Maternal adiposity alters the human milk metabolome: associations between nonglucose monosaccharides and infant adiposity

Human Milk Composition Is Associated with Maternal Body Mass Index in a Cross-Sectional, Untargeted Metabolomics Analysis of Human Milk from Guatemalan Mothers

Background

Maternal overweight and obesity has been associated with poor lactation performance including delayed lactogenesis and reduced duration. However, the effect on human milk composition is less well understood.

Objectives

We evaluated the relationship of maternal BMI on the human milk metabolome among Guatemalan mothers.

Methods

We used data from 75 Guatemalan mothers who participated in the Household Air Pollution Intervention Network trial. Maternal BMI was measured between 9 and <20 weeks of gestation. Milk samples were collected at a single time point using aseptic collection from one breast at 6 mo postpartum and analyzed using high-resolution mass spectrometry. A cross-sectional untargeted high-resolution metabolomics analysis was performed by coupling hydrophilic interaction liquid chromatography (HILIC) and reverse phase C18 chromatography with mass spectrometry. Metabolic features associated with maternal BMI were determined by a metabolome-wide association study (MWAS), adjusting for baseline maternal age, education, and dietary diversity, and perturbations in metabolic pathways were identified by pathway enrichment analysis.

Results

The mean age of participants at baseline was 23.62 ± 3.81 y, and mean BMI was 24.27 ± 4.22 kg/m2. Of the total metabolic features detected by HILIC column (19,199 features) and by C18 column (11,594 features), BMI was associated with 1026 HILIC and 500 C18 features. Enriched pathways represented amino acid metabolism, galactose metabolism, and xenobiotic metabolic metabolism. However, no significant features were identified after adjusting for multiple comparisons using the Benjamini-Hochberg false discovery rate procedure (FDRBH < 0.2).

Conclusions

Findings from this untargeted MWAS indicate that maternal BMI is associated with metabolic perturbations of galactose metabolism, xenobiotic metabolism, and xenobiotic metabolism by cytochrome p450 and biosynthesis of amino acid pathways. Significant metabolic pathway alterations detected in human milk were associated with energy metabolism-related pathways including carbohydrate and amino acid metabolism.This trial was registered at clinicaltrials.gov as NCT02944682.

Understanding risk and causal mechanisms for developing obesity in infants and young children: A National Institutes of Health workshop

Obesity in children remains a major public health problem, with the current prevalence in youth ages 2-19 years estimated to be 19.7%. Despite progress in identifying risk factors, current models do not accurately predict development of obesity in early childhood. There is also substantial individual variability in response to a given intervention that is not well understood. On April 29-30, 2021, the National Institutes of Health convened a virtual workshop on "Understanding Risk and Causal Mechanisms for Developing Obesity in Infants and Young Children." The workshop brought together scientists from diverse disciplines to discuss (1) what is known regarding epidemiology and underlying biological and behavioral mechanisms for rapid weight gain and development of obesity and (2) what new approaches can improve risk prediction and gain novel insights into causes of obesity in early life. Participants identified gaps and opportunities for future research to advance understanding of risk and underlying mechanisms for development of obesity in early life. It was emphasized that future studies will require multi-disciplinary efforts across basic, behavioral, and clinical sciences. An exposome framework is needed to elucidate how behavioral, biological, and environmental risk factors interact. Use of novel statistical methods may provide greater insights into causal mechanisms.

Exercised breastmilk: a kick-start to prevent childhood obesity?

Exercise has systemic health benefits through effects on multiple tissues, with intertissue communication. Recent studies indicate that exercise may improve breastmilk composition and thereby reduce the intergenerational transmission of obesity. Even if breastmilk is considered optimal infant nutrition, there is evidence for variations in its composition between mothers who are normal weight, those with obesity, and those who are physically active. Nutrition early in life is important for later-life susceptibility to obesity and other metabolic diseases, and maternal exercise may provide protection against the development of metabolic disease. Here we summarize recent research on the influence of maternal obesity on breastmilk composition and discuss the potential role of exercise-induced adaptations to breastmilk as a kick-start to prevent childhood obesity.

The visceral adipose tissue bacterial microbiota provides a signature of obesity based on inferred metagenomic functions

BACKGROUND

Metabolic inflammation mediated obesity requires bacterial molecules to trigger immune and adipose cells leading to inflammation and adipose depot development. In addition to the well-established gut microbiota dysbiosis, a leaky gut has been identified in patients with obesity and animal models, characterized by the presence of a tissue microbiota in the adipose fat pads.

METHODS

To determine its potential role, we sequenced the bacterial 16 S rRNA genes in the visceral adipose depot of patients with obesity. Taking great care (surgical, biochemical, and bioinformatic) to avoid environmental contaminants. We performed statistical discriminant analyses to identify specific signatures and constructed network of interactions between variables.

RESULTS

The data showed that a specific 16SrRNA gene signature was composed of numerous bacterial families discriminating between lean versus patients with obesity and people with severe obesity. The main discriminant families were Burkholderiaceae, Yearsiniaceae, and Xanthomonadaceae, all of which were gram-negative. Interestingly, the Morganellaceae were totally absent from people without obesity while preponderant in all in patients with obesity. To generate hypotheses regarding their potential role, we inferred metabolic pathways from the 16SrRNA gene signatures. We identified several pathways associated with adenosyl-cobalamine previously described to be linked with adipose tissue development. We further identified chorismate biosynthesis, which is involved in aromatic amino-acid metabolism and could play a role in fat pad development. This innovative approach generates novel hypotheses regarding the gut to adipose tissue axis.

CONCLUSIONS

This innovative approach generates novel hypotheses regarding the gut to adipose tissue axis in obesity and notably the potential role of tissue microbiota.

Evidence for human milk as a biological system and recommendations for study design-a report from "Breastmilk Ecology: Genesis of Infant Nutrition (BEGIN)" Working Group 4

Human milk contains all of the essential nutrients required by the infant within a complex matrix that enhances the bioavailability of many of those nutrients. In addition, human milk is a source of bioactive components, living cells and microbes that facilitate the transition to life outside the womb. Our ability to fully appreciate the importance of this matrix relies on the recognition of short- and long-term health benefits and, as highlighted in previous sections of this supplement, its ecology (i.e., interactions among the lactating parent and breastfed infant as well as within the context of the human milk matrix itself). Designing and interpreting studies to address this complexity depends on the availability of new tools and technologies that account for such complexity. Past efforts have often compared human milk to infant formula, which has provided some insight into the bioactivity of human milk, as a whole, or of individual milk components supplemented with formula. However, this experimental approach cannot capture the contributions of the individual components to the human milk ecology, the interaction between these components within the human milk matrix, or the significance of the matrix itself to enhance human milk bioactivity on outcomes of interest. This paper presents approaches to explore human milk as a biological system and the functional implications of that system and its components. Specifically, we discuss study design and data collection considerations and how emerging analytical technologies, bioinformatics, and systems biology approaches could be applied to advance our understanding of this critical aspect of human biology.

Parental factors that impact the ecology of human mammary development, milk secretion, and milk composition-a report from "Breastmilk Ecology: Genesis of Infant Nutrition (BEGIN)" Working Group 1

The goal of Working Group 1 in the Breastmilk Ecology: Genesis of Infant Nutrition (BEGIN) Project was to outline factors influencing biological processes governing human milk secretion and to evaluate our current knowledge of these processes. Many factors regulate mammary gland development in utero, during puberty, in pregnancy, through secretory activation, and at weaning. These factors include breast anatomy, breast vasculature, diet, and the lactating parent's hormonal milieu including estrogen, progesterone, placental lactogen, cortisol, prolactin, and growth hormone. We examine the effects of time of day and postpartum interval on milk secretion, along with the role and mechanisms of lactating parent-infant interactions on milk secretion and bonding, with particular attention to the actions of oxytocin on the mammary gland and the pleasure systems in the brain. We then consider the potential effects of clinical conditions including infection, pre-eclampsia, preterm birth, cardiovascular health, inflammatory states, mastitis, and particularly, gestational diabetes and obesity. Although we know a great deal about the transporter systems by which zinc and calcium pass from the blood stream into milk, the interactions and cellular localization of transporters that carry substrates such as glucose, amino acids, copper, and the many other trace metals present in human milk across plasma and intracellular membranes require more research. We pose the question of how cultured mammary alveolar cells and animal models can help answer lingering questions about the mechanisms and regulation of human milk secretion. We raise questions about the role of the lactating parent and the infant microbiome and the immune system during breast development, secretion of immune molecules into milk, and protection of the breast from pathogens. Finally, we consider the effect of medications, recreational and illicit drugs, pesticides, and endocrine-disrupting chemicals on milk secretion and composition, emphasizing that this area needs much more research attention.

Influence of maternal body mass index on human milk composition and associations to infant metabolism and gut colonisation: MAINHEALTH - a study protocol for an observational birth cohort

INTRODUCTION

Human milk provides all macronutrients for growth, bioactive compounds, micro-organisms and immunological components, which potentially interacts with and primes infant growth and, development, immune responses and the gut microbiota of the new-born. Infants with an overweight mother are more likely to become overweight later in life and overweight has been related to the gut microbiome. Therefore, it is important to investigate the mother-milk-infant triad as a biological system and if the maternal weight status influences the human milk composition, infant metabolism and gut microbiome.

METHODS AND ANALYSIS

This study aims to include 200 mother-infant dyads stratified into one of three body mass index (BMI) categories based on mother's prepregnancy BMI. Multiomics analyses include metabolomics, proteomics, glycomics and microbiomics methods, aiming to characterise human milk from the mothers and further relate the composition to infant gut microbiota and its metabolic impact in the infant. Infant gut microbiota is analysed using 16S sequencing of faeces samples. Nuclear magnetic resonance and mass spectrometry are used for the remaining omics analysis. We investigate whether maternal pre-pregnancy BMI results in a distinct human milk composition that potentially affects the initial priming of the infant's gut environment and metabolism early in life.

ETHICS AND DISSEMINATION

The Central Denmark Region Committees on Health Research Ethics has approved the protocol (J-nr. 1-10-72-296-18). All participants have before inclusion signed informed consent and deputy informed consent in accordance with the Declaration of Helsinki II. Results will be disseminated to health professionals including paediatricians, research community, nutritional policymakers, industry and finally the public. The scientific community will be informed via peer-reviewed publications and presentations at scientific conferences, the industry will be invited for meetings, and the public will be informed via reports in science magazines and the general press. Data cleared for personal data, will be deposited at public data repositories.

TRIAL REGISTRATION NUMBER

Danish regional committee of the Central Jutland Region, journal number: 1-10-72-296-18, version 6.Danish Data Protection Agency, journal number: 2016-051-000001, 1304.

CLINICALTRIALS

gov, identifier: NCT05111990.

Associations between maternal obesity and offspring gut microbiome in the first year of life

BACKGROUND

Maternal obesity is an important determinant of offspring obesity risk, which may be mediated via changes in the infant microbiome.

OBJECTIVES

We examined infant faecal microbiome, short-chain fatty acids (SCFA), and maternal human milk oligosaccharides (HMO) in mothers with overweight/obese body mass index (BMI) (OW) compared with normal weight (NW) (Clinicaltrials.gov NCT01131117).

METHODS

Infant stool samples at 1, 6, and 12 months were analysed by 16S rRNA sequencing. Maternal (BODPOD) and infant (quantitative nuclear magnetic resonance [QMR]) adiposity were measured. HMOs at 2 months postpartum and faecal SCFAs at 1 month were also assessed. Statistical analyses included multivariable and mixed linear models for assessment of microbiome diversity, composition, and associations of taxonomic abundance with metabolic and anthropometric variables.

RESULTS

At 1 month, offspring of women with obesity had lower abundance of SCFA-producing bacteria (including Ruminococcus and Turicibacter) and lower faecal butyric acid levels. Lachnospiraceae abundance was lower in OW group at 6 months, and infant fat mass was negatively associated with the levels of Sutterella. Gradient boosting machine models indicated that higher α-diversity and specific microbial taxa at 1 month predicted elevated adiposity at 12 months with overall accuracy of 76.5%. Associations between maternal HMO concentrations and infant bacterial taxa differed between NW and OW groups.

CONCLUSIONS

Elevated maternal BMI is associated with relative depletion of butyrate-producing microbes and faecal butyrate in the early infant faecal microbiome. Overall microbial richness may aid in prediction of elevated adiposity in later infancy.

Dynamic Changes in the Human Milk Metabolome Over 25 Weeks of Lactation

Human milk (HM) provides essential nutrition for ensuring optimal infant growth and development postpartum. Metabolomics offers insight into the dynamic composition of HM. Studies have reported the impact of lactation stage, maternal genotype, and gestational age on HM metabolome. However, the majority of the studies have considered changes within the first month of lactation or sampled with large intervals. This leaves a gap in the knowledge of progressing variation in HM composition beyond the first month of lactation. The objective of this study was to investigate whether the HM metabolome from mothers with term deliveries varies beyond 1 month of lactation, during the period in which HM is considered fully mature. Human milk samples (n = 101) from 59 mothers were collected at weeks 1–2, 3–5, 7–9, and 20–25 postpartum and analyzed using ¹H nuclear magnetic resonance spectroscopy. Several metabolites varied over lactation and exhibited dynamic changes between multiple time points. Higher levels of HM oligosaccharides, cis-aconitate, O-phosphocholine, O-acetylcarnitine, gluconate, and citric acid were observed in early lactation, whereas later in lactation, levels of lactose, 3-fucosyllactose, glutamine, glutamate, and short- and medium-chain fatty acids were increased. Notably, we demonstrate that the HM metabolome is dynamic during the period of maturity.

Bioactive compounds in mothers milk affecting offspring outcomes: A narrative review

BACKGROUND

Compared to the exhaustive study of transgenerational programming of obesity and diabetes through exposures in the prenatal period, postnatal programming mechanisms are understudied, including the potential role of breast milk composition linking maternal metabolic status (body mass index and diabetes) and offspring growth, metabolic health and future disease risk.

METHODS

This narrative review will principally focus on four emergent bioactive compounds [microRNA's (miRNA), lipokines/signalling lipids, small molecules/metabolites and fructose] that, until recently were not known to exist in breast milk. The objective of this narrative review is to integrate evidence across multiple fields of study that demonstrate the importance of these compositional elements of breast milk during lactation and the subsequent effect of breast milk components on the health of the infant.

RESULTS

Current knowledge on the presence of miRNA's, lipokines/signalling lipids, small molecules/metabolites and fructose in breast milk and their associations with infant outcomes is compelling, but far from resolved. Two themes emerge: (1) maternal metabolic phenotypes are associated with these bioactives and (2) though existing in milk at low concentrations, they are also associated with offspring growth and body composition.

CONCLUSION

Breast milk research is gaining momentum though we must remain focused on understanding how non-nutritive bioactive components are affected by the maternal phenotype, how they subsequently impact infant outcomes. Though early, there is evidence to suggest fructose is associated with fat mass in the 1st months of life whereas 12,13 diHOME (brown fat activator) and betaine are negatively associated with early adiposity and growth.

Human Milk Metabolomics Are Related to Maternal Adiposity, Infant Growth Rate and Allergies: The Chinese Human Milk Project

The metabolomic profiles of Chinese human milk have been poorly documented. The objective of the study was to explore associations between human milk metabotypes, maternal adiposity, infant growth patterns, and risk of allergies. Two hundred mother−infant dyads from seven cities were randomly selected from the Chinese Human Milk Project (CHMP). Untargeted human milk metabolomic profiles were determined using HPLC-MS/MS. Two human milk metabotypes were identified using principal component analysis. Principal component (PC) 1 was characterized by high linoleic acid metabolites with low purine nucleosides and metabolites of glutamate and glutathione metabolism. PC 2 was characterized by high glycerophospholipids and sphingomyelins content. Higher PC1 scores were associated with slower infant growth rate and higher ambient temperature (p < 0.05). Higher PC 2 scores were related to higher maternal BMI and increased risk of infant allergies (p < 0.05). Future work is needed to understand the biologic mechanisms of these human milk metabotypes.

NMR Metabonomic Profile of Preterm Human Milk in the First Month of Lactation: From Extreme to Moderate Prematurity

Understanding the composition of human milk (HM) can provide important insights into the links between infant nutrition, health, and development. In the present work, we have longitudinally investigated the metabolome of milk from 36 women delivering preterm at different gestational ages (GA): extremely (<28 weeks GA), very (29–31 weeks GA) or moderate (32–34 weeks GA) premature. Milk samples were collected at three lactation stages: colostrum (3–6 days post-partum), transitional milk (7–15 days post-partum) and mature milk (16–26 days post-partum). Multivariate and univariate statistical data analyses were performed on the ¹H NMR metabolic profiles of specimens in relation to the degree of prematurity and lactation stage. We observed a high impact of both the mother’s phenotype and lactation time on HM metabolome composition. Furthermore, statistically significant differences, although weak, were observed in terms of GA when comparing extremely and moderately preterm milk. Overall, our study provides new insights into preterm HM metabolome composition that may help to optimize feeding of preterm newborns, and thus improve the postnatal growth and later health outcomes of these fragile patients.

Untargeted Metabolomic Analysis of Human Milk from Mothers of Preterm Infants

The application of metabolomics in neonatology offers an approach to investigate the complex relationship between nutrition and infant health. Characterization of the metabolome of human milk enables an investigation into nutrients that affect the neonatal metabolism and identification of dietary interventions for infants at risk of diseases such as necrotizing enterocolitis (NEC). In this study, we aimed to identify differences in the metabolome of breast milk of 48 mothers with preterm infants with NEC and non-NEC healthy controls. A minimum significant difference was observed in the human milk metabolome between the mothers of infants with NEC and mothers of healthy control infants. However, significant differences in the metabolome related to fatty acid metabolism, oligosaccharides, amino sugars, amino acids, vitamins and oxidative stress-related metabolites were observed when comparing milk from mothers with control infants of ≤1.0 kg birth weight and >1.5 kg birth weight. Understanding the functional biological features of mothers’ milk that may modulate infant health is important in the future of tailored nutrition and care of the preterm newborn.

Salivary Metabolites are Promising Non-Invasive Biomarkers of Hepatocellular Carcinoma and Chronic Liver Disease

Background

Hepatocellular carcinoma (HCC) is a leading causes of cancer mortality worldwide. Improved tools are needed for detecting HCC so that treatment can begin as early as possible. Current diagnostic approaches and existing biomarkers, such as alpha-fetoprotein (AFP) lack sensitivity, resulting in too many false negative diagnoses. Machine-learning may be able to identify combinations of biomarkers that provide more robust predictions and improve sensitivity for detecting HCC. We sought to evaluate whether metabolites in patient saliva could distinguish those with HCC, cirrhosis, and those with no documented liver disease.

Methods and Results

We tested 125 salivary metabolites from 110 individuals (43 healthy, 37 HCC, 30 cirrhosis) and identified 4 metabolites that displayed significantly different abundance between groups (FDR P <.2). We also developed four tree-based, machine-learning models, optimized to include different numbers of metabolites, that were trained using cross-validation on 99 patients and validated on a withheld test set of 11 patients. A model using 12 metabolites -octadecanol, acetophenone, lauric acid, 1-monopalmitin, dodecanol, salicylaldehyde, glycyl-proline, 1-monostearin, creatinine, glutamine, serine and 4-hydroxybutyric acid- had a cross-validated sensitivity of 84.8%, specificity of 92.4% and correctly classified 90% of the HCC patients in the test cohort. This model outperformed previously reported sensitivities and specificities for AFP (20-100ng/ml) (61%, 86%) and AFP plus ultrasound (62%, 88%).

Conclusions and Impact

Metabolites detectable in saliva may represent products of disease pathology or a breakdown in liver function. Notably, combinations of salivary metabolites derived from machine-learning may serve as promising non-invasive biomarkers for the detection of HCC.

Comprehensive Human Milk Patterns Are Related to Infant Growth and Allergy in the CHMP Study

SCOPE

The aim of the present study is to identify human milk pattern using multi-omics datasets and to explore association between patterns, infant growth, and allergy using data from the Chinese Human Milk Project (CHMP) study.

METHODS AND RESULTS

Three patterns are identified from integrative analysis of proteome, lipidome, and glycome profiles of 143 mature human milk samples. Factor 1 is positively associated with 128 proteins, phospholipids, and human milk oligosaccharides (HMOs) including lacto N-neohexaose (LNnH) and lacto-N-difucohexaose II (LNDFH II); factor 2 is negatively associated with as₁ -casein, phospholipids while positively associates with HMOs including LNnH, lactosialyl tetrasaccharide c (LSTc), and 2'-fucosyllactose (2'FL); factor 3 is positively associated with lysophospholipids while negatively associates with 27 proteins, triglycerides with two saturated fatty acids, 6'-sialyllactose (6'SL) and 2'FL. In general, factor 1 and factor 2 are associated with slower while factor 3 is associated with faster growth rate (p < 0.044). One unit higher in loadings of factor 2 is associated with 34% lower risk of allergies (p ≤ 0.017). Associations are not significant after adjustment for city except for factor 1.

CONCLUSIONS

Three possible human milk patterns with varying degree of stability are identified. Future work is needed to understand these patterns in terms of generalization, biologic mechanisms, and genotype influences.

New Insights Into Microbiota Modulation-Based Nutritional Interventions for Neurodevelopmental Outcomes in Preterm Infants

Gut microbiota and the central nervous system have parallel developmental windows during pre and post-natal life. Increasing evidences suggest that intestinal dysbiosis in preterm infants predisposes the neonate to adverse neurological outcomes later in life. Understanding the link between gut microbiota colonization and brain development to tailor therapies aimed at optimizing initial colonization and microbiota development are promising strategies to warrant adequate brain development and enhance neurological outcomes in preterm infants. Breast-feeding has been associated with both adequate cognitive development and healthy microbiota in preterms. Infant formula are industrially produced substitutes for infant nutrition that do not completely recapitulate breast-feeding benefices and could be largely improved by the understanding of the role of breast milk components upon gut microbiota. In this review, we will first discuss the nutritional and bioactive component information on breast milk composition and its contribution to the assembly of the neonatal gut microbiota in preterms. We will then discuss the emerging pathways connecting the gut microbiota and brain development. Finally, we will discuss the promising microbiota modulation-based nutritional interventions (including probiotic and prebiotic supplementation of infant formula and maternal nutrition) for improving neurodevelopmental outcomes.

The clinical impact of maternal weight on offspring health: lights and shadows in breast milk metabolome

INTRODUCTION

Pre-pregnancy overweight and obesity, depending on maternal nutrition and metabolic state, can influence fetal, neonatal and long-term offspring health, regarding cardio-metabolic, respiratory, immunological and cognitive outcomes. Thus, maternal weight can act, through mechanisms that are not full understood, on the physiology and metabolism of some fetal organs and tissues, to adapt themselves to the intrauterine environment and nutritional reserves. These effects could occur by modulating gene expression, neonatal microbiome, and through breastfeeding.

AREAS COVERED

In this paper, we investigated the potential effects of metabolites found altered in breast milk (BM) of overweight/obese mothers, through an extensive review of metabolomics studies, and the potential short- and long-term clinical effects in the offspring, especially regarding overweight, glucose homeostasis, insulin resistance, oxidative stress, infections, immune processes, and neurodevelopment.

EXPERT OPINION

Metabolomics seems the ideal tool to investigate BM variation depending on maternal or fetal/neonatal factors. In particular, BM metabolome alterations according to maternal conditions were recently pointed out in cases of gestational diabetes, preeclampsia, intrauterine growth restriction and maternal overweight/obesity. In our opinion, even if BM is the food of choice in neonatal nutrition, the deepest comprehension of its composition in overweight/obese mothers could allow targeted supplementation, to improve offspring health and metabolic homeostasis.

Protein Profile and Simulated Digestive Behavior of Breast Milk from Overweight and Normal Weight Mothers

Human milk proteins have shown to vary in concentration and distribution through lactation. However, while some regulatory components, such as hormones, have shown associations with regard to the mothers' body mass index, there is limited information on the possible influence of this condition on the whole protein distribution. The objective of this study was to evaluate the protein profile of human milk from normal weight and overweight or obese mothers to identify differences in protein expression in colostrum, transitional and mature milk. The mass spectrometry analysis showed the ability to class with a high degree of confidence the lactation state and the milk profile according to the mother's condition. Individual milk samples were subjected to a digestion in vitro model that takes into account the specificities of the gastrointestinal conditions of full-term newborn infants. The digestion products were compared with available data from the digestive contents in newborns. The behavior of the most abundant proteins and the overall peptide generation and survival, showed good correspondence with in vivo data.

Gestational diabetes mellitus-associated changes in the breast milk metabolome alters the neonatal growth trajectory

BACKGROUND

Gestational diabetes mellitus (GDM) is the most common metabolic disturbance during pregnancy and leads to an altered metabolic profile of human breast milk (HBM). The association between HBM metabolites and neonatal growth in GDM pregnancies has not been thoroughly investigated.

AIMS

The primary aim was to quantify differences in the HBM metabolome between normal and GDM pregnancies. The secondary aim was to identify metabolites associated with neonatal growth during the first year postpartum.

METHODS

In the present study, mothers intending to exclusively breastfeed (BF) and their newborns (mother-infant pairs) were recruited at delivery (n = 129 normal pregnancies and n = 98 GDM pregnancies). HBM samples (colostrum, transition milk, and mature milk) from mothers with normal pregnancies (n = 50) and GDM pregnancies (n = 50) were subjected to metabolomic profiling via liquid chromatography tandem mass spectrometry (LC-MS/MS). Receiver operating characteristic (ROC) analysis revealed the metabolomic fingerprints of GDM-associated mature HBM. Correlations between metabolites and neonatal body weight gain (BWG) were evaluated by Spearman correlation analysis.

RESULTS

In total, 620 metabolites were identified in each HBM sample; 253 compounds had the same variation patterns, whereas 38 compounds had significantly different pattern transitions between the GDM and normal groups. Moreover, 12, 49 and 28 metabolites exhibited significant differences in the 3 milk types between the 2 groups. Twenty-two metabolites were confirmed by ROC analysis as metabolomic fingerprints in the mature BM of GDM patients. Ten compounds were significantly negatively correlated with neonatal growth, and only 2 unsaturated lipids (eicosatrienoic acid (FA 20:3) and lysophosphatidylcholine (LysoPC) (22:6)) were positively correlated with neonatal BWG.

CONCLUSIONS

GDM is associated with alterations in the HBM metabolome. Only a small subset of compounds are associated with neonatal body weight (BW).

TRIAL REGISTRATION

ChiCTR-ROC-17011508. Prospectively registered on 26 May 2017 (http://www.chictr.org.cn/listbycreater.aspx).

The Metabolomic Analysis of Human Milk Offers Unique Insights into Potential Child Health Benefits

PURPOSE OF REVIEW

Human milk is the gold standard of infant nutrition. The milk changes throughout lactation and is tailored for the infant providing the nutrients, minerals and vitamins necessary for supporting healthy infant growth. Human milk also contains low molecular weight compounds (metabolites) possibly eliciting important bioactivity. Metabolomics is the study of these metabolites. The purpose of this review was to examine recent metabolomics studies and cohort studies on human milk to assess the impact of human milk metabolomic analyses combined with investigations of infant growth and development.

RECENT FINDINGS

The metabolite profile of human milk varies among other factors according to lactation stage, gestation at birth, and maternal genes, diet and disease state. Few studies investigate how these variations impact infant growth and development. Several time-related factors affecting human milk metabolome are potentially ubiquitous among mothers, although maternal-related factors are heavily confounded, which complicates studies of metabolite abundancies and variabilities and further possibilities of observing cause and effect in infants.

The Triad Mother-Breast Milk-Infant as Predictor of Future Health: A Narrative Review

The benefits of human milk for both mother and infant are widely acknowledged. Human milk could represent a link between maternal and offspring health. The triad mother-breast milk-infant is an interconnected system in which maternal diet and lifestyle might have effects on infant's health outcome. This link could be in part explained by epigenetics, even if the underlining mechanisms have not been fully clarified yet. The aim of this paper is to update the association between maternal diet and human milk, pointing out how maternal diet and lifestyle could be associated with breast-milk composition, hence with offspring's health outcome.

Human Milk Oligosaccharide Concentrations and Infant Intakes Are Associated with Maternal Overweight and Obesity and Predict Infant Growth

Human milk oligosaccharides (HMOs) are bioactive molecules playing a critical role in infant health. We aimed to quantify the composition of HMOs of women with normal weight (18.5–24.9 kg/m²), overweight (25.0–29.9 kg/m²), or obesity (30.0–60.0 kg/m²) and determine the effect of HMO intake on infant growth. Human milk (HM) samples collected at 2 months (2 M; n = 194) postpartum were analyzed for HMO concentrations via high-performance liquid chromatography. Infant HM intake, anthropometrics and body composition were assessed at 2 M and 6 M postpartum. Linear regressions and linear mixed-effects models were conducted examining the relationships between maternal BMI and HMO composition and HMO intake and infant growth over the first 6 M, respectively. Maternal obesity was associated with lower concentrations of several fucosylated and sialylated HMOs and infants born to women with obesity had lower intakes of these HMOs. Maternal BMI was positively associated with lacto-N-neotetraose, 3-fucosyllactose, 3-sialyllactose and 6-sialyllactose and negatively associated with disialyllacto-N-tetraose, disialyllacto-N-hexaose, fucodisialyllacto-N-hexaose and total acidic HMOs concentrations at 2 M. Infant intakes of 3-fucosyllactose, 3-sialyllactose, 6-sialyllactose, disialyllacto-N-tetraose, disialyllacto-N-hexaose, and total acidic HMOs were positively associated with infant growth over the first 6 M of life. Maternal obesity is associated with changes in HMO concentrations that are associated with infant adiposity.

Brown Fat-Activating Lipokine 12,13-diHOME in Human Milk Is Associated With Infant Adiposity

CONTEXT

Little is known about the specific breastmilk components responsible for protective effects on infant obesity. Whether 12,13-dihydroxy-9Z-octadecenoic acid (12,13-diHOME), an oxidized linoleic acid metabolite and activator of brown fat metabolism, is present in human milk, or linked to infant adiposity, is unknown.

OBJECTIVE

To examine associations between concentrations of 12,13-diHOME in human milk and infant adiposity.

DESIGN

Prospective cohort study from 2015 to 2019, following participants from birth to 6 months of age.

SETTING

Academic medical centers.

PARTICIPANTS

Volunteer sample of 58 exclusively breastfeeding mother-infant pairs; exclusion criteria included smoking, gestational diabetes, and health conditions with the potential to influence maternal or infant weight gain.

MAIN OUTCOME MEASURES

Infant anthropometric measures including weight, length, body mass index (BMI), and body composition at birth and at 1, 3, and 6 months postpartum.

RESULTS

We report for the first time that 12,13-diHOME is present in human milk. Higher milk 12,13-diHOME level was associated with increased weight-for-length Z-score at birth (β = 0.5742, P = 0.0008), lower infant fat mass at 1 month (P = 0.021), and reduced gain in BMI Z-score from 0 to 6 months (β = -0.3997, P = 0.025). We observed similar associations between infant adiposity and milk abundance of related oxidized linoleic acid metabolites 12,13-Epoxy-9(Z)-octadecenoic acid (12,13-epOME) and 9,10-Dihydroxy-12-octadecenoic acid (9,10-diHOME), and metabolites linked to thermogenesis including succinate and lyso-phosphatidylglycerol 18:0. Milk abundance of 12,13-diHOME was not associated with maternal BMI, but was positively associated with maternal height, milk glucose concentration, and was significantly increased after a bout of moderate exercise.

CONCLUSIONS

We report novel associations between milk abundance of 12,13-diHOME and adiposity during infancy.

Obesogenic Programming Effects during Lactation: A Narrative Review and Conceptual Model Focusing on Underlying Mechanisms and Promising Future Research Avenues

Animal studies have consistently demonstrated that maternal obesity and a high-fat diet during lactation enhances obesity risk in the offspring. However, less is known about these potential obesogenic programming effects in obese humans. We propose three important pathways that may explain obesogenic programming effects of human breastmilk. First, human milk components and hormones may directly affect child eating and satiety characteristics. Second, human milk constituents can affect child microbiota that, in turn, may influence child eating and weight outcomes. Third, human milk composition may affect child eating and weight outcomes through flavor exposure. We reviewed a few very recent findings from well-powered longitudinal or experimental human research with regard to these three pathways. Moreover, we provide a research agenda for future intervention research with the overarching aim to prevent excessive pediatric weight gain during lactation and beyond. The ideas presented in this paper may represent important “black box” constructs that explain obesogenic programming effects during lactation. It should be noted, however, that given the scarcity of studies, findings should be seen as working hypotheses to further test in future research.