Multiplatform characterization of dynamic changes in breast milk during lactation

Effect of rhGH treatment on lipidome and brown fat activity in prepuberal small for gestational age children: a pilot study

Recombinant human growth hormone (rhGH) therapy is the primary treatment for children born small for gestational age (SGA) who fail to show spontaneous catch-up growth by two or four years. While its effects on white adipose tissue are well-documented, this pilot study aimed to investigate its impact on the lipidome and the thermogenic and endocrine activities of brown adipose tissue (BAT) in SGA children following rhGH treatment. The study involved 11 SGA children divided into two groups: (a) SGA children who were not treated with rhGH (n = 4) and (b) SGA children who received rhGH treatment with Saizen® (n = 7). This second group of seven SGA children was followed for 12 months after initiating rhGH treatment. Interventions included 12-hour fasting blood extraction and infrared thermography at baseline and 3 and 12 months post-treatment. Five appropriate-for-gestational-age (AGA) children served as controls. Exclusion criteria included endocrinological, genetic, or chronic diseases. Untargeted lipidomics analysis was performed using liquid chromatography-mass spectrometry (LC-MS), and serum biomarker levels were measured using ELISA assays. Serum lipidomic analysis revealed that free fatty acids (FFAs) increased to levels close to those of the AGA group after three months of rhGH administration, including polyunsaturated fatty acids, correlating with reduced leptin levels. Elevated levels of 1a,1b-dihomo-PGJ2 and adrenic acid suggested potential aging markers. rhGH treatment also significantly reduced meteorin-like (METRNL) and monocyte chemoattractant protein-1 (MCP1) serum levels to control levels. rhGH influences the serum lipidome, promoting changes in maturation and metabolism. Further research is required to clarify the direct effects of rhGH on specific lipid species and batokines, potentially addressing metabolic disturbances linked to obesity and aging.

Comprehensive lipidomic profiling of human milk from lactating women across varying lactation stages and gestational ages

An untargeted lipidomic analysis was conducted to investigate the lipid composition of human milk across different lactation stages and gestational ages systematically. A total of 25 lipid subclasses and 934 lipid species as well as 90 free fatty acids were identified. Dynamic changes of the lipids throughout lactation and gestational phases were highlighted. In general, lactation stages introduced more variations in the lipid composition of human milk than gestational ages. Most lipids decreased as the milk progressed from the colostral stage to the mature stage, with some reaching a peak at the transitional stage. Significant variations in lipid composition across gestational ages were predominantly evident during early lactation period. In mature milks, most of the lipids exhibited no discernible statistical differences among gestational ages. This elucidation offers valuable insights and guidance for tailoring precise nutritional strategies for infants with diverse health needs.

Evaluating Metabolic Profiling of Human Milk Using Biocrates MxP® QUANT 500 Assay

Background/Objectives: Metabolic profiling of human milk (HM) is indispensable for elucidating mother-milk-infant relationships. Methods: We evaluated the Biocrates MxP® Quant 500 assay for HM-targeted metabolomics (106 small molecules, 524 lipids) and analyzed in a feasibility test HM from apparently healthy Brazilian mothers (A: 2-8, B: 28-50, C: 88-119 days postpartum, ntotal = 25). Results: Of the 630 possible signatures detectable with this assay, 506 were above the limits of detection in an HM-pool (10 µL) used for assay evaluation, 12 of them above the upper limit of quantitation. Analyzing five different HM-pool volumes (2-20 µL) revealed acceptable linearity for 458 metabolites. Intraday accuracy of 80-120% was attained by 469 metabolites after spiking and for 342 after a 1:2 dilution. Analyzing HM from Brazilian mothers revealed significantly lower concentrations in colostrum vs. mature milk for many flow-injection analyses (FIA) and only a few LC-MS metabolites, including triglycerides, sphingomyelins, and phosphatidylcholines. Higher concentrations at the later lactation stages were found predominantly for amino acids and related compounds. Conclusions: The MxP Quant® 500 assay is a useful tool for HM metabolic profiling, minimizing analytical bias between matrices, and enhancing our ability to study milk as a biological system.

Research progress on factors affecting the human milk metabolome

Human milk is the gold standard for infant nutrition and contains macronutrients, micronutrients, and various bioactive substances. The human milk composition and metabolite profiles are complex and dynamic, complicating its specific analysis. Metabolomics, a recently emerging technology, has been used to identify human milk metabolites classes. Applying metabolomics to study the factors affecting human milk metabolites can provide significant insights into the relationship between infant nutrition, health, and development and better meet the nutritional needs of infants during growth. Here, we systematically review the current status of human milk metabolomic research, and related methods, offering an in-depth analysis of the influencing factors and results of human milk metabolomics from a metabolic perspective to provide novel ideas to further advance human milk metabolomics.

Characterising glycosaminoglycans in human breastmilk and their potential role in infant health

Human breastmilk is composed of many well researched bioactive components crucial for infant nutrition and priming of the neonatal microbiome and immune system. Understanding these components gives us crucial insight to the health and wellbeing of infants. Research surrounding glycosaminoglycans (GAGs) previously focused on those produced endogenously; however, recent efforts have shifted to understanding GAGs in human breastmilk. The structural complexity of GAGs makes detection and analysis complicated therefore, research is time consuming and limited to highly specialised teams experienced in carbohydrate analysis. In breastmilk, GAGs are present in varying quantities in four forms; chondroitin sulphate, heparin/heparan sulphate, dermatan sulphate and hyaluronic acid, and are hypothesised to behave similar to other bioactive components with suspected roles in pathogen defense and proliferation of beneficial gut bacteria. Chondroitin sulphate and heparin, being the most abundant, are expected to have the most impact on infant health. Their decreasing concentration over lactation further indicates their role and potential importance during early life.

Metabolic maturation in the infant urine during the first 3 months of life

The infant urine metabolome provides a body metabolic snapshot, and the sample collection can be done without stressing the fragile infant. 424 infant urine samples from 157 infants were sampled longitudinally at 1-, 2-, and 3 months of age. 49 metabolites were detected using proton nuclear magnetic resonance spectroscopy. Data were analyzed with multi- and univariate statistical methods to detect differences related to infant age-stage, gestational age, mother's pre-pregnancy BMI, C-section, infant birth weight, and infant sex. Significant differences were identified between age-stage (pbonferoni < 0.05) in 30% (15/49) of the detected metabolites. Urine creatinine increased significantly from 1 to 3 months. In addition, myo-inositol, taurine, methionine, and glucose seem to have conserved levels within the individual over time. We calculated a urine metabolic maturation age and found that the metabolic age at 3 months is negatively correlated to weight at 1 year. These results demonstrate that the metabolic maturation can be observed in urine metabolome with implications on infant growth and specifically suggesting that the systematic age effect on creatinine promotes caution in using this as normalization of other urine metabolites.

Changes in the Immunology of Breast Milk From Obese or Overweight Women: a Brief Review

A systematic search was carried out through search platforms and specialized databases, such as Academic Google, PubMed, and Scopus, using thesauri: breast feeding, obesity, immunology, and human milk in English and Spanish, and those articles published from January 2000 to December 2021, in both languages. Only those reports that included quantitative data on immunological components in the milk of normal-weight and overweight women were considered. The PRISMA 2020 guides were used, and a total of 306 articles were reviewed, of which a total of 33 were included, according to the basic inclusion criteria. It was observed that in obese mothers, there is an increase in certain immune cells, such as B lymphocytes, cytotoxic T lymphocytes, and NK cells, and cytokines, such as IL-6 and IFN-γ; other alterations included the bacterial population and proteins with antibacterial action. Also, a decrease in growth factors such as TGF-β and IFG-1 was documented in overweight women. Immunoglobulin concentrations did not show substantial changes. This brief review shows that maternal overweight is associated with changes in the biochemical and immunological parameters of milk.

Impact of Breastfeeding Duration on Adenoid Hypertrophy, Snoring and Acute Otitis Media: A Case-Control Study in Preschool Children

BACKGROUND

The aim of this study was to analyze the relationship between breastfeeding duration and adenoid size, snoring and acute otitis media (AOM).

METHODS

We analyzed the medical history of children admitted to the ENT outpatient clinic in 2022 and 2023, reported symptoms, ear, nose and throat (ENT) examination, and flexible nasopharyngoscopy examination of 145 children aged 3-5 years.

RESULTS

Breastfeeding duration of 3 and 6 months or more had a significant effect on the reduction of snoring (p = 0.021; p = 0.039). However, it had no effect on the adenoid size, mucus coverage and sleeping with an open mouth. Snoring was correlated with open mouth sleeping (p < 0.001), adenoid size with a 75% A/C ratio or more (p < 0.001), and adenoid mucus coverage in the Mucus of Adenoid Scale by Nasopharyngoscopy Assessment-MASNA scale (p = 0.009). Children who were breastfed for less than 3 months had more than a four-fold greater risk of snoring. There was a statistically significant correlation between AOM and gender (p = 0.033), breastfeeding duration in groups fed 1, 3 or 6 months or more (p = 0.018; p = 0.004; p = 0.004) and those fed with mother's breast milk 3 or 6 months or more (p = 0.009; p = 0.010). Moreover, a correlation was found between adenoid size and mucus coverage, tympanogram, and open-mouth sleeping (p < 0.001). Independent factors of snoring in 3- to 5-year-old children were breastfeeding duration of less than 3 months (p = 0.032), adenoid size with an A/C ratio of 75% or more (p = 0.023) and open mouth sleeping (p = 0.001).

CONCLUSIONS

Children breastfed for 3 and 6 months or more exhibited reduced rates of snoring. There was no effect of breastfeeding duration on adenoid size in children aged 3 to 5 years, suggesting that the link between breastfeeding duration and snoring is primarily associated with craniofacial development and muscle tone stimulation. A breastfeeding duration of 1 month or more plays a key role in reducing the rate of AOM. The mother's milk plays a protective role against AOM. The presence of mucus might be responsible for snoring in preschool children. A medical history of breastfeeding should be taken into consideration when snoring children are suspected of adenoid hypertrophy.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Pre-analytical aspects in metabolomics of human biofluids - sample collection, handling, transport, and storage

Metabolomics is the field of omics research that offers valuable insights into the complex composition of biological samples. It has found wide application in clinical diagnostics, disease investigation, therapy prediction, monitoring of treatment efficiency, drug discovery, or in-depth analysis of sample composition. A suitable study design constitutes the fundamental requirements to ensure robust and reliable results from the study data. The study design process should include a careful selection of conditions for each experimental step, from sample collection to data analysis. The pre-analytical variability that can introduce bias to the subsequent analytical process, decrease the outcome reliability, and confuse the final results of the metabolomics research, should also be considered. Herein, we provide key information regarding the pre-analytical variables affecting the metabolomics studies of biological fluids that are the most desirable type of biological samples. Our work offers a practical review that can serve and guide metabolomics pre-analytical design. It indicates pre-analytical factors, which can introduce artificial data variation and should be identified and understood during experimental design (through literature overview or analytical experiments).

Metabolomics can provide new insights into perinatal nutrition

Perinatal nutrition is a key factor related to the Developmental Origin of Health and Disease hypothesis, which states that each and every event that happens during the periconceptional period and pregnancy can affect the health status of an individual. Metabolomics can be a very useful tool for gathering information about the effect of perinatal nutrition on both mothers and newborn infants. This non-systematic review focuses on the main metabolites detected by this technique, with regard to gestational diabetes, intrauterine growth restriction and breast milk. Conclusion. Nutrition, metabolome and microbiome interactions are gaining interest in the scientific community.

Gastrointestinal, vaginal, nasopharyngeal, and breast milk microbiota profiles and breast milk metabolomic changes in Gambian infants over the first two months of lactation: A prospective cohort study

Microbiota composition in breast milk affects intestinal and respiratory microbiota colonization and the mucosal immune system's development in infants. The metabolomic content of breast milk is thought to interact with the microbiota and may influence developing infant immunity. One hundred seven Gambian mothers and their healthy, vaginally delivered, exclusively breastfed infants were included in our study. We analyzed 32 breast milk samples, 51 maternal rectovaginal swabs and 30 infants' rectal swabs at birth. We also analyzed 9 breast milk samples and 18 infants' nasopharyngeal swabs 60 days post-delivery. We used 16S rRNA gene sequencing to determine the microbiota composition. Metabolomic profiling analysis was performed on colostrum and mature breast milk samples using a multiplatform approach combining 1-H Nuclear Magnetic Resonance Spectroscopy and Gas Chromatography-Mass Spectrometry. Bacterial communities were distinct in composition and diversity across different sample types. Breast milk composition changed over the first 60 days of lactation. α-1,4- and α-1,3-fucosylated human milk oligosaccharides, and other 33 key metabolites in breast milk (monosaccharides, sugar alcohols and fatty acids) increased between birth and day 60 of life. This study's results indicate that infant gut and respiratory microbiota are unique bacterial communities, distinct from maternal gut and breast milk, respectively. Breast milk microbiota composition and metabolomic profile change throughout lactation. These changes may contribute to the infant's immunological, metabolic, and neurological development and could consist the basis for future interventions to correct disrupted early life microbial colonization.

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.

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.

Human Breast Milk: From Food to Active Immune Response With Disease Protection in Infants and Mothers

Breastfeeding is associated with long-term wellbeing including low risks of infectious diseases and non-communicable diseases such as asthma, cancer, autoimmune diseases and obesity during childhood. In recent years, important advances have been made in understanding the human breast milk (HBM) composition. Breast milk components such as, non-immune and immune cells and bioactive molecules, namely, cytokines/chemokines, lipids, hormones, and enzymes reportedly play many roles in breastfed newborns and in mothers, by diseases protection and shaping the immune system of the newborn. Bioactive components in HBM are also involved in tolerance and appropriate inflammatory response of breastfed infants if necessary. This review summarizes the current literature on the relationship between mother and her infant through breast milk with regard to disease protection. We will shed some light on the mechanisms underlying the roles of breast milk components in the maintenance of health of both child and mother.

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.

Human milk oligosaccharides and infant gut microbiota: Molecular structures, utilization strategies and immune function

Human milk oligosaccharides (HMOs) are a unique class of non-digestible carbohydrates present in the mother milk, which play a key role in the development of infant gut microbiota, epithelial barrier and immune function. The deficiency of HMOs in the bovine milk-based infant formula has been widely recognized as a major culprit for the much higher incidence of immune disorders of formula-fed infants. This report was to give an up-to-date review on the structure characteristics of HMOs and the possible mechanisms, and strategies for their cellular uptake, and metabolism by the gut bacteria and the associated effects on the infant gut microbiome, and immune function. Most previous studies have been carried out in animals or in vitro model systems on the utilization strategies for HMOs in infant bacteria and their roles in infant microbiome, and gut immune function. A few HMO molecules have been synthesized artificially and applied in infant formulas.

Analytical Platforms for Mass Spectrometry-Based Metabolomics of Polar and Ionizable Metabolites

Metabolomics studies rely on the availability of suitable analytical platforms to determine a vast collection of chemically diverse metabolites in complex biospecimens. Liquid chromatography-mass spectrometry operated under reversed-phase conditions is the most commonly used platform in metabolomics, which offers extensive coverage for nonpolar and moderately polar compounds. However, complementary techniques are required to obtain adequate separation of polar and ionic metabolites, which are involved in several fundamental metabolic pathways. This chapter focuses on the main mass-spectrometry-based analytical platforms used to determine polar and/or ionizable compounds in metabolomics (GC-MS, HILIC-MS, CE-MS, IPC-MS, and IC-MS). Rather than comprehensively describing recent applications related to GC-MS, HILIC-MS, and CE-MS, which have been covered in a regular basis in the literature, a brief discussion focused on basic principles, main strengths, limitations, as well as future trends is presented in this chapter, and only key applications with the purpose of illustrating important analytical aspects of each platform are highlighted. On the other hand, due to the relative novelty of IPC-MS and IC-MS in the metabolomics field, a thorough compilation of applications for these two techniques is presented here.

The Relationship Between Breast Milk Components and the Infant Gut Microbiota

The assembly of the newborn's gut microbiota during the first months of life is an orchestrated process resulting in specialized microbial ecosystems in the different gut compartments. This process is highly dependent upon environmental factors, and many evidences suggest that early bacterial gut colonization has long-term consequences on host digestive and immune homeostasis but also metabolism and behavior. The early life period is therefore a "window of opportunity" to program health through microbiota modulation. However, the implementation of this promising strategy requires an in-depth understanding of the mechanisms governing gut microbiota assembly. Breastfeeding has been associated with a healthy microbiota in infants. Human milk is a complex food matrix, with numerous components that potentially influence the infant microbiota composition, either by enhancing specific bacteria growth or by limiting the growth of others. The objective of this review is to describe human milk composition and to discuss the established or purported roles of human milk components upon gut microbiota establishment. Finally, the impact of maternal diet on human milk composition is reviewed to assess how maternal diet could be a simple and efficient approach to shape the infant gut microbiota.

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.

Comparative Lipidomics Analysis of Human Milk and Infant Formulas Using UHPLC-Q-TOF-MS

The lipidome and fatty acid composition of human milk and different infant formulas with animal- and/or plant-based fat sources are analyzed and compared in this study. The results obtained using positive and negative ionization modes indicate that there are 48 and 71 lipid species, respectively, that are common between the human milk and infant formulas. Moreover, the fatty acid composition in infant formulas varies significantly, depending on the fat source. Human milk is rich in triacylglycerols that contain linoleic acid, α-linolenic acid, arachidonic acid, and docosahexaenoic acid. Meanwhile, the triacylglycerols in IFB comprise long-chain fatty acids at the sn-1,3 position. Compared to human milk, IFC has the same level of sphingomyelin species. Based on univariate and multivariate analyses, there are 37, 34, 31, and 36 lipid species that can be used to distinguish between human milk and infant formulas. Overall, the results reported herein are useful in designing new milk formulas that better mimic human milk.

Simple, Rapid Lipidomic Analysis of Triacylglycerols in Bovine Milk by Infusion-Electrospray Mass Spectrometry

Bovine milk is a complex mixture of lipids, proteins, carbohydrates, and other factors of which lipids comprise 3-5% of the total mass. Rapid analysis and characterization of the triacylglycerols (TAG) that comprise about 95% of the total lipid is daunting given the numerous TAG species. In the attached methods paper, we demonstrate an improved method for identifying and quantifying TAG species by infusion-based "shotgun" lipidomics. Because of the broad range of TAG species in milk, a single internal standard was insufficient for the analysis and required sectioning the spectrum into three portions based upon mass range to provide accurate quantitation of TAG species. Isobaric phospholipid interferences were removed using a simple dispersive solid-phase extraction step. Using this method, > 100 TAG species were quantitated by acyl carbon number and desaturation level in a sample of commercially purchased bovine milk.

Identifying unknown metabolites using NMR-based metabolic profiling techniques

Metabolic profiling of biological samples provides important insights into multiple physiological and pathological processes but is hindered by a lack of automated annotation and standardized methods for structure elucidation of candidate disease biomarkers. Here we describe a system for identifying molecular species derived from nuclear magnetic resonance (NMR) spectroscopy-based metabolic phenotyping studies, with detailed information on sample preparation, data acquisition and data modeling. We provide eight different modular workflows to be followed in a recommended sequential order according to their level of difficulty. This multi-platform system involves the use of statistical spectroscopic tools such as Statistical Total Correlation Spectroscopy (STOCSY), Subset Optimization by Reference Matching (STORM) and Resolution-Enhanced (RED)-STORM to identify other signals in the NMR spectra relating to the same molecule. It also uses two-dimensional NMR spectroscopic analysis, separation and pre-concentration techniques, multiple hyphenated analytical platforms and data extraction from existing databases. The complete system, using all eight workflows, would take up to a month, as it includes multi-dimensional NMR experiments that require prolonged experiment times. However, easier identification cases using fewer steps would take 2 or 3 days. This approach to biomarker discovery is efficient and cost-effective and offers increased chemical space coverage of the metabolome, resulting in faster and more accurate assignment of NMR-generated biomarkers arising from metabolic phenotyping studies. It requires a basic understanding of MATLAB to use the statistical spectroscopic tools and analytical skills to perform solid phase extraction (SPE), liquid chromatography (LC) fraction collection, LC-NMR-mass spectroscopy and one-dimensional and two-dimensional NMR experiments.

Comparative Lipidomic Study of Human Milk from Different Lactation Stages and Milk Formulas

In this report, we present a detailed comparison of the lipid composition of human milk (HM) and formula milk (FM) targeting different lactation stages and infant age range. We studied HM samples collected from 26 Polish mothers from colostrum to 19 months of lactation, along with FM from seven brands available on the Polish market (infant formula, follow-on formula and growing-up formula). Lipid extracts were analysed using liquid chromatography coupled to high-resolution mass spectrometry (LC-Q-TOF-MS). We found that the lipid composition of FM deviates significantly from the HM lipid profile in terms of qualitative and quantitative differences. FM had contrasting lipid profiles mostly across brands and accordingly to the type of fat added but not specific to the target age range. The individual differences were dominant in HM; however, differences according to the lactation stage were also observed, especially between colostrum and HM collected in other lactation stages. Biologically and nutritionally important lipids, such as long-chain polyunsaturated fatty acids (LC-PUFAs) containing lipid species, sphingomyelines or ether analogues of glycerophosphoethanoloamines were detected in HM collected in all studied lactation stages. The observed differences concerned all the major HM lipid classes and highlight the importance of the detailed compositional studies of both HM and FM.

A Comparison of Breastfeeding Exposure, Attitude, and Knowledge Between Collegiate African American and White Males with no Biological Children

BACKGROUND

Human milk is the preferred source of infant nourishment; yet, acceptance of human milk as the norm for infant feeding is debated. In the United States there is a disparity in breastfeeding rates, which are significantly lower in African Americans compared to Whites. Multiple variables appear to influence breastfeeding, including the male partner.

OBJECTIVES

To assess and compare breastfeeding exposure, attitude, and knowledge between African American and White college males with no biological children. A second objective was to explore the relationship between breastfeeding variables and educational attainment, academic major, and sibling presence.

METHODS

A subset of responses from a larger cross-sectional survey were analyzed. African American and White collegiate males aged 18-40 years without biological children were included in the study. The questionnaire included demographic, exposure, attitude, and knowledge items.

RESULTS

A total of 117 African American and 713 White males were included and represented all academic colleges on campus. African American participants documented less exposure to breastfeeding, a more positive attitude, and similar poor knowledge scores compared to their White counterparts. Sibling presence was linked with exposure, and exposure was linked to attitude. Both African American and White science majors scored higher on all factors than humanities or business majors.

CONCLUSIONS FOR PRACTICE

Breastfeeding exposure influences males' attitudes toward breastfeeding. Future research should consider types of exposure to identify the sources most influential. Furthermore, tailoring breastfeeding interventions to increase exposure and knowledge in core wellness courses may improve attitudes and social acceptance among collegiate males.

Current Practice in Untargeted Human Milk Metabolomics

Human milk (HM) is considered the gold standard for infant nutrition. HM contains macro- and micronutrients, as well as a range of bioactive compounds (hormones, growth factors, cell debris, etc.). The analysis of the complex and dynamic composition of HM has been a permanent challenge for researchers. The use of novel, cutting-edge techniques involving different metabolomics platforms has permitted to expand knowledge on the variable composition of HM. This review aims to present the state-of-the-art in untargeted metabolomic studies of HM, with emphasis on sampling, extraction and analysis steps. Workflows available from the literature have been critically revised and compared, including a comprehensive assessment of the achievable metabolome coverage. Based on the scientific evidence available, recommendations for future untargeted HM metabolomics studies are included.

Investigation of the Defatted Colostrum 1H-NMR Metabolomics Profile of Gilts and Multiparous Sows and Its Relationship with Litter Performance

Simple Summary

Swine colostrum quality and quantity can influence the growth and survival of piglets and contribute to the differences in productive traits of gilts and multiparous sows. The aim of the study was to characterize the soluble metabolomics profile of defatted colostrum of sows at different parity number (PA) and to correlate the metabolomics profile with the colostrum Brix percentage as an estimate measure of immunoglobulin G (IgG) concentration and sow productive traits. The metabolomics profile of colostrum reveals a slight influence of parity, which can influence the quantity of specific metabolites including glycine and lactose. Specific metabolites including lactose creatine, myo-inositol, and O-phosphocholine partially explain the colostrum IgG Brix percentage. Sows’ productive traits performance, including the litter weight at birth and piglets’ mortality, can be influenced by the metabolites related to a sow’s metabolic condition. Increasing knowledge on the interplay between colostrum composition and litter performance can pave the way to define management strategies to provide piglets with good-quality colostrum, improving welfare and economic sustainability of pig rearing by reducing piglet mortality.

Abstract

The aim of the study was to characterize the soluble metabolomics profile of defatted colostrum of sows at different parity number (PA) and to correlate the metabolomics profile with the Brix percentage estimate of colostrum immunoglobulin G (IgG) and sow productive traits. A total of 96 Meidam (crossbreed Large White × Meishan) sows of PA from 1–4 (PA1: 28; PA2:26; PA3:12; PA4:26) were included, and their productive traits were recorded at 10 days post-farrowing. Colostrum IgG was quantified using a Brix refractometer, and metabolomics profile was assessed using ¹H-NMR spectroscopy. Sows’ PA slightly influenced the metabolomics profile of colostrum. lactose and glycine were higher in PA1 compared with PA4 (p 0.05) and N-acetylglucosamine (GlcNAc) tended to be higher in PA2 than PA3 and PA4 (p < 0.10). The Brix percentage of IgG was negatively associated with lactose and positively with creatine, myo-inositol, and O-phosphocholine (p < 0.05). Taurine was positively related to litter weight at birth. GlcNAc and myo-inositol were linked to piglet mortality at day 10 with a negative and positive trend, respectively. In conclusion, colostrum of gilts and multiparous sows had a similar metabolomics profile. Specific metabolites contributed to explanation of the variability in colostrum Brix percentage estimate of IgG concentration and the sows’ productive performance.

Advantages and Limitations of the Neonatal Immune System

During early post-natal life, neonates must adjust to the transition from the sheltered intra-uterine environment to the microbe-laden external world, wherein they encounter a constellation of antigens and the colonization by the microbiome. At this vulnerable stage, neonatal immune responses are considered immature and present significant differences to those of adults. Pertinent to innate immunity, functional and quantitative deficiencies in antigen-presenting cells and phagocytes are often documented. Exposure to environmental antigens and microbial colonization is associated with epigenetic immune cell reprogramming and activation of effector and regulatory mechanisms that ensure age-depended immune system maturation and prevention of tissue damage. Moreover, neonatal innate immune memory has emerged as a critical mechanism providing protection against infectious agents. Still, in neonates, inexperience to antigenic exposure, along with enhancement of tissue-protective immunosuppressive mechanisms are often associated with severe immunopathological conditions, including sepsis and neurodevelopmental disorders. Despite significant advances in the field, adequate vaccination in newborns is still in its infancy due to elemental restrictions associated also with defective immune responses. In this review, we provide an overview of neonatal innate immune cells, highlighting phenotypic and functional disparities with their adult counterparts. We also discuss the effects of epigenetic modifications and microbial colonization on the regulation of neonatal immunity. A recent update on mechanisms underlying dysregulated neonatal innate immunity and linked infectious and neurodevelopmental diseases is provided. Understanding of the mechanisms that augment innate immune responsiveness in neonates may facilitate the development of improved vaccination protocols that can protect against pathogens and organ damage.

Clinical insights gained through metabolomic analysis of human breast milk

Introduction: Among the OMICS technologies, that have emerged in recent years, metabolomics has allowed relevant step forwards in clinical research. Several improvements in disease diagnosis and clinical management have been permitted, even in neonatology. Among potentially evaluable biofluids, breast milk (BM) results are highly interesting, representing a fluid of conjunction between mothers newborns, describing their interaction.Areas covered: in this review, updating a previous review article, we discuss research articles and reviews on BM metabolomics and found in MEDLINE using metabolomics, breast milk, neonatal nutrition, breastfeeding, human milk composition, and preterm neonates as keywords.Expert opinion: Our research group has a profound interest in metabolomics research. In 2012, we published the first metabolomic analysis on BM samples, reporting interesting data on its composition and relevant differences with formula milk (FM), useful to improve FM composition. As confirmed by successive studies, such technology can detect the specific BM composition and its dependence on several variables, including lactation stage, gestational age, maternal or environmental conditions. Moreover, since BM contaminants or drug levels can be detected, metabolomics also results useful to determine BM safety. These are only a few practical applications of BM analysis, which will be reviewed in this paper.

Relationship among Breastfeeding Exposure, Knowledge, and Attitudes in Collegiate Males Residing in East Texas

BACKGROUND

Researchers exploring breastfeeding attitudes and knowledge among women suggest the decision to breastfeed is influenced by the male partner, yet few studies address males. Because collegiate males will soon enter fatherhood, assessment of their attitudes and knowledge may inform interventions aimed at increasing intention to breastfeed.

RESEARCH AIM

This study aimed to describe collegiate males' exposure to, attitude toward, and knowledge about breastfeeding.

METHODS

A cross-sectional online survey was used with males ≥ 18 years of age enrolled at a Texas public university. Attitude indices measured included social limitations, public displays of breastfeeding, and employer accommodations. Descriptive statistics, correlational and regression analyses were employed.

RESULTS

The participants' (N = 949) average age was 25.48 years; > 80% reported not being fathers. Exposure to breastfeeding was high; > 80% witnessed breastfeeding and/or had someone close breastfeed. High attitude scores indicated social acceptability of breastfeeding. Knowledge appeared limited: only 16% identified the recommendation of exclusive breastfeeding for the first 6 months of life; > 50% overlooked the reduced risk for overweight/obesity, ear infections, diarrhea, or food allergies. Correlations between knowledge, exposure, total attitude, and index scores were positive (p < .01) except for the public displays index. Stepwise multiple regression determined that breastfeeding exposure, knowledge scores, and father's educational level predicted total attitude score, (R² = 0.13, F (3,851) = 44.02, p < .01).

CONCLUSION

The positive attitudes outcome among this male population is promising for breastfeeding support and advocacy. Education efforts improving knowledge will likely increase behavioral intention, resulting in increased breastfeeding rates and duration.

Straight nano-electrospray ionization and its coupling of mobility capillary electrophoresis to mass spectrometry

Mobility capillary electrophoresis (MCE) was developed previously in our group, which has the capabilities of ion separation and biomolecule hydrodynamic radius analysis. The coupling of MCE with mass spectrometry (MS) would greatly improve complex sample identification capability as well as system detection sensitivity. In the present study, a simple and robust ionization source, named as straight nano-electrospray ionization (nanoESI) source was developed, which was applied to couple MCE with MS. A stainless-steel needle attached directly at the end of an MCE capillary was used as the nanoESI emitter, and the connection between this emitter to the liquid flow in the MCE separation channel was established through a liquid bridge. After optimization, this straight nanoESI source enhanced the ion signal intensity by ~10 times when compared with a commercial nanoESI source. The MCE-straight nanoESI-MS system was also characterized in terms of mixture separation and peptide hydrodynamic radius measurements. Compared to our previous work when a UV detector was used in a commercial Lumex CE system (model Capel 105 M, St. Petersburg, Russia), peptides with much lower concentrations could be analyzed (from ~1 mg/mL to ~20 μg/mL) in terms of radius measurement.

Capillary electrophoresis of small ions and molecules in less conventional human body fluid samples: A review

In recent years, advances in sensitive analytical techniques have encouraged the analysis of various compounds in biological fluids. While blood serum, blood plasma and urine still remain the golden standards in clinical, toxicological and forensic science, analyses of other body fluids, such as breast milk, exhaled breath condensate, sweat, saliva, amniotic fluid, cerebrospinal fluid, or capillary blood in form of dried blood spots are becoming more popular. This review article focuses on capillary electrophoresis and microchip electrophoresis of small ions and molecules (e.g. inorganic cations/anions, basic/acidic drugs, small acids/bases, amino acids, peptides and other low molecular weight analytes) in various less conventional human body fluids and hopes to stimulate further interest in the field.

A new dilution-enrichment sample preparation strategy for expanded metabolome monitoring of human breast milk that overcomes the simultaneous presence of low- and high-abundance lipid species

The complex nature of human breast milk (HBM) makes samples difficult to analyze, requiring several extraction techniques and analytical platforms to obtain high metabolome coverage. In this work, we combined liquid-liquid extraction (LLE) and solid-phase extraction (SPE) techniques to prepare HBM samples to overcome the challenge of low- and high-abundance lipid species, enabling the semiquantitative analysis of total HBM lipids in one liquid chromatography-mass spectrometry (LC-MS) run. A nonorganic fraction obtained during the LLE step was used to analyze small polar metabolites. This analytical approach allows extensive metabolome coverage, especially for low-abundance glycerophospholipids and sphingolipids. The method was applied to monitor short-term metabolome changes in HBM composition within individual mothers and the results showed variable metabolite composition patterns. Simultaneous detection of high-abundance glycerolipids and low-abundance but not less significant phospholipids in one LC-MS run saves time, decreases cost, and enables comprehensive insight into the dynamics of HBM composition.

A scoring approach for multi-platform acquisition in metabolomics

Since the ultimate goal of untargeted metabolomics is the analysis of the broadest possible range of metabolites, some new metrics have to be used by researchers to evaluate and select different analytical strategies when multi-platform analyses are considered. In this context, we aimed at developing a scoring approach allowing to compare the performance of different LC-MS conditions for metabolomics studies. By taking into account both chromatographic and MS attributes of the analytes' peaks (i.e. retention, signal-to-noise ratio, peak intensity and shape), the newly proposed score reflects the potential of a set of LC-MS operating conditions to provide useful analytical information for a given compound. A chemical library containing 597 metabolites was used as a benchmark to apply this approach on two RPLC and three HILIC methods hyphenated to high resolution mass spectrometry (HRMS) in positive and negative ionization modes. The scores not only allowed to evaluate each analytical platform, but also to optimize the number of analytical methods needed for the analysis of metabolomics samples. As a result, the most informative combination of three LC methods and ionization modes was found, leading to a coverage of nearly 95% of the detected compounds. It was therefore demonstrated that the overall performance reached with three selected methods was almost equivalent to the performance reached when five LC-MS conditions were used.

Chemistry of Human Breast Milk-A Comprehensive Review of the Composition and Role of Milk Metabolites in Child Development

Early nutrition has an enormous influence on a child's physiological function, immune system maturation, and cognitive development. Human breast milk (HBM) is recognized as the gold standard for human infant nutrition. According to a WHO report, breastfeeding is considered as an unequaled way of providing ideal food to the infant, which is required for his healthy growth and development. HBM contains various macronutrients (carbohydrates, proteins, lipids, and vitamins) as well as numerous bioactive compounds and interactive elements (growth factors, hormones, cytokines, chemokines, and antimicrobial compounds. The aim of this review is to summarize and discuss the current knowledge about metabolites, which are the least understood components of HBM, and their potential role in infant development. We focus on small metabolites (<1500 Da) and characterize the chemical structure and biological function of polar metabolites such as human milk oligosaccharides, nonprotein molecules containing nitrogen (creatine, amino acids, nucleotides, polyamines), and nonpolar lipids. We believe that this manuscript will provide a comprehensive insight into a HBM metabolite composition, chemical structure, and their role in a child's early life nutrition.

Evaluation of sample preparation methods for NMR-based metabolomics of cow milk

The quality of milk metabolome analyzed by nuclear magnetic resonance (NMR) is greatly influenced by the way samples are prepared. Although this analytical method is increasingly used to study milk metabolites, a thorough examination of available sample preparation protocols for milk has not been reported yet. We evaluated the performance of eight milk preparation methods namely (1) raw milk without any processing; (2) skimmed milk; (3) ultrafiltered milk; (4) skimming followed by ultrafiltration; (5) ultracentrifuged milk; (6) methanol; (7) dichloromethane; and (8) methanol/dichloromethane, in terms of spectra quality, repeatability, signal-to-noise ratio, extraction efficiency and yield criteria. A pooled sample of milk was used for all protocols. Skimming, ultracentrifugation and unprocessed milk protocols showed poor NMR spectra quality. Protocols involving multiple steps, namely methanol/dichloromethane extraction, and skimming followed by ultrafiltration produced inadequate results for signal-to-noise ratio parameter. Methanol and skimming associated to ultrafiltration provided good repeatability results compared to the other protocols. Chemical-based sample preparation protocols, particularly methanol, showed more efficient metabolite extraction compared to physical preparation methods. When considering all evaluation parameters, the methanol extraction protocol proved to be the best method. As a proof of utility, methanol protocol was then applied to milk samples from dairy cows fed a diet with or without a feed additive, showing a clear separation between the two groups of cows.

Early life nutrition

Nutritionally, the first 1,000 days of an infant's life - from conception to two years - has been identified as a highly influential period, during which lasting health can be achieved. Significant evidence links patterns of infant feeding to both short and long-term health outcomes, many of which can be prevented through nutritional modifications. Recommended globally, breastfeeding is recognised as the gold standard of infant nutrition; providing key nutrients to achieve optimal health, growth and development, and conferring immunologic protective effects against disease. Nevertheless, infant formulas are often the sole source of nutrition for many infants during the first stage of life. Producers of infant formula strive to supply high quality, healthy, safe alternatives to breast milk with a comparable balance of nutrients to human milk imitating its composition and functional performance measures. The concept of 'nutritional programming', and the theory that exposure to specific conditions, can predispose an individual's health status in later life has become an accepted dictum, and has sparked important nutritional research prospects. This review explores the impact of early life nutrition, specifically, how different feeding methods affect health outcomes.

Human Milk Lipidomics: Current Techniques and Methodologies

Human milk contains a complex combination of lipids, proteins, carbohydrates, and minerals, which are essential for infant growth and development. While the lipid portion constitutes only 5% of the total human milk composition, it accounts for over 50% of the infant’s daily energy intake. Human milk lipids vary throughout a feed, day, and through different stages of lactation, resulting in difficulties in sampling standardization and, like blood, human milk is bioactive containing endogenous lipases, therefore appropriate storage is critical in order to prevent lipolysis. Suitable sample preparation, often not described in studies, must also be chosen to achieve the aims of the study. Gas chromatography methods have classically been carried out to investigate the fatty acid composition of human milk lipids, but with the advancement of other chromatographic techniques, such as liquid and supercritical fluid chromatography, as well as mass spectrometry, intact lipids can also be characterized. Despite the known importance, concise and comprehensive analysis of the human milk lipidome is limited, with gaps existing in all areas of human milk lipidomics, discussed in this review. With appropriate methodology and instrumentation, further understanding of the human milk lipidome and the influence it has on infant outcomes can be achieved.

Metabolomic Profiles Reveal Potential Factors that Correlate with Lactation Performance in Sow Milk

Sow milk contains necessary nutrients for piglets; however, the relationship between the levels of metabolites in sow milk and lactation performance has not been thoroughly elucidated to date. In this study, we analysed the metabolites in sow milk from Yorkshire sows with high lactation (HL) or low lactation (LL) performance; these categories were assigned based on the weight gain of piglets during the entire lactation period (D1 to D21). The concentration of milk fat in the colostrum tended to be higher in the HL group (P = 0.05), the level of mannitol was significantly lower in the HL group (P < 0.05) and the level of glucuronic acid lactone was significantly higher in the HL group (P < 0.05) compared to those in LL group. In mature milk, the levels of lactose, creatine, glutamine, glutamate, 4-hydroxyproline, alanine, asparagine, and glycine were significantly higher (P < 0.05) in the HL group than those in LL group. The level of fatty acids showed no significant difference between the two groups in both the colostrum and mature milk. This study suggested that lactation performance may be associated with the levels of lactose and several amino acids in sow milk, and these results can be used to develop new feed additives to improve lactation performance in sows.

Preanalytical Processing and Biobanking Procedures of Biological Samples for Metabolomics Research: A White Paper, Community Perspective (for "Precision Medicine and Pharmacometabolomics Task Group"-The Metabolomics Society Initiative)

BACKGROUND

The metabolome of any given biological system contains a diverse range of low molecular weight molecules (metabolites), whose abundances can be affected by the timing and method of sample collection, storage, and handling. Thus, it is necessary to consider the requirements for preanalytical processes and biobanking in metabolomics research. Poor practice can create bias and have deleterious effects on the robustness and reproducibility of acquired data.

CONTENT

This review presents both current practice and latest evidence on preanalytical processes and biobanking of samples intended for metabolomics measurement of common biofluids and tissues. It highlights areas requiring more validation and research and provides some evidence-based guidelines on best practices.

SUMMARY

Although many researchers and biobanking personnel are familiar with the necessity of standardizing sample collection procedures at the axiomatic level (e.g., fasting status, time of day, "time to freezer," sample volume), other less obvious factors can also negatively affect the validity of a study, such as vial size, material and batch, centrifuge speeds, storage temperature, time and conditions, and even environmental changes in the collection room. Any biobank or research study should establish and follow a well-defined and validated protocol for the collection of samples for metabolomics research. This protocol should be fully documented in any resulting study and should involve all stakeholders in its design. The use of samples that have been collected using standardized and validated protocols is a prerequisite to enable robust biological interpretation unhindered by unnecessary preanalytical factors that may complicate data analysis and interpretation.

Metabolic phenotyping of malnutrition during the first 1000 days of life

Nutritional restrictions during the first 1000 days of life can impair or delay the physical and cognitive development of the individual and have long-term consequences for their health. Metabolic phenotyping (metabolomics/metabonomics) simultaneously measures a diverse range of low molecular weight metabolites in a sample providing a comprehensive assessment of the individual's biochemical status. There are a growing number of studies applying such approaches to characterize the metabolic derangements induced by various forms of early-life malnutrition. This includes acute and chronic undernutrition and specific micronutrient deficiencies. Collectively, these studies highlight the diverse and dynamic metabolic disruptions resulting from various forms of nutritional deficiencies. Perturbations were observed in many pathways including those involved in energy, amino acid, and bile acid metabolism, the metabolic interactions between the gut microbiota and the host, and changes in metabolites associated with gut health. The information gleaned from such studies provides novel insights into the mechanisms linking malnutrition with developmental impairments and assists in the elucidation of candidate biomarkers to identify individuals at risk of developmental shortfalls. As the metabolic profile represents a snapshot of the biochemical status of an individual at a given time, there is great potential to use this information to tailor interventional strategies specifically to the metabolic needs of the individual.

The investigation of immunoprotective and sedative hypnotic effect of total polysaccharide from Suanzaoren decoction by serum metabonomics approach

Suanzaoren decoction, as one of the traditional Chinese medicine prescriptions, has been most commonly used in Asian countries and reported to inhibit the process of immunodeficiency insomnia. Polysaccharide is important component which also contributes to the role of immunoprotective and sedative hypnotic effects. This study was aimed to explore the immunoprotective and sedative hypnotic mechanisms of polysaccharide from Suanzaoren decoction by serum metabonomics approach. With this purpose, complex physical and chemical immunodeficiency insomnia models were firstly established according to its multi-target property. Serum samples were analyzed using UHPLC/Q-TOF-MS spectrometry approach to determine endogenous metabolites. Then, principal component analysis was used to distinguish the groups, and partial least squares discriminate analysis was carried out to confirm the important variables. The serum metabolic profiling was identified and pathway analysis was performed after the total polysaccharide administration. The twenty-one potential biomarkers were screened, and the levels were all reversed to different degrees in the total polysaccharide treated groups. These potential biomarkers were mainly related to vitamin, sphingolipid, bile acid, phospholipid and acylcarnitine metabolisms. The result has indicated that total polysaccharide could inhibit insomnia triggered by immunodeficiency stimulation through regulating those metabolic pathways. This study provides a useful approach for exploring the mechanism and evaluating the efficacy of total polysaccharide from Suanzaoren decoction.

Breast Milk Lipidome Is Associated with Early Growth Trajectory in Preterm Infants

Human milk is recommended for feeding preterm infants. The current pilot study aims to determine whether breast-milk lipidome had any impact on the early growth-pattern of preterm infants fed their own mother's milk. A prospective-monocentric-observational birth-cohort was established, enrolling 138 preterm infants, who received their own mother's breast-milk throughout hospital stay. All infants were ranked according to the change in weight Z-score between birth and hospital discharge. Then, we selected infants who experienced "slower" (n = 15, -1.54 ± 0.42 Z-score) or "faster" (n = 11, -0.48 ± 0.19 Z-score) growth; as expected, although groups did not differ regarding gestational age, birth weight Z-score was lower in the "faster-growth" group (0.56 ± 0.72 vs. -1.59 ± 0.96). Liquid chromatography-mass spectrometry lipidomic signatures combined with multivariate analyses made it possible to identify breast-milk lipid species that allowed clear-cut discrimination between groups. Validation of the selected biomarkers was performed using multidimensional statistical, false-discovery-rate and ROC (Receiver Operating Characteristic) tools. Breast-milk associated with faster growth contained more medium-chain saturated fatty acid and sphingomyelin, dihomo-γ-linolenic acid (DGLA)-containing phosphethanolamine, and less oleic acid-containing triglyceride and DGLA-oxylipin. The ability of such biomarkers to predict early-growth was validated in presence of confounding clinical factors but remains to be ascertained in larger cohort studies.