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

Untargeted metabolomics study of mature human milk from women with and without gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is a prevalent metabolic disorder during pregnancy that alters the metabolites in human milk. Integrated Gas Chromatography-Mass Spectrometry (GC-MS) and Liquid Chromatography-Mass Spectrometry (LC-MS) were employed for comprehensive identification and comparison of metabolites in mature human milk (MHM) from women with and without GDM. A total of 268 differentially expressed metabolites (DEMs) were identified. Among these, linoleic acid, arachidonic acid, 9R-HODE and L-glutamic acid were significantly elevated and 12,13-DHOME was significantly decreased in MHM of women with GDM. These metabolites are significantly enriched in linoleic acid metabolism, fatty acid biosynthesis, galactose metabolism and ABC transporters pathways. Disorders in these metabolic pathways are associated with insulin resistance and poor glucose metabolism indicating these conditions may persist postpartum.

Gestational Diabetes Mellitus-Induced Milk Fat Globule Membrane Protein Changes of Human Mature Milk Based on TMT Proteomic Analysis

Breastfeeding by mothers with gestational diabetes mellitus (GDM) has been shown to reduce maternal insulin demands and diminish the risks of diabetes in infants, leading to improved long-term health outcomes. Milk fat globule membrane (MFGM) proteins play a crucial role in influencing the immunity and cognitive development of infants. Understanding the alterations in MFGM proteins in breastmilk from mothers with GDM is essential for enhancing their self-efficacy and increase breastfeeding rates. The objective of this study is to investigate and compare MFGM proteins in milk from mothers with GDM and without based on tandem mass tag (TMT) labeling and liquid chromatography tandem mass spectrometry (LC-MS) techniques. A total of 5402 proteins were identified, including 4 upregulated proteins and 24 downregulated proteins. These significantly altered proteins were found to be associated with human diseases, cellular processes, and metabolism pathways. Additionally, the oxidative phosphorylation pathway emerged as the predominant pathway through Gene Set Enrichment Analysis (GSEA) involving all genes.

Human milk composition and infant anthropometrics: overview of a systematic review with clinical and research implications

BACKGROUND

Despite global public health organizations endorsing breastfeeding or human milk (HM) as the optimal source of nutrition for infants, detailed knowledge of how HM composition influences infant growth is lacking. In this commentary we summarize and interpret the key findings of a large systematic review on HM components and child growth (N = 141 articles included). We highlight the most consistent associations, discuss study quality issues, explore socio-economic and time trends in this body of research, and identify gaps and future research directions.

KEY FINDINGS OF SYSTEMATIC REVIEW

We grouped HM components into three categories: micronutrients (28 articles), macronutrients (57 articles), and bioactives (75 articles). Overall, we struggled to find consistent associations between HM components and infant growth. The majority of studies (85%) were of moderate or low-quality, with inconsistent HM collection and analysis strategies being identified as the most substantial quality concerns. Additional quality issues included failing to account for potential confounding by factors such as breastfeeding exclusivity and maternal body mass index.

CONSIDERATIONS FOR FUTURE HUMAN MILK RESEARCH

Many opportunities exist for the future of HM research. Using untargeted metabolomics will expand our understanding of HM components beyond previously defined and well-understood components. Machine learning will allow researchers to investigate HM as an integrated system, rather than a collection of individual components. Future research on HM composition should incorporate evidence-based HM sampling strategies to encompass circadian variation as well as infant consumption. Additionally, researchers need to focus on developing high quality growth data using consistent growth metrics and definitions. Building multidisciplinary research teams will help to ensure that outcomes are meaningful and clinically relevant.

CONCLUSION

Despite a large body of literature, there is limited quality evidence on the relationship between HM composition and infant growth. Future research should engage in more accurate collection of breastfeeding data, use standardized HM collection strategies and employ assays that are validated for HM. By systematically evaluating the existing literature and identifying gaps in existing research methods and practice, we hope to inspire standardized methods and reporting guidelines to support robust strategies for examining relationships between HM composition and child growth.

Critical Factors in Sample Collection and Preparation for Clinical Metabolomics of Underexplored Biological Specimens

This review article compiles critical pre-analytical factors for sample collection and extraction of eight uncommon or underexplored biological specimens (human breast milk, ocular fluids, sebum, seminal plasma, sweat, hair, saliva, and cerebrospinal fluid) under the perspective of clinical metabolomics. These samples are interesting for metabolomics studies as they reflect the status of living organisms and can be applied for diagnostic purposes and biomarker discovery. Pre-collection and collection procedures are critical, requiring protocols to be standardized to avoid contamination and bias. Such procedures must consider cleaning the collection area, sample stimulation, diet, and food and drug intake, among other factors that impact the lack of homogeneity of the sample group. Precipitation of proteins and removal of salts and cell debris are the most used sample preparation procedures. This review intends to provide a global view of the practical aspects that most impact results, serving as a starting point for the designing of metabolomic experiments.

Human Milk Bioactive Components and Child Growth and Body Composition in the First 2 Years: A Systematic Review

Human milk (HM) contains macronutrients, micronutrients, and a multitude of other bioactive factors, which can have a long-term impact on infant growth and development. We systematically searched MEDLINE, EMBASE, Cochrane Library, Scopus, and Web of Science to synthesize evidence published between 1980 and 2022 on HM components and anthropometry through 2 y of age among term-born infants. From 9992 abstracts screened, 141 articles were included and categorized based on their reporting of HM micronutrients, macronutrients, or bioactive components. Bioactives including hormones, HM oligosaccharides (HMOs), and immunomodulatory components are reported here, based on 75 articles from 69 unique studies reporting observations from 9980 dyads. Research designs, milk collection strategies, sampling times, geographic and socioeconomic settings, reporting practices, and outcomes varied considerably. Meta-analyses were not possible because data collection times and reporting were inconsistent among the studies included. Few measured infant HM intake, adjusted for confounders, precisely captured breastfeeding exclusivity, or adequately described HM collection protocols. Only 5 studies (6%) had high overall quality scores. Hormones were the most extensively examined bioactive with 46 articles (n = 6773 dyads), compared with 13 (n = 2640 dyads) for HMOs and 12 (n = 1422 dyads) for immunomodulatory components. Two studies conducted untargeted metabolomics. Leptin and adiponectin demonstrated inverse associations with infant growth, although several studies found no associations. No consistent associations were found between individual HMOs and infant growth outcomes. Among immunomodulatory components in HM, IL-6 demonstrated inverse relationships with infant growth. Current research on HM bioactives is largely inconclusive and is insufficient to address the complex composition of HM. Future research should ideally capture HM intake, use biologically relevant anthropometrics, and integrate components across categories, embracing a systems biology approach to better understand how HM components work independently and synergistically to influence infant growth.

The Human Milk Metabolome: A Scoping Literature Review

BACKGROUND

Human milk is a complex source of nutrition and other bioactives that protects infants from disease, holding a lifetime of beneficial effects. The field of metabolomics provides a robust platform through which we can better understand human milk at a level rarely examined.

RESEARCH AIM

To Identify, describe, synthesize, and critically analyze the literature within the past 5 years related to the human milk metabolome.

METHODS

We conducted a scoping literature review and quality analysis of the recent science reflecting untargeted metabolomic approaches to examining human milk. We searched six databases using the terms "breast milk," "metabolome," "metabolite," and "human milk," Out of more than 1,069 abstracts, we screened and identified 22 articles that met our inclusion criteria.

RESULTS

We extracted data related to the study author, geographic location, research design, analyses, platform used, and results. We also extracted data related to human milk research activities, including collection protocol, infant/maternal considerations, and time. Selected studies focused on a variety of phenotypes, including maternal and infant disease. Investigators used varying approaches to evaluate the metabolome, and differing milk collection protocols were observed.

CONCLUSION

The human milk metabolome is informed by many factors-which may contribute to infant health outcomes-that have resulted in disparate milk metabolomic profiles. Standardized milk collection and storage procedures should be implemented to minimize degradation. Investigators may use our findings to develop research questions that test a targeted metabolomic approach.

Analysis of milk with liquid chromatography–mass spectrometry: a review

As a widely consumed foodstuff, milk and dairy products are increasingly studied over the years. At the present time, milk profiling is used as a benchmark to assess the properties of milk. Modern biomolecular mass spectrometers have become invaluable to fully characterize the milk composition. This review reports the analysis of milk and its components using liquid chromatography coupled with mass spectrometry (LC–MS). LC–MS analysis as a whole will be discussed subdivided into the major constituents of milk, namely, lipids, proteins, sugars and the mineral fraction.

Association of ambient fine particulate matter exposure with gestational diabetes mellitus and blood glucose levels during pregnancy

BACKGROUND

Previous studies have examined the associations between ambient fine particulate matter (PM_2.5) exposure and gestational diabetes mellitus (GDM). However, limited studies explored the relationships between PM_2.5 exposure and blood glucose levels during pregnancy, especially in highly polluted areas.

OBJECTIVES

To examine the associations of prenatal ambient PM_2.5 exposure with GDM and blood glucose levels, and to identify the sensitive exposure windows in a highly air-polluted area.

METHODS

From July 2016 to October 2017, a birth cohort study was conducted in Beijing, China. Participants were interviewed in each trimester regarding demographics, lifestyle, living and working environment, and medical conditions. Participant's daily ambient PM_2.5 levels from 3 m before last menstrual period (LMP) to the third trimester was estimated by a hybrid spatiotemporal model. Indoor air quality index was calculated based on environmental tobacco smoke, ventilation, cooking, painting, pesticide, and herbicide use. Distributed lag non-linear model was applied to explore the sensitive weeks of PM_2.5 exposure.

RESULTS

Of 165 pregnant women, 23 (13.94%) developed GDM. After adjusting for potential confounders, PM_2.5 exposure during the 1^st trimester was associated with higher odds of GDM (10 μg/m³ increase: OR = 1.89, 95% CI: 1.04-3.49). Each 10 μg/m³ increase in PM_2.5 during the 2^nd trimester was associated with 17.70% (2.21-33.20), 15.99% (2.96-29.01), 18.82% (4.11-33.52), and 17.10% (3.28-30.92) increase in 1-h, 2-h, Δ1h-fasting (1-h minus fasting), and Δ2h-fasting (2-h minus fasting) blood glucose levels, respectively. PM_2.5 exposure at 24^th-27^th weeks after LMP was associated with increased GDM risk. We identified sensitive exposure windows of 21^st-24^th weeks for higher 1-h and 2-h blood glucose levels and of 20^th-22^nd weeks for increased Δ1h-fasting and Δ2h-fasting.

CONCLUSIONS

Ambient PM_2.5 exposure during the second trimester was associated with higher odds of GDM and higher blood glucose levels. Avoiding exposure to high air pollution levels during the sensitive windows might prevent women from developing GDM.

Maternal consumption of a fermented diet protects offspring against intestinal inflammation by regulating the gut microbiota

The neonatal intestinal tract is immature and can be easily infected by pathogens causing inflammation. Maternal diet manipulation is a promising nutritional strategy to enhance the gut health of offspring. A fermented diet is a gut microbiota targeting diet containing live probiotics and their metabolites, which benefit the gut and overall health host. However, it remains unclear how a maternal fermented diet (MFD) affects neonatal intestinal inflammation. Here, in vivo and in vitro models together with multi-omics analysis were applied to investigate the impacts and the underlying mechanism through which an MFD prevents from gut inflammation in neonates. An MFD remarkably improved the performance of both sows and piglets and significantly altered the gut microbiome and milk metabolome of sows. In addition, the MFD significantly accelerated the maturation of the gut microbiota of neonates and increased the abundance of gut Lactobacillus and the microbial functions of amino acid-related enzymes and glucose metabolism on the weaning day. Notably, the MFD reduced susceptibility to colonic inflammation in offspring. The fecal microbiota of sows was then transplanted into mouse dams and it was found that the mouse dams and pups in the MFD group alleviated the LPS-induced decrease in gut Lactobacillus abundance and barrier injury. Milk L-glutamine (GLN) and gut Lactobacillus reuteri (LR) were found as two of the main MFD-induced sow effectors that contributed to the gut health of piglets. The properties of LR and GLN in modulating gut microbiota and alleviating colonic inflammation by inhibiting the phosphorylation of p38 and JNK and activation of Caspase 3 were further verified. These findings provide the first data revealing that an MFD drives neonate gut microbiota development and ameliorates the colonic inflammation by regulating the gut microbiota. This fundamental evidence might provide references for modulating maternal nutrition to enhance early-life gut health and prevent gut inflammation.

Identification of differential metabolites using untargeted metabolomics between gestational diabetes and normal pregnant women

OBJECTIVE

To study the metabonomics differences between pregnant women with gestational diabetes mellitus (GDM) in the third trimester and those in a group without GDM by screening a group of highly efficient and sensitive markers for GDM and validating previously published early metabolic markers of GDM.

METHODS

A cross-sectional cohort study based on ultra performance liquid chromatography tandem mass spectrometry untargeted metabolomics analysis of serum samples collected from 59 pregnant women with GDM and 59 pregnant women without GDM.

RESULTS

A total of 121 metabolites were detected, and 27 were identified as differential metabolites between GDM and control. The combination of 27 metabolic peaks had area under curve (AUC) values of 0.90, 0.92, and 0.93 in the prediction models using support vector machine, partial least squares, and random forest, respectively. Finally, five metabolite biomarkers were selected to construct logistic regression models: L-valine, hypoxanthine, eicosapentaenoic acid, 2-amino-1,3,4-octadecanotriol, and choline. The AUC value of these metabolites was 0.769 between the GDM group and the control group.

CONCLUSIONS

The discovery of a group of differential metabolites in pregnant women with GDM in the third trimester and in pregnant women without GDM may facilitate the study of the pathologic mechanism of GDM; it may be possible to find an efficient and sensitive alternative GDM detection method.

Maternal and Fetal Metabolites in Gestational Diabetes Mellitus: A Narrative Review

Gestational diabetes mellitus (GDM) is a major public health issue of our century due to its increasing prevalence, affecting 5% to 20% of all pregnancies. The pathogenesis of GDM has not been completely elucidated to date. Increasing evidence suggests the association of environmental factors with genetic and epigenetic factors in the development of GDM. So far, several metabolomics studies have investigated metabolic disruptions associated with GDM. The aim of this review is to highlight the usefulness of maternal metabolites as diagnosis markers of GDM as well as the importance of both maternal and fetal metabolites as prognosis biomarkers for GDM and GDM’s transition to type 2 diabetes mellitus T2DM.

Comprehensive Metabolomic Profiling of Cord Blood and Placental Tissue in Surviving Monochorionic Twins Complicated by Twin-Twin Transfusion Syndrome With or Without Fetoscopic Laser Coagulation Surgery: A Retrospective Cohort Study

Objectives: To investigate metabolomic perturbations caused by twin-twin transfusion syndrome, metabolic changes associated with fetoscopic laser coagulation in both placental tissue and cord plasma, and to investigate differential metabolites pertinent to varying fetal outcomes, including hemodynamic status, birth weight, and cardiac function, of live-born babies.

Methods: Placental tissue and cord plasma samples from normal term or uncomplicated preterm-born monochorionic twins and those complicated by twin-twin transfusion syndrome treated with or without fetoscopic laser coagulation were analyzed by high-performance liquid chromatography metabolomic profiling. Sixteen comparisons of different co-twin groups were performed. Partial least squares–discriminant analysis, metabolic pathway analysis, biomarker analysis, and Spearman’s correlation analysis were conducted based on differential metabolites used to determine potential biomarkers in different comparisons and metabolites that are pertinent to neonatal birth weight and left ventricular ejection fraction.

Results: These metabolomic investigations showed that the cord plasma metabolome has a better performance in discriminating fetuses among different hemodynamic groups than placental tissue. The metabolic alteration of twin-twin transfusion syndrome in these two types of samples centers on fatty acid and lipid metabolism. The fetoscopic laser coagulation procedure improves the metabolomic change brought by this syndrome, making the metabolomes of the treated group less distinguishable from those of the control and preterm birth groups. Certain compounds, especially lipids and lipid-like molecules, are noted to be potential biomarkers of this morbid disease and pertinent to neonatal birth weight and ejection fraction.

Conclusions: Fetoscopic laser coagulation can ameliorate the metabolomic alteration caused by twin-twin transfusion syndrome in placental tissue and cord plasma, which are involved mainly in fatty acid and lipid-like molecule metabolism. Certain lipids and lipid-like molecules are helpful in differentiating co-twins of different hemodynamic statuses and are significantly correlated with neonatal birth weight or ejection fraction.

Impact of maternal gestational weight gain in twin pregnancies on early childhood obesity risk: A longitudinal birth cohort study

OBJECTIVES

To investigate the impact of gestational weight gain (GWG) on the body mass index-for-age z score (BAZ) and obesity risk among twin offspring.

METHODS

This study included 263 women who were pregnant with twins and their offspring. Maternal GWG was measured in each trimester, and infant weight and length were measured at 6, 12, and 24 months.

RESULTS

Total GWG was positively correlated with offspring birthweight and BAZ at 6, 12 and 24 months [adjusted β 0.013 (95% CI: 0.008-0.019), 0.028 (95% CI: 0.005-0.050), 0.033 (95% CI: 0.010-0.056) and 0.025 (95% CI: 0.004-0.047), respectively]. Excessive total GWG was related to an increased relative risk (RR) of large for gestational age (LGA) and overweight at 6 and 12 months. Only the second trimester gestational weight gain rate (GWGR) was positively correlated with birthweight (adjusted β 0.380, 95% CI: 0.256-0.504), and RRs of 6.818 (95% CI: 1.568-29.642) and 2.852 (95% CI: 1.466-5.548) were found for LGA and overweight at 12 months, respectively.

CONCLUSIONS

Total GWG and the second trimester GWGR were correlated with BAZ and overweight/obesity risk in twin offspring; the impact was obvious in the first year of life and gradually disappeared over time.

CLINICAL TRIAL REGISTRATION

ChiCTR-OOC-16008203, Registered on 1 April 2016 at the Chinese Clinical Trial Registry.

Association of infant feeding patterns with body fat mass and obesity in the first 2 years of life: a longitudinal twin birth cohort study

Childhood obesity is a major public health problem with no effective intervention. We explored the influence of feeding patterns on infants' growth indices within the first 2 years in a twin birth cohort. Dietary intake at 12 months was recorded with a food frequency questionnaire, and dietary patterns were identified by principal component analysis. Milk feeding methods in first 6 months were categorised as breastfeeding or exclusive formula feeding. Correlations between feeding patterns and infants' growth indices were examined via generalised estimating equations. Two dietary patterns were identified and neither of which was related to growth indices. Breastfed infants had a higher body fat mass (BFM) percentage at 12 months, a higher body mass index (BMI) increment from birth to 6 months and a lower BMI increment from 6 to 12 months. Breastfed infants were likely positively correlated with BFM at 12 months; as complementary food was added, the effect of breastfeeding on growth gradually decreased.