Journal article
Targeted newborn metabolomics: prediction of gestational age from cord blood
Journal of perinatology, Vol.42(2), pp.181-186
02/2022
DOI: 10.1038/s41372-021-01253-w
PMCID: PMC8830770
PMID: 35067676
Abstract
Our study sought to determine whether metabolites from a retrospective collection of banked cord blood specimens could accurately estimate gestational age and to validate these findings in cord blood samples from Busia, Uganda.
Forty-seven metabolites were measured by tandem mass spectrometry or enzymatic assays from 942 banked cord blood samples. Multiple linear regression was performed, and the best model was used to predict gestational age, in weeks, for 150 newborns from Busia, Uganda.
The model including metabolites and birthweight, predicted the gestational ages within 2 weeks for 76.7% of the Ugandan cohort. Importantly, this model estimated the prevalence of preterm birth <34 weeks closer to the actual prevalence (4.67% and 4.00%, respectively) than a model with only birthweight which overestimates the prevalence by 283%.
Models that include cord blood metabolites and birth weight appear to offer improvement in gestational age estimation over birth weight alone.
Details
- Title: Subtitle
- Targeted newborn metabolomics: prediction of gestational age from cord blood
- Creators
- Elizabeth A Jasper - Department of Epidemiology, University of Iowa, Iowa, IA, USAScott P Oltman - UCSF California Preterm Birth Initiative, San Francisco, CA, USAElizabeth E Rogers - Department of Pediatrics, University of California San Francisco, San Francisco, CA, USAJohn M Dagle - Department of Pediatrics, University of Iowa, Iowa, IA, USAJeffrey C Murray - Department of Pediatrics, University of Iowa, Iowa, IA, USAMoses Kamya - Department of Medicine, Makerere University College of Health Sciences, Kampala, UgandaAbel Kakuru - Infectious Diseases Research Collaboration, Kampala, UgandaRichard Kajubi - Infectious Diseases Research Collaboration, Kampala, UgandaTeddy Ochieng - Infectious Diseases Research Collaboration, Kampala, UgandaHarriet Adrama - Infectious Diseases Research Collaboration, Kampala, UgandaMartin Okitwi - Infectious Diseases Research Collaboration, Kampala, UgandaPeter Olwoch - Infectious Diseases Research Collaboration, Kampala, UgandaPrasanna Jagannathan - Department of Medicine, Stanford University Medical Center, Stanford, CA, USATamara D Clark - Department of Medicine, University of California, San Francisco School of Medicine, San Francisco, CA, USAGrant Dorsey - Department of Medicine, University of California, San Francisco School of Medicine, San Francisco, CA, USATheodore Ruel - Department of Pediatrics, University of California, San Francisco School of Medicine, San Francisco, CA, USALaura L Jelliffe-Pawlowski - UCSF California Preterm Birth Initiative, San Francisco, CA, USAKelli K Ryckman - Department of Epidemiology, University of Iowa, Iowa, IA, USA. Kelli-ryckman@uiowa.edu
- Resource Type
- Journal article
- Publication Details
- Journal of perinatology, Vol.42(2), pp.181-186
- DOI
- 10.1038/s41372-021-01253-w
- PMID
- 35067676
- PMCID
- PMC8830770
- NLM abbreviation
- J Perinatol
- ISSN
- 0743-8346
- eISSN
- 1476-5543
- Grant note
- OPP1134783, OPP1141549, OPP1127641 / Bill and Melinda Gates Foundation (Bill & Melinda Gates Foundation) P01 HD059454 / NICHD NIH HHS
- Language
- English
- Date published
- 02/2022
- Academic Unit
- Anatomy and Cell Biology; Stead Family Department of Pediatrics; Epidemiology; Pediatric Dentistry; Craniofacial Anomalies Research Center; Biochemistry and Molecular Biology; Dental Research; Neonatology
- Record Identifier
- 9984216628002771
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