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Peptidome analysis of human milk from women delivering macrosomic fetuses reveals multiple means of protection for infants.

ABSTRACT: Breastfeeding is associated with a lower incidence of obesity, diabetes, and cardiovascular disease later in life. While macrosomic infants have a higher risk of developing obesity and other metabolic disorders. Breast milk may contain special nutrients to meet the different growth needs of different infants. Whether mothers make breast milk different to meet the requirement of macrosomic infants is still unknown. Here, we conducted a comparison between mothers delivering macrosomic and non-macrosomic infants in colostrum endogenous peptides. More than 400 peptides, originating from at least 34 protein precursors, were identified by Liquid Chromatography/Mass Spectrometry (LC/MS). Out of these, 29 peptides found to be significant differently expressed (|fold change| ? 3, P < 0.01). Blastp analysis revealed 41 peptides may have established biological activities, which exhibit immunomodulating, antibacterial action, antioxidation, opioid agonist and antihypertensive activity. Furthermore, we found that peptide located at ?-Casein 24-38 AA has antimicrobial effect against E. coli, Y. enterocolitica and S. aureus. While, ?-Casein 89-109 AA-derived peptide plays as a regulator of preadipocyte proliferation. The profile of endogenous peptides from macrosomic term infants is different from non-macrosomic terms. This different peptide expression potentially has specific physiological function to benefit macrosomic infants. Finally, we believe that our research is a meaningfull finding which may add to the understanding of milk peptide physiological action.

SUBMITTER: Cui X

PROVIDER: S-EPMC5325381 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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Peptidome analysis of human milk from women delivering macrosomic fetuses reveals multiple means of protection for infants.

Cui Xianwei X Li Yun Y Yang Lei L You Lianghui L Wang Xing X Shi Chunmei C Ji Chenbo C Guo Xirong X

Oncotarget 20160901 39

Breastfeeding is associated with a lower incidence of obesity, diabetes, and cardiovascular disease later in life. While macrosomic infants have a higher risk of developing obesity and other metabolic disorders. Breast milk may contain special nutrients to meet the different growth needs of different infants. Whether mothers make breast milk different to meet the requirement of macrosomic infants is still unknown. Here, we conducted a comparison between mothers delivering macrosomic and non-macr ...[more]

PMID: 27566575

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Project description:PurposeThe Japanese Human Milk Study, a longitudinal prospective cohort study, was set up to clarify how maternal health, nutritional status, lifestyle and sociodemographic and economic factors affect breastfeeding practices and human milk composition. This would eventually determine factors affecting the growth and development of infants and children.ParticipantsA total of 1210 Japanese lactating women who satisfied the inclusion criteria, were invited across the country at various participating sites, between 2014 and 2019. Finally a total of 1122 women were enrolled in this study.Findings to dateAmong 1122 eligible participants, mean age at delivery was 31.2 (SD 4.4) years and mean prepregnancy BMI was 20.8 (SD 2.7). Among these women, 35% were previously nulliparous and 77.7% had college, university or higher education. The mean gestational period was 39.0 (SD 1.3) weeks. Caesarean section was reported among 11.9%; mean infant birth weight was 3082 (SD 360) g. Of the infants, 53.7% were male. Overall, our participants appeared to be healthier than the general population in Japan. Analyses of the 1079 eligible human milk samples obtained at the first and second months postpartum showed the following composition: carbohydrate, 8.13 (SD 0.32) g/100 mL; fat, 3.77 (SD 1.29) g/100 mL; and crude protein, 1.20 (SD 0.23) g/100 mL. We also analysed osteopontin, fatty acid, vitamin D and phospholipid levels in limited subcohorts of the samples.Future plansFollow-up surveys will be conducted to obtain milk samples every 2 months for 12 months and to investigate mother and child health until the children reach 5 years of age. These will be completed in 2024. We plan to longitudinally analyse the composition of macronutrients and various bioactive factors in human milk and investigate the lifestyle and environmental factors that influence breastfeeding practices, maternal and child health, and child development.Trial registration numberUMIN000015494; pre-results.

Project description:BackgroundFetal macrosomia is associated with an increased risk of several maternal and newborn complications. Antenatal predication of fetal macrosomia remains challenging. We aimed to develop a nomogram model for the prediction of macrosomia using real-world clinical data to improve the sensitivity and specificity of macrosomia prediction.MethodsIn the present study, we performed a retrospective, observational study based on 13,403 medical records of pregnant women who delivered singleton infants at a tertiary hospital in Shanghai from 1 January 2018 through 31 December 2019. We split the original dataset into a training set (n = 9382) and a validation set (n = 4021) at a 7:3 ratio to generate and validate our model. The candidate variables, including maternal characteristics, laboratory tests, and sonographic parameters were compared between the two groups. A univariate and multivariate logistic regression was carried out to explore the independent risk factors for macrosomia in pregnant women. Thus, the regression model was adopted to establish a nomogram to predict the risk of macrosomia. Nomogram performance was determined by discrimination and calibration metrics. All the statistical analysis was analyzed using R software.ResultsWe compared the differences between the macrosomic and non-macrosomic groups within the training set and found 16 independent risk factors for macrosomia (P < 0.05), including biparietal diameter (BPD), head circumference (HC), femur length (FL), amniotic fluid index (AFI) at the last prenatal examination, pre-pregnancy body mass index (BMI), and triglycerides (TG). Values for the areas under the curve (AUC) for the nomogram model were 0.917 (95% CI, 0.908-0.927) and 0.910 (95% CI, 0.894-0.927) in the training set and validation set, respectively. The internal and external validation of the nomogram demonstrated favorable calibration as well as discriminatory capability of the model.ConclusionsOur model has precise discrimination and calibration capabilities, which can help clinical healthcare staff accurately predict macrosomia in pregnant women.

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Peptidome analysis of human milk from women delivering macrosomic fetuses reveals multiple means of protection for infants.

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Peptidome analysis of human milk from women delivering macrosomic fetuses reveals multiple means of protection for infants.

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