Metabolomics can provide new insights into perinatal nutrition

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TL;DR

This narrative review examines how metabolomics—the large-scale study of metabolites—can provide new insights into perinatal nutrition, focusing on gestational diabetes mellitus (GDM), intrauterine growth restriction (IUGR), and breast milk composition. Across 71 studies, key metabolites such as choline, glycine, lipids, and amino acids were consistently altered in GDM and IUGR, while human milk oligosaccharides, lipids, lactose, and choline were the most studied components of breast milk. Metabolomics offers a promising tool for personalized perinatal care by identifying metabolic fingerprints that may predict complications and guide nutrition for mothers and neonates.

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**Background:** The Developmental Origin of Health and Disease (DOHaD) hypothesis posits that perinatal events, including maternal nutrition and metabolic conditions, can affect an individual's health into adulthood. Gestational diabetes mellitus (GDM) and intrauterine growth restriction (IUGR) are major obstetrical syndromes that adversely affect both mother and offspring. Breast milk is the gold standard for neonatal nutrition, tailored to each infant's needs. Metabolomics, using techniques such as LC-MS, GC-MS, and ¹H-NMR spectroscopy, can identify and quantify metabolites in biological fluids, providing a molecular snapshot of physiological and pathological states. This non-systematic review discusses how metabolomics has been applied to investigate GDM, IUGR, and breast milk.

**Methods:** The authors searched PubMed for studies on metabolomics and GDM, IUGR, and breast milk, identifying 71 studies in total. For GDM, 32 studies (2010–2021) involving 3694 mothers with GDM and 3120 controls, plus 312 neonates born to mothers with GDM and 862 controls, were identified. LC-MS was the most used technique (45% of studies), and urine was the most analyzed sample (28%). For IUGR, 18 studies (2011–2020) included 365 mothers of neonates with IUGR and 998 controls, plus 338 neonates with IUGR and 337 controls. LC-MS was used in 42% of studies, and umbilical cord blood was the most analyzed sample (37%). For breast milk, 21 studies (2014–2020) involved 1497 mothers and 781 infants; ¹H-NMR was the most used technique (62.5%), and breast milk was the most analyzed sample (69.5%).

**Key Results:** In GDM, the most frequently reported metabolites were choline and its derivatives (n=7 studies), lipids and phospholipids (n=7), glycine (n=5), sphingomyelins (n=4), carnitine and acylcarnitine (n=4), and alanine, betaine, creatinine, and histidine (n=3 each). Choline derivatives showed variable directionality: increased in cord blood, urine, and serum in some studies, but decreased in serum, umbilical cord blood, amniotic fluid, and plasma in others. Glycine was consistently decreased across all five studies in cord blood, plasma, serum, breast milk, and amniotic fluid. Sphingomyelins were decreased in plasma but elevated in amniotic fluid of female foetuses. Carnitine and acylcarnitine were increased in urine and plasma but decreased in umbilical cord blood. In IUGR, the most relevant metabolites were tyrosine (n=6 studies), valine (n=5), alanine (n=5), myoinositol (n=4), glutamine and acetyl-glutamine (n=4), choline and phosphocholine (n=3), and methionine (n=3). Tyrosine was increased in umbilical cord blood of monochorionic twins and singletons with IUGR but decreased in urine, maternal hair, and plasma in other studies. Myoinositol was consistently elevated in the urine of infants with IUGR across all four studies. In breast milk studies, the most relevant metabolites were human milk oligosaccharides (HMOs) (n=7 studies), lipids (n=7), lactose (n=6), and choline and its derivatives (n=5). HMO levels were higher in preterm than term milk. One study identified 98 lipids not previously detected in breast milk. Lactose was elevated in milk of mothers who delivered large-for-gestational-age or IUGR infants and in preterm milk, but decreased in milk of mothers with inflammatory bowel disease.

**Clinical Implications:** Metabolomics can identify specific metabolic alterations associated with GDM and IUGR, potentially enabling earlier diagnosis and better risk stratification. For GDM, metabolites such as choline, glycine, and sphingomyelins may serve as biomarkers of disease progression and type 2 diabetes risk. For IUGR, metabolites like tyrosine, myoinositol, and valine may help predict and characterize the condition. Metabolomic analysis of breast milk reveals how its composition adapts to the needs of preterm, IUGR, and large-for-gestational-age infants, and can distinguish between mothers with different metabolic profiles. These insights support the move toward personalized perinatal nutrition and care, though further studies are needed to validate predictive biomarkers and translate these findings into clinical practice.