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Targeted newborn metabolomics: prediction of gestational age from cord blood

Journal of Perinatology volume 42, pages 181–186 (2022)Cite this article

Subjects

Abstract

Objective

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.

Study Design

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.

Results

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%.

Conclusion

Models that include cord blood metabolites and birth weight appear to offer improvement in gestational age estimation over birth weight alone.

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Fig. 1: Receiver operator curves for associations with gestational age.

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Data availability

Data collected for the study including individual participant data and data dictionaries defining fields in the datasets have been made available to others through request to the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Data and Specimen Hub (DASH): https://dash.nichd.nih.gov/Resource/Tutorial. Data available include de-identified individual level screening and enrollment data, individual participant data, repeated measures during pregnancy, QTc repeated measures, repeated doses for vomiting, and corresponding data dictionaries. Related study documents made available include the study protocol, statistical analysis plan, case report forms, and informed consent documents. Data can be accessed through the NICHD-DASH website (https://dash.nichd.nih.gov/Study/20027) following user registration and a research data request process. The NICHD DASH Data Access Committee reviews all requests to determine that a requester’s proposed use of the data is scientifically and ethically appropriate and does not conflict with constraints or informed consent limitations identified by the institutions that submitted the data. Metabolic data can be accessed through the Bill & Melinda Gates foundation following appropriate procedures and data access request process.

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Acknowledgements

We thank the women who participated in the study, the dedicated study staff, practitioners at Masafu General Hospital, and members of the Infectious Diseases Research Collaboration (IDRC). We would also like to thank the staff at the State of Iowa Hygienic Laboratory for sample processing and analysis and Nancy Weathers and Bruce Bedell at the University of Iowa for data and sample management.

Funding

This research was support by grants from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (P01 HD059454) and the Bill and Melinda Gates Foundation (OPP1134783, OPP1141549, OPP1127641). The content is solely the responsibility of the authors and does not necessarily represent the official views of the Eunice Kennedy Shriver National Institute of Child Health and Human Development or the National Institutes of Health.

Author information

Authors and Affiliations

  1. Department of Epidemiology, University of Iowa, Iowa, IA, USA

    Elizabeth A. Jasper & Kelli K. Ryckman

  2. Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA, USA

    Scott P. Oltman & Laura L. Jelliffe-Pawlowski

  3. UCSF California Preterm Birth Initiative, San Francisco, CA, USA

    Scott P. Oltman & Laura L. Jelliffe-Pawlowski

  4. Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA

    Elizabeth E. Rogers

  5. Department of Pediatrics, University of Iowa, Iowa, IA, USA

    John M. Dagle & Jeffrey C. Murray

  6. Infectious Diseases Research Collaboration, Kampala, Uganda

    Moses Kamya, Abel Kakuru, Richard Kajubi, Teddy Ochieng, Harriet Adrama, Martin Okitwi & Peter Olwoch

  7. Department of Medicine, Makerere University College of Health Sciences, Kampala, Uganda

    Moses Kamya

  8. Department of Medicine, Stanford University Medical Center, Stanford, CA, USA

    Prasanna Jagannathan

  9. Department of Medicine, University of California, San Francisco School of Medicine, San Francisco, CA, USA

    Tamara D. Clark & Grant Dorsey

  10. Department of Pediatrics, University of California, San Francisco School of Medicine, San Francisco, CA, USA

    Theodore Ruel

Authors
  1. Elizabeth A. Jasper
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Contributions

KKR and EAJ designed the study analysis plan, performed analyses, drafted the initial manuscript, and reviewed and revised the manuscript. SPO, RK, TO, AK, HA, MO, and PO helped collect and analyze specimens and data and reviewed and revised the manuscript. EER, JMD, JCM, MK, TDC, GD, TR, PJ, and LLJ-P provided critical input on the intellectual content of the manuscript and reviewed and revised the manuscript. All authors approved the final manuscript as submitted and agreed to be accountable for all aspects of the work.

Corresponding author

Correspondence to Kelli K. Ryckman.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

The study was approved by the ethics committees of Makerere University School of Biomedical Sciences (Kampala, Uganda), the Uganda National Council for Science and Technology (Kampala, Uganda), the University of California San Francisco (San Francisco, CA, USA) and the University of Iowa (Iowa City, IA, USA). All study participants provided written informed consent.

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Jasper, E.A., Oltman, S.P., Rogers, E.E. et al. Targeted newborn metabolomics: prediction of gestational age from cord blood. J Perinatol 42, 181–186 (2022). https://doi.org/10.1038/s41372-021-01253-w

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