The Journal of clinical endocrinology and metabolism · 2019
Cord Blood Metabolomics: Association With Newborn Anthropometrics and C-Peptide Across Ancestries.
СтатьяНаблюдательное исследованиеПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Kadakia Rachel, Talbot Octavious, Kuang Alan, Bain James R, Muehlbauer Michael J, Stevens Robert D, Ilkayeva Olga R, Lowe Lynn P, Metzger Boyd E, Newgard Christopher B, Scholtens Denise M, Lowe William L, HAPO Study Cooperative Research Group
Аннотация
CONTEXT: Newborn adiposity is associated with childhood obesity. Cord blood metabolomics is one approach that can be used to understand early-life contributors to adiposity and insulin resistance.
OBJECTIVE: To determine the association of cord blood metabolites with newborn adiposity and hyperinsulinemia in a multiethnic cohort of newborns.
DESIGN: Cross-sectional, observational study.
SETTING: Hyperglycemia and Adverse Pregnancy Outcome study.
PARTICIPANTS: One thousand six hundred multiethnic mother-newborn pairs.
MAIN OUTCOME MEASURE: Cord blood C-peptide, birthweight, and newborn sum of skinfolds.
RESULTS: Meta-analyses across four ancestry groups (Afro-Caribbean, Northern European, Thai, and Mexican American) demonstrated significant associations of cord blood metabolites with cord blood C-peptide, birthweight, and newborn sum of skinfolds. Several metabolites, including branched-chain amino acids (BCAAs), medium- and long-chain acylcarnitines, nonesterified fatty acids, and triglycerides were negatively associated with cord C-peptide but positively associated with birthweight and/or sum of skinfolds. 1,5-Anhydroglucitol, an inverse marker of recent maternal glycemia, was significantly inversely associated with birthweight and sum of skinfolds. Network analyses revealed groups of interrelated amino acid, acylcarnitine, and fatty acid metabolites associated with all three newborn outcomes.
CONCLUSIONS: Cord blood metabolites are associated with newborn size and cord blood C-peptide levels after adjustment for maternal body mass index and glucose during pregnancy. Negative associations of metabolites with C-peptide at birth were observed. 1,5-Anhydroglucitol appears to be a marker of adiposity in newborns. BCAAs were individually associated with birthweight and demonstrated possible associations with newborn adiposity in network analyses.
OBJECTIVE: To determine the association of cord blood metabolites with newborn adiposity and hyperinsulinemia in a multiethnic cohort of newborns.
DESIGN: Cross-sectional, observational study.
SETTING: Hyperglycemia and Adverse Pregnancy Outcome study.
PARTICIPANTS: One thousand six hundred multiethnic mother-newborn pairs.
MAIN OUTCOME MEASURE: Cord blood C-peptide, birthweight, and newborn sum of skinfolds.
RESULTS: Meta-analyses across four ancestry groups (Afro-Caribbean, Northern European, Thai, and Mexican American) demonstrated significant associations of cord blood metabolites with cord blood C-peptide, birthweight, and newborn sum of skinfolds. Several metabolites, including branched-chain amino acids (BCAAs), medium- and long-chain acylcarnitines, nonesterified fatty acids, and triglycerides were negatively associated with cord C-peptide but positively associated with birthweight and/or sum of skinfolds. 1,5-Anhydroglucitol, an inverse marker of recent maternal glycemia, was significantly inversely associated with birthweight and sum of skinfolds. Network analyses revealed groups of interrelated amino acid, acylcarnitine, and fatty acid metabolites associated with all three newborn outcomes.
CONCLUSIONS: Cord blood metabolites are associated with newborn size and cord blood C-peptide levels after adjustment for maternal body mass index and glucose during pregnancy. Negative associations of metabolites with C-peptide at birth were observed. 1,5-Anhydroglucitol appears to be a marker of adiposity in newborns. BCAAs were individually associated with birthweight and demonstrated possible associations with newborn adiposity in network analyses.