberta and the Universidad Autónoma de Zacatecas.
The study examined the chemical composition of urine samples from 48 healthy, full-term newborn babies in the first hours after their birth, helping to establish a baseline for healthy chemical levels. Urine can be used to diagnose and monitor many conditions in infants, including metabolic disorders, genetic diseases, and birth-trauma effects.
“The challenge is that we do not have reference points for healthy ranges of these chemicals in urine for newborn babies,” explained David Wishart, professor in the University of Alberta's Department of Biological Sciences, Department of Computing Science, and Department of Laboratory Medicine and Pathology. “As a result, it's hard for doctors or clinical chemists to determine if a newborn is really sick or their chemical concentrations in urine or blood are normal.”
The research team, led by Wishart in partnership with Yamile Lopez-Herndandez from the Universidad Autónoma de Zacatecas in Zacatecas, Mexico, used mass spectrometry to measure the concentrations of nearly 140 different chemicals in the babies’ urine. The results quantified 86 chemicals that had never been measured in newborn urine before and another 20 chemicals that had never even been measured in human urine before.
“This research is really intended to help doctors and clinical chemists make more informed diagnoses with newborns using urine analysis,” explained Wishart. “It provides reference data that every doctor or neonatologist around the world can freely use in order to compare sick newborns with their healthy counterparts.”
Funding for this research was provided by the Canada Foundation for Innovation, the Canadian Institutes of Health Research, CONACyT, Genome Canada, and Western Economic Diversification Canada.
The paper, “The urinary metabolome of healthy newborns,” was published in Metabolites (doi: 10.3390/metabo10040165).