Performance of metabonomic serum analysis for diagnostics in paediatric tuberculosis.

We applied a metabonomic strategy to identify host biomarkers in serum to diagnose paediatric tuberculosis (TB) disease. 112 symptomatic children with presumptive TB were recruited in The Gambia and classified as bacteriologically-confirmed TB, clinically diagnosed TB, or other diseases. Sera were analysed using 1H nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS). Multivariate data analysis was used to distinguish patients with TB from other diseases. Diagnostic accuracy was evaluated using Receiver Operating Characteristic (ROC) curves. Model performance was tested in a validation cohort of 36 children from the UK. Data acquired using 1H NMR demonstrated a sensitivity, specificity and Area Under the Curve (AUC) of 69% (95% confidence interval [CI], 56-73%), 83% (95% CI, 73-93%), and 0.78 respectively, and correctly classified 20% of the validation cohort from the UK. The most discriminatory MS data showed a sensitivity of 67% (95% CI, 60-71%), specificity of 86% (95% CI, 75-93%) and an AUC of 0.78, correctly classifying 83% of the validation cohort. Amongst children with presumptive TB, metabolic profiling of sera distinguished bacteriologically-confirmed and clinical TB from other diseases. This novel approach yielded a diagnostic performance for paediatric TB comparable to that of Xpert MTB/RIF and interferon gamma release assays.

Serologic Responses in Childhood Pulmonary Tuberculosis.

BACKGROUND: Identification of the Mycobacterium tuberculosis immunoproteome and antigens associated with serologic responses in adults has renewed interest in developing a serologic test for childhood tuberculosis (TB). We investigated IgG antibody responses against M. tuberculosis antigens in children with well-characterized TB. METHODS: We studied archived sera obtained from hospitalized children with suspected pulmonary TB, and classified as having confirmed TB (culture-confirmed), unlikely TB (clinical improvement without TB treatment), or unconfirmed TB (all others). A multiplexed bead-based assay for IgG antibodies against 119 M. tuberculosis antigens was developed, validated and used to test sera. The area under the curves (AUCs) of the empiric receiver-operator characteristic curves were generated as measures of predictive ability. A cross-validated generalized linear model was used to select the most predictive combinations of antigens. RESULTS: For the confirmed TB versus unlikely TB comparison, the maximal single antigen AUC was 0.63, corresponding to sensitivity 0.60 and specificity 0.60. Older (age: 60+ months old) children's responses were better predictive of TB status than younger (age: 12-59 months old) children's, with a maximal single antigen AUC of -0.76. For the confirmed TB versus unlikely TB groups, the most predictive combinations of antigens assigned TB risk probabilities of 0.33 and 0.33, respectively, when all ages were considered, and 0.57 (interquartile range: 0.48-0.64) and 0.35 (interquartile range: 0.32-0.40) when only older children were considered. CONCLUSION: An antigen-based IgG test is unlikely to meet the performance characteristics required of a TB detection test applicable to all age groups.

Role of human milk oligosaccharides in Group B Streptococcus colonisation.

Group B Streptococcus (GBS) infection is a major cause of morbidity and mortality in infants. The major risk factor for GBS disease is maternal and subsequent infant colonisation. It is unknown whether human milk oligosaccharides (HMOs) protect against GBS colonisation. HMO production is genetically determined and linked to the Lewis antigen system. We aimed to investigate the association between HMOs and infant GBS colonisation between birth and postnatal day 90. Rectovaginal swabs were collected at delivery, as well as colostrum/breast milk, infant nasopharyngeal and rectal swabs at birth, 6 days and days 60-89 postpartum from 183 Gambian mother/infant pairs. GBS colonisation and serotypes were determined using culture and PCR. (1)H nuclear magnetic resonance spectroscopy was used to characterise the mother's Lewis status and HMO profile in breast milk. Mothers who were Lewis-positive were significantly less likely to be colonised by GBS (X (2)=12.50, P<0.001). Infants of Lewis-positive mothers were less likely GBS colonised at birth (X (2)=4.88 P=0.03) and more likely to clear colonisation between birth and days 60-89 than infants born to Lewis-negative women (P=0.05). There was no association between Secretor status and GBS colonisation. In vitro work revealed that lacto-N-difucohexaose I (LNDFHI) correlated with a reduction in the growth of GBS. Our results suggest that HMO such as LNDFHI may be a useful adjunct in reducing maternal and infant colonisation and hence invasive GBS disease. Secretor status offers utility as a stratification variable in GBS clinical trials.

Impact of maternal BMI and sampling strategy on the concentration of leptin, insulin, ghrelin and resistin in breast milk across a single feed: a longitudinal cohort study.

OBJECTIVES: We tested the hypothesis that there is a positive association between maternal body mass index (BMI) and the concentration of appetite-regulating hormones leptin, insulin, ghrelin and resistin in breast milk. We also aimed to describe the change in breast milk hormone concentration within each feed, and over time. SETTING: Mothers were recruited from the postpartum ward at a university hospital in London. Breast milk samples were collected at the participants' homes. PARTICIPANTS: We recruited 120 healthy, primiparous, breastfeeding mothers, aged over 18 years. Mothers who smoked, had multiple births or had diabetes were excluded. Foremilk and hindmilk samples were collected from 105 women at 1 week postpartum and 92 women at 3 months postpartum. PRIMARY AND SECONDARY OUTCOME MEASURES: We recorded maternal and infant anthropometric measurements at each sample collection and measured hormone concentrations using a multiplex assay. RESULTS: The concentration of leptin in foremilk correlated with maternal BMI at the time of sample collection, at 7 days (r=0.31, p=0.02) and 3 months postpartum (r=0.30, p=<0.00). Foremilk insulin correlated with maternal BMI at 3 months postpartum (r=0.22, p=0.04). Breast milk ghrelin and resistin were not correlated with maternal BMI. Ghrelin concentrations at 3 months postpartum were increased in foremilk compared with hindmilk (p=0.01). Concentrations of ghrelin were increased in hindmilk collected at 1  week postpartum compared with samples collected at 3 months postpartum (p=0.03). A trend towards decreased insulin concentrations in hindmilk was noted. Concentrations of leptin and resistin were not seen to alter over a feed. CONCLUSIONS: A positive correlation between maternal BMI and foremilk leptin concentration at both time points studied, and foremilk insulin at 3 months postpartum was observed. This may have implications for infant appetite regulation and obesity risk.

Human breast milk: A review on its composition and bioactivity.

Breast milk is the perfect nutrition for infants, a result of millions of years of evolution, finely attuning it to the requirements of the infant. Breast milk contains many complex proteins, lipids and carbohydrates, the concentrations of which alter dramatically over a single feed, as well as over lactation, to reflect the infant's needs. In addition to providing a source of nutrition for infants, breast milk contains a myriad of biologically active components. These molecules possess diverse roles, both guiding the development of the infants immune system and intestinal microbiota. Orchestrating the development of the microbiota are the human milk oligosaccharides, the synthesis of which are determined by the maternal genotype. In this review, we discuss the composition of breast milk and the factors that affect it during the course of breast feeding. Understanding the components of breast milk and their functions will allow for the improvement of clinical practices, infant feeding and our understanding of immune responses to infection and vaccination in infants.

Multiplatform characterization of dynamic changes in breast milk during lactation.

The multicomponent analysis of human breast milk (BM) by metabolic profiling is a new area of study applied to determining milk composition, and is capable of associating BM composition with maternal characteristics, and subsequent infant health outcomes. A multiplatform approach combining HPLC-MS and ultra-performance LC-MS, GC-MS, CE-MS, and 1 H NMR spectroscopy was used to comprehensively characterize metabolic profiles from seventy BM samples. A total of 710 metabolites spanning multiple molecular classes were defined. The utility of the individual and combined analytical platforms was explored in relation to numbers of metabolites identified, as well as the reproducibility of the methods. The greatest number of metabolites was identified by the single phase HPLC-MS method, while CE-MS uniquely profiled amino acids in detail and NMR was the most reproducible, whereas GC-MS targeted volatile compounds and short chain fatty acids. Dynamic changes in BM composition were characterized over the first 3 months of lactation. Metabolites identified as altering in abundance over lactation included fucose, di- and triacylglycerols, and short chain fatty acids, known to be important for infant immunological, neurological, and gastrointestinal development, as well as being an important source of energy. This extensive metabolic coverage of the dynamic BM metabolome provides a baseline for investigating the impact of maternal characteristics, as well as establishing the impact of environmental and dietary factors on the composition of BM, with a focus on the downstream health consequences this may have for infants.

Effect of maternal body mass index on hormones in breast milk: a systematic review.

BACKGROUND: Maternal Body Mass Index (BMI) is positively associated with infant obesity risk. Breast milk contains a number of hormones that may influence infant metabolism during the neonatal period; these may have additional downstream effects on infant appetite regulatory pathways, thereby influencing propensity towards obesity in later life. OBJECTIVE: To conduct a systematic review of studies examining the association between maternal BMI and the concentration of appetite-regulating hormones in breast milk. METHOD: Pubmed was searched for studies reporting the association between maternal BMI and leptin, adiponectin, insulin, ghrelin, resistin, obestatin, Peptide YY and Glucagon-Like Peptide 1 in breast milk. RESULTS: Twenty six studies were identified and included in the systematic review. There was a high degree of variability between studies with regard to collection, preparation and analysis of breast milk samples. Eleven of fifteen studies reporting breast milk leptin found a positive association between maternal BMI and milk leptin concentration. Two of nine studies investigating adiponectin found an association between maternal BMI and breast milk adiponectin concentration; however significance was lost in one study following adjustment for time post-partum. No association was seen between maternal BMI and milk adiponectin in the other seven studies identified. Evidence for an association between other appetite regulating hormones and maternal BMI was either inconclusive, or lacking. CONCLUSIONS: A positive association between maternal BMI and breast milk leptin concentration is consistently found in most studies, despite variable methodology. Evidence for such an association with breast milk adiponectin concentration, however, is lacking with additional research needed for other hormones including insulin, ghrelin, resistin, obestatin, peptide YY and glucagon-like peptide-1. As most current studies have been conducted with small sample sizes, future studies should ensure adequate sample sizes and standardized methodology.