Maternal Dietary Protein Patterns and Neonatal Anthropometrics: A Prospective Study with Insights from NMR Metabolomics in Amniotic Fluid.
Charikleia KyrkouCharalambos FotakisAristea DimitropoulouFoteini TsakoumakiPanagiotis ZoumpoulakisGeorgios C MenexesCostas G BiliaderisApostolos P AthanasiadisAlexandra-Maria MichaelidouPublished in: Metabolites (2023)
This study aimed to characterize dietary protein patterns (DPPs) in a sample pool of 298 well-nourished pregnant women and explore potential associations between DPPs and neonatal anthropometrics. Maternal dietary data were collected using a validated food frequency questionnaire. Neonatal anthropometrics were abstracted from health booklets. A hierarchical cluster analysis identified three DPPs: "Dairy-focused", "Med-fusion", and "Traditional-inspired". The "Dairy-focused" DPP exhibited the highest protein intake ( p < 0.001), predominantly animal protein ( p < 0.001), while the "Traditional-inspired" DPP presented higher plant protein ( p < 0.001) and fiber intakes ( p < 0.001), and, therefore, a reduced carbohydrate-to-fiber quotient ( p < 0.001). The "Med-fusion" DPP had the lowest protein-to-fat ratio ( p < 0.001). Infants of women following the "Dairy-focused" DPP had the highest birth height centiles ( p = 0.007) and the lowest ponderal index ( p = 0.003). The NMR-metabolomics approach was implemented on a subset of women that provided amniotic fluid (AF) specimens ( n = 62) to elucidate distinct metabolic signatures associated with DPPs. PCA and OPLS-DA models verified the adherence to three DPPs, revealing that the levels of several amino acids (AAs) were the highest in "Dairy-focused", reflecting its protein-rich nature. The "Traditional-inspired" DPP showed decreased AAs and glucose levels. This knowledge may contribute to optimizing maternal dietary recommendations. Further research is needed to validate these findings and better understand the relationships between maternal diet, AF metabolic signature, and neonatal anthropometrics.
Keyphrases
- amino acid
- pregnant women
- pregnancy outcomes
- protein protein
- birth weight
- healthcare
- binding protein
- mass spectrometry
- public health
- type diabetes
- polycystic ovary syndrome
- atrial fibrillation
- small molecule
- climate change
- gene expression
- risk assessment
- weight gain
- skeletal muscle
- blood pressure
- weight loss
- social media
- mesenchymal stem cells
- deep learning
- african american