Alterations in newborn metabolite patterns with preterm birth and diabetes in pregnancy

Heindel, J. J. et al. Developmental origins of health and disease: integrating environmental influences. Endocrinology 156, 3416–3421 (2015).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Hoffman, D. J., Reynolds, R. M. & Hardy, D. B. Developmental origins of health and disease: current knowledge and potential mechanisms. Nutr. Rev. 75, 951–970 (2017).

Article  PubMed  Google Scholar 

Bianco, M. E. & Josefson, J. L. Hyperglycemia during pregnancy and long-term offspring outcomes. Curr. Diab. Rep. 19, 143 (2019).

Article  PubMed  PubMed Central  Google Scholar 

Boney, C. M., Verma, A., Tucker, R. & Vohr, B. R. Metabolic syndrome in childhood: association with birth weight, maternal obesity, and gestational diabetes mellitus. Pediatrics 115, e290–e296 (2005).

Article  PubMed  Google Scholar 

Catalano, P. M. et al. The hyperglycemia and adverse pregnancy outcome study: associations of GDM and obesity with pregnancy outcomes. Diab. Care 35, 780–786 (2012).

Article  CAS  Google Scholar 

Crume, T. L. et al. The impact of in utero exposure to diabetes on childhood body mass index growth trajectories: the Epoch study. J. Pediatrics 158, 941–946 (2011).

Article  Google Scholar 

Hammoud, N. M. et al. Long-term BMI and growth profiles in offspring of women with gestational diabetes. Diabetologia 61, 1037–1045 (2018).

Article  PubMed  PubMed Central  Google Scholar 

Group, H. S. C. R. Hyperglycemia and adverse pregnancy outcome (Hapo) study: associations with neonatal anthropometrics. Diabetes 58, 453–459 (2009).

Article  Google Scholar 

Logan, K. M., Gale, C., Hyde, M. J., Santhakumaran, S. & Modi, N. Diabetes in pregnancy and infant adiposity: systematic review and meta-analysis. Arch. Dis. Child Fetal Neonatal. Ed. 102, F65–F72 (2017).

Article  PubMed  Google Scholar 

Buck, C. O., Shabanova, V., Clark, R. H. & Taylor, S. N. Diabetes in pregnancy, neonatal morbidities, and early growth in moderate or late preterm infants. Pediatrics. 152, e2023061285(2023).

Landon, M. B. et al. A multicenter, randomized trial of treatment for mild gestational diabetes. N. Engl. J. Med. 361, 1339–1348 (2009).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Buck, C. O., Shabanova, V. & Taylor, S. N. Growth patterns among late preterm infants of mothers with diabetes. J. Matern. Fetal Neonatal. Med. 35, 1–8 (2022).

Johnson, M. J., Wootton, S. A., Leaf, A. A. & Jackson, A. A. Preterm birth and body composition at term equivalent age: a systematic review and meta-analysis. Pediatrics 130, E640–E649 (2012).

Article  PubMed  Google Scholar 

Noto, A., Fanos, V. & Dessi, A. Metabolomics in newborns. Adv. Clin. Chem. 74, 35–61 (2016).

Article  CAS  PubMed  Google Scholar 

Voerman, E. et al. Associations of maternal and infant metabolite profiles with foetal growth and the odds of adverse birth outcomes. Pediatr. Obes. 17, e12844 (2022).

Article  PubMed  Google Scholar 

Hellmuth, C. et al. Cord blood metabolome is highly associated with birth weight, but less predictive for later weight development. Obes. Facts 10, 85–100 (2017).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kadakia, R. et al. Cord blood metabolomics: association with newborn anthropometrics and C-peptide across ancestries. J. Clin. Endocrinol. Metab. 104, 4459–4472 (2019).

Article  PubMed  PubMed Central  Google Scholar 

Patel, N. et al. Cord metabolic profiles in obese pregnant women: insights into offspring growth and body composition. J. Clin. Endocrinol. Metab. 103, 346–355 (2018).

Article  PubMed  Google Scholar 

Lowe, W. L. Jr. et al. Maternal BMI and glycemia impact the fetal metabolome. Diab. Care 40, 902–910 (2017).

Article  CAS  Google Scholar 

Lu, Y. P. et al. Fetal serum metabolites are independently associated with gestational diabetes mellitus. Cell Physiol. Biochem. 45, 625–638 (2018).

Article  CAS  PubMed  Google Scholar 

Schmelzle, H. R. & Fusch, C. Body fat in neonates and young infants: validation of skinfold thickness versus dual-energy X-ray absorptiometry. Am. J. Clin. Nutr. 76, 1096–1100 (2002).

Article  CAS  PubMed  Google Scholar 

Dauncey, M. J., Gandy, G. & Gairdner, D. Assessment of total body fat in infancy from skinfold thickness measurements. Arch. Dis. Child 52, 223–227 (1977).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Daly-Wolfe, K. M., Jordan, K. C., Slater, H., Beachy, J. C. & Moyer-Mileur, L. J. Mid-arm circumference is a reliable method to estimate adiposity in preterm and term infants. Pediatr. Res. 78, 336–341 (2015).

Article  PubMed  Google Scholar 

Cheikh Ismail, L. et al. Precision of recumbent crown-heel length when using an infantometer. BMC Pediatr. 16, 186 (2016).

Article  PubMed  PubMed Central  Google Scholar 

Fenton, T. R. et al. Validating the weight gain of preterm infants between the reference growth curve of the fetus and the term infant. BMC Pediatrics 13, 92 (2013).

Aris, I. M. et al. Body fat in Singaporean infants: development of body fat prediction equations in Asian newborns. Eur. J. Clin. Nutr. 67, 922–927 (2013).

Article  CAS  PubMed  Google Scholar 

Slaughter, M. H. et al. Skinfold equations for estimation of body fatness in children and youth. Hum. Biol. 60, 709–723 (1988).

CAS  PubMed  Google Scholar 

Wendel, D. et al. body composition estimation using skinfolds in children with and without health conditions affecting growth and body composition. Ann. Hum. Biol. 44, 108–120 (2017).

Article  PubMed  Google Scholar 

Acog Practice Bulletin No. 201: Pregestational Diabetes Mellitus. Obstet. Gynecol 132, e228-e248 (2018).

Acog Practice Bulletin No. 190 Summary: Gestational Diabetes Mellitus. Obstet. Gynecol 131, 406-408 (2018).

Bijlsma, S. et al. Large-scale human metabolomics studies: a strategy for data (pre-) processing and validation. Anal. Chem. 78, 567–574 (2006).

Article  CAS  PubMed  Google Scholar 

Fabrigar, L. R., Wegener, D. T. & Ebrary, I. Exploratory Factor Analysis 1st edn (Oxford University Press, 2012).

Knekta, E., Runyon, C. & Eddy, S. One size doesn’t fit all: using factor analysis to gather validity evidence when using surveys in your research. Cbe-Life Sci. Educ. 18, rm1 (2019).

Kramer, A., Green, J., Pollard, J. Jr. & Tugendreich, S. Causal analysis approaches in ingenuity pathway analysis. Bioinformatics 30, 523–530 (2014).

Article  PubMed  Google Scholar 

Mudunuri, U., Che, A., Yi, M. & Stephens, R. M. Biodbnet: the biological database network. Bioinformatics 25, 555–556 (2009).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Lopez-Ibanez, J., Pazos, F. & Chagoyen, M. Mbrole 2.0-functional enrichment of chemical compounds. Nucleic Acids Res. 44, W201–W204 (2016).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kim, S. et al. PubChem 2023 update. Nucleic Acids Res. 51, D1373–D1380 (2023).

Article  PubMed  Google Scholar 

Wishart, D. S. et al. Hmdb 5.0: the human metabolome database for 2022. Nucleic Acids Res. 50, D622–D631 (2022).

Article  CAS  PubMed  Google Scholar 

Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B 57, 289–300 (1995).

Article  Google Scholar 

Mansell, T. et al. The newborn metabolome: associations with gestational diabetes, sex, gestation, birth mode, and birth weight. Pediatr. Res. 91, 1864–1873 (2022).

Article  CAS  PubMed 

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