Metabolic switch in infants with congenital heart defect undergoing atrial septostomy.
Creators
- 1. Neonatal Research Unit, Health Research Institute Hospital La Fe, Avenida Fernando Abril Martorell 106, 46026 Valencia, Spain
- 2. Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland, Stenbackinkatu 9, 00029 Helsinki, Finland.
- 3. University of Oulu, Pentti Kaiteran katu 1, 90570, Oulu, Finland.
- 4. Leitat Technological Center and Analytical Unit, Health Research Institute La Fe, Avenida. Fernando Abril Martorell 106, 46026 Valencia, Spain
- 5. Department of Anaesthesia and Intensive Care, , Helsinki University Hospital and University of Helsinki, Helsinki, Stenbackinkatu 9, 00029 Helsinki, Finland.
- 6. Pediatric Research Center, Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Stenbackinkatu 9, 00029 Helsinki, Finland
- 7. Neonatal Research Unit, Health Research Institute Hospital La Fe, Avenida Fernando andDivision of Neonatology, University & Polytechnic Hospital La Fe, Avenida Fernando Abril Martorell 106, 46026 Valencia, Spain
Description
Transposition of the great arteries (TGA), a congenital heart disease characterized by hypoxemia and abnormal circulation, is responsible for brain alterations and long-term neurodevelopmental delay. Atrial septostomy causes a sudden increase in arterial blood oxygenation leading to complex metabolic changes. We studied the metabolic switch in infants with TGA after atrial septostomy in order to shed light on the effect of the changes in cerebral oxygenation. Blood samples of 9 newborns with TGA were collected 5 minutes before and at several time points after the intervention (i.e. 5 min, 6 h, 24 h, 48 h, and 72 h). Plasma samples were measured employing Ultra-Performance-Liquid-Chromatography quadrupole-time-of-flight-Mass-Spectrometry (UPLC-qTOFMS) operating in positive and negative electrospray mode. Peak tables were extracted using the XCMS online platform and within-batch effect was corrected employing quality control samples and support vector regression. After data clean-up and MS/MS-based annotation, statistical analysis was performed employing Principal Component Analysis (PCA), Pearson correlations, and network analysis (mummichog algorithm, and Metaboanalyst). We observed correlation of metabolic features with cerebral tissue oxygen extraction (FTOE) and affected pathways with significant differences included pentose phosphate pathway (P-value = 0. 00002), pentose and glucuronate interconversions (P-value = 0. 003), ascorbate and aldarate metabolism (P-value = 0. 013), inositol phosphate metabolism (P-value = 0. 03), and primary bile acid biosynthesis (P-value = 0. 04).
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