Daragh S O'Boyle1, Warwick B Dunn2, Donna O'Neill3, Jennifer A Kirwan4, David I Broadhurst5, Boubou Hallberg6, Geraldine B Boylan1, Deirdre M Murray7. 1. Department of Pediatrics and Child Health, University College Cork, Cork, Ireland; The Irish Centre for Maternal and Child Health Research (INFANT), University College Cork, Cork, Ireland. 2. School of Biosciences and Phenome Centre Birmingham, University of Birmingham, Birmingham, UK; Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK. 3. School of Biosciences and Phenome Centre Birmingham, University of Birmingham, Birmingham, UK. 4. Berlin Institute for Health Metabolomics Platform, Max-Delbrück-Center for Molecular Medicine, Berlin, Germany. 5. Center for Integrative Metabolomics & Computational Biology, School of Science, Edith Cowan University, Joondalup, Australia. 6. Department of Neonatology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden. 7. Department of Pediatrics and Child Health, University College Cork, Cork, Ireland; The Irish Centre for Maternal and Child Health Research (INFANT), University College Cork, Cork, Ireland. Electronic address: d.murray@ucc.ie.
Abstract
OBJECTIVE: To validate our previously identified candidate metabolites, and to assess the ability of these metabolites to predict hypoxic-ischemic encephalopathy (HIE) both individually and combined with clinical data. STUDY DESIGN: Term neonates with signs of perinatal asphyxia, with and without HIE, and matched controls were recruited prospectively at birth from 2 large maternity units. Umbilical cord blood was collected for later batch metabolomic analysis by mass spectroscopy along with clinical details. The optimum selection of clinical and metabolites features with the ability to predict the development of HIE was determined using logistic regression modelling and machine learning techniques. Outcome of HIE was determined by clinical Sarnat grading and confirmed by electroencephalogram grade at 24 hours. RESULTS: Fifteen of 27 candidate metabolites showed significant alteration in infants with perinatal asphyxia or HIE when compared with matched controls. Metabolomic data predicted the development of HIE with an area under the curve of 0.67 (95% CI, 0.62-0.71). Lactic acid and alanine were the primary metabolite predictors for the development of HIE, and when combined with clinical data, gave an area under the curve of 0.96 (95% CI, 0.92-0.95). CONCLUSIONS: By combining clinical and metabolic data, accurate identification of infants who will develop HIE is possible shortly after birth, allowing early initiation of therapeutic hypothermia.
OBJECTIVE: To validate our previously identified candidate metabolites, and to assess the ability of these metabolites to predict hypoxic-ischemic encephalopathy (HIE) both individually and combined with clinical data. STUDY DESIGN: Term neonates with signs of perinatal asphyxia, with and without HIE, and matched controls were recruited prospectively at birth from 2 large maternity units. Umbilical cord blood was collected for later batch metabolomic analysis by mass spectroscopy along with clinical details. The optimum selection of clinical and metabolites features with the ability to predict the development of HIE was determined using logistic regression modelling and machine learning techniques. Outcome of HIE was determined by clinical Sarnat grading and confirmed by electroencephalogram grade at 24 hours. RESULTS: Fifteen of 27 candidate metabolites showed significant alteration in infants with perinatal asphyxia or HIE when compared with matched controls. Metabolomic data predicted the development of HIE with an area under the curve of 0.67 (95% CI, 0.62-0.71). Lactic acid and alanine were the primary metabolite predictors for the development of HIE, and when combined with clinical data, gave an area under the curve of 0.96 (95% CI, 0.92-0.95). CONCLUSIONS: By combining clinical and metabolic data, accurate identification of infants who will develop HIE is possible shortly after birth, allowing early initiation of therapeutic hypothermia.
Authors: Gabriel Fernando Todeschi Variane; João Paulo Vasques Camargo; Daniela Pereira Rodrigues; Maurício Magalhães; Marcelo Jenné Mimica Journal: Front Pediatr Date: 2022-03-23 Impact factor: 3.418
Authors: Catherine Mooney; Daragh O'Boyle; Mikael Finder; Boubou Hallberg; Brian H Walsh; David C Henshall; Geraldine B Boylan; Deirdre M Murray Journal: Heliyon Date: 2021-06-29